Treatment outcomes of patients with tuberculosis in war affected region of Khyber Pakhtunkhwa, Pakistan

Ahmad, Tauseef; Jadoon, Muhammad Ayub; Khan, Muhammad Mumtaz; Haroon, ​; Hussain, Akhtar; Musa, Taha Hussein; Waqar, Muhammad; Ejeta, Eyasu; Karami, Manoochehr; Alene, Kefyalew Addis; Jin, Hui

doi:10.1186/s12879-020-05184-3

Cited by 6 publications

(14 citation statements)

References 22 publications

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“…Internal factors consist of 11 determinants from within the TB patient, namely age, gender, education, HIV status, TB location, treatment category, alcohol consumption, drug use, smoking, type of ARB (Acid Resistant Bacteria), and comorbidities (Ahmad et al, 2020;Atif et al, 2014;Babalik et al, 2014;Banerjee et al, 2020;DesJardin et al, 2020;García-Basteiro et al, 2016;Habte et al, 2020;Khazaei et al, 2016;Mohammadzadeh et al, 2016;Mulogo et al, 2017;Muluye et al, 2018;Mundra et al, 2019;Ogbudebe et al, 2018;Oladimeji et al, 2021;Sadana et al, 2020;Sahyog et al, 2018;Son et al, 2021;Tesema et al, 2020;Tetteh et al, 2018;Umeokonkwo et al, 2020;Wen et al, 2018). 13 articles described age as an internal factor for TB treatment outcomes (Ahmad et al, 2020;Atif et al, 2014;Babalik et al, 2014;Habte et al, 2020;Mundra et al, 2019;Ogbudebe et al, 2018;Oladimeji et al, 2021;Sadana et al, 2020;Son et al, 2021;Tesema et al, 2020;Tetteh et al, 2018;Umeokonkwo et al, 2020;Wen et al, 2018). The likelihood of a successful treatment outcome was higher among patients aged 15-24 years, compared to patients younger than 14 years (Tesema et al, 2020), and over 61 years (Ahmad et al, 2020;Habte et al, 2020).…”

Section: Internal Factorsmentioning

confidence: 99%

“…13 articles described age as an internal factor for TB treatment outcomes (Ahmad et al, 2020;Atif et al, 2014;Babalik et al, 2014;Habte et al, 2020;Mundra et al, 2019;Ogbudebe et al, 2018;Oladimeji et al, 2021;Sadana et al, 2020;Son et al, 2021;Tesema et al, 2020;Tetteh et al, 2018;Umeokonkwo et al, 2020;Wen et al, 2018). The likelihood of a successful treatment outcome was higher among patients aged 15-24 years, compared to patients younger than 14 years (Tesema et al, 2020), and over 61 years (Ahmad et al, 2020;Habte et al, 2020). The determinants of TB treatment outcomes can be seen in Table 2.…”

Section: Internal Factorsmentioning

confidence: 99%

“…The location of TB as a determinant of treatment outcome was identified by eight studies. One study reported a higher probability of successful treatment outcomes in smear-positive PTB patients than in extrapulmonary TB patients (Ahmad et al, 2020). However, seven studies argue otherwise (Atif et al, 2014;Mundra et al, 2019;Oladimeji et al, 2021;Sadana et al, 2020;Son et al, 2021;Tetteh et al, 2018;Wen et al, 2018).…”

Section: Internal Factorsmentioning

confidence: 99%

“…However, seven studies argue otherwise (Atif et al, 2014;Mundra et al, 2019;Oladimeji et al, 2021;Sadana et al, 2020;Son et al, 2021;Tetteh et al, 2018;Wen et al, 2018). Three articles cited the medication category as a cause of unfavorable TB treatment outcomes (Ahmad et al, 2020;Banerjee et al, 2020;Mundra et al, 2019). Patients with category one TB treatment had a higher successful treatment outcome than those with category two.…”

Section: Internal Factorsmentioning

confidence: 99%

“…For this reason, WHO recommends that treatment outcomes be evaluated annually. The monitoring of treatment outcomes provides evidence to assess the effectiveness of TB control programs (Ahmad et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Determinants of tuberculosis treatment outcomes in Asia and Africa

Yuliyani

Sartika

2021

ijhs

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Tuberculosis (TB) is a disease that is both infectious and deadly. Although it can be prevented and treated, the increasing number of TB patients is a nation-wide and global challenge, and thus it requires efforts to control the disease appropriately leading to good treatment outcomes. Identifying the determinants of treatment outcomes is necessary to improve control strategies and programs for TB. Scientific evidence on this issue is still limited. This systematic review aims to describe the potential determinants of TB treatment outcomes regarding the patient’s internal and external factors. The review was carried out using the procedures specified in the PRISMA guidelines. Five databases were used to identify studies related to the determinants of treatment outcomes obtained. There were 829 articles meeting the screening criteria, 23 meeting the criteria for full article review, and 21 for analysis. Most scientific evidence reports the age, sex, HIV status, and location of TB as determinants of treatment outcomes. Sorting and selecting data consistently are necessary in reporting the results of TB treatment which then becomes the foundation for formulating appropriate, targeted, effective, and most needed policies or interventions in improving treatment outcomes and reducing incidence of TB.

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Section: Internal Factorsmentioning

confidence: 99%

Section: Internal Factorsmentioning

confidence: 99%

Section: Internal Factorsmentioning

confidence: 99%

Section: Internal Factorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Determinants of tuberculosis treatment outcomes in Asia and Africa

Yuliyani

Sartika

2021

ijhs

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Treatment outcomes and risk factors of death in childhood tuberculous meningitis in Kandahar, Afghanistan: a prospective observational cohort study

Rahimi

Niazi

Rahimi

et al. 2022

Transactions of the Royal Society of Tropical Medicine and Hygiene

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Background Tuberculous meningitis (TBM) is the most severe form of TB. We prospectively documented the treatment outcomes and the risk factors for death in children with TBM from Kandahar, Afghanistan. Methods This prospective observational cohort study was conducted from February 2017 to January 2020 in hospitalised TBM children. All the patients were prospectively followed up for 12 mo. Data were analysed by using descriptive statistics, χ2 and multivariate logistic regression. Results A total of 818 TBM hospitalised patients with median age 4.8 (0.8–14.5) y were recruited. Females accounted for 60.9% (498/818). Upon admission 53.9% (n=441) and 15.2% (n=124) had TBM stages II and III, respectively, and 23.2% (n=190) had focal neurological signs. The case fatality rate was 20.2% (160/794) and 30.6% (243/794) survived with neurological sequelae. Independent risk factors for death were being unvaccinated for BCG (adjusted OR [AOR] 3.8, 95% CI 1.8 to 8.1), not receiving dexamethasone (AOR 2.5, 95% CI 1.5 to 4.2), being male (AOR 2.3, 95% CI 1.5 to 3.6), history of recent weight loss (AOR 2.2, 95% CI 1.3 to 3.9) and having stage III TBM (AOR 2.0, 95% CI 1.2 to 3.3). Conclusions TBM continues to cause high morbidity and mortality in Afghan children. Strategies to reduce mortality should emphasise early diagnosis and treatment, routine use of dexamethasone and increased BCG vaccination.

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Predicting Tuberculosis Incidence and Its Trend in Tigray, Ethiopia: A Reality-Counterfactual Modeling Approach

Gebregergs,

Berhe,

Gebrehiwot

et al. 2024

IDR

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Background The Tigray region of Ethiopia, which has been affected by civil war from 2020 to 2022, is facing an increase in tuberculosis in the damaged health system. Our study employed mathematical modeling to predict the incidence of tuberculosis and its trends during the war and in the post-conflict setting of Tigray, Northern Ethiopia. Methods We predicted the incidence of tuberculosis from 2020 to 2025 in Tigray using the SEIRD model in the context of the recent war and compared it with its counterfactual trend in the absence of war. The counterfactual trend was forecasted using an autoregressive integrated moving average (ARIMA) model for stationary time-series data. We performed rolling origin cross-validation for ARIMA and sensitivity analysis for the SEIRD model. The initial tuberculosis data and model parameters were obtained from the Institute for Health Metrics and Evaluation and the literature, respectively. Results Between 2000 and 2017, the incidence of tuberculosis in Tigray decreased at an annual rate of 3.0%. Shortly before the war, the incidence of tuberculosis in the region was 178 per 100,000 people. In a counterfactual scenario where there was no war, the incidence was projected to decrease to 144.3 in 2022 and 126.3 in 2025. However, owing to the war and siege, the SEIRD-projected incidence of tuberculosis would have increased to 965.5 (95% CI: 958.5–972.7) in 2022 and 372.4 (95% CI: 367.7–376.6) in 2025. Over 800 cases of tuberculosis per 100,000 people were attributed to the war in 2022. In the postwar period, the incidence is projected to decrease by 30% by 2023. Conclusion The Tigray War reversed a two-decade decline in tuberculosis cases, causing a five-fold increase compared to the no-war scenario. Urgent interventions are needed to support tuberculosis prevention, testing, and treatment, particularly in key and vulnerable populations.

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Treatment outcomes of patients with tuberculosis in war affected region of Khyber Pakhtunkhwa, Pakistan

Cited by 6 publications

References 22 publications

Determinants of tuberculosis treatment outcomes in Asia and Africa

Determinants of tuberculosis treatment outcomes in Asia and Africa

Treatment outcomes and risk factors of death in childhood tuberculous meningitis in Kandahar, Afghanistan: a prospective observational cohort study

Predicting Tuberculosis Incidence and Its Trend in Tigray, Ethiopia: A Reality-Counterfactual Modeling Approach

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