TB_Pharmacy
Magassouba AS
15/07/2020
library(readxl)
collecte_tb_pharmacie_survey_ <- read_excel("collecte_tb_pharmacie_survey..xlsx")
attach(collecte_tb_pharmacie_survey_)
pharmacie=ifelse(collecte_tb_pharmacie_survey_$Nom_pharmacie=="Point de vente",yes =0,no=1)
pharmacie=factor(pharmacie,levels = c(0,1),labels = c("informelle","formelle"))
date_enquete="Date de l'enquête"
Age=collecte_tb_pharmacie_survey_$Age
Sexe= collecte_tb_pharmacie_survey_$Sexe
Residence= collecte_tb_pharmacie_survey_$`Résidence (quartier)`
toux= collecte_tb_pharmacie_survey_$`Avez-vous toussé au delà de 2 semaines ?`
fievre=collecte_tb_pharmacie_survey_$`Avez-vous de la fièvre activement ou pendant les deux dernieres semaines?`
duree_signes= collecte_tb_pharmacie_survey_$`Si oui depuis combiens de temps? (nombre de jours)`
cohabite_contact=collecte_tb_pharmacie_survey_$`Avez-vous cohabité avec un tousseur les 6 derniers mois ?`
temps_contact= collecte_tb_pharmacie_survey_$`Si oui ! pendant combiens de temps? (nombre mois)`
Amaigrisement= collecte_tb_pharmacie_survey_$`Avez-vous maigri ces derniers temps ?`
Date_col_crachat= collecte_tb_pharmacie_survey_$`Date de collecte de l'échantillon`
Type_echantillon= collecte_tb_pharmacie_survey_$`Type d'échantillon`
Aspect_crachat= collecte_tb_pharmacie_survey_$`Aspect visuel (traces de sang, mucopurulence ou présence de pu)`
Resultat_miscrop= ifelse(collecte_tb_pharmacie_survey_$`Resultats de la microscopie`=="neg",yes = 0,no=1)
Resultat_miscrop=factor(Resultat_miscrop,levels = c(0,1),labels = c("Négatif","Positif"))
Resultat_geneXpert= collecte_tb_pharmacie_survey_$`M. tuberculosis`
Résistance_rifampicine=collecte_tb_pharmacie_survey_$`Résistance à la rifampicine`
data_pharmay=data.frame(Age, Sexe , toux, fievre, duree_signes, cohabite_contact, temps_contact, Amaigrisement, Type_echantillon , Aspect_crachat , Resultat_miscrop, Resultat_geneXpert , Résistance_rifampicine,pharmacie)
detach(collecte_tb_pharmacie_survey_)
attach(data_pharmay)
library("gtsummary", lib.loc="/Library/Frameworks/R.framework/Versions/4.0/Resources/library")## Warning: package 'gtsummary' was built under R version 4.0.1Descrition des patients
data_pharmay%>%
tbl_summary()%>%
add_n()%>%
bold_labels()| Characteristic | N | N = 10251 |
|---|---|---|
| Age | 1025 | 30 (21, 47) |
| Sexe | 1025 | |
| f | 470 (46%) | |
| m | 555 (54%) | |
| toux | 1025 | 923 (90%) |
| fievre | 1025 | 903 (88%) |
| duree_signes | 1025 | 14 (10, 15) |
| cohabite_contact | 1025 | 139 (14%) |
| temps_contact | 134 | 5.0 (3.0, 6.0) |
| Unknown | 891 | |
| Amaigrisement | 1025 | 493 (48%) |
| Type_echantillon | 1025 | |
| crach | 853 (83%) | |
| crach_mil | 172 (17%) | |
| Aspect_crachat | 1025 | |
| Mucopurulent | 440 (43%) | |
| Mucus | 3 (0.3%) | |
| Mucus+Salivaire | 62 (6.0%) | |
| Purulent | 5 (0.5%) | |
| Salivaire | 512 (50%) | |
| Sanguinolant | 3 (0.3%) | |
| Resultat_miscrop | 1025 | |
| Négatif | 890 (87%) | |
| Positif | 135 (13%) | |
| Resultat_geneXpert | 11 | |
| detect | 3 (27%) | |
| nondetect | 8 (73%) | |
| Unknown | 1014 | |
| Résistance_rifampicine | 6 | |
| nondet | 5 (83%) | |
| other | 1 (17%) | |
| Unknown | 1019 | |
| pharmacie | 1025 | |
| informelle | 530 (52%) | |
| formelle | 495 (48%) | |
|
1
Statistics presented: median (IQR); n (%)
|
||
Repartition des patients selon les resultats de la microscopie
data_pharmay%>%
tbl_summary(by="Resultat_miscrop")%>%
add_p()%>%
add_overall()%>%
add_n()%>%
bold_labels()| Characteristic | N | Overall, N = 1025 | Négatif, N = 8901 | Positif, N = 1351 | p-value2 |
|---|---|---|---|---|---|
| Age | 1025 | 30 (21, 47) | 31 (21, 48) | 28 (21, 38) | 0.024 |
| Sexe | 1025 | 0.004 | |||
| f | 470 (46%) | 424 (48%) | 46 (34%) | ||
| m | 555 (54%) | 466 (52%) | 89 (66%) | ||
| toux | 1025 | 923 (90%) | 790 (89%) | 133 (99%) | <0.001 |
| fievre | 1025 | 903 (88%) | 769 (86%) | 134 (99%) | <0.001 |
| duree_signes | 1025 | 14 (10, 15) | 14 (9, 15) | 14 (12, 16) | 0.11 |
| cohabite_contact | 1025 | 139 (14%) | 108 (12%) | 31 (23%) | 0.001 |
| temps_contact | 134 | 5.0 (3.0, 6.0) | 5.0 (3.5, 6.0) | 5.0 (2.5, 6.0) | 0.5 |
| Unknown | 891 | 787 | 104 | ||
| Amaigrisement | 1025 | 493 (48%) | 370 (42%) | 123 (91%) | <0.001 |
| Type_echantillon | 1025 | 0.024 | |||
| crach | 853 (83%) | 731 (82%) | 122 (90%) | ||
| crach_mil | 172 (17%) | 159 (18%) | 13 (9.6%) | ||
| Aspect_crachat | 1025 | <0.001 | |||
| Mucopurulent | 440 (43%) | 350 (39%) | 90 (67%) | ||
| Mucus | 3 (0.3%) | 3 (0.3%) | 0 (0%) | ||
| Mucus+Salivaire | 62 (6.0%) | 57 (6.4%) | 5 (3.7%) | ||
| Purulent | 5 (0.5%) | 4 (0.4%) | 1 (0.7%) | ||
| Salivaire | 512 (50%) | 473 (53%) | 39 (29%) | ||
| Sanguinolant | 3 (0.3%) | 3 (0.3%) | 0 (0%) | ||
| Resultat_geneXpert | 11 | 0.2 | |||
| detect | 3 (27%) | 1 (12%) | 2 (67%) | ||
| nondetect | 8 (73%) | 7 (88%) | 1 (33%) | ||
| Unknown | 1014 | 882 | 132 | ||
| Résistance_rifampicine | 6 | 0.2 | |||
| nondet | 5 (83%) | 5 (100%) | 0 (0%) | ||
| other | 1 (17%) | 0 (0%) | 1 (100%) | ||
| Unknown | 1019 | 885 | 134 | ||
| pharmacie | 1025 | 0.011 | |||
| informelle | 530 (52%) | 446 (50%) | 84 (62%) | ||
| formelle | 495 (48%) | 444 (50%) | 51 (38%) | ||
|
1
Statistics presented: median (IQR); n (%)
2
Statistical tests performed: Wilcoxon rank-sum test; chi-square test of independence; Fisher's exact test
|
|||||
Repartition des patients selons les types de pharmacie frequentés
data_pharmay%>%
tbl_summary(by = "pharmacie")%>%
add_p()%>%
add_overall()%>%
add_n()%>%
bold_labels()| Characteristic | N | Overall, N = 1025 | informelle, N = 5301 | formelle, N = 4951 | p-value2 |
|---|---|---|---|---|---|
| Age | 1025 | 30 (21, 47) | 30 (21, 47) | 30 (22, 47) | 0.9 |
| Sexe | 1025 | 0.6 | |||
| f | 470 (46%) | 238 (45%) | 232 (47%) | ||
| m | 555 (54%) | 292 (55%) | 263 (53%) | ||
| toux | 1025 | 923 (90%) | 496 (94%) | 427 (86%) | <0.001 |
| fievre | 1025 | 903 (88%) | 522 (98%) | 381 (77%) | <0.001 |
| duree_signes | 1025 | 14 (10, 15) | 14 (8, 14) | 14 (12, 21) | <0.001 |
| cohabite_contact | 1025 | 139 (14%) | 74 (14%) | 65 (13%) | 0.8 |
| temps_contact | 134 | 5.0 (3.0, 6.0) | 4.0 (3.0, 6.0) | 6.0 (3.5, 7.0) | 0.019 |
| Unknown | 891 | 459 | 432 | ||
| Amaigrisement | 1025 | 493 (48%) | 269 (51%) | 224 (45%) | 0.089 |
| Type_echantillon | 1025 | <0.001 | |||
| crach | 853 (83%) | 497 (94%) | 356 (72%) | ||
| crach_mil | 172 (17%) | 33 (6.2%) | 139 (28%) | ||
| Aspect_crachat | 1025 | <0.001 | |||
| Mucopurulent | 440 (43%) | 255 (48%) | 185 (37%) | ||
| Mucus | 3 (0.3%) | 3 (0.6%) | 0 (0%) | ||
| Mucus+Salivaire | 62 (6.0%) | 0 (0%) | 62 (13%) | ||
| Purulent | 5 (0.5%) | 3 (0.6%) | 2 (0.4%) | ||
| Salivaire | 512 (50%) | 267 (50%) | 245 (49%) | ||
| Sanguinolant | 3 (0.3%) | 2 (0.4%) | 1 (0.2%) | ||
| Resultat_miscrop | 1025 | 0.011 | |||
| Négatif | 890 (87%) | 446 (84%) | 444 (90%) | ||
| Positif | 135 (13%) | 84 (16%) | 51 (10%) | ||
| Resultat_geneXpert | 11 | 0.5 | |||
| detect | 3 (27%) | 0 (0%) | 3 (38%) | ||
| nondetect | 8 (73%) | 3 (100%) | 5 (62%) | ||
| Unknown | 1014 | 527 | 487 | ||
| Résistance_rifampicine | 6 | >0.9 | |||
| nondet | 5 (83%) | 0 (NA%) | 5 (83%) | ||
| other | 1 (17%) | 0 (NA%) | 1 (17%) | ||
| Unknown | 1019 | 530 | 489 | ||
|
1
Statistics presented: median (IQR); n (%)
2
Statistical tests performed: Wilcoxon rank-sum test; chi-square test of independence; Fisher's exact test
|
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d=glm(as.factor(Resultat_miscrop)~Age+Sexe+toux+fievre+duree_signes+cohabite_contact+Amaigrisement+pharmacie ,family=binomial(logit), data=data_pharmay)
t1 <- tbl_regression(d, exponentiate = TRUE)
e=glm(pharmacie~Age+Sexe+toux+fievre+duree_signes+cohabite_contact+Amaigrisement+Resultat_miscrop ,family=binomial(logit), data=data_pharmay)
t2 <- tbl_regression(e, exponentiate = TRUE)
library("survival", lib.loc="/Library/Frameworks/R.framework/Versions/4.0/Resources/library")
library("survminer", lib.loc="/Library/Frameworks/R.framework/Versions/4.0/Resources/library")## Warning: package 'ggplot2' was built under R version 4.0.1n=coxph(Surv(duree_signes, as.numeric(Resultat_miscrop)) ~ Age+Sexe+toux+fievre+cohabite_contact+Amaigrisement+pharmacie,data = data_pharmay)%>%
gtsummary::tbl_regression(exp = TRUE) Determinants de la TB chez les patients qui visitent les pharmacies
tbl_merge( tbls = list(t1,t2,n),tab_spanner = c("**Resultat de microscopie**", "**Type de pharmacie**","**Time to test**"))| Characteristic | Resultat de microscopie | Type de pharmacie | Time to test | ||||||
|---|---|---|---|---|---|---|---|---|---|
| OR1 | 95% CI1 | p-value | OR1 | 95% CI1 | p-value | HR1 | 95% CI1 | p-value | |
| Age | 0.98 | 0.97, 0.99 | 0.006 | 1.00 | 0.99, 1.01 | 0.5 | 0.99 | 0.98, 1.00 | 0.009 |
| Sexe | |||||||||
| f | — | — | — | — | — | — | |||
| m | 1.57 | 1.04, 2.39 | 0.033 | 0.97 | 0.74, 1.27 | 0.8 | 1.35 | 0.95, 1.94 | 0.10 |
| toux | |||||||||
| no | — | — | — | — | — | — | |||
| yes | 8.18 | 2.44, 50.9 | 0.004 | 0.85 | 0.50, 1.45 | 0.5 | 5.97 | 1.46, 24.3 | 0.013 |
| fievre | |||||||||
| no | — | — | — | — | — | — | |||
| yes | 10.7 | 2.24, 193 | 0.021 | 0.06 | 0.03, 0.12 | <0.001 | 9.40 | 1.31, 67.7 | 0.026 |
| duree_signes | 1.00 | 0.99, 1.02 | 0.6 | 1.05 | 1.04, 1.06 | <0.001 | |||
| cohabite_contact | |||||||||
| no | — | — | — | — | — | — | |||
| yes | 0.96 | 0.58, 1.54 | 0.9 | 1.08 | 0.71, 1.63 | 0.7 | 0.97 | 0.65, 1.46 | 0.9 |
| Amaigrisement | |||||||||
| no | — | — | — | — | — | — | |||
| yes | 15.4 | 8.54, 30.2 | <0.001 | 0.80 | 0.58, 1.08 | 0.14 | 11.7 | 6.40, 21.6 | <0.001 |
| pharmacie | |||||||||
| informelle | — | — | — | — | |||||
| formelle | 0.73 | 0.47, 1.11 | 0.14 | 0.40 | 0.28, 0.58 | <0.001 | |||
| Resultat_miscrop | |||||||||
| Négatif | — | — | |||||||
| Positif | 0.79 | 0.52, 1.21 | 0.3 | ||||||
|
1
OR = Odds Ratio, CI = Confidence Interval, HR = Hazard Ratio
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# Delai de depistage des patients frequantant les pharmacies
ggsurvplot(fit = survfit(Surv(duree_signes, as.numeric(Resultat_miscrop)) ~ 1,data =data_pharmay ), xlab = "Days", ylab = "Overall survival probability",pval = T,risk.table = T,conf.int = T,surv.median.line = "hv")## Warning in .pvalue(fit, data = data, method = method, pval = pval, pval.coord = pval.coord, : There are no survival curves to be compared.
## This is a null model.## Warning in .add_surv_median(p, fit, type = surv.median.line, fun = fun, : Median
## survival not reached.
# Comparaison des delais de diagnostic des patients entre les patients frequantant les pharmacies formelles et informelles
ggsurvplot(fit = survfit(Surv(duree_signes, as.numeric(Resultat_miscrop)) ~ pharmacie,data =data_pharmay ), xlab = "Days", ylab = "Overall survival probability",pval = T,risk.table = T,conf.int = T,surv.median.line = "hv")## Warning in .add_surv_median(p, fit, type = surv.median.line, fun = fun, : Median
## survival not reached.## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.