Papre 24: Composite Blood Pressure and LDL-Cholesterol Control

Importing Data

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df_pings2_bp <- 
    dget("Data/pings_2_data_with_bps_ready") 

df_for_outc <- 
  df_pings2_bp |>
  select(pid, eventname, sbp, ff_ldl_12) |>
  arrange(pid, eventname) |>
  group_by(pid)|>
  fill(ff_ldl_12) |>
  filter(eventname == "Month12")|>
  select(-eventname)|>
  mutate(
    outc_140_18 = case_when(
      (sbp < 140 & ff_ldl_12 < 1.8) ~ "Yes", 
      !(is.na(sbp) | is.na(ff_ldl_12)) ~ "No"),
    outc_130_14 = case_when(
      (sbp < 130 & ff_ldl_12 < 1.4) ~ "Yes", 
      !(is.na(sbp) | is.na(ff_ldl_12)) ~ "No"))
  


df_baseline <- 
    dget("Data/df_for_papers") %>%
    labelled::unlabelled() %>% 
    mutate(
        d_st_type = as.character(d_st_type),
        d_st_type = case_when(
            d_st_type == "Ischemic With Hemorrhagic Transformation" ~ 
            "Ischemic Stroke", 
            is.na(d_st_type) ~ "Untyped Stroke (no CT scan available)",
            TRUE ~ d_st_type)) |> 
    labelled::set_variable_labels(
            d_st_type = "Stroke Type")

df_antihypt <- 
    df_pings2_bp |> 
    filter(eventname == "Baseline") |> 
    select(
        pid, h_antihpt, h_ccb, h_acei, h_arb, h_bb, 
        h_alpha_md, h_diuretics, h_alpha_ab, h_antiplt, 
        h_statins)

df_drugs_temp <- 
  readxl::read_xlsx(
      "Data/drugs_data_clean_10122025.xlsx", sheet = 1) 

df_max_drug_doses_temp <- 
  readxl::read_xlsx(
      "Data/PINGS_Antihypertensive Maximum doses.xlsx", sheet = 2)

Data manipulation

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df_sbp <- 
    df_pings2_bp |> # labelled::look_for("acei")
    select(sbp, dbp, pid, eventname) |> 
    mutate(
        mth = parse_number(eventname),
        mth = case_when(
            eventname == "Baseline" ~ 0, 
            TRUE ~ mth)) |> 
    pivot_wider(
        id_cols = pid, 
        values_from = sbp, 
        names_from = mth, 
        names_prefix = "sbp_m_") |> 
    drop_na()

df_dbp <- 
    df_pings2_bp |> # labelled::look_for("acei")
    select(sbp, dbp, pid, eventname) |> 
    mutate(
        mth = parse_number(eventname),
        mth = case_when(
            eventname == "Baseline" ~ 0, 
            TRUE ~ mth)) |> 
    pivot_wider(
        id_cols = pid, 
        values_from = dbp, 
        names_from = mth, 
        names_prefix = "dbp_m_") |> 
    drop_na()

df_drugs <-  
    df_drugs_temp %>% 
    left_join(df_max_drug_doses_temp, by = "drug") %>%
    mutate(
        dose_index = freq_number*dose_number/maxi,
        antihpt  = case_when(is.na(antihpt) ~ 0, TRUE ~ antihpt)) %>% 
    filter(antihpt == 1) %>% 
    group_by(pid, eventname, arm) %>% 
    summarize(
      n_hpts = sum(antihpt), 
      dose_index = sum(dose_index)) %>% 
    ungroup() |> 
    filter(eventname == "Baseline") |> 
    select(pid, dose_index)

df_paper_20 <- 
    df_pings2_bp |> # labelled::look_for("acei")
    select(sbp, dbp, pid, eventname) |> 
    mutate(
        sbp_high = sbp >= 140, 
        dbp_high = dbp >= 90, 
        hpt = sbp_high | dbp_high, 
        mth = parse_number(eventname),
        mth = case_when(
            eventname == "Baseline" ~ 0, 
            TRUE ~ mth)) |> 
    select(pid, mth, hpt) |> 
    arrange(pid, mth) |> 
    pivot_wider(
        id_cols = pid, 
        values_from = hpt, 
        names_from = mth, 
        names_prefix = "m_") |> 
    drop_na() |> 
    mutate(
        m_0 = case_when(m_0 == FALSE ~ TRUE, TRUE ~ m_0),
        total_1 = rowSums(across(c(m_0:m_12))),
        hpt_class = case_when(
             total_1 == 1 ~ "Early",
             total_1 == 6 ~ "Persistent", 
             total_1 == 5 & m_12 == FALSE ~ "Late", 
             total_1 == 5 ~ "Fluctuating", 
             total_1 == 4 & m_9 == FALSE & m_12 == FALSE~ "Late",
             m_0 & m_1 & m_3 == FALSE & m_6 == FALSE & m_9 == FALSE & 
                 m_12 == FALSE~ "Early", 
             m_0 & m_1 & m_3 & m_6 == FALSE & m_9 == FALSE & m_12 == FALSE~ "Early", 
             m_0 & m_1 & m_3 & m_6 & m_9 == FALSE & m_12 == FALSE~ "Late",
             m_0 & m_1 & m_3 & m_6 & m_9 & m_12 == FALSE~ "Late", 
             m_0 & m_1 & m_3 & m_6 == FALSE & m_9 & m_12 == FALSE~ "Fluctuating", 
             m_0 & m_1 & m_3 & m_6 == FALSE & m_9 == FALSE & m_12 ~ "Fluctuating",
             m_0 & m_1 & m_3 == FALSE & m_6 & m_9 & m_12 == FALSE~ "Fluctuating", 
             total_1 == 4 & m_9 == FALSE & m_12 ~ "Fluctuating", 
             total_1 == 4 & m_9 & m_12 == FALSE~ "Fluctuating", 
             total_1 == 4 ~ "Fluctuating", 
             total_1 == 3 ~ "Fluctuating", 
             total_1 == 2 ~ "Fluctuating")) |> 
    left_join(df_baseline) |> 
    left_join(df_antihypt) |> 
    left_join(df_sbp) |> 
    left_join(df_dbp) |>
    left_join(df_drugs) |> 
    left_join(df_for_outc) |>
    mutate(
        no_of_hpts = 
            (h_acei == "Checked") + (h_arb == "Checked") + 
            (h_bb == "Checked") + (h_ccb == "Checked") + 
            (h_diuretics  == "Checked") + (h_alpha_md  == "Checked") + 
            (h_alpha_ab == "Checked"),
        arm = case_when(
            arm == "Arm 1- Intervention Arm" ~ "Intervention", 
            arm == "Arm 2- Routine Care" ~ "Routine") |> 
          factor(levels = c("Routine", "Intervention")),
        alcohol_curr = case_when(
            g_alcohol == "Currently uses alcohol" ~ "Yes",
            g_alcohol %in% c(
                "Never used alcohol", 
                "Past 12 months", 
                "Past 30 days", 
                "Formerly used alcohol", 
                "Stopped after the stroke occured") ~ "No"))



df_ready <- 
    df_paper_20 |> 
  mutate(
    bmi_cat = case_when(
      bmi < 25 ~ "Normal", 
      bmi < 30 ~ "Overweight", 
      bmi >= 30 ~ "Obese")|> 
        factor(levels = c("Normal","Overweight", "Obese")), 
    hba1c_high = case_when(
      ff_hba1c_0 >= 6.5 ~ "Yes", 
      ff_hba1c_0 < 6.5 ~ "No"), 
    across(
      c(h_acei, h_arb, h_bb, h_ccb, h_diuretics, h_alpha_md, h_alpha_ab), 
      .fns = ~case_when(
        .x == "Checked" ~ "Yes", 
        .x == "Unchecked" ~ "No"))) |>
    select(
        a_agebase, a_gender, educ, maristat, a_domicile, income,    
        a_religion, d_stroke_ct, d_st_type, nihss_scale, ranking, 
        dm, tobacco_use, bmi_cat, waist_hip_ratio, arm,hyperlipidemia,
        alcohol_curr, ff_hba1c_0, hba1c_high,  h_acei, h_arb, h_bb, h_ccb,
        h_diuretics, h_alpha_md, h_alpha_ab,h_antiplt, h_statins, hillbone, 
        aa_hkq, eq_5d,  hosp_cat, dose_index, outc_140_18, outc_130_14)

Labelling data

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df_ready <- 
    df_ready |> 
    labelled::set_variable_labels(
            h_arb = "Angiotensin Receptor Blocker",
            h_acei = "ACE-Inhibitors",
            h_alpha_md = "Alpha Methyl Dopa",
            h_bb = "Beta blockers",
            h_ccb = "Calcium Channel Blocker",
            h_diuretics = "Diuretics",
            h_alpha_ab = "Alpha Adrenergic Blockers", 
#            no_of_hpts = "No. of Antihypertensives", 
            h_antiplt = "Antiplatelet", 
            h_statins = "Statins",
            dose_index = "Antihypertensive treatment intensity",
            eq_5d = "Health Related QoL", 
            arm = "Study Arm", 
            bmi_cat = "Categorised Body Mass Index", 
            hba1c_high = "High HbA1C")

Table 0

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gtsummary::theme_gtsummary_compact()

Setting theme "Compact"

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gtsummary::theme_gtsummary_eda()

Setting theme "Exploratory Data Analysis"

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df_ready |> # labelled::look_for("alc")
    gtsummary::tbl_summary(missing_text = "Missing") |> 
    gtsummary::bold_labels()

Characteristic	N = 365¹
Age in years
Median (Q1, Q3)	58 (50, 67)
Mean (SD)	58 (11)
Min, Max	29, 86
Gender
Male	207 (56.7%)
Female	158 (43.3%)
Educational Status
None	31 (8.49%)
Primary	152 (41.6%)
Secondary	117 (32.1%)
Tertiary	65 (17.8%)
Marital Status
Currently Married	244 (66.8%)
Previously Married	101 (27.7%)
Never Married	20 (5.48%)
Domicile
Rural	24 (6.58%)
Semi-Urban	124 (34.0%)
Urban	217 (59.5%)
Income in GHC
0-100	130 (35.8%)
101-250	113 (31.1%)
251-500	81 (22.3%)
>500	39 (10.7%)
Missing	2
Religion
Christianity	332 (91.0%)
Islam	31 (8.49%)
Other	2 (0.55%)
Stroke Subtype ( with results of Brain CT scan)
Ischaemic	237 (73.8%)
Haemorrhage infarct	10 (3.12%)
Haemorrhagic	66 (20.6%)
Ischaemic and Haemorrhagic	8 (2.49%)
Missing	44
Stroke Type
Intracerebral Hemorrhagic Stroke	76 (20.8%)
Ischemic Stroke	260 (71.2%)
Untyped Stroke (no CT scan available)	29 (7.95%)
NIH Stroke Scale
Median (Q1, Q3)	2.0 (0.0, 7.0)
Mean (SD)	4.3 (4.9)
Min, Max	0.0, 23.0
Missing	4
Modified Ranking Score
0	26 (7.12%)
1	84 (23.0%)
2	117 (32.1%)
3	72 (19.7%)
4	65 (17.8%)
5	1 (0.27%)
Diabetes Mellitus	123 (33.7%)
History of tobacco use	25 (7.00%)
Missing	8
Categorised Body Mass Index
Normal	151 (42.3%)
Overweight	117 (32.8%)
Obese	89 (24.9%)
Missing	8
Waist-Hip Ratio
Median (Q1, Q3)	0.93 (0.89, 0.96)
Mean (SD)	1.17 (4.63)
Min, Max	0.09, 88.30
Missing	8
Study Arm
Routine	184 (50.4%)
Intervention	181 (49.6%)
Hyperlipidemia	120 (32.9%)
alcohol_curr	39 (10.7%)
HBA1C (Baseline)
Median (Q1, Q3)	5.80 (5.40, 6.70)
Mean (SD)	6.44 (2.03)
Min, Max	3.00, 16.10
Missing	69
High HbA1C	85 (28.7%)
Missing	69
ACE-Inhibitors	29 (7.95%)
Angiotensin Receptor Blocker	33 (9.04%)
Beta blockers	14 (3.84%)
Calcium Channel Blocker	162 (44.4%)
Diuretics	15 (4.11%)
Alpha Methyl Dopa	17 (4.66%)
Alpha Adrenergic Blockers	5 (1.37%)
Antiplatelet	48 (14.0%)
Missing	21
Statins	35 (10.4%)
Missing	29
Total Hillbone Score
Median (Q1, Q3)	53.0 (50.0, 53.0)
Mean (SD)	51.4 (3.7)
Min, Max	30.0, 56.0
Missing	6
Total HKQ Score
Median (Q1, Q3)	9 (6, 10)
Mean (SD)	8 (3)
Min, Max	0, 13
Missing	15
Health Related QoL
Median (Q1, Q3)	10.00 (8.00, 11.00)
Mean (SD)	9.71 (1.94)
Min, Max	6.00, 15.00
Missing	144
Health institution category
Primary	112 (30.7%)
Secondary	81 (22.2%)
Tertiary	172 (47.1%)
Antihypertensive treatment intensity
Median (Q1, Q3)	1.44 (0.83, 1.92)
Mean (SD)	1.48 (0.79)
Min, Max	0.06, 4.50
Missing	43
outc_140_18	50 (17.9%)
Missing	86
outc_130_14	18 (6.45%)
Missing	86
¹ n (%)

Table 1A - Composite score (140mmHg, 1.8mmol/L)

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gtsummary::reset_gtsummary_theme()
gtsummary::theme_gtsummary_compact()

Setting theme "Compact"

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df_ready |>
  select(-c(outc_130_14, hyperlipidemia))|>
  gtsummary::tbl_summary(by = outc_140_18) |> 
  gtsummary::modify_spanning_header(
        gtsummary::all_stat_cols() ~ "**SBP < 140, LDL < 1.8 mmol/L**") %>% 
  gtsummary::add_overall(last = T) |>
  gtsummary::add_p()|>
  gtsummary::bold_p()|>
  gtsummary::bold_labels() |>
  gtsummary::modify_caption(
      "**Table 1A**: DEMOGRAPHIC & CLINICAL CHARACTERISTICS OF STUDY PARTICIPANTS**")

86 missing rows in the "outc_140_18" column have been removed.

**Table 1A**: DEMOGRAPHIC & CLINICAL CHARACTERISTICS OF STUDY PARTICIPANTS**
Characteristic	SBP < 140, LDL < 1.8 mmol/L		Overall N = 279¹	p-value²
Characteristic	No N = 229¹	Yes N = 50¹	Overall N = 279¹	p-value²
Age in years	57 (50, 65)	61 (53, 70)	58 (51, 66)	0.072
Gender				0.8
Male	132 (58%)	30 (60%)	162 (58%)
Female	97 (42%)	20 (40%)	117 (42%)
Educational Status				0.4
None	17 (7.4%)	6 (12%)	23 (8.2%)
Primary	97 (42%)	18 (36%)	115 (41%)
Secondary	74 (32%)	20 (40%)	94 (34%)
Tertiary	41 (18%)	6 (12%)	47 (17%)
Marital Status				0.9
Currently Married	150 (66%)	35 (70%)	185 (66%)
Previously Married	69 (30%)	13 (26%)	82 (29%)
Never Married	10 (4.4%)	2 (4.0%)	12 (4.3%)
Domicile				0.6
Rural	12 (5.2%)	4 (8.0%)	16 (5.7%)
Semi-Urban	78 (34%)	14 (28%)	92 (33%)
Urban	139 (61%)	32 (64%)	171 (61%)
Income in GHC				>0.9
0-100	84 (37%)	20 (40%)	104 (38%)
101-250	67 (30%)	15 (30%)	82 (30%)
251-500	51 (22%)	10 (20%)	61 (22%)
>500	25 (11%)	5 (10%)	30 (11%)
Unknown	2	0	2
Religion				0.2
Christianity	214 (93%)	44 (88%)	258 (92%)
Islam	13 (5.7%)	6 (12%)	19 (6.8%)
Other	2 (0.9%)	0 (0%)	2 (0.7%)
Stroke Subtype ( with results of Brain CT scan)				0.4
Ischaemic	148 (71%)	33 (79%)	181 (72%)
Haemorrhage infarct	10 (4.8%)	0 (0%)	10 (4.0%)
Haemorrhagic	43 (21%)	9 (21%)	52 (21%)
Ischaemic and Haemorrhagic	7 (3.4%)	0 (0%)	7 (2.8%)
Unknown	21	8	29
Stroke Type				0.6
Intracerebral Hemorrhagic Stroke	54 (24%)	9 (18%)	63 (23%)
Ischemic Stroke	160 (70%)	37 (74%)	197 (71%)
Untyped Stroke (no CT scan available)	15 (6.6%)	4 (8.0%)	19 (6.8%)
NIH Stroke Scale	3.0 (0.0, 7.0)	2.0 (0.0, 9.0)	2.0 (0.0, 7.0)	0.7
Unknown	2	0	2
Modified Ranking Score				0.5
0	20 (8.7%)	1 (2.0%)	21 (7.5%)
1	51 (22%)	12 (24%)	63 (23%)
2	69 (30%)	20 (40%)	89 (32%)
3	44 (19%)	8 (16%)	52 (19%)
4	44 (19%)	9 (18%)	53 (19%)
5	1 (0.4%)	0 (0%)	1 (0.4%)
Diabetes Mellitus	65 (28%)	25 (50%)	90 (32%)	0.003
History of tobacco use	18 (8.1%)	5 (10%)	23 (8.5%)	0.6
Unknown	7	0	7
Categorised Body Mass Index				0.052
Normal	103 (46%)	13 (27%)	116 (43%)
Overweight	67 (30%)	19 (40%)	86 (32%)
Obese	53 (24%)	16 (33%)	69 (25%)
Unknown	6	2	8
Waist-Hip Ratio	0.93 (0.88, 0.96)	0.93 (0.89, 0.97)	0.93 (0.89, 0.96)	0.5
Unknown	6	0	6
Study Arm				0.012
Routine	123 (54%)	17 (34%)	140 (50%)
Intervention	106 (46%)	33 (66%)	139 (50%)
alcohol_curr	23 (10%)	9 (18%)	32 (11%)	0.11
HBA1C (Baseline)	5.70 (5.30, 6.40)	5.85 (5.40, 7.10)	5.80 (5.40, 6.70)	0.10
Unknown	31	4	35
High HbA1C	48 (24%)	19 (41%)	67 (27%)	0.020
Unknown	31	4	35
ACE-Inhibitors	12 (5.2%)	7 (14%)	19 (6.8%)	0.055
Angiotensin Receptor Blocker	22 (9.6%)	4 (8.0%)	26 (9.3%)	>0.9
Beta blockers	9 (3.9%)	1 (2.0%)	10 (3.6%)	>0.9
Calcium Channel Blocker	92 (40%)	23 (46%)	115 (41%)	0.4
Diuretics	7 (3.1%)	2 (4.0%)	9 (3.2%)	0.7
Alpha Methyl Dopa	8 (3.5%)	1 (2.0%)	9 (3.2%)	>0.9
Alpha Adrenergic Blockers	2 (0.9%)	1 (2.0%)	3 (1.1%)	0.4
Antiplatelet	28 (13%)	6 (13%)	34 (13%)	>0.9
Unknown	10	5	15
Statins	22 (10%)	3 (7.0%)	25 (9.6%)	0.8
Unknown	12	7	19
Total Hillbone Score	52.0 (51.0, 53.0)	52.0 (50.0, 53.0)	52.0 (50.0, 53.0)	0.2
Unknown	4	0	4
Total HKQ Score	9 (7, 10)	8 (5, 10)	9 (7, 10)	0.2
Unknown	10	2	12
Health Related QoL	10.00 (8.00, 11.00)	10.00 (9.00, 10.00)	10.00 (8.00, 11.00)	0.4
Unknown	90	19	109
Health institution category				>0.9
Primary	73 (32%)	15 (30%)	88 (32%)
Secondary	41 (18%)	9 (18%)	50 (18%)
Tertiary	115 (50%)	26 (52%)	141 (51%)
Antihypertensive treatment intensity	1.50 (0.83, 1.83)	1.44 (1.00, 1.92)	1.46 (0.92, 1.83)	0.9
Unknown	32	8	40
¹ Median (Q1, Q3); n (%)
² Wilcoxon rank sum test; Pearson’s Chi-squared test; Fisher’s exact test

Table 2 - Composite score (130mmHg, 1.4mm/L)

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gtsummary::reset_gtsummary_theme()
gtsummary::theme_gtsummary_compact()

Setting theme "Compact"

Show code

df_ready |>
  select(-c(outc_140_18, hyperlipidemia))|>
  gtsummary::tbl_summary(by = outc_130_14) |> 
  gtsummary::modify_spanning_header(
        gtsummary::all_stat_cols() ~ "**SBP < 130, LDL < 1.4 mmol/L**") %>% 
  gtsummary::add_overall(last = T) |>
  gtsummary::add_p()|>
  gtsummary::bold_p()|>
  gtsummary::bold_labels() |>
  gtsummary::modify_caption(
      "**Table 1B**: DEMOGRAPHIC & CLINICAL CHARACTERISTICS OF STUDY PARTICIPANTS**")

86 missing rows in the "outc_130_14" column have been removed.

**Table 1B**: DEMOGRAPHIC & CLINICAL CHARACTERISTICS OF STUDY PARTICIPANTS**
Characteristic	SBP < 130, LDL < 1.4 mmol/L		Overall N = 279¹	p-value²
Characteristic	No N = 261¹	Yes N = 18¹	Overall N = 279¹	p-value²
Age in years	58 (50, 66)	58 (52, 67)	58 (51, 66)	>0.9
Gender				0.2
Male	149 (57%)	13 (72%)	162 (58%)
Female	112 (43%)	5 (28%)	117 (42%)
Educational Status				0.3
None	21 (8.0%)	2 (11%)	23 (8.2%)
Primary	111 (43%)	4 (22%)	115 (41%)
Secondary	86 (33%)	8 (44%)	94 (34%)
Tertiary	43 (16%)	4 (22%)	47 (17%)
Marital Status				0.7
Currently Married	171 (66%)	14 (78%)	185 (66%)
Previously Married	78 (30%)	4 (22%)	82 (29%)
Never Married	12 (4.6%)	0 (0%)	12 (4.3%)
Domicile				>0.9
Rural	15 (5.7%)	1 (5.6%)	16 (5.7%)
Semi-Urban	86 (33%)	6 (33%)	92 (33%)
Urban	160 (61%)	11 (61%)	171 (61%)
Income in GHC				0.7
0-100	98 (38%)	6 (33%)	104 (38%)
101-250	76 (29%)	6 (33%)	82 (30%)
251-500	58 (22%)	3 (17%)	61 (22%)
>500	27 (10%)	3 (17%)	30 (11%)
Unknown	2	0	2
Religion				0.2
Christianity	243 (93%)	15 (83%)	258 (92%)
Islam	16 (6.1%)	3 (17%)	19 (6.8%)
Other	2 (0.8%)	0 (0%)	2 (0.7%)
Stroke Subtype ( with results of Brain CT scan)				>0.9
Ischaemic	169 (72%)	12 (75%)	181 (72%)
Haemorrhage infarct	10 (4.3%)	0 (0%)	10 (4.0%)
Haemorrhagic	48 (21%)	4 (25%)	52 (21%)
Ischaemic and Haemorrhagic	7 (3.0%)	0 (0%)	7 (2.8%)
Unknown	27	2	29
Stroke Type				>0.9
Intracerebral Hemorrhagic Stroke	59 (23%)	4 (22%)	63 (23%)
Ischemic Stroke	184 (70%)	13 (72%)	197 (71%)
Untyped Stroke (no CT scan available)	18 (6.9%)	1 (5.6%)	19 (6.8%)
NIH Stroke Scale	3.0 (0.0, 7.0)	1.5 (0.0, 8.0)	2.0 (0.0, 7.0)	0.8
Unknown	2	0	2
Modified Ranking Score				0.8
0	20 (7.7%)	1 (5.6%)	21 (7.5%)
1	57 (22%)	6 (33%)	63 (23%)
2	83 (32%)	6 (33%)	89 (32%)
3	50 (19%)	2 (11%)	52 (19%)
4	50 (19%)	3 (17%)	53 (19%)
5	1 (0.4%)	0 (0%)	1 (0.4%)
Diabetes Mellitus	82 (31%)	8 (44%)	90 (32%)	0.3
History of tobacco use	22 (8.7%)	1 (5.6%)	23 (8.5%)	>0.9
Unknown	7	0	7
Categorised Body Mass Index				0.5
Normal	111 (44%)	5 (31%)	116 (43%)
Overweight	79 (31%)	7 (44%)	86 (32%)
Obese	65 (25%)	4 (25%)	69 (25%)
Unknown	6	2	8
Waist-Hip Ratio	0.93 (0.88, 0.96)	0.93 (0.89, 0.98)	0.93 (0.89, 0.96)	0.8
Unknown	6	0	6
Study Arm				0.6
Routine	130 (50%)	10 (56%)	140 (50%)
Intervention	131 (50%)	8 (44%)	139 (50%)
alcohol_curr	30 (11%)	2 (11%)	32 (11%)	>0.9
HBA1C (Baseline)	5.80 (5.40, 6.70)	5.70 (5.40, 6.70)	5.80 (5.40, 6.70)	0.7
Unknown	34	1	35
High HbA1C	62 (27%)	5 (29%)	67 (27%)	0.8
Unknown	34	1	35
ACE-Inhibitors	15 (5.7%)	4 (22%)	19 (6.8%)	0.026
Angiotensin Receptor Blocker	25 (9.6%)	1 (5.6%)	26 (9.3%)	>0.9
Beta blockers	9 (3.4%)	1 (5.6%)	10 (3.6%)	0.5
Calcium Channel Blocker	105 (40%)	10 (56%)	115 (41%)	0.2
Diuretics	8 (3.1%)	1 (5.6%)	9 (3.2%)	0.5
Alpha Methyl Dopa	9 (3.4%)	0 (0%)	9 (3.2%)	>0.9
Alpha Adrenergic Blockers	3 (1.1%)	0 (0%)	3 (1.1%)	>0.9
Antiplatelet	31 (13%)	3 (19%)	34 (13%)	0.4
Unknown	13	2	15
Statins	24 (9.8%)	1 (6.3%)	25 (9.6%)	>0.9
Unknown	17	2	19
Total Hillbone Score	52.0 (51.0, 53.0)	51.5 (48.0, 53.0)	52.0 (50.0, 53.0)	0.12
Unknown	4	0	4
Total HKQ Score	9 (7, 10)	8 (5, 11)	9 (7, 10)	0.6
Unknown	12	0	12
Health Related QoL	10.00 (8.00, 10.00)	11.00 (9.00, 13.00)	10.00 (8.00, 11.00)	0.2
Unknown	99	10	109
Health institution category				0.5
Primary	83 (32%)	5 (28%)	88 (32%)
Secondary	45 (17%)	5 (28%)	50 (18%)
Tertiary	133 (51%)	8 (44%)	141 (51%)
Antihypertensive treatment intensity	1.46 (0.92, 1.83)	1.42 (0.96, 2.00)	1.46 (0.92, 1.83)	0.9
Unknown	36	4	40
¹ Median (Q1, Q3); n (%)
² Wilcoxon rank sum test; Pearson’s Chi-squared test; Fisher’s exact test

Regression - Composite score (140mmHg, 1.8mmol/L)

Show code

df_ready |>
  select(-c(outc_130_14, hyperlipidemia)) |>
  mutate(outc_140_18 = factor(outc_140_18))|>
  drop_na(outc_140_18)|>
  gtsummary::tbl_uvregression(
        y = outc_140_18, 
        method = glm,
        method.args = list(family = binomial),
        exponentiate = TRUE,
        pvalue_fun = function(x) gtsummary::style_pvalue(x, digits = 3)) |>
  gtsummary::bold_p()|>
  gtsummary::bold_labels()

Characteristic	N	OR	95% CI	p-value
Age in years	279	1.02	1.00, 1.05	0.089
Gender	279
Male		—	—
Female		0.91	0.48, 1.68	0.760
Educational Status	279
None		—	—
Primary		0.53	0.19, 1.62	0.234
Secondary		0.77	0.28, 2.35	0.620
Tertiary		0.41	0.11, 1.50	0.173
Marital Status	279
Currently Married		—	—
Previously Married		0.81	0.39, 1.59	0.548
Never Married		0.86	0.13, 3.44	0.847
Domicile	279
Rural		—	—
Semi-Urban		0.54	0.16, 2.14	0.338
Urban		0.69	0.22, 2.60	0.544
Income in GHC	277
0-100		—	—
101-250		0.94	0.44, 1.97	0.871
251-500		0.82	0.35, 1.86	0.649
>500		0.84	0.26, 2.33	0.751
Religion	279
Christianity		—	—
Islam		2.24	0.75, 6.02	0.120
Other		0.00		0.989
Stroke Subtype ( with results of Brain CT scan)	250
Ischaemic		—	—
Haemorrhage infarct		0.00		0.990
Haemorrhagic		0.94	0.40, 2.04	0.879
Ischaemic and Haemorrhagic		0.00		0.991
Stroke Type	279
Intracerebral Hemorrhagic Stroke		—	—
Ischemic Stroke		1.39	0.65, 3.23	0.417
Untyped Stroke (no CT scan available)		1.60	0.39, 5.69	0.482
NIH Stroke Scale	277	1.02	0.96, 1.08	0.566
Modified Ranking Score	279	1.03	0.80, 1.33	0.800
Diabetes Mellitus	279
No		—	—
Yes		2.52	1.35, 4.73	0.004
History of tobacco use	272
No		—	—
Yes		1.26	0.40, 3.35	0.665
Categorised Body Mass Index	271
Normal		—	—
Overweight		2.25	1.05, 4.95	0.039
Obese		2.39	1.07, 5.42	0.033
Waist-Hip Ratio	273	0.96		0.790
Study Arm	279
Routine		—	—
Intervention		2.25	1.20, 4.35	0.013
alcohol_curr	279
No		—	—
Yes		1.97	0.81, 4.44	0.115
HBA1C (Baseline)	244	1.10	0.95, 1.27	0.190
High HbA1C	244
No		—	—
Yes		2.20	1.11, 4.29	0.021
ACE-Inhibitors	279
No		—	—
Yes		2.94	1.04, 7.76	0.032
Angiotensin Receptor Blocker	279
No		—	—
Yes		0.82	0.23, 2.26	0.724
Beta blockers	279
No		—	—
Yes		0.50	0.03, 2.75	0.514
Calcium Channel Blocker	279
No		—	—
Yes		1.27	0.68, 2.35	0.449
Diuretics	279
No		—	—
Yes		1.32	0.19, 5.67	0.733
Alpha Methyl Dopa	279
No		—	—
Yes		0.56	0.03, 3.18	0.593
Alpha Adrenergic Blockers	279
No		—	—
Yes		2.32	0.11, 24.6	0.496
Antiplatelet	264
Yes		—	—
No		0.95	0.39, 2.68	0.920
Statins	260
Yes		—	—
No		1.50	0.49, 6.57	0.523
Total Hillbone Score	275	0.96	0.89, 1.05	0.358
Total HKQ Score	267	0.91	0.83, 1.01	0.084
Health Related QoL	170	1.10	0.90, 1.35	0.331
Health institution category	279
Primary		—	—
Secondary		1.07	0.42, 2.62	0.887
Tertiary		1.10	0.55, 2.26	0.789
Antihypertensive treatment intensity	239	1.03	0.64, 1.64	0.905
Abbreviations: CI = Confidence Interval, OR = Odds Ratio

Regression - Composite score (130mmHg, 1.4mmol/L)

Show code

df_ready |>
  select(-c(outc_140_18, hyperlipidemia)) |>
  mutate(outc_130_14 = factor(outc_130_14))|>
  drop_na(outc_130_14)|>
  gtsummary::tbl_uvregression(
        y = outc_130_14, 
        method = glm,
        method.args = list(family = binomial),
        exponentiate = TRUE,
        pvalue_fun = function(x) gtsummary::style_pvalue(x, digits = 3)) |>
  gtsummary::bold_p()|>
  gtsummary::bold_labels()

Characteristic	N	OR	95% CI	p-value
Age in years	279	1.00	0.96, 1.04	0.883
Gender	279
Male		—	—
Female		0.51	0.16, 1.40	0.215
Educational Status	279
None		—	—
Primary		0.38	0.07, 2.85	0.279
Secondary		0.98	0.22, 6.79	0.977
Tertiary		0.98	0.18, 7.45	0.979
Marital Status	279
Currently Married		—	—
Previously Married		0.63	0.17, 1.81	0.422
Never Married		0.00		0.989
Domicile	279
Rural		—	—
Semi-Urban		1.05	0.16, 20.5	0.967
Urban		1.03	0.18, 19.5	0.977
Income in GHC	277
0-100		—	—
101-250		1.29	0.39, 4.27	0.670
251-500		0.84	0.17, 3.33	0.816
>500		1.81	0.36, 7.37	0.420
Religion	279
Christianity		—	—
Islam		3.04	0.66, 10.4	0.104
Other		0.00		0.990
Stroke Subtype ( with results of Brain CT scan)	250
Ischaemic		—	—
Haemorrhage infarct		0.00		0.994
Haemorrhagic		1.17	0.32, 3.54	0.790
Ischaemic and Haemorrhagic		0.00		0.995
Stroke Type	279
Intracerebral Hemorrhagic Stroke		—	—
Ischemic Stroke		1.04	0.35, 3.81	0.944
Untyped Stroke (no CT scan available)		0.82	0.04, 5.99	0.863
NIH Stroke Scale	277	1.00	0.90, 1.09	0.986
Modified Ranking Score	279	0.86	0.57, 1.28	0.468
Diabetes Mellitus	279
No		—	—
Yes		1.75	0.65, 4.59	0.258
History of tobacco use	272
No		—	—
Yes		0.62	0.03, 3.25	0.650
Categorised Body Mass Index	271
Normal		—	—
Overweight		1.97	0.61, 6.86	0.262
Obese		1.37	0.33, 5.34	0.651
Waist-Hip Ratio	273	0.95		0.897
Study Arm	279
Routine		—	—
Intervention		0.79	0.29, 2.08	0.638
alcohol_curr	279
No		—	—
Yes		0.96	0.15, 3.61	0.961
HBA1C (Baseline)	244	1.04	0.80, 1.27	0.754
High HbA1C	244
No		—	—
Yes		1.11	0.34, 3.12	0.852
ACE-Inhibitors	279
No		—	—
Yes		4.69	1.22, 15.0	0.014
Angiotensin Receptor Blocker	279
No		—	—
Yes		0.56	0.03, 2.89	0.575
Beta blockers	279
No		—	—
Yes		1.65	0.09, 9.55	0.645
Calcium Channel Blocker	279
No		—	—
Yes		1.86	0.71, 5.01	0.207
Diuretics	279
No		—	—
Yes		1.86	0.10, 11.0	0.569
Alpha Methyl Dopa	279
No		—	—
Yes		0.00		0.991
Alpha Adrenergic Blockers	279
No		—	—
Yes		0.00		0.992
Antiplatelet	264
Yes		—	—
No		0.62	0.19, 2.81	0.473
Statins	260
Yes		—	—
No		1.64	0.31, 30.2	0.641
Total Hillbone Score	275	0.92	0.84, 1.03	0.119
Total HKQ Score	267	0.94	0.81, 1.11	0.449
Health Related QoL	170	1.37	0.97, 1.96	0.075
Health institution category	279
Primary		—	—
Secondary		1.84	0.49, 6.96	0.353
Tertiary		1.00	0.32, 3.40	0.998
Antihypertensive treatment intensity	239	1.08	0.49, 2.24	0.846
Abbreviations: CI = Confidence Interval, OR = Odds Ratio