Abstract
Background
Tuberculosis (TB) prevalence is increasing among women of reproductive age (WRA) in sub-Saharan Africa, yet undiagnosed and untreated cases remain rather high with serious health and socio-economic consequences. We aimed to assess the prevalence and predictors of TB in WRA seeking health care for acute respiratory symptoms.
Methods
We consecutively enrolled outpatient WRA with acute respiratory symptoms seeking care at four healthcare facilities in Ethiopia between July 2019 and December 2020. Data on sociodemographic characteristics and clinical information were collected using a structured questionnaire administered by trained nurses. Posteroanterior chest X-ray was performed in non-pregnant WRA and interpreted independently by two radiologists. Sputum samples were collected from all patients and tested for pulmonary TB using Xpert MTB/RIF and/or smear microscopy. Predictors of bacteriologically confirmed TB cases were determined using binary logistic regression, with clinically relevant variables included in the final Firth’s multivariate-penalized logistic regression model.
Results
We enrolled 577 participants, of whom 95 (16%) were pregnant, 67 (12%) were living with HIV, 512 (89%) had cough of less than 2 weeks, and 56 (12%) had chest-x-ray findings suggestive of TB. The Overall prevalence of TB was 3% (95% CI: 1.8%-4.7%) with no significant difference observed between patient groups categorized by duration of cough or HIV serostatus (P-value = 0.9999). In multivariable analysis, TB-suggestive CXR abnormality (AOR 18.83 [95% CI, 6.20–57.18]) and history of weight loss (AOR 3.91 [95% CI, 1.25–12.29]) were associated with bacteriologically-confirmed TB cases.
Conclusions
We found a high TB prevalence among low-risk women of reproductive age with acute respiratory symptoms. Routine CXR may improve early case detection and thereby TB treatment outcomes.
Keywords: Chest X-ray, Pulmonary tuberculosis, Women of reproductive age, EXIT-TB, Acute respiratory symptoms, Ethiopia
1. Introduction
Tuberculosis (TB) is a leading infectious cause of morbidity and mortality, including in women of reproductive age (WRA) between the ages of 15 and 49, with an estimated 1.6 million deaths in 2021 [1], [2], [3]. Of all HIV-related TB deaths worldwide in 2020, about half are women [4] and almost 90% of HIV-related TB deaths in women occur in sub-Saharan Africa (SSA) [5]. Although most TB cases are still diagnosed in men [1], reported cases in WRA are increasing in SSA [2], [6]. Most available anti-TB regimens are safe and effective even during pregnancy, with a good compliance rate reported [7], [8], Yet TB patients are often diagnosed late in the disease course, with 60% of the estimated number of cases going undiagnosed or unreported in 2021 [1], [9]. In TB-endemic countries, untreated TB remains a notorious cause of infertility and poor maternal and perinatal outcomes [5], [8], [10], [11].
The literature reports that the prevalence of TB in WRA age is high, even in asymptomatic or acutely symptomatic patients [6], [12], [13], [14], [15]. A study also found a high prevalence of pulmonary TB in patients presenting to outpatient clinics for a cough lasting less than two weeks [16]. In contrast, some studies have reported a low TB prevalence in predominantly HIV-negative pregnant cohorts, regardless of the duration of respiratory symptoms [17], [18], [19], and a cough lasting longer than two weeks has been suggested as a better criterion for HIV-negative pregnant women [18].
Recognizing the importance of early TB case detection, recent WHO guidelines have included tools that increase the sensitivity of TB case detection, namely chest X-ray (CXR), C-reactive protein (CRP) in people living with HIV, and rapid molecular diagnostic tests [9]. However, performing CXR raises safety concerns in pregnant women [20], and molecular diagnostic tests may not be sensitive in patients living with HIV [14], [21] or unavailable in most health facilities where patients first encounter the healthcare system [22]. Physicians reported seeing a large number of patient cases in reproductive and child health (RCH) clinics and tend to focus on “more common” diagnoses as available resources do not allow them to follow guidelines [18].
In WRA, there is a need to improve case detection capabilities [10], however, which patients should be tested to maximize case detection while giving due consideration to resource implications remains a topic of research and controversy. Besides, optimal TB case-finding methods for pregnant women are ill-investigated. This study aimed to assess the prevalence and predictors of pulmonary TB in WRA seeking healthcare for acute respiratory symptoms.
2. Methods
2.1. Study design setting
This study was part of the EXIT-TB (Scaling up Evidence Based Multiple Focus Integrated Intensified TB Screening to End TB research project; a multi-center implementation study that implements and evaluates EXIT-TB package to increase TB case detection in the East African region [23], [24], [25], [26]. The study followed a quantitative, multicenter cross-sectional study design. It was conducted in four health institutions in Ethiopia from July 2019 to December 2020; two hospitals were in urban areas, namely, Hiwot Fana Specialized University Hospital found in Harari Region and Zewditu Memorial Hospital found in Addis Ababa City Government, and one hospital and one health center located in rural areas, thus Chelenko Primary Hospital and Melka Jebdu Health Center found in Oromia Region. Site selection was done using stratified random sampling taking into account the difference between urban and rural settings [23] and referral bias.
2.2. Participants
Participants were WRA with acute respiratory symptoms seeking outpatient care in the four study facilities. Acute respiratory symptom was defined primarily as a cough of less than two weeks duration. The Sample size was estimated using a single proportion formula with a 95% confidence level, 80% power, 3% margin of error, 15% contingency, and an assumed bacteriologically-confirmed pulmonary TB prevalence among WRA of 5.3% [12]. These reached a final sample size of 577. Participants with diabetes, HIV/AIDS, alcohol use disorders, smoking and malnutrition were considered high-risk groups for developing TB according to guidelines [9].
2.3. Data collection procedures
WRA attending outpatient clinics for acute respiratory symptoms with no confirmed pulmonary TB and consented to participate in the study were consecutively enrolled in the study. To determine the prevalence and predictors of bacteriologically confirmed TB in WRA age who presented with cough of acute duration, four trained data collectors administered a structured and pre-tested questionnaire that included socioeconomic and demographic variables, risk factors for TB, and active respiratory symptoms.
All study participants, except pregnant women, underwent quality-controlled posteroanterior CXRs, and two experienced radiologists blinded to clinical information interpreted the films. Inter-observer agreement for all CXR films obtained as part of the project was checked and we found an adequate agreement for TB suggestive findings [kappa = 95% (95% CI: 87.598.6%)].
All study participants gave sputum specimens which were tested for TB using Xpert MTB/RIF (Cepheid, Sunnyvale, CA, USA) and/or smear microscopy based on the national TB guideline [24]. Laboratory-confirmed cases were referred and linked to treatment.
2.4. Statistical analysis
Collected data were cleaned, entered into EpiData version 3.1 and then transferred to Stata version 14.2 (StataCorp, College Station, Texas, USA) for statistical analysis. First, descriptive statistics were generated for sociodemographic variables, TB risk factors, and active respiratory symptoms and associations with TB status checked using Fisher's exact test. Subsequently, predictors of bacteriologically confirmed TB cases were determined using binary logistic regression, with clinically relevant variables included in the final multivariate-penalized logistic regression model (firthlogit). Odds ratios with 95% confidence intervals (CIs) were reported and a P-value of less than 5% was considered statistically significant.
2.5. Ethical approval
This study was approved by the Institutional Review Board of the College of Health Sciences, Addis Ababa University, and the Institutional Health Research Ethics Review Committee of the College of Health and Medical Sciences, Haramaya University. Written consent was obtained from each participant or parents as applicable, and assent was sought from children under the age of 18. All patients received standard care according to national guidelines and those diagnosed with TB were linked to TB treatment clinics [27].
3. Results
3.1. Sociodemographic characteristics of study participants
A total of 577 WRA were included, of whom 95 (16%) were pregnant. The participants had a mean age (SD) of 29.8 (9) years and 262 (46%) were in the 25–34 age group. Four participants were under the age of 18. Descriptive statistics on sociodemographic variables and classification by bacteriologically-confirmed TB status are presented in Table 1.
Table 1.
Socio-demographic Characteristics | N = 577 % | Smear/X pert Positive | Smear/X pert negative | P-value* |
---|---|---|---|---|
Health Facility | ||||
Melka Jebdu Health center | 181 (31) | 1 | 180 | 0.0700 |
Hiwot Fana University Hospital | 178 (31) | 8 | 170 | |
Zewditu Memorial Hospital | 120 (21) | 4 | 116 | |
Chelenko Primary Hospital | 98 (17) | 4 | 94 | |
Clinic | ||||
Out-patient department | 475 (82.4) | 17 | 458 | 0.2850 |
Antenatal care | 94 (16.2) | 0 | 94 | |
Diabetic clinic | 3 (0.5) | 0 | 3 | |
Family planning | 1 (0.2) | 0 | 1 | |
Labor ward | 1 (0.2) | 0 | 1 | |
Postnatal care | 3 (0.5) | 0 | 3 | |
Age category | ||||
15–24 | 169 (29) | 7 | 162 | 0.5430 |
25–34 | 262 (46) | 7 | 255 | |
35–49 | 146 (25) | 3 | 143 | |
Level of education | ||||
Never attended | 295 (51) | 9 | 286 | 0.6510 |
Primary Education | 138 (24) | 3 | 135 | |
Secondary Education | 80 (14) | 3 | 77 | |
Vocational Training | 20 (3) | 0 | 20 | |
Tertiary education | 27 (5) | 2 | 25 | |
Traditional Education | 17 (3) | 0 | 17 | |
Marital Status | ||||
Single | 102 (18) | 4 | 98 | 0.1070 |
Married | 410 (71) | 9 | 401 | |
Separated | 23 (4) | 1 | 22 | |
Divorced | 20 (3) | 0 | 20 | |
Widow/Widower | 22 (4) | 3 | 19 | |
Occupation | ||||
Student | 51 (9) | 1 | 50 | 1.0000 |
Employed | 87 (15) | 2 | 85 | |
Peasant | 65 (11) | 2 | 63 | |
Housewife | 342 (59) | 11 | 331 | |
Business owner | 32 (6) | 1 | 31 | |
Residence | ||||
Rural | 278 (18) | 11 | 267 | 0.1280 |
Urban | 299 (52) | 5 | 293 |
*p-values are expressed from Fisher's exact tests; N: absolute frequency; %: percentage.
3.2. Clinical symptoms and TB risk factors
Of the total, 67 (12%) of the participants were living with HIV and 51 (76%) of them were on ART. Five hundred twelve (89%) participants had a cough less than two weeks, and 306 (53%) reported one or more accompanying respiratory symptoms such as fever, hemoptysis, chest pain, or shortness of breath. CXR was performed in 482 non-pregnant participants, of whom 56 (12%) had findings suggestive of TB (Table 2).
Table 2.
Risk factors and Clinical Presentation | N = 577 % | Xpert/Smear positive | Smear/X pert negative | P-value |
---|---|---|---|---|
HIV serostatus | ||||
Positive | 67 (12) | 2 | 65 | 0.9999 |
Negative | 510 (88) | 15 | 495 | |
Is the patient on ART | ||||
Yes | 51 (76) | 1 | 50 | 0.4180 |
No | 16 (24) | 1 | 15 | |
TB contact history | ||||
Yes | 67 (12) | 5 | 62 | 0.0390 |
No | 503 (87) | 12 | 491 | |
Not sure | 7 (1) | 0 | 7 | |
Chronic diseases | ||||
Chronic disease/s present | 28 (5) | 0 | 28 | 0.9999 |
No chronic disease | 549 (95) | 17 | 532 | |
Alcohol intake | ||||
Yes | 90 (16) | 3 | 87 | 0.7380 |
No | 487 (84) | 14 | 473 | |
Cigarette smoking | ||||
Yes | 12 (2) | 1 | 11 | 0.3040 |
No | 565 (98) | 16 | 549 | |
Duration of cough | ||||
Cough < 2 weeks | 512 (89) | 15 | 497 | 0.9999 |
Cough ≥ 2 weeks | 65 (11) | 2 | 63 | |
fever | ||||
Yes | 236 (41) | 4 | 232 | 0.2100 |
No | 341 (59) | 13 | 328 | |
Hemoptysis | ||||
Yes | 80 (14) | 4 | 76 | 0.2750 |
No | 497 (86) | 13 | 484 | |
Chest pain | ||||
Yes | 15 (3) | 0 | 17 | 0.9999 |
No | 560 (97) | 17 | 543 | |
Shortness of breath | ||||
Yes | 8 (1) | 0 | 8 | 0.9999 |
No | 569 (99) | 17 | 552 | |
Night sweat | ||||
Yes | 310 (54%) | 10 | 300 | 0.8070 |
No | 267 (46%) | 7 | 260 | |
Weight loss | ||||
yes | 88 (15) | 6 | 82 | 0.0320 |
No | 489 (85) | 11 | 478 | |
Chest X-ray | ||||
Suggestive of TB | 56 (10) | 11 | 45 | 0.0001 |
Normal/Non-suggestive | 426 (74) | 6 | 420 | |
Not done | 95 (16) | 0 | 95 |
N: absolute frequency; %: percentage; ART: antiretroviral treatment
Xpert MTB/RIF was done for all participants and sputum smear microscopy was performed in all except 11 participants. 17 patients [3% (95% CI: 1.8%-4.7%)] had bacteriologically confirmed TB. In pregnant WRA, there were no diagnosed cases of TB. Similarly, no clinically diagnosed TB case was recorded in this study. The prevalence of TB in WRA with coughs lasting less than 2 weeks was 2.93%, which was comparable to those with chronic coughs at 3.08% (Fisher's exact p-value = 0.9999) (Table 2). Likewise, no significant difference in TB prevalence was found between WRA living with or without HIV (Fisher's exact p-value = 0.9999).
3.3. Association between participant characteristics and pulmonary TB
A CXR abnormality suggestive of TB was strongly associated with bacteriologically confirmed TB cases, even after controlling for confounders (P < 0.0001) (Table 3). The odds of TB diagnosis in patients with TB-suggestive CXR findings were 19 times higher than those with normal CXR findings or non-TB-suggestive abnormal findings (AOR, 18.83 [95% CI, 6.20–57.18]). In addition, patients with weight loss had 4 times odds to be diagnosed with TB (AOR, 3.91 [95% CI, 1.25–12.29]). We observed an association between previous contact with a known TB patient and diagnosed TB cases although it does not reach statistical significance when other variables are accounted for (P = 0.1300). There was also no significant difference in the odds of being diagnosed with TB depending on the duration of cough (P = 0.4900) and the presence of established risk factors for TB (Table 3).
Table 3.
Variables | Categories | COR | P | AOR | P |
---|---|---|---|---|---|
95% CI | 95% CI | ||||
Age category | 15–24 | 2.06 (0.52–8.11) | 0.30 | 2.74 (0.66–11.32) | 0.1600 |
25–35 | 1.31 (0.33–5.14) | 0.70 | 1.14 (0.27–4.81) | 0.8600 | |
36–49 | --- | --- | --- | --- | |
HIV serostatus | Positive | 1.02 (0.23–4.54) | 0.98 | 1.33 (0.27–6.57) | 0.7200 |
Negative | --- | --- | --- | --- | |
TB contact History | Yes | 3.30 (1.13–9.68) | 0.03 | 0.38 (0.11–1.27) | 0.1300 |
No | --- | --- | --- | --- | |
Duration of cough | < 2 weeks | --- | --- | --- | --- |
≥ 2 weeks | 0.95 (0.21–4.25) | 0.95 | 0.59 (0.13–2.64) | 0.4900 | |
Other respiratory symptoms* | Present | 0.79 (0.30–2.08) | 0.64 | 0.57 (0.19–1.67) | 0.3100 |
Absent | --- | --- | --- | --- | |
Night sweat | Yes | 1.24 (0.46–3.29) | 0.67 | 0.45 (0.14–1.42) | 0.1700 |
No | --- | --- | --- | --- | |
Weight loss | Yes | 3.18 (1.14–8.83) | <0.01 | 3.91 (1.25–12.29)** | 0.0200 |
No | --- | --- | --- | --- | |
CXR finding | TB suggestive | 17.23 (6.08–48.81) | <0.001 | 18.83 (6.20–57.18) *** | <0.0001 |
Not TB suggestive | --- | --- | --- | --- |
*Other respiratory symptoms: fever, hemoptysis, chest pain and shortness of breath; **Statistically significant for tuberculosis at P value <0.05; ***Statistically significant for tuberculosis at P value <0.0001; CI: confidence interval; COR: crude odds ratio; AOR: Adjusted odds ratio.
4. Discussion
This study aimed to determine the prevalence and predictors of bacteriologically-confirmed pulmonary TB among WRA with acute respiratory symptoms visiting healthcare facilities for treatment. CXR abnormality suggestive of TB and a history of weight loss had significant associations with bacteriologically-confirmed TB cases.
This study found a higher TB prevalence among out-patients with acute duration of cough than previously reported study in Ethiopia, at 1.9% [16], although lower than the prevalence in chronic coughers [12], [16]. In the first study, however, only 46% of the study participants were women and no data was available on how many were in the reproductive age groups [16]. There were no confirmed TB cases among pregnant women in our study, which was comparable with a previous study [17] that reported no culture-confirmed cases out of 174 pregnant women with a cough duration of more than 2 weeks. No significant difference in TB prevalence was observed among WRA living with or without HIV, unlike studies from elsewhere that noted limited TB cases in HIV-negative women [12], [13], [18], [19]. A possible explanation for the observed difference could be that the previous studies have enrolled comparatively higher number of women living with HIV/AIDS [12], [13]. In addition, some of the studies have included a confirmatory culture test [13], or addressed only chronically coughing WRA [12].
In this study, the prevalence of TB was fairly comparable among participants presenting with a duration of cough of less or more than two weeks, as also reported elsewhere [24]. Although there are previous studies that questioned cough duration as a significant risk factor, they reported a discrepant occurrence of TB in the two groups [28], [29]. In addition, a recent study from Eswatini found no difference in TB prevalence between symptomatic and asymptomatic patients [13]. Currently, symptom-based screening for TB, even modified to include patients with cough of any duration, is becoming less preferred as it missed to detect a significant number of TB cases [14], [30] although it was found to have good specificity [31] and cost-effectiveness. The findings of this study challenge the use of 2-week cough criteria to prioritize patients for the limited TB diagnostic resources. A separate study found a TB prevalence of 14% among all acutely coughing outpatients and recommended that patients with acute cough should undergo a TB workup including CXR [23]. Despite the low TB prevalence of 3% we found in WRA, the same recommendations can be made considering the grave consequences of TB in these patients.
A CXR abnormality suggestive of TB was found to be better at predicting cases in the present study, and it may outperform cough duration-based algorithms in assigning low-risk WRA to different TB likelihood categories. Furthermore, CXR has documented benefits in improving TB case detection compared to symptom-based screening in adults [30], [31] and there is increasing interest in adopting CXR-based screening in national TB programs in line with WHO recommendations [9]. It is important to keep in mind that 35% of TB cases occurred in patients who did not have suggestive CXR findings. Although computer-aided detection of TB suggestive findings may have improved the performance and feasibility of CXR-based diagnosis in a study setting, it is not widely available today [32], [33].
We could not perform a subgroup analysis in pregnant women as no TB case was identified among them. Although we included few pregnant women in our study, a sputum sample was obtained from all and analyzed according to national guidelines. However, bacteriological TB diagnostic tests, particularly smear microscopy, are known to have low sensitivity in pregnant women [8], [15]. There is also a recent study reporting reduced sensitivity of molecular diagnostic tests in pregnant women compared to confirmatory culture [14]. In multivariable analysis, patients with suggestive CXR abnormalities and weight loss had higher odds of being diagnosed with TB. As is well known, physicians hesitate to order CXR in pregnant women, and these patients are less likely to present with weight loss [7]. However, TB can present with acute respiratory symptoms during pregnancy and shielded CXR is an option to improve case detection [8]. A clinically diagnosed case of TB was also not documented among enrolled patients, possibly reflecting the ingrained thinking of health workers that associates TB with a cough lasting longer than 2 weeks. The wider clinical, public health, social and structural forces are all important in decisions surrounding TB screening, diagnosis, and management [34], [35], [36], [37], [38], [39].
This study reported solid evidence about the prevalence and predictors of TB in WRA seeking health care for acute respiratory symptoms in one of the high TB burden countries, Ethiopia. However, the study has some limitations. First, most study participants were nonpregnant, low-risk WRA, and the results may not be generalizable to high-risk WRA. Second, we did not include as many women with chronic symptoms, which may have reduced the number of cases identified and influenced the comparison.
5. Conclusion
TB is prevalent in low-risk women of reproductive age with acute respiratory symptoms. Routine CXR may improve early case detection and thereby TB treatment outcomes, thus should be performed and interpreted with TB in mind to identify and put more cases into treatment. More studies that included a larger number of pregnant and HIV-positive women are recommended to provide better insight into the TB burden among high-risk women.
Funding
This work was funded by the European and Developing Countries Clinical Trials Partnership (EDCTP2) program supported by the European Union under grant number CSA2016S-1608.
Ethics approval and consent to participate
This study was approved by the Institutional Review Board of the College of Health Sciences, Addis Ababa University, and the Institutional Health Research Ethics Review Committee of the College of Health and Medical Sciences, Haramaya University, Ethiopia.
Consent for publication
Study participants have given their full consent for publication.
Availability of data and materials
The datasets used and/or analyzed during the current study will be available from the corresponding author on reasonable request.
CRediT authorship contribution statement
Tesfahunegn Hailemariam: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing. Getnet Yimer: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing. Hussen Mohammed: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing. Haileleul Bisrat: Visualization, Project administration, Methodology, Validation, Writing – review & editing. Tigist Ajeme: Visualization, Project administration, Methodology, Validation, Writing – review & editing. Merga Belina: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing. Lemessa Oljira: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing. Kedir Teji Roba: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing. Fekadu Belay: Data curation, Formal analysis, Methodology, Software. Tsion Andrias: Data Curation, Formal analysis. Esther Ngadaya: Visualization, Project administration, Methodology, Validation, Writing – review & editing. Tsegahun Manyazewal: Conceptualization, Methodology, Writing – review & editing, Supervision.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
The authors thank the Center for Innovative Drug Development and Therapeutic Trials for Africa (CDT-Africa), College of Health Sciences, Addis Ababa University, Ethiopia, for providing technical support and managing the grant. The authors thank Haramaya University for supporting the execution of the project.
Contributor Information
Tesfahunegn Hailemariam, Email: tesfa.feleke21@aau.edu.et.
Getnet Yimer, Email: Getnet.Yimer@Pennmedicine.upenn.edu.
Haileleul Bisrat, Email: haileleul.bisrat@aau.edu.et.
Tigist Ajeme, Email: tigist.ajeme@aau.edu.et.
Merga Belina, Email: merga.belina@aau.edu.et.
Tsegahun Manyazewal, Email: tsegahun.manyazewal@aau.edu.et.
References
- 1.Bagcchi S. WHO's Global Tuberculosis Report 2022. The Lancet Microbe. 2023;4(1):e20. doi: 10.1016/S2666-5247(22)00359-7. [DOI] [PubMed] [Google Scholar]
- 2.Korri R., Bakuli A., Owolabi O.A., Lalashowi J., Azize C., Rassool M., et al. Tuberculosis and Sexual and Reproductive Health of Women in Four African Countries. Int J Environ Res Public Health. 2022;19(22):15103. doi: 10.3390/ijerph192215103. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Dheresa M., Tura A.K., Daraje G., Abebe M., Dingeta T., Shore H., et al. Trend and determinants of mortality among women of reproductive age: a twelve-year open cohort study in Eastern Ethiopia. Front Global Women's Health. 2021;2 doi: 10.3389/fgwh.2021.762984. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.World Health Organization, Global tuberculosis report 2021: supplementary material. 2022.
- 5.World Health Organization, WHO Tuberculosis in women factsheet. 2019.
- 6.Walles J., Tesfaye F., Jansson M., Balcha T.T., Sturegård E., Kefeni M., et al. Tuberculosis infection in women of reproductive age: a cross-sectional study at antenatal care clinics in an Ethiopian city. Clin Infect Dis. 2021;73(2):203–210. doi: 10.1093/cid/ciaa561. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.van de Water B.J., Brooks M.B., Huang C.-C., Trevisi L., Lecca L., Contreras C., et al. Tuberculosis clinical presentation and treatment outcomes in pregnancy: a prospective cohort study. BMC Infect Dis. 2020;20(1) doi: 10.1186/s12879-020-05416-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Annie H.S.Y., Lao T.T. Tuberculosis in pregnancy. Best Pract Res Clin Obstet Gynaecol. 2022 doi: 10.1016/j.bpobgyn.2022.07.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.World Health Organization, WHO consolidated guidelines on tuberculosis: module 2: screening: systematic screening for tuberculosis disease. 2021: World Health Organization. [PubMed]
- 10.Salazar-Austin N., Hoffmann J., Cohn S., Mashabela F., Waja Z., Lala S., et al. Poor obstetric and infant outcomes in human immunodeficiency virus-infected pregnant women with tuberculosis in South Africa: the Tshepiso study. Clin Infect Dis. 2018;66(6):921–929. doi: 10.1093/cid/cix851. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Mussie K.M., Gradmann C., Manyazewal T. Bridging the gap between policy and practice: a qualitative analysis of providers' field experiences tinkering with directly observed therapy in patients with drug-resistant tuberculosis in Addis Ababa, Ethiopia. BMJ Open. 2020;10(6):e035272. doi: 10.1136/bmjopen-2019-035272. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Berju A., Haile B., Nigatu S., Mengistu A., Birhan G. Smear-positive tuberculosis prevalence and associated factors among pregnant women attending antinatal care in North Gondar Zone Hospitals, Ethiopia. Int J Microbiol. 2019;2019:1–6. doi: 10.1155/2019/9432469. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Pasipamire M., Broughton E., Mkhontfo M., Maphalala G., Simelane-Vilane B., Haumba S. Detecting tuberculosis in pregnant and postpartum women in Eswatini. Afr J Laboratory Med. 2020;9(1) doi: 10.4102/ajlm.v9i1.837. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.LaCourse SM, et al., Tuberculosis case finding in HIV-infected pregnant women in Kenya reveals poor performance of symptom screening and rapid diagnostic tests. J Acquired Immune Deficiency Syndromes (1999), 2016. 71(2): p. 219. [DOI] [PMC free article] [PubMed]
- 15.Kali P.B.N., Gray G.E., Violari A., Chaisson R.E., McIntyre J.A., Martinson N.A. Combining PMTCT with active case finding for tuberculosis. JAIDS J Acquired Immune Deficiency Syndromes. 2006;42(3):379–381. doi: 10.1097/01.qai.0000218434.20404.9c. [DOI] [PubMed] [Google Scholar]
- 16.Eliso E., Medhin G., Belay M. Prevalence of smear positive pulmonary tuberculosis among outpatients presenting with cough of any duration in Shashogo Woreda, Southern Ethiopia. MC Public Health. 2015;15(1):1–6. doi: 10.1186/s12889-015-1411-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Gebreegziabiher D., Adane K., Abebe M. A survey on undiagnosed active pulmonary tuberculosis among pregnant mothers in Mekelle and surrounding districts in Tigray, Ethiopia. Int J Mycobacteriol. 2017;6(1):43. doi: 10.4103/2212-5531.201889. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Vijayageetha M., Kumar A.MV., Ramakrishnan J., Sarkar S., Papa D., Mehta K., et al. Tuberculosis screening among pregnant women attending a tertiary care hospital in Puducherry, South India: is it worth the effort? Glob Health Action. 2019;12(1):1564488. doi: 10.1080/16549716.2018.1564488. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Adjobimey M., Ade S., Wachinou P., Esse M., Yaha L., Bekou W., et al. Prevalence, acceptability, and cost of routine screening for pulmonary tuberculosis among pregnant women in Cotonou, Benin. PLoS One. 2022;17(2):e0264206. doi: 10.1371/journal.pone.0264206. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Hartsough K., Teasdale C.A., Shongwe S., Geller A., Pimentel De Gusmao E., Dlamini P., et al. Enhanced integration of TB services in reproductive maternal newborn and child health (RMNCH) settings in Eswatini. PLOS Global Public Health. 2022;2(4):e0000217. doi: 10.1371/journal.pgph.0000217. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Getachew E., Adebeta T., Gebrie D., Charlie L., Said B., Assefa D.G., et al. Pyrosequencing for diagnosis of multidrug and extensively drug-resistant tuberculosis: a systemic review and meta-analysis. J Clin Tuberc Other Mycobact Dis. 2021;24 doi: 10.1016/j.jctube.2021.100254. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.García-Basteiro A.L., DiNardo A., Saavedra B., Silva D.R., Palmero D., Gegia M., et al. Point of care diagnostics for tuberculosis. Pulmonology. 2018;24(2):73–85. doi: 10.1016/j.rppnen.2017.12.002. [DOI] [PubMed] [Google Scholar]
- 23.Mohammed H., Oljira L., Roba K.T., Ngadaya E., Manyazewal T., Ajeme T., et al. Tuberculosis prevalence and predictors among health care-seeking people screened for cough of any duration in Ethiopia: a multicenter cross-sectional study. Front Public Health. 2022;9 doi: 10.3389/fpubh.2021.805726. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Mohammed H., Oljira L., Roba K.T., Ngadaya E., Tesfaye D., Manyazewal T., et al. Impact of early chest radiography on delay in pulmonary tuberculosis case notification in Ethiopia. Int J Mycobacteriol. 2021;10(4):364. doi: 10.4103/ijmy.ijmy_216_21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Mohammed H., Oljira L., Teji Roba K., Ngadaya E., Mehari R., Manyazewal T., et al. Who to involve and where to start integrating tuberculosis screening into routine healthcare services: positive cough of any duration as the first step for screening tuberculosis in Ethiopia. Risk Manag Healthc Policy. 2021;14:4749–4756. doi: 10.2147/RMHP.S337392. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Mohammed H., Oljira L., Roba K.T., Ngadaya E., Ajeme T., Haile T., et al. Burden of tuberculosis and challenges related to screening and diagnosis in Ethiopia. J Clin Tuberc Other Mycobact Dis. 2020;19 doi: 10.1016/j.jctube.2020.100158. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Health, F.D.R.o.E.M.o., National guidelines for TB, DR-TB and leprosy in Ethiopia. 2018, MoH Addis Ababa.
- 28.Ngadaya E.S., et al. Pulmonary tuberculosis among women with cough attending clinics for family planning and maternal and child health in Dar Es Salaam, Tanzania. BMC Public Health. 2009;9(1):1–6. doi: 10.1186/1471-2458-9-278. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Ngadaya E.S., et al. Detection of pulmonary tuberculosis among patients with cough attending outpatient departments in Dar Es Salaam, Tanzania: does duration of cough matter? BMC Health Serv Res. 2009;9:1–5. doi: 10.1186/1472-6963-9-112. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.van't Hoog A., Viney K., Biermann O., Yang B., Leeflang M.MG., Langendam M.W. Symptom-and chest-radiography screening for active pulmonary tuberculosis in HIV-negative adults and adults with unknown HIV status. Cochrane Database Syst Rev. 2022;2022(5) doi: 10.1002/14651858.CD010890.pub2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Dhana A., Hamada Y., Kengne A.P., Kerkhoff A.D., Rangaka M.X., Kredo T., et al. Tuberculosis screening among ambulatory people living with HIV: a systematic review and individual participant data meta-analysis. Lancet Infect Dis. 2022;22(4):507–518. doi: 10.1016/S1473-3099(21)00387-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.MacPherson P., Webb E.L., Kamchedzera W., Joekes E., Mjoli G., Lalloo D.G., et al. Computer-aided X-ray screening for tuberculosis and HIV testing among adults with cough in Malawi (the PROSPECT study): a randomised trial and cost-effectiveness analysis. PLoS Med. 2021;18(9):e1003752. doi: 10.1371/journal.pmed.1003752. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Bashir S., Kik S.V., Ruhwald M., Khan A., Tariq M., Hussain H., et al. Economic analysis of different throughput scenarios and implementation strategies of computer-aided detection software as a screening and triage test for pulmonary TB. PLoS One. 2022;17(12):e0277393. doi: 10.1371/journal.pone.0277393. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Woods A.M., Mara K.C., Rivera C.G. Clinical pharmacists' interventions and therapeutic drug monitoring in patients with mycobacterial infections. J Clin Tuberc Other Mycobact Dis. 2023;30 doi: 10.1016/j.jctube.2023.100346. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Mussie K.M., Yimer S.A., Manyazewal T., Gradmann C., Torpey K. Exploring local realities: perceptions and experiences of healthcare workers on the management and control of drug-resistant tuberculosis in Addis Ababa, Ethiopia. PLoS One. 2019;14(11):e0224277. doi: 10.1371/journal.pone.0224277. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Manyazewal T., Woldeamanuel Y., Holland D.P., Fekadu A., Marconi V.C. Effectiveness of a digital medication event reminder and monitor device for patients with tuberculosis (SELFTB): a multicenter randomized controlled trial. BMC Med. 2022;20(1):310. doi: 10.1186/s12916-022-02521-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Chilot D., Woldeamanuel Y., Manyazewal T. Real-time impact of COVID-19 on clinical care and treatment of patients with tuberculosis: a multicenter cross-sectional study in Addis Ababa, Ethiopia. Ann Glob Health. 2021;87(1) doi: 10.5334/aogh.3481. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Manyazewal T., Ali M.K., Kebede T., Magee M.J., Getinet T., Patel S.A., et al. Mapping digital health ecosystems in Africa in the context of endemic infectious and non-communicable diseases. NPJ Digit Med. 2023;6(1) doi: 10.1038/s41746-023-00839-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Manyazewal T., et al. Patient-reported usability and satisfaction with electronic medication event reminder and monitor device for tuberculosis: a multicentre, randomised controlled trial. EClinicalMedicine. 2023;56 doi: 10.1016/j.eclinm.2022.101820. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analyzed during the current study will be available from the corresponding author on reasonable request.