gs4_deauth()

sym_ <- read_sheet("https://docs.google.com/spreadsheets/d/1u5jGDmdz7ROWMQYDdtfwjMpeYMcsGGKz_XZoQpA6WFc/edit#gid=241327815", sheet = "symptoms") %>% 
  rename(overall = `overall pain`,
         forearm = `forearm pain`,
         back = `back pain`,
         focus = `focus / concentration issues`,
         skin = `skin condition`,
         leg = `leg function`) %>% 
  mutate(date = ymd(date)) %>%
  mutate(swim = ifelse(Swimming == "Yes", 1, 0),
         stretch = ifelse(Stretching == "Yes", 1, 0),
         si = ifelse(`suicidal ideation` == "yes", 1, 0),
         night = ifelse(nightmares == "yes", 1, 0),
         peri = ifelse(period == "Yes", 1, 0),
         k = ifelse(str_detect(notes, "keta"), 1, 0),
         rainbow = ifelse(str_detect(notes, "rainbow"), 1, 0)) %>% 
  mutate(night3 = ifelse(nightmares == "not sure/don't remember", 
                         "unsure", nightmares)) %>% 
  mutate(cyst = ifelse(str_detect(skin, "cyst"), 1, 0),
         activeCyst = case_when(str_detect(skin, "active cyst") ~ "Active",
                                str_detect(skin, "healing cyst") ~ "Healing",
                                TRUE ~ NA))

pain <- sym_ %>% 
  pivot_longer(c(overall, forearm, back, fatigue, mood, anxiety, 
                 focus, leg, dizziness, headache, productivity)) %>% 
  pivot_longer(c(si, night, swim, cyst), 
               names_to = "points", 
               values_to = "point_value") %>% 
  mutate(sym_label = case_when(name == "overall" ~ "Overall pain",
                               name == "forearm" ~ "Forearm pain",
                               name == "back" ~ "Back pain",
                               name == "fatigue" ~ "Fatigue",
                               name == "mood" ~ "Depression",
                               name == "anxiety" ~ "Anxiety",
                               name == "focus" ~ "Focus Issues",
                               name == "leg" ~ "Legs",
                               name == "dizziness" ~ "Dizziness",
                               name == "headache" ~ "Headache",
                               name == "productivity" ~ "Productivity"),
         dummies = case_when(points == "si" ~ "S.I.",
                             points == "night" ~ "Nightmares",
                             points == "swim" ~ "Swimming",
                             points == "cyst" ~ "Skin Cyst")) %>% 
  mutate(tip_line = paste0(format(date, "%b %e"), 
                           "<br>", sym_label, 
                           " - ", value),
         tip_point = paste0(dummies, 
                            "<br>", format(date, "%b %e"), 
                            " (Overall pain - ", value, ")")) 

place <- readRDS("data/place.RDS") %>% 
  distinct()

keep_last_observation <- function(place) {
  place %>%
    group_by(date) %>%
    slice(n()) %>%
    ungroup()
}

place_ <- keep_last_observation(place)

sym <- sym_ %>% 
  left_join(place_, by = "date") %>% 
  rename(state = pm.state) 


nearest <- function(index) {
  i <- index - 1
  
  while (i >= 1 && is.na(sym$state[i])) {
    i <- i - 1
  }
  
  if (i >= 1) {
    return(sym$state[i])
  } else {
    return(NA)
  }
}

missing_indices <- which(is.na(sym$state))
sym$state[missing_indices] <- sapply(missing_indices, nearest)

si <- sym %>% 
  filter(si == 1)
night <- sym %>% 
  filter(night == 1)
swim <- sym %>% 
  filter(swim == 1)
k <- sym %>% 
  filter(k == 1)
rb <- sym %>% 
  filter(rainbow == 1)
stretch <- sym %>% 
  filter(stretch == 1)
peri <- sym %>% 
  filter(peri == 1)

k_start <- min(k$date)
k_end <- max(k$date)

sym <- sym %>% 
  mutate(before_k = ifelse(date < k_start, TRUE, FALSE),
         after_k = ifelse(date > k_end, TRUE, FALSE)) %>% 
  mutate(state = ifelse(date == "2024-03-12", "AL", state)) %>% 
  mutate(state = ifelse(date == "2024-03-13", "MS", state)) %>% 
  mutate(state = ifelse(date == "2024-03-14" | date == "2024-03-15" , "LA", state)) %>% 
  mutate(state = ifelse(date > "2024-03-15", "TX", state))

Daily Symptoms

Last 20 Weeks Stacked

pain %>% 
  filter(date > (today() - 140),
         name != "productivity") %>% 
  mutate(sym_height = as.numeric(factor(sym_label)) * 10) %>% 
  ggplot(aes(date, sym_label)) +
  geom_vline(data = k %>% filter(date > (today() - 140)),
             aes(xintercept = date),
             color = "#FFFFBB", 
             linewidth = 3) +
  geom_vline(data = rb %>% filter(date > (today() - 140)),
             aes(xintercept = date),
             color = "#3ACC14", 
             linewidth = 3,
             alpha = .225) +
  geom_vline(data = peri %>% filter(date > (today() - 140)),
             aes(xintercept = date),
             color = "#CC0AA4", 
             linewidth = 2,
             alpha = .2) +
  geom_vline(data = si %>% filter(date > (today() - 140)),
             aes(xintercept = date - .1),
             color = "#CC1F14", 
             linewidth = 1) +
  geom_vline(data = night %>% filter(date > (today() - 140)),
             aes(xintercept = date + .1),
             color = "#456699", 
             linewidth = 1) +
  geom_vline(data = swim %>% filter(date > (today() - 140)),
             aes(xintercept = date),
             color = "#0CEBFF", 
             linewidth = 1.5,
             alpha = .25) +
  geom_ridgeline(aes(fill = sym_label, 
                     height = (value / 10),
                     color = sym_label),
                 alpha = .85) +
  geom_point(data = stretch %>% filter(date > (today() - 140)),
             aes(date, 1.5),
             color = "#FFD1F9",
             size = 6,
             shape = "+") +
  geom_text(data = k %>% filter(date > (today() - 140)),
            aes(date, 11.75, 
                label = "k"),
            size = 3,
            family = "Changa",
            color = "#310873") +
  scale_x_date(breaks = date_breaks(width = "10 days"),
               labels = date_format("%b %e"),
               expand = expansion(mult = c(.01,.01), add = c(.01,.01)),
               position = "top") +
  scale_y_discrete(limits = rev,
                   expand = expansion(mult = c(0,.05), add = c(0,1.5))) +
  scale_color_manual(values = colors,
                     guide = "none",
                     limits = c("Overall pain", "Forearm pain", 
                                "Back pain", "Fatigue",
                                "Depression", "Anxiety", "Focus Issues",
                                "Legs", "Dizziness", "Headache")) +
  scale_fill_manual(values = colors,
                    guide = "none",
                    limits = c("Overall pain", "Forearm pain", 
                               "Back pain", "Fatigue",
                               "Depression", "Anxiety", "Focus Issues",
                               "Legs", "Dizziness", "Headache")) +
  annotate(geom = "text",
           x = (today() - 20), y = 1.15,
           label = "Overall pain",
           color = "#FFD1F9",
           family = "Changa") +
  annotate(geom = "text",
           x = (today() - 10), y = 2.15,
           label = "Legs",
           color = "#FFD1F9",
           family = "Changa") +
  annotate(geom = "text",
           x = (today() - 20), y = 3.15,
           label = "Headache",
           color = "#FFD1F9",
           family = "Changa") +
  annotate(geom = "text",
           x = (today() - 10), y = 4.15,
           label = "Forearm pain",
           color = "#FFD1F9",
           family = "Changa") +
  annotate(geom = "text",
           x = (today() - 20), y = 5.15,
           label = "Focus Issues",
           color = "#FFD1F9",
           family = "Changa") +
  annotate(geom = "text",
           x = (today() - 10), y = 6.15,
           label = "Fatigue",
           color = "#310873",
           family = "Changa") +
  annotate(geom = "text",
           x = (today() - 20), y = 7.15,
           label = "Dizziness",
           color = "#FFD1F9",
           family = "Changa") +
  annotate(geom = "text",
           x = (today() - 10), y = 8.15,
           label = "Depression",
           color = "#310873",
           family = "Changa") +
  annotate(geom = "text",
           x = (today() - 20), y = 9.15,
           label = "Back pain",
           color = "#FFD1F9",
           family = "Changa") +
  annotate(geom = "text",
           x = (today() - 10), y = 10.15,
           label = "Anxiety",
           color = "#310873",
           family = "Changa") +
  annotate(geom = "text",
           x = (as.Date("2024-01-15") + .5), y = 1.22,
           label = "Stretched",
           color = "#FFD1F9",
           family = "Changa",
           alpha = .8) +
  annotate(geom = "segment",
           x = (as.Date("2024-01-17")), 
           xend = (as.Date("2024-01-19")),
           y = 1.33, yend = 1.45,
           color = "#FFD1F9",
           linewidth = .6,
           arrow = arrow(angle = 25,
                         length = unit(0.5, "lines")),
           alpha = .8) +
  # annotate(geom = "text",
  #          x = (as.Date("2023-11-20") - .5), y = 11.2,
  #          label = "S.I.",
  #          color = "#4D221F",
  #          family = "Changa") +
  # annotate(geom = "segment",
  #          x = (as.Date("2023-11-20") - .5), 
  #          xend = (as.Date("2023-11-21") - .5),
  #          y = 11.35, yend = 11.6,
  #          color = "#4D221F",
  #          linewidth = .6,
  #          arrow = arrow(angle = 25,
  #                        length = unit(0.5, "lines"))) +
  annotate(geom = "text", 
           x = (as.Date("2024-01-29")), 
           y = 11.4, 
           label = "Nightmares", 
           color = "black",
           family = "Changa") +
  annotate(geom = "segment", 
           x = (as.Date("2024-01-30")), 
           xend = (as.Date("2024-02-02") + .75), 
           y = 11.525, yend = 11.8, 
           color = "black", 
           linewidth = .6,
           arrow = arrow(angle = 25, 
                         length = unit(0.5, "lines"))) +
  annotate(geom = "text",
           x = c(as.Date("2024-02-10"), 
                 as.Date("2024-03-9")), 
           y = 11.25, 
           label = "rainbow",
           size = 3.5,
           family = "Changa",
           color = "#310873") +
  annotate(geom = "text",
           x = as.Date("2024-02-27"), y = 11.25, 
           label = "bleeding",
           size = 3.5,
           family = "Changa",
           color = "#310873") +
  labs(x = NULL,
       y = NULL,
       fill = NULL,
       color = NULL) +
  th_med +
  theme(axis.text.y = element_blank(),
        panel.grid.major = element_blank(),
        panel.border = element_rect(color = NA,
                                    linewidth = 1,
                                    fill = NA))

ggsave("stacked.png",
       device = png, type = "cairo", dpi = 300,
       width = 12, height = 12 / 1.618)

Physical Pain (Previous 30 Days)

This highlights the trends of the last 30 days for physical symptoms.

pain1 <- sym %>% 
  pivot_longer(c(overall, forearm, back, fatigue, leg, dizziness, headache)) 

pain1 %>% 
  filter(date > (today() - 30)) %>% 
  ggplot(aes(color = name)) +
  geom_line(aes(date, value, 
                linetype = name), 
            linewidth = 2) +
  geom_point(data = sym %>% filter(Swimming == "Yes", date > (today() - 30)), 
             aes(date, overall,
                 shape = Swimming),
             color = "#0E0ACC", 
             fill = "#0CEBFF", 
             size = 5.5) +
  scale_x_date(breaks = date_breaks(width = "3 days"),
               labels = date_format("%b %d"),
               expand = c(.01,.01)) +
  scale_y_continuous(breaks = seq(0,10,2),
                     limits = c(1,10)) +
  scale_color_manual(values = c("#7400CC", "#CC0AA4", "#0E0ACC", 
                                "#1471CC", "#805713", "#4F008C"),
                     limits = c("overall", "forearm", 
                                "back", "leg", 
                                "dizziness", "headache"),
                     labels = c("Overall pain", "Forearm pain", 
                                "Back pain", "Legs", 
                                "Dizziness", "Headache")) +
  scale_linetype_manual(values = c("solid", "twodash", 
                                   "twodash", "twodash", 
                                   "twodash", "twodash"), 
                        limits = c("overall", "forearm", 
                                   "back", "leg", 
                                   "dizziness", "headache"),
                        labels = c("Overall pain", "Forearm pain", 
                                   "Back pain", "Legs", 
                                   "Dizziness", "Headache")) +
  scale_shape_manual(values = 21,
                     labels = "Swimming") +
  labs(x = NULL,
       y = "Pain Level",
       color = NULL,
       linetype = NULL,
       shape = NULL,
       title = "Daily Physical Pain") +
  th_med +
  theme(panel.grid.major.x = element_blank(),
        panel.grid.major.y = element_line(color = "#3ACC14", 
                                          linetype = "dotted"),
        panel.grid.minor.x = element_blank(),
        panel.grid.minor.y = element_line(color = "#9DDD99", 
                                          linetype = "dotted"),
        legend.position = "bottom",
        legend.text = element_text(color = "#310873", 
                                   family = "Changa"))

Mental Health (Previous 30 Days)

This highlights the trends for the last 30 days for mental health symptoms.

mental <- sym %>% 
  pivot_longer(c(mood, anxiety, focus, fatigue)) 

dum <- pain %>% 
  filter(dummies == "S.I." | dummies == "Nightmares", 
         name == "mood",
         point_value == 1,
         date > (today() - 30))

mental %>% 
  filter(date > (today() - 30)) %>% 
  ggplot(aes(color = name)) +
  geom_line(aes(date, value), 
            linewidth = 2, 
            linetype = "twodash") +
  scale_x_date(breaks = date_breaks(width = "3 days"),
               labels = date_format("%b %d"),
               expand = c(.01,.01)) +
  scale_y_continuous(breaks = seq(0,10,2),
                     limits = c(1,10)) +
  scale_color_manual(values = colors2,
                     limits = c("mood", "anxiety", 
                                "focus", "fatigue"),
                     labels = c("Depression", "Anxiety", 
                                "Focus Issues", "Fatigue")) +
  geom_point(data = dum, 
             aes(date, value,
                 # color = dummies,
                 # fill = dummies,
                 # size = dummies,
                 shape = "Nightmares"),
             color = "#456699",
             size = 6
             ) +
  labs(color = NULL) +
  # new_scale_color() +
  # scale_color_manual(values = c("#700000", "black"),
  #                    labels = c("S.I.", "Nightmares"),
  #                    limits = rev) +
  # scale_fill_manual(values = c("#CC1F14", "#456699"),
  #                    labels = c("S.I.", "Nightmares"),
  #                    limits = rev) +
  # scale_size_manual(values = c(4,6),
  #                   guide = "none") +
  labs(x = NULL,
       y = "Severity Level",
       color = NULL,
       fill = NULL,
       shape = NULL,
       alpha = NULL,
       title = "Daily Mental Health") +
  # guides(fill = guide_legend(override.aes = list(size = 5)),
  #        color = guide_legend(override.aes = list(size = 5))) +
  th_med +
  theme(panel.grid.major.x = element_blank(),
        panel.grid.major.y = element_line(color = "#3ACC14", 
                                          linetype = "dotted"),
        panel.grid.minor.x = element_blank(),
        panel.grid.minor.y = element_line(color = "#9DDD99", 
                                          linetype = "dotted"),
        legend.position = "bottom",
        legend.text = element_text(color = "#310873", 
                                   family = "Changa"))

Skin

sym %>% 
  filter(cyst == 1) %>% 
  ggplot(aes(date, cyst, 
             color = activeCyst,
             fill = activeCyst)) +
  geom_vline(xintercept = c(as.Date("2023-07-22"), # end doxy
                            as.Date("2023-10-14"), # mycin/rifampin start
                            as.Date("2023-10-29"), # mycin end
                            as.Date("2023-11-12"), # rifampin end
                            as.Date("2023-11-19"), # doxy start
                            as.Date("2023-12-28"), # cyst removal
                            as.Date("2024-02-01")), # doxy end
             linewidth = .75,
             linetype = "longdash",
             color = "#310873") +
  geom_vline(xintercept = c(as.Date("2023-08-25"), # infection
                            as.Date("2023-09-24"), # start 
                            as.Date("2023-09-24") + 10), # end
             linewidth = .75,
             linetype = "longdash",
             color = "#B785DD") +
  annotate("rect",
           xmin = as.Date("2023-12-04"),
           xmax = as.Date("2023-12-07"),
           ymin = min(sym$cyst), 
           ymax = 3.75,
           fill = "#B785DD",
           alpha = .5) +
  annotate("text", 
           x = as.Date("2023-07-29") + .5,
           y = 2.3,
           label = "Doxy\nEnded",
           family = "Changa",
           color = "#310873") +
  geom_curve(x = as.Date("2023-07-29"), 
             xend = as.Date("2023-07-23"), 
             y = 2, yend = 1.75,
             curvature = -0.25,
             arrow = arrow(angle = 25,
                           length = unit(0.75, "lines")),
             color = "#310873") +
  annotate("text", 
           x = as.Date("2023-08-23") - .5,
           y = 2.25,
           label = "Wound Infection Noticed",
           family = "Changa",
           size = 3.25,
           color = "#310873",
           angle = 90) +
  annotate("text", 
           x = as.Date("2023-09-16") - .5,
           y = 2.8,
           label = "Bactrim\nStarted\n& Ended",
           family = "Changa",
           color = "#310873") +
  geom_curve(x = as.Date("2023-09-17"), 
             xend = as.Date("2023-09-23"), 
             y = 3.2, yend = 3.3,
             curvature = -0.25,
             arrow = arrow(angle = 25,
                           length = unit(0.5, "lines")),
             color = "#310873") +
  geom_curve(x = as.Date("2023-09-19"), 
             xend = as.Date("2023-09-24") + 9, 
             y = 2.35, yend = 2.25,
             curvature = 0.25,
             arrow = arrow(angle = 25,
                           length = unit(0.65, "lines")),
             color = "#310873") +
  annotate("text", 
           x = as.Date("2023-10-12") - .5,
           y = 2.4,
           label = "Clindamycin & Rifampin Started",
           family = "Changa",
           size = 3.25,
           color = "#310873",
           angle = 90) +
  annotate("text", 
           x = as.Date("2023-10-27") - .5,
           y = 2.25,
           label = "Clindamycin Stopped",
           family = "Changa",
           size = 3.25,
           color = "#310873",
           angle = 90) +
  annotate("text", 
           x = as.Date("2023-11-10") - .5,
           y = 2.25,
           label = "Rifampin Stopped",
           family = "Changa",
           size = 3.25,
           color = "#310873",
           angle = 90) +
  annotate("text", 
           x = as.Date("2023-11-17") - .5,
           y = 2.25,
           label = "Doxy Started",
           family = "Changa",
           size = 3.25,
           color = "#310873",
           angle = 90) +
  annotate("text", 
           x = as.Date("2023-12-05") + .25,
           y = 2.25,
           label = "Missed Doxy",
           family = "Changa",
           size = 3.25,
           color = "#310873",
           angle = 90) +
  annotate("text", 
           x = as.Date("2023-12-19") - .5,
           y = 2.2,
           label = "Surgical\nCyst\nRemoval",
           family = "Changa",
           color = "#310873") +
  geom_curve(x = as.Date("2023-12-20") - .5, 
             xend = as.Date("2023-12-27"), 
             y = 2.6, yend = 2.85,
             curvature = -0.25,
             arrow = arrow(angle = 25,
                           length = unit(0.75, "lines")),
             color = "#310873") +
  annotate("text", 
           x = as.Date("2024-01-25") - .5,
           y = 2.3,
           label = "Doxy\nEnded",
           family = "Changa",
           color = "#310873") +
  geom_curve(x = as.Date("2024-01-25"), 
             xend = as.Date("2024-01-31"), 
             y = 2.5, yend = 2.75,
             curvature = -0.25,
             arrow = arrow(angle = 25,
                           length = unit(0.75, "lines")),
             color = "#310873") +
  geom_point(size = 6, 
             shape = 22) +
  scale_x_date(breaks = date_breaks(width = "17 days"),
               limits = c(as.Date("2023-05-08"), today()),
               labels = date_format("%b %e"),
               expand = expansion(mult = c(0.02,0.02), 
                                  add = c(0.02,0.02))) +
  scale_y_continuous(expand = expansion(mult = c(0,0), 
                                  add = c(0,0))) +
  scale_fill_manual(values = colors) +
  scale_color_manual(values = c("#CC0AA4", "#7400CC")) +
  coord_cartesian(xlim = c(as.Date("2023-05-08"), today())) +
  labs(color = NULL,
       fill = NULL,
       title = "Skin Cysts") +
  th_med +
  theme(panel.grid.major = element_blank(),
        axis.title = element_blank(),
        axis.text.y = element_blank(),
        legend.position = "top")

# sym %>% 
#   filter(cyst == 1,
#          date > (today() - 90)) %>% 
#   ggplot(aes(date, cyst, 
#              color = activeCyst,
#              fill = activeCyst)) +
#   geom_vline(xintercept = c(as.Date("2023-10-29"), # mycin end
#                             as.Date("2023-11-12"), # rifampin end
#                             as.Date("2023-11-19"), # doxy start
#                             as.Date("2023-12-28")), # cyst removal
#              linewidth = .75,
#              linetype = "longdash",
#              color = "#310873") +
#   annotate("rect",
#            xmin = as.Date("2023-12-04"),
#            xmax = as.Date("2023-12-07"),
#            ymin = min(sym$cyst), 
#            ymax = 3.75,
#            fill = "#B785DD",
#            alpha = .5) +
#   annotate("text", 
#            x = as.Date("2023-10-28"),
#            y = 2.25,
#            label = "Clindamycin Stopped",
#            family = "Changa",
#            size = 3.25,
#            color = "#310873",
#            angle = 90) +
#   annotate("text", 
#            x = as.Date("2023-11-11"),
#            y = 2.25,
#            label = "Rifampin Stopped",
#            family = "Changa",
#            size = 3.25,
#            color = "#310873",
#            angle = 90) +
#   annotate("text", 
#            x = as.Date("2023-11-23"),
#            y = 2.5,
#            label = "Doxy\nStarted",
#            family = "Changa",
#            color = "#310873") +
#   geom_curve(x = as.Date("2023-11-23"), 
#              xend = as.Date("2023-11-19") + .5, 
#              y = 2.2, yend = 1.95,
#              curvature = -0.25,
#              arrow = arrow(angle = 25,
#                            length = unit(0.75, "lines")),
#              color = "#310873") +
#   annotate("text", 
#            x = as.Date("2023-12-05") + .4,
#            y = 2.25,
#            label = "Missed Doxy",
#            family = "Changa",
#            size = 3.25,
#            color = "#310873",
#            angle = 90) +
#   annotate("text", 
#            x = as.Date("2023-12-24"),
#            y = 1.6,
#            label = "Surgical\nCyst\nRemoval",
#            family = "Changa",
#            color = "#310873") +
#   geom_curve(x = as.Date("2023-12-24"), 
#              xend = as.Date("2023-12-27") + .5, 
#              y = 2, yend = 2.25,
#              curvature = -0.25,
#              arrow = arrow(angle = 25,
#                            length = unit(0.75, "lines")),
#              color = "#310873") +
#   geom_point(size = 6, 
#              shape = 22) +
#   scale_x_date(breaks = date_breaks(width = "1 week"),
#                limits = c((today() - 90), today()),
#                labels = date_format("%b %e"),
#                expand = expansion(mult = c(0.02,0.02), 
#                                   add = c(0.02,0.02))) +
#   scale_y_continuous(expand = expansion(mult = c(0,0), 
#                                   add = c(0,0))) +
#   scale_fill_manual(values = colors) +
#   scale_color_manual(values = c("#CC0AA4", "#7400CC")) +
#   labs(color = NULL,
#        fill = NULL,
#        title = NULL,
#        subtitle = "Last 90 days") +
#   th_med +
#   theme(panel.grid.major = element_blank(),
#         axis.title = element_blank(),
#         axis.text.y = element_blank(),
#         legend.position = "top")

Digestion

poop <- sym %>% 
  drop_na(`Bowel Movements`) %>% 
  mutate(healthy = ifelse(str_detect(`Bowel Movements`, "Healthy"), 
                          "Healthy", "Not Healthy"),
         gassy = ifelse(str_detect(`Bowel Movements`, "Gassy"), 
                        "Gassy", "Not Gassy"),
         frequent = ifelse(str_detect(`Bowel Movements`, "Frequent"),
                           "Frequent", "Not Frequent"),
         diarrhea = ifelse(str_detect(`Bowel Movements`, "Diarrhea"),
                           "Diarrhea", "No Diarrhea"),
         difficult = ifelse(str_detect(`Bowel Movements`, "Difficult"),
                           "Difficult", "Not Difficult"),
         number = factor(`Number of Bowel Movements`))

poop %>% 
  ggplot() +
  geom_point(aes(date, healthy, 
                 color = gassy, 
                 fill = gassy, 
                 size = number, 
                 shape = diarrhea)) + 
  geom_vline(xintercept = c(as.Date("2023-10-14"), 
                            as.Date("2023-10-29"),
                            as.Date("2023-11-12")),
             linewidth = .75,
             linetype = "longdash",
             color = "#310873") +
  geom_vline(data = peri,
             aes(xintercept = date),
             color = "#CC0AA4", 
             linewidth = 1.5,
             alpha = .2) +
  annotate(geom = "text",
           x = as.Date("2024-02-27"), y = 2.3, 
           label = "period",
           size = 3,
           family = "Changa",
           color = "#310873") +
  annotate("text", 
           x = as.Date("2023-10-05") - .25,
           y = 1.45,
           label = "Clindamycin\n& Rifampin\nStarted",
           family = "Changa",
           color = "#310873",
           size = 3.5) +
  geom_curve(x = as.Date("2023-10-06"), 
             xend = as.Date("2023-10-14") - .75, 
             y = 1.7, yend = 1.8,
             curvature = -0.25,
             arrow = arrow(angle = 25,
                           length = unit(0.75, "lines")),
             color = "#310873",
             size = .85) +
  annotate("text", 
           x = as.Date("2023-10-27") + .25,
           y = 1.85,
           label = "Clindamycin Stopped",
           family = "Changa",
           size = 3.25,
           color = "#310873",
           angle = 90) +
  annotate("text", 
           x = as.Date("2023-11-10") + .25,
           y = 1.85,
           label = "Rifampin Stopped",
           family = "Changa",
           size = 3.25,
           color = "#310873",
           angle = 90) +
  scale_x_date(breaks = date_breaks(width = "2 weeks"),
               limits = c(as.Date("2023-08-06"), today()),
               labels = date_format("%b %e"),
               expand = expansion(mult = c(0.02,0.02), 
                                  add = c(0.02,0.02))) +
  scale_shape_manual(values = c(21,24), limits = rev) +
  scale_size_manual(values = seq(0,20,1.5), guide = "none") +
  labs(shape = NULL,
       size = NULL) +
  new_scale("shape") +
  new_scale("size") +
  geom_point(data = poop %>% 
               filter(difficult == "Difficult"), 
             aes(date, healthy, 
                 color = gassy, 
                 fill = gassy, 
                 shape = difficult,
                 size = number)) + 
  scale_y_discrete(limits = rev) +
  scale_fill_manual(values = colors_, limits = rev) +
  scale_color_manual(values = colors_, limits = rev) +
  scale_size_manual(values = seq(4,24,1.5), guide = "none") +
  scale_shape_manual(values = c(13,1)) +
  labs(x = NULL,
       y = NULL,
       color = NULL,
       fill = NULL,
       size = NULL,
       shape = NULL,
       title = "Bowel Movements",
       subtitle = "Sized by Frequency") +
  guides(shape = guide_legend(override.aes = list(size = 6)),
         fill = guide_legend(override.aes = list(size = 6)),
         color = guide_legend(override.aes = list(size = 6))) +
  th_med +
  theme(panel.grid.major = element_blank(),
        axis.title = element_blank(),
        axis.text.y = element_text(size = 10,
                                   family = "Changa"),
        legend.position = "top")

Reproductive

periods <- sym %>% 
  select(date, starts_with("period")) %>% 
  filter(period == "Yes") 

start_days <- periods %>% 
  filter(period_day == 1) %>% 
  mutate(days_since = as.numeric(date - lag(date))) 

# start_days %>% 
#   mean(days_since)

s <- as.numeric(today() - as.numeric(max(start_days$date)))

sym %>% 
  filter(date > min(periods$date)) %>% 
  ggplot(aes(date, period_pain)) +
  geom_point(aes(fill = period_flow, color = period_flow),
             size = 5,
             shape = 23) +
  geom_line(linewidth = 1, 
            lineend = "round",
            color = "#310873",
            linetype = "longdash") +
  scale_x_date(breaks = date_breaks(width = "1 week"),
               labels = date_format("%b %e"),
               expand = expansion(mult = c(0.02,0.02), 
                                  add = c(0.02,0.02))) +
  scale_y_continuous(limits = c(1,10), 
                     breaks = seq(2,10,2)) +
  scale_color_steps2(low = "#FFF4FB",
                     mid = "#CC0AA4",
                     high = "black",
                     midpoint = 7.5,
                     breaks = seq(2,10,2)) +
  scale_fill_steps2(low = "#FFF4FB",
                     mid = "#CC0AA4",
                     high = "black",
                     midpoint = 7.5,
                     breaks = seq(2,10,2)) +
  coord_cartesian(xlim = c(min(periods$date), today())) +
  labs(x = NULL,
       y = "Pain Level",
       color = str_wrap("Flow Level", 5),
       fill = str_wrap("Flow Level", 5),
       title = "Period Pain and Flow Tracker") +
  th_med +
  theme(panel.grid.major.x = element_blank(),
        legend.text = element_text(color = "#310873", 
                                   size = 10, 
                                   family = "Cambria"),
        legend.title = element_text(color = "#310873", 
                                   size = 12, 
                                   family = "Changa"))

5 days since the start of my last period on May 13.

Interactive

This graph is interactive.

Click each symptom in the legend to toggle visibility.
Double click to toggle only the selected symptom, or double click in the panel to revert to the original.
Click and drag areas of the panel to zoom in; double click to zoom out.

symplot <- pain %>% 
  ggplot() +
  geom_vline(data = k,
             aes(xintercept = date,
                 text = "Ketamine Treatment"),
             color = "#FFFFBB", 
             linewidth = 1.5) +
  geom_vline(data = rb,
             aes(xintercept = date,
                 text = "Rainbow Gathering"),
             color = "#3ACC14", 
             linewidth = 2,
             alpha = .3) +
  geom_vline(data = peri,
             aes(xintercept = date,
                 text = "Bleeding"),
             color = "#CC0AA4", 
             linewidth = 2,
             alpha = .2) +
  # geom_text(data = k,
  #           aes(date, .15, 
  #               label = "k",
  #               text = "Ketamine Treatment"),
  #           size = 3,
  #          family = "Changa",
  #          color = "#310873") +
  geom_line(aes(date, value, 
                color = sym_label,
                linetype = sym_label), 
            linewidth = 1) +
  geom_point(aes(date, value, 
                 color = sym_label,
                 text = tip_line), 
             size = .1) +
  geom_point(data = pain %>% filter(point_value == 1, 
                                    name == "overall"), 
             aes(date, case_when(dummies == "Nightmares" ~ 1.85,
                                 dummies == "S.I." ~ 1.4,
                                 dummies == "Skin Cyst" ~ .95,
                                 dummies == "Swimming" ~ .5),
                 fill = dummies,
                 text = tip_point),
             size = 3, alpha = .75) +
  scale_x_date(#breaks = date_breaks(width = "7 days"),
               labels = date_format("%b %e"),
               expand = expansion(mult = c(0,0), add = c(0,0))) +
  scale_y_continuous(breaks = seq(0,10,2)) +
  scale_color_manual(values = colors,
                     limits = c("Overall pain", "Forearm pain", 
                                "Back pain", "Fatigue",
                                "Depression", "Anxiety", 
                                "Focus Issues", "Legs", 
                                "Dizziness", "Headache",
                                "Productivity")) +
  scale_linetype_manual(values = c("solid", "twodash", 
                                   "twodash", "twodash", 
                                   "twodash", "twodash", 
                                   "twodash", "twodash", 
                                   "twodash", "twodash",
                                   "dotted"), 
                        limits = c("Overall pain", "Forearm pain", 
                                   "Back pain", "Fatigue",
                                   "Depression", "Anxiety", 
                                   "Focus Issues", "Legs", 
                                   "Dizziness", "Headache",
                                   "Productivity")) +
  scale_fill_manual(values = c("#456699", "#CC1F14", "#CC1483", "#0CEBFF")) +
  scale_shape_manual(values = c(21,22,23)) +
  labs(x = NULL,
       y = "Severity Level",
       color = NULL,
       fill = NULL,
       linetype = NULL,
       title = "Daily Symptoms") +
  theme_light() + 
  theme(panel.border = element_blank(),
        panel.grid.major.x = element_blank(),
        panel.grid.major.y = element_line(color = "#9DDD99"),
        axis.text = element_text(color = "#310873",
                                 family = "Cambria"),
        axis.title = element_text(color = "#310873"),
        axis.ticks = element_blank(),
        plot.title = element_text(color = "#310873",
                                  size = 14,
                                  face = "bold"))

p <- ggplotly(symplot, tooltip = "text", dynamicTicks = TRUE) 

p$x$data[[1]]$legendgroup <- p$x$data[[1]]$name
p$x$data[[1]]$name <- "Ketamine"

p$x$data[[2]]$legendgroup <- p$x$data[[2]]$name
p$x$data[[2]]$name <- "Rainbow"

p$x$data[[3]]$legendgroup <- p$x$data[[3]]$name
p$x$data[[3]]$name <- "Bleeding"

p$x$data[[4]]$legendgroup <- p$x$data[[4]]$name
p$x$data[[4]]$name <- "Anxiety"

p$x$data[[5]]$legendgroup <- p$x$data[[5]]$name
p$x$data[[5]]$name <- "Back Pain"

p$x$data[[6]]$legendgroup <- p$x$data[[6]]$name
p$x$data[[6]]$name <- "Depression"

p$x$data[[7]]$legendgroup <- p$x$data[[7]]$name
p$x$data[[7]]$name <- "Dizziness"

p$x$data[[8]]$legendgroup <- p$x$data[[8]]$name
p$x$data[[8]]$name <- "Fatigue"

p$x$data[[9]]$legendgroup <- p$x$data[[9]]$name
p$x$data[[9]]$name <- "Focus Issues"

p$x$data[[10]]$legendgroup <- p$x$data[[10]]$name
p$x$data[[10]]$name <- "Forearm pain"

p$x$data[[11]]$legendgroup <- p$x$data[[11]]$name
p$x$data[[11]]$name <- "Headache"

p$x$data[[12]]$legendgroup <- p$x$data[[12]]$name
p$x$data[[12]]$name <- "Legs"

p$x$data[[13]]$legendgroup <- p$x$data[[13]]$name
p$x$data[[13]]$name <- "Overall Pain"

p$x$data[[14]]$legendgroup <- p$x$data[[14]]$name
p$x$data[[14]]$name <- "Productivity"

p$x$data[[26]]$legendgroup <- p$x$data[[26]]$name
p$x$data[[26]]$name <- "Nightmares"

p$x$data[[27]]$legendgroup <- p$x$data[[27]]$name
p$x$data[[27]]$name <- "S.I."

p$x$data[[28]]$legendgroup <- p$x$data[[28]]$name
p$x$data[[28]]$name <- "Skin Cyst"

p$x$data[[29]]$legendgroup <- p$x$data[[29]]$name
p$x$data[[29]]$name <- "Swimming"

p

Storytime

p2 <- pain %>% 
  filter(name != "dizziness",
         name != "leg",
         name != "productivity") %>% 
  mutate(sym_label = str_wrap(sym_label, 8),
         value = factor(value)) 

p2 %>% 
  ggplot() +
  geom_tile(aes(sym_label, date, 
                fill = sym_label)) +
  geom_tile(aes(sym_label, date,
                alpha = value),
            fill = "white") +
  scale_alpha_manual(values = c("1" = .95,
                                "2" = .85,
                                "3" = .5,
                                "4" = .25,
                                "5" = .01,
                                "6" = 0,
                                "7" = 0,
                                "8" = 0,
                                "9" = 0,
                                "10" = 0),
                     guide = "none") +
  new_scale("alpha") +
  geom_tile(aes(sym_label, date,
                alpha = value),
            fill = "black") +
  scale_alpha_manual(values = c("1" = 0,
                                "2" = 0,
                                "3" = 0,
                                "4" = 0,
                                "5" = 0,
                                "6" = 0,
                                "7" = .05,
                                "8" = .1,
                                "9" = .5,
                                "10" = .5),
                     guide = "none") +
  geom_tile(data = p2 %>% filter(value != "10",
                                 value != "1"),
            aes(sym_label, date,
                fill = sym_label),
            alpha = .075) +
  scale_x_discrete(position = "top") +
  scale_y_date(breaks = date_breaks(width = "2 weeks"),
               labels = date_format("%b %d"),
               expand = c(0,0)) +
  scale_fill_manual(values = colors3, 
                    guide = "none") +
  labs(x = NULL,
       y = NULL,
       alpha = NULL,
       title = "Symptoms Tell the Story") +
  th_med +
  theme(panel.grid.major.y = element_blank(),
        axis.text.x = element_text(family = "Changa", 
                                   size = 11))

ggsave("story.jpg", height = 18, width = 6.5,
       device = png, type = "cairo", dpi = 300)

Location Based Mood

sts <- sym %>% 
  group_by(state) %>% 
  summarise(mean_mood = mean(mood),
            mean_angst = mean(anxiety),
            mean_head = mean(headache),
            mean_focus = mean(focus),
            mean_prod = mean(productivity),
            mean_pain = mean(overall),
            mean_back = mean(back),
            mean_arm = mean(forearm),
            mean_fati = mean(fatigue),
            n = n()) %>% 
  filter(n > 2)

sts_k <- sym %>% 
  group_by(state, after_k) %>% 
  summarise(mean_mood = mean(mood),
            mean_angst = mean(anxiety),
            mean_head = mean(headache),
            mean_focus = mean(focus),
            mean_prod = mean(productivity),
            mean_pain = mean(overall),
            mean_back = mean(back),
            mean_arm = mean(forearm),
            mean_fati = mean(fatigue),
            n = n()) %>% 
  filter(n > 2)

sts_k %>% 
  ggplot(aes(reorder(state, mean_mood), mean_mood, 
             fill = state, color = after_k)) +
  geom_col(position = position_dodge(width = .5)) +
  scale_y_continuous(breaks = seq(0,10,2), 
                     limits = c(0,10)) +
  scale_fill_manual(values = colors) +
  scale_color_manual(values = c("white", "white"), guide = "none") +
  annotate("text",
           x = 1.86,
           y = 4.45,
           label = "Before K Treatment",
           angle = 90,
           family = "Cambria",
           color = "white",
           size = 4.5) +
  annotate("text",
           x = 2.11,
           y = 1.11,
           label = "After",
           angle = 90,
           family = "Cambria",
           color = "white",
           size = 4.5) +
  labs(x = NULL,
       y = "Average Depression Severity",
       fill = NULL,
       color = NULL,
       title = "Depression by State",
       subtitle = "for states where I spent more than 2 days") +
  th_med +
  theme(panel.grid.major.x = element_blank())

ggsave("states_mood.jpg", height = 8 / 1.618, width = 8,
       device = png, type = "cairo", dpi = 300)

sts_k %>% 
  ggplot(aes(reorder(state, mean_angst), mean_angst, 
             fill = state, color = after_k)) +
  geom_col(position = position_dodge(width = .5)) +
  scale_y_continuous(breaks = seq(0,10,2), 
                     limits = c(0,10)) +
  scale_fill_manual(values = colors) +
  scale_color_manual(values = c("white", "white"), guide = "none") +
  annotate("text",
           x = 2.875,
           y = 4.9,
           label = "Before K Treatment",
           angle = 90,
           family = "Cambria",
           color = "white",
           size = 4) +
  annotate("text",
           x = 3.125,
           y = 1.55,
           label = "After",
           angle = 90,
           family = "Cambria",
           color = "white",
           size = 4) +
  labs(x = NULL,
       y = "Average Anxiety Severity",
       fill = NULL,
       title = "Anxiety by State",
       subtitle = "for states where I spent more than 2 days") +
  th_med +
  theme(panel.grid.major.x = element_blank())

ggsave("states_angst.jpg", height = 8 / 1.618, width = 8,
       device = png, type = "cairo", dpi = 300)

Correlations and other stats

Ketamine

since <- as.numeric(today() - k_end - 1)

before <- sym %>% 
  filter(date < k_start,
         date > (k_start - since)) %>% 
  summarise(n = n()) %>% 
  pluck(1,1)

after <- sym %>% 
  filter(date > k_end) %>% 
  summarise(n = n()) %>% 
  pluck(1,1)

night_before <- sym %>% 
  filter(date < k_start,
         date > (k_start - since)) %>% 
  group_by(night) %>% 
  summarise(n = n()) %>% 
  pluck(2,2)

night_after <- sym %>% 
  filter(date > k_end) %>% 
  group_by(night) %>% 
  summarise(n = n()) %>% 
  pluck(2,2)

si_before <- sym %>% 
  filter(date < k_start,
         date > (k_start - since)) %>% 
  group_by(si) %>% 
  summarise(n = n()) %>% 
  pluck(2,2)

si_after <- sym %>% 
  filter(date > k_end) %>% 
  group_by(si) %>% 
  summarise(n = n()) %>% 
  pluck(2,2) 

si_after <- ifelse(is.null(si_after), 0, si_after)

k_si_night_ <- data.frame(name = c("Nightmares", "Nightmares",
                                   "Suicidal Ideation", "Suicidal Ideation"),
                          time = c("Before", "After",
                                   "Before", "After"),
                          value = c(night_before, night_after,
                                    si_before, si_after))

k_si_night <- k_si_night_ %>% 
  mutate(rate = (value / (since)) * 100)

k_si_night %>% 
  ggplot(aes(name, rate, fill = reorder(time, desc(time)))) +
  geom_col(position = position_dodge()) +
  geom_text(data = k_si_night %>% filter(time == "Before"),
            aes(name,
                rate + 2, 
                label = paste0(round(rate, 1), "%")),
            family = "Changa",
            size = 8,
            color = "#CC0AA4",
            nudge_x = -.2) +
  geom_text(data = k_si_night %>% filter(time == "After"),
            aes(name,
                rate + 2, 
                label = paste0(round(rate, 1), "%")),
            family = "Changa",
            size = 7.5,
            color = "#CC0AA4",
            nudge_x = .24) +
  scale_y_continuous(labels = label_percent(scale = 1),
                     breaks = seq(0, 100, 5)) +
  scale_fill_manual(values = colors_) +
  labs(x = NULL,
       y = "Rate",
       fill = NULL,
       title = "Nightmares and S.I. Before and After Ketamine Treatment",
       caption = paste0("Before includes ", 
                        since, 
                        " days before treatment began; After includes ", 
                        since, 
                        " days since treatment ended.")) +
  th_med +
  theme(panel.grid.major.x = element_blank(),
        legend.position = "bottom",
        axis.text.x = element_text(family = "Changa",
                                   size = 12))

ggsave("ksinight.png",
       device = png, type = "cairo", dpi = 300,
       width = 8, height = (8 / 1.618))

k_ <- sym %>% 
  mutate(before_k = date < k_start,
         after_k = date > k_end) %>% 
  filter(date < k_start | date > k_end,
         date > (k_start - (since))) %>% 
  group_by(after_k) %>% 
  summarise(mood = mean(mood),
            anxiety = mean(anxiety),
            focus = mean(focus),
            fatigue = mean(fatigue),
            dizziness = mean(dizziness, na.rm = TRUE),
            headache = mean(headache)) %>% 
  pivot_longer(c(mood:headache)) 

k_2 <- k_ %>% 
  mutate(date = ifelse(after_k == TRUE, 
                       "After", 
                       "Before")) %>% 
  select(!after_k) %>% 
  pivot_wider(names_from = date, 
              values_from = value) %>% 
  mutate(change = Before - After,
         pctChange = ((After - Before) / Before) * 100)

# k_ %>% 
#   ggplot() +
#   geom_col(aes(name, value, fill = after_k),
#            position = position_dodge()) +
#   geom_text(data = k_2,
#             aes(name,
#                 1.15, 
#                 label = paste0("-", round(change, 1))),
#             family = "Changa",
#             size = 8.5,
#             color = "#0ACCC5") +
#   geom_text(data = k_2,
#             aes(name,
#                 .4, 
#                 label = paste0(round(pctChange, 0), "%")),
#             family = "Changa",
#             size = 6,
#             color = "#0ACCC5") +
#   geom_text(data = k_ %>% filter(after_k == FALSE),
#             aes(name, 
#                 value - .75,
#                 label = round(value, 1)),
#             family = "Changa",
#             size = 4.5,
#             color = "#D2B3FF",
#             nudge_x = -.22) +
#   geom_text(data = k_ %>% filter(after_k == TRUE),
#             aes(name, 
#                 value - .75,
#                 label = round(value, 1)),
#             family = "Changa",
#             size = 4.5,
#             color = "#FFD1F9",
#             nudge_x = .22) +
#   scale_x_discrete(labels = c("Anxiety", "Dizziness", 
#                               "Fatigue", "Focus Issues", 
#                               "Headache", "Depression")) + 
#   scale_y_continuous(limits = c(0,10),
#                      breaks = seq(2,10,2)) +
#   scale_fill_manual(values = colors,
#                     labels = c("Before Treatment",
#                                "After Treatment")) +
#   labs(x = NULL,
#        y = "Average Value",
#        fill = NULL,
#        title = "Other Symptoms Before and After Ketamine Treatment",
#        caption = paste0("Before includes ", 
#                         since, 
#                         " days before treatment began; After includes ", 
#                         since, 
#                         " days since treatment ended.")) +
#   th_med +
#   theme(legend.position = "bottom",
#         panel.grid.major.x = element_blank(),
#         axis.text.x = element_text(family = "Changa",
#                                    size = 10))
# 
# ggsave("ksince.png",
#        device = png, type = "cairo", dpi = 300,
#        width = 8, height = (8 / 1.618))

k_mh <- sym %>%
  mutate(before_k = date < k_start,
         after_k = date > k_end) %>%
  filter(date < k_start | date > k_end,
         date > (k_start - since)
         ) %>%
  group_by(after_k) %>%
  summarise(mood = mean(mood),
            anxiety = mean(anxiety),
            focus = mean(focus)) %>%
  pivot_longer(c(mood:focus))

k_mh2 <- k_mh %>%
  mutate(date = ifelse(after_k == TRUE,
                       "After",
                       "Before")) %>%
  select(!after_k) %>%
  pivot_wider(names_from = date,
              values_from = value) %>%
  mutate(change = Before - After) %>%
  mutate(change = Before - After,
         pctChange = ((After - Before) / Before) * 100)

k_mh %>%
  ggplot() +
  geom_col(aes(name, value, fill = after_k),
           position = position_dodge()) +
  geom_text(data = k_mh2,
            aes(name,
                1,
                label = paste0("-", round(change, 1))),
            family = "Changa",
            size = 9,
            color = "#0ACCC5") +
  geom_text(data = k_mh %>% filter(after_k == FALSE),
            aes(name,
                value - .75,
                label = round(value, 1)),
            family = "Changa",
            size = 5,
            color = "#D2B3FF",
            nudge_x = -.22) +
  geom_text(data = k_mh %>% filter(after_k == TRUE),
            aes(name,
                value - .75,
                label = round(value, 1)),
            family = "Changa",
            size = 5,
            color = "#FFD1F9",
            nudge_x = .22) +
  geom_text(data = k_mh2,
            aes(name,
                .3,
                label = paste0(round(pctChange, 0), "%")),
            family = "Changa",
            size = 6,
            color = "#0ACCC5") +
  scale_x_discrete(labels = c("Anxiety",
                              "Focus Issues",
                              "Depression")) +
  scale_y_continuous(limits = c(0,10),
                     breaks = seq(2,10,2)) +
  scale_fill_manual(values = colors,
                    labels = c("Before Treatment",
                               "After Treatment")) +
  labs(x = NULL,
       y = "Average Value",
       fill = NULL,
       title = "Before and After Ketamine Treatment",
       caption = paste0("Before includes ",
                        since,
                        " days before treatment began; After includes ",
                        since,
                        " days since treatment ended.")) +
  th_med +
  theme(legend.position = "bottom",
        panel.grid.major.x = element_blank(),
        axis.text.x = element_text(family = "Changa",
                                   size = 10),
        plot.caption = element_text(size = 8))

ggsave("ksince_mh.png",
       device = png, type = "cairo", dpi = 300,
       width = 8, height = (8 / 1.618))

Nightmares and S.I.

sin <- sym %>% 
  select(night, si, overall) %>% 
  mutate(both = ifelse(night == 1 & si == 1, 1, 0),
         nightonly = ifelse(night == 1 & si == 0, 1, 0),
         sionly = ifelse(night == 0 & si == 1, 1, 0),
         none = ifelse(night == 0 & si == 0, 1, 0),
         status = case_when(night == 1 & si == 1 ~ str_wrap("Nightmares and S.I.", 10),
                            night == 1 & si == 0 ~ str_wrap("Nightmares Only", 10),
                            night == 0 & si == 1 ~ "S.I. Only",
                            night == 0 & si == 0 ~ str_wrap("Neither Nightmares nor S.I.", 18)))

sin %>% 
  filter(none != 1) %>% 
  ggplot(aes(status, fill = overall, group = overall)) +
  geom_bar() +
  scale_y_continuous(breaks = seq(0,200,10)) +
  scale_x_discrete(limits = rev) +
  scale_fill_steps2(low = "#E9E4FC",
                    mid = "#6610F2",
                    high = "black",
                    midpoint = 7.5,
                    breaks = seq(1,10,1)) +
  labs(x = NULL,
       y = "Days",
       fill = "Overall Pain") +
  th_med +
  theme(axis.title.x = element_blank(),
        axis.text.x = element_text(family = "Changa"),
        panel.grid.major.x = element_blank(),
        legend.position = "top")

Density

pain %>% 
  filter(name != "productivity") %>% 
  ggplot(aes(value, sym_label)) +
  geom_density_ridges(aes(fill = sym_label), 
                      color = "white",
                      alpha = .75) +
  scale_fill_manual(values = colors,
                    guide = "none",
                    limits = c("Overall pain", "Forearm pain", 
                               "Back pain", "Fatigue",
                               "Depression", "Anxiety", "Focus Issues",
                               "Legs", "Dizziness", "Headache")) +
  scale_x_continuous(breaks = seq(1,10,1),
                     limits = c(1,11.25),
                     expand = expansion(mult = 0, add = 0)) +
  scale_y_discrete(limits = rev) +
  labs(x = "Severity",
       y = NULL,
       title = "Density of Severity Levels by Symptoms") +
  th_med +
  theme(panel.grid.major.x = element_line(linetype = "dotted", 
                                          color = "#FFD1F9"))

Pain and Mood

fmt1 <- "~ {p == %.3f}"

mod <- lm(mood ~ overall, data = sym)
sum <- summary(mod)
lab <- sprintf(fmt1, coef(sum)[8])

sym %>% 
  ggplot(aes(overall, mood)) +
  geom_smooth(method = "lm", 
              color = "#7400CC", 
              fill = "#CCB1FA") +
  geom_jitter(aes(color = anxiety), 
              size = 3, 
              alpha = .75,
              position = position_jitter(width = 0.35, 
                                         height = 0.35, 
                                         seed = 80085)) +
  annotate("text", x = 9.5, y = 1.5, 
           label = lab, 
           parse = TRUE, 
           hjust = 0, 
           color = "#7400CC", 
           family = "Cambria", 
           size = 5) +
  scale_x_continuous(limits = c(4,10.5), 
                     breaks = seq(1,10,1)) +
  scale_y_continuous(limits = c(1,10.5), 
                     breaks = seq(1,10,1)) +
  scale_color_steps2(low = "#E9E4FC",
                     mid = "#6610F2",
                     high = "black",
                     midpoint = 7.5) +
  labs(x = "Overall Pain",
       y = "Depression",
       fill = "Anxiety",
       title = "Overall pain and Depressed mood") +
  th_med

model <- lm(si ~ overall,
            data = sym)
model2 <- lm(si ~ forearm,
             data = sym)
model3 <- lm(si ~ back,
             data = sym)

my_gof <- tribble(
  ~raw, ~clean, ~fmt,
  "nobs", "N", 0)

modelsummary(list(model, model2, model3),
             output = "kableExtra",
             estimate = "{estimate}{stars}",
             statistic = "statistic",
             fmt =  2,
             gof_map = my_gof) %>% 
  row_spec(c(3,5,7), background = "#CCB1FA")

Table 1: Pain and S.I.
	(1)	(2)	(3)
(Intercept)	−0.41*	−0.57***	0.42***
	(−2.31)	(−7.95)	(3.52)
overall	0.07***
	(3.51)
forearm		0.10***
		(11.26)
back			−0.02+
			(−1.80)
N	377	377	377

# sym %>% 
#   ggplot(aes(si)) +
#   geom_density(fill = "#7400CC") +
#   th_med
# 
# m1 <- stan_glm(si ~ mood, 
#                data = sym, 
#                family = binomial,
#                chains = 4, iter = 5000*2, seed = 84735)
# 
# tidy(m1)
# 
# color_scheme_set("purple")
# ppc_dens_overlay(y = sym$si,
#                  yrep = posterior_predict(m1, 
#                                           draws = 50)) +
#   th_med
# 
# mood_b <- k_2 %>% 
#   pluck(2,1)
# mood_a <- k_2 %>% 
#   pluck(3,1)
# 
# mini <- expand_grid(mood = c(mood_b, mood_a))
# 
# m1 %>%
#   gather_draws(mood) %>%
#   ggplot(aes(.value, .variable)) +
#   stat_dotsinterval(.width = c(.8,.95),
#                     color = "#7400CC",
#                     size = 5) +
#   # scale_y_continuous(limits = c(0,1),
#   #                    breaks = seq(0,1,.2),
#   #                    labels = label_percent()) +
#   th_med

set.seed(05062023)

fmt <- "%s: ~ {p == %.3f}"

mod1o <- lm(si ~ overall, data = sym)
sum1o <- summary(mod1o)
lab1o <- sprintf(fmt, "S.I. (pink)", coef(sum1o)[8])

mod2o <- lm(night ~ overall, data = sym)
sum2o <- summary(mod2o)
lab2o <- sprintf(fmt, "Nightmares (purple)", coef(sum2o)[8])

mod1f <- lm(si ~ forearm, data = sym)
sum1f <- summary(mod1f)
lab1f <- sprintf(fmt, "S.I. (pink)", coef(sum1f)[8])

mod2f <- lm(night ~ forearm, data = sym)
sum2f <- summary(mod2f)
lab2f <- sprintf(fmt, "Nightmares (purple)", coef(sum2f)[8])

lab1 <- "S.I."
lab2 <- "Nightmares"

min_both <- min(c(min(sym$overall), min(sym$forearm)))

o <- sym %>% 
  ggplot(aes(overall, si)) +
  geom_smooth(aes(overall, night), 
              method = "lm", 
              color = "#7400CC", 
              fill = "#CCB1FA") +
  geom_smooth(method = "lm", 
              color = "#CC0AA4", 
              fill = "#FFD1F9") +
  geom_jitter(aes(color = productivity), 
              size = 3, 
              position = position_jitter(width = .35, 
                                         height = .35)) +
  annotate("text", 
           x = min_both + .5,
           y = c(1.2, 1),
           label = c(lab1, lab2),
           parse = TRUE, 
           hjust = 0, 
           color = c("#CC0AA4", "#7400CC"), 
           family = "Cambria", 
           face = "bold",
           size = 4) +
  scale_x_continuous(breaks = seq(1,10,1),
                     expand = expansion(mult = c(0.01,0.01), 
                                        add = c(0.01,0.01))) +
  scale_y_continuous(breaks = seq(0,1,1), 
                     labels = c("No", "Yes")) +
  coord_cartesian(xlim = c(min_both, 10.5), 
                  ylim = c(-.25,1.5)) +
  scale_color_stepsn(colors = c("#C3DEC8", "#A8DD9B", "#6FD555", 
                                "#3ACC14", "#4CB045", "#2F660F"),
                     n.breaks = 6) +
  labs(x = "Overall Pain",
       y = "S.I.",
       color = "Pro-\nduct-\nivity") +
  th_med +
  theme(panel.grid.major.y = element_blank())

f <- sym %>% 
  ggplot(aes(forearm, si)) +
  geom_smooth(aes(forearm, night), 
              method = "lm", 
              color = "#7400CC", 
              fill = "#CCB1FA") +
  geom_smooth(method = "lm", 
              color = "#CC0AA4", 
              fill = "#FFD1F9") +
  geom_jitter(aes(color = productivity), 
              size = 3,
              position = position_jitter(width = 0.35, 
                                         height = .35)) +
  annotate("text", 
           x = min_both + .5, 
           y = c(1.2, 1),
           label = c(lab1, lab2), 
           parse = TRUE, 
           hjust = 0, 
           color = c("#CC0AA4", "#7400CC"), 
           family = "Cambria", 
           face = "bold",
           size = 4) +
  scale_x_continuous(breaks = seq(1,10,1),
                     expand = expansion(mult = c(0.01,0.01), 
                                        add = c(0.01,0.01))) +
  scale_y_continuous(breaks = seq(0,1,1), 
                     labels = c("No", "Yes")) +
  coord_cartesian(xlim = c(min_both, 10.5), 
                  ylim = c(-.25,1.5)) +
  scale_color_stepsn(colors = c("#C3DEC8", "#A8DD9B", "#6FD555", 
                                "#3ACC14", "#4CB045", "#2F660F"),
                     n.breaks = 6) +
  labs(x = "Forearm Pain",
       y = "S.I.",
       color = "Pro-\nduct-\nivity") +
  th_med +
  theme(panel.grid.major.y = element_blank())

(o / f) +
  plot_layout(guides = "collect") &
  theme(legend.position = "left")

Other Correlations

mod3 <- lm(fatigue ~ overall, data = sym)
sum3 <- summary(mod3)
lab3 <- sprintf(fmt1, coef(sum3)[8])

sym %>% 
  ggplot(aes(overall, fatigue)) +
  geom_smooth(method = "lm", color = "#7400CC", fill = "#CCB1FA") +
  geom_jitter(aes(color = focus), 
              size = 3, 
              alpha = .75,
              position = position_jitter(width = 0.35, 
                                         height = 0.35, 
                                         seed = 80085)) +
  annotate("text", 
           x = 9.5, y = 4.5, 
           label = lab3, 
           parse = TRUE, 
           hjust = 0, 
           color = "#7400CC", 
           family = "Cambria", 
           size = 5) +
  scale_x_continuous(limits = c(4,10.5), 
                     breaks = seq(1,10,1)) +
  scale_y_continuous(limits = c(4,10.5), 
                     breaks = seq(1,10,1)) +
  scale_color_steps2(low = "#E9E4FC",
                     mid = "#6610F2",
                     high = "black",
                     midpoint = 7.5) +
  labs(x = "Overall Pain",
       y = "Fatigue",
       fill = "Focus Issues",
       title = "Overall Pain and Fatigue") +
  th_med

mod4 <- lm(focus ~ overall, data = sym)
sum4 <- summary(mod4)
lab4 <- sprintf(fmt1, coef(sum4)[8])

sym %>% 
  ggplot(aes(overall, focus)) +
  geom_smooth(method = "lm", color = "#7400CC", fill = "#CCB1FA") +
  geom_jitter(aes(color = fatigue), 
              size = 3, 
              alpha = .75,
              position = position_jitter(width = 0.35, 
                                         height = 0.35, 
                                         seed = 80085)) +
  annotate("text", 
           x = 9.5, y = 1.5, 
           label = lab4, 
           parse = TRUE, 
           hjust = 0, 
           color = "#7400CC", 
           family = "Cambria", 
           size = 5) +
  scale_x_continuous(limits = c(4,10.5), 
                     breaks = seq(1,10,1)) +
  scale_y_continuous(limits = c(1,10.5), 
                     breaks = seq(1,10,1)) +
  scale_color_steps2(low = "#E9E4FC",
                     mid = "#6610F2",
                     high = "black",
                     midpoint = 8) +
  labs(x = "Overall Pain",
       y = "Focus Issues",
       fill = "Fatigue",
       title = "Overall pain and Focus issues") +
 th_med

mod5 <- lm(focus ~ fatigue, data = sym)
sum5 <- summary(mod5)
lab5 <- sprintf(fmt1, coef(sum5)[8])

sym %>% 
  ggplot(aes(fatigue, focus)) +
  geom_smooth(method = "lm", 
              color = "#7400CC", 
              fill = "#CCB1FA") +
  geom_jitter(aes(color = overall), 
              size = 3, 
              alpha = .75,
              position = position_jitter(width = 0.35, 
                                         height = 0.35, 
                                         seed = 80085)) +
  annotate("text", 
           x = 9.5, y = 1.5, 
           label = lab5, 
           parse = TRUE, 
           hjust = 0, 
           color = "#7400CC", 
           family = "Cambria", 
           size = 5) +
  scale_x_continuous(limits = c(4,10.5), 
                     breaks = seq(1,10,1)) +
  scale_y_continuous(limits = c(1,10,1), 
                     breaks = seq(1,10,1)) +
  scale_color_steps2(low = "#E9E4FC",
                     mid = "#6610F2",
                     high = "black",
                     midpoint = 8) +
  labs(x = "Fatigue",
       y = "Focus Issues",
       fill = "Overall Pain",
       title = "Fatigue and Focus issues") +
  th_med

model <- lm(focus ~ overall,
            data = sym)
model2 <- lm(focus ~ mood,
             data = sym)
model3 <- lm(focus ~ fatigue,
             data = sym)

my_gof <- tribble(
  ~raw, ~clean, ~fmt,
  "nobs", "N", 0)

modelsummary(list(model, model2, model3),
             output = "kableExtra",
             estimate = "{estimate}{stars}",
             statistic = "statistic",
             fmt =  2,
             gof_map = my_gof) %>% 
  row_spec(c(3,5), background = "#CCB1FA") %>% 
  row_spec(7, background = "#7400CC", color = "white")

Table 2: Focus Issues
	(1)	(2)	(3)
(Intercept)	4.14**	2.87***	−1.75***
	(3.30)	(13.97)	(−3.43)
overall	0.18
	(1.31)
mood		0.55***
		(16.67)
fatigue			0.98***
			(15.13)
N	377	377	377

History Highlights

General info

38 y/o
Female
White/Jewish
Married
5’5”
~297 lbs
Pansexual
Moderate caffeine use
Every day smoker since age 14
No alcohol
Daily cannabis use for pain since 2016
Not pregnant and no desire for children
1 pregnancy, stillborn at 42 weeks 08/2006 (age 21)

Family history

brother (32): type 1 diabetes (diagnosed at age 11), ADHD, additional mental health issues
brother (36): type 1 diabetes and celiac (diagnosed in 30s)
sister (27): mental health issues, obesity, chronic back pain (disk issues), hidradenitis suppuritiva
father (64): obesity, gastric bypass, alcoholism, substance abuse, opiate dependency, narcissism, likely additional unknown and undiagnosed mental health issues
mother (62): obesity, type 2 diabetes, arthritis
paternal grandmother (deceased): lupus, bipolar
paternal grandfather (deceased): unknown
paternal aunt (deceased): breast cancer (diagnosed age ~40, died at age ~43)
paternal aunt (deceased): unknown
maternal grandmother (deceased): unknown psychiatric issues, chronic back pain, carpal tunnel syndrome, opiate dependency
maternal grandfather (deceased): relatively healthy to my knowledge, died of intestinal disease (unsure of specifics)
maternal uncle: unknown
maternal uncle (deceased): COVID-19

Symptoms/Diagnoses

Constant electric, shooting pain from my abdomen to my right thigh, numbness of the top and outer area of my right thigh, disrupting sleep, painful to empty bladder, reducing mobility
- since 10/12/2023
Chronic and increasing pain in both forearms (spreading to wrists and hands)
- since 12/2021
Chronic back pain varying from moderate to severe, but always present
- since 2015
Chronic and debilitating fatigue
- since 2019
Limited mobility and inability to complete many regular daily activities without assistance
- since 2020
Obesity and increased weight gain due to mobility issues and pain
- since 2022
Various other intermittent issues
- Recurring subcutaneous cyst (neck)
  - since 02/2022
- Hidradenitis suppuritiva
  - since 2018 (diagnosed 2022)
- Cutaneous lupus
  - diagnosed 06/2020
Mental health
- GAD
  - since 2018
- SAD/Agoraphobia
  - since 07/2019
- Depression
  - since age 11
- ADHD
  - diagnosed age 7
- PTSD
  - since 11/2006
- Nightmares
  - since 2005
- SI
  - since age 11
Hepatitis C
- diagnosed 2011
- treated with Harvoni in 2015
- no viral load detected since 2015

Recent Imaging

MRI - 11/07/2023
- Brain
  - All clear
- Lumbar
  - Herniated disks L3/L4/L5
Back X-ray - 10/24/2023
- All clear
MRI - 06/08/2023
- Lumbar, Thoracic, Cervical
  - No evidence of cord compression
Chest X-ray - 06/08/2023
- All clear
CT - 06/07/2023
- No evidence of muscle inflammation or breakdown
Upper limbs X-ray - 05/31/2023
- All clear

Medications and Providers

gs4_deauth()

meds <- read_sheet("https://docs.google.com/spreadsheets/d/10jHvDuHzhdgbULzjpjv14cypUSejCKa4GL92owiFsDQ/edit#gid=932747361", sheet = "meds") %>% 
  mutate(amount = ifelse(amount > 1, as.character(round(amount, 1)), as.character(amount)))

meds %>% 
  mutate(`per day` = ifelse(is.na(`per day`), "", `per day`)) %>% 
  gt() %>% 
  tab_header("Current Medications") %>%
  cols_align(align = c("center"),
             columns = everything()) %>% 
  cols_label(medication = html("<b>Medication</b>"),
             amount = html("<b>Amount</b>"),
             unit = html("<b>Unit</b>"),
             `per day` = html("<b>Per day</b>"),
             time = html("<b>Time of day</b>"),
             specialty = html("<b>Prescriber</b>"),
             reason = html("<b>Reason</b>"))

Medication	Amount	Unit	Per day	Time of day	Prescriber	Reason
Current Medications
Venlafaxine	150	mg	1	AM	Psychiatry	depression
Hydroxychloroquine	200	mg	2	AM/PM	Rheumatology	cutaneous lupus
Pregabalin	200	mg	3	AM/lunch/PM	Orthopedic	pain
Prazosin	2	mg	1	PM	Psychiatry	nightmares
Nortriptyline	20	mg	1	PM	Neurology	nerve pain
Meloxicam	15	mg		PRN	Rheumatology	pain
Tizanidine	2	mg		PRN	Pain Management	pain
Methocarbamal	1000	mg		PRN	PCP	back pain
Clindamycin	1	%	topical	PRN	Dermatology	skin cysts
Triamcinolone	0.1	%	topical	PRN	Dermatology	eczema
Vyvanse	10	mg	rarely	PRN	Psychiatry	focus
Alprazolam	0.5	mg	rarely	PRN	Psychiatry	panic attacks

gs4_deauth()

drs <- read_sheet("https://docs.google.com/spreadsheets/d/10jHvDuHzhdgbULzjpjv14cypUSejCKa4GL92owiFsDQ/edit#gid=932747361", sheet = "drs") %>% 
  select(-meds)

drs %>% 
  gt() %>% 
  tab_header("Providers and Diagnoses") %>%
  cols_align(align = c("center"),
             columns = everything()) %>% 
  cols_label(doc = html("<b>Provider</b>"),
             specialty = html("<b>Specialty</b>"),
             issue = html("<b>Issue(s)</b>"),
             diagnosis = html("<b>Diagnoses</b>"),
             last = html("<b>Last Visit</b>"),
             `next` = html("<b>Next Visit</b>")) %>% 
  cols_width(doc ~ pct(12.5),
             issue ~ pct(24.5),
             diagnosis ~ pct(37.5),
             last ~ pct(12.5),
             `next` ~ pct(13)) %>% 
  fmt_date(columns = c(last, `next`),
           date_style = "m_day_year")

Provider	Specialty	Issue(s)	Diagnoses	Last Visit	Next Visit
Providers and Diagnoses
Karensa Lynch, LPC	Therapy	mental health concerns	depression, GAD, SAD/social phobia, ADHD, PTSD	Dec 21, 2023	Dec 28, 2023
Matthew Smith, DO	General Surgery	subcutaneous cyst (neck)	surgical removal	Dec 18, 2023	Dec 28, 2023
Dr. Chandra Adams	Gynocology	IUD removal, PCOS?	bacterial vaginosis	Dec 18, 2023	Dec 28, 2023
Anne Engelhart, NP	Internal Medicine	primary care	NA	Nov 30, 2023	Dec 28, 2023
Dr. Ana Rodriguez	Psychiatry	mental health concerns	depression, GAD, SAD/social phobia, ADHD, PTSD	Dec 1, 2023	Dec 29, 2023
Dr. Myint Myat Thway	Rheumatology	fatigue, chronic pain, muscle weakness	cutaneous lupus	Dec 11, 2023	Jan 12, 2024
Dr. Nolan Gall	Orthopaedics	lower back pain	herniated disk	Nov 22, 2023	Nov 22, 2023
First Coast Dermatology	Dermatology	skin cysts, rash, infections	hidradenitis suppurativa, subcutaneous cyst, eczema	Nov 29, 2023	Nov 29, 2023
Dr. Ramon E Bautista	Neurology	fatigue, chronic pain, muscle weakness	no neurological issue	Nov 14, 2023	NA
Midtown Neurology	Neurology	fatigue, chronic pain, muscle weakness	no neurological issue	Nov 8, 2023	NA
Dr. Christian Albert Koch	Endorcrinology	fatigue, chronic pain, muscle weakness	no thyroid issue	Oct 31, 2023	NA
Florida Regional Pain	Pain Management	chronic pain, treatment-resistant depression	NA	Oct 30, 2023	NA
Dermatology Associated of Georgia	Dermatology	skin cysts, rash	hidradenitis suppurativa, subcutaneous cyst	Sep 10, 2023	NA
Dr. Margaret Ann Riso	Pain Management	forearm pain	NA	Sep 7, 2023	NA
Dr. Sabitha Aligeti	Psychiatry	mental health concerns	depression, GAD, SAD/social phobia, ADHD, PTSD	Aug 28, 2023	NA
Dr. Katina Christina Tsagaris	Rheumatology	fatigue, chronic pain, hair thinning	cutaneous lupus	Jun 19, 2023	NA
Dr. Lattisha Bilbrew	Orthopaedics	forearm pain	bilateral tennis elbow	May 31, 2023	NA
Dr. Amanda Lauren Dempsey	Orthopaedics	forearm pain	bilateral radial tunnel syndrome	May 17, 2023	NA
Dr. Joshua Huffman	Chiropractor	lower back pain	herniated disk	Jun 1, 2021	NA

Full History

I have been experiencing pain in various parts of my body for about 10 years. I have been to a variety of specialists over the past 8 years with no diagnosis other than cutaneous lupus but the rheumatologists have confirmed that it’s only in my skin, and there is no indication of a flare-up causing pain.

The following is an edited report from the doctor who took a full history while admitted at Emory University Hospital in June 2023:

-2009 completed rehab for IV substance use (heroin, cocaine) with few relapses after 1.5 years of substance use

-2010-2012 pt active, living “clean” with high attention to her diet, able to bike 50+ miles per day

-2010-2013 had regular periods

-2011 diagnosed with hepatitis C

-2013-2014 began to have bouts of diffuse pain “flares” lasting days at a time, which would significantly limit her ability - these lasted for several days and would abate on their own

-02/2013 Mirena IUD placed for contraception

-06/2014 moved to Atlanta and secured housing

-2014-2020 ongoing intermittent back pain and flares that incompletely self-resolved after several days

-01/2015 secured medical insurance

-09/2015 treated for hepatitis C infection for 3 months as part of Harvoni trial, hep C quant negative at 6 months

-11/2018 first appearance of hidradenitis suppuritiva (lower abdomen)

-03/2019 increased frequency of hidradenitis suppuritiva (usually under breasts, occasionally in the groin)

-06/2019 SAD symptoms began, including agoraphobia

-10/2019 involuntary psychiatric hospitalization for SI

-04/2020 IUD removed, replaced

-06/2020 noted by dermatology to have rash on the face/arms with sun sensitivity, diagnosed with cutaneous lupus

-2020 started on Plaquenil

-09/2020 lumbar MRI showed 3 protruding disks, decompression treatment with PT, massage, ultrasound, and electrotherapy ~8 weeks, minor temporary results

-09/2020-07/2021 regular PT and worked up to 10-20 min walks almost daily

-12/2021 began having BL forearm pain (first in right forearm, left began several months after)

-01-08/2022 regular aquatic exercise (2-3x/week), reduced back pain

-03/2022 first noticed and attempted to drain subcutaneous cyst seen on imaging, became inflamed several times with increasing size, pain, and duration

-01/2023 began being much more limited by her forearm and back pain and more sedentary, requiring significant help with ADLs from partner, increased SAD symptoms including agoraphobia (and fear of driving)

-02/2023 I&D in ER for subcutaneous cyst (neck)

-06/2023 progressive worsening of muscle weakness, most profound and on a daily basis in last 3 months, able to walk short distances but quickly becomes fatigued and achy all over before she has to stop