<i>Purpose.</i> In the Philippines, drug-resistant tuberculosis (DRTB) is a growing concern. Healthcare workers face challenges in retaining patients with DRTB in care. This study intends to understand their perspectives on the factors that influence patient treatment outcomes and to propose potential programmatic solutions for strengthening care services for the patients. <i>Methods</i>. A mixed-methods study was conducted in the Philippines between December 2017 and March 2018 to understand the major barriers for healthcare workers to provide quality care to DRTB patients across the care continuum. In the quantitative phase, healthcare workers participated in an online survey; in the qualitative phase, in-depth interviews were conducted with a select number of the survey respondents to better understand their survey responses. <i>Results</i>. 272 healthcare workers participated in the survey, and of those, 11 were interviewed. Survey results identified economic constraints, patient perceptions of care, family-related concerns, and limited accessibility to healthcare services as the major patient-related barriers across the care continuum. Major health-system-related barriers were insufficient human resources, lack of financial and political support, and limited knowledge about DRTB by healthcare providers. Interviews revealed more elaborate, contextualized, and nuanced aspects of each of the major challenges. The elaborated patient-related barriers included expenses needed during treatment (e.g., transportation); fear of being stigmatized by family, community, or healthcare staff; worries about adverse drug reactions from medication; a lack of family support; and the location of patients’ homes. The health-system-related barriers revealed through interviews included the limited capacities of facility staff to provide DRTB care due to insufficient human resources; the shortage of funds to support treatment completion (e.g., transportation allowance and food package for patients, service vehicles and mobile phone costs for outreach actions at the facility level); and discrimination by healthcare staff against patients with DRTB attributed to the staff’s limited knowledge and experiences of treating the patients. <i>Conclusion</i>. This study identified the main barriers for DRTB facility staff in the Philippines from the perspectives of providers. Further exploration of the barriers and best practices in facilities may be useful for improving DRTB care in the Philippines.

Yutaka Endo

Jahn Jaramillo

Rajendra Prasad Hubraj Yadav

Patient- and Health-System-Related Barriers to Treatment Adherence for Patients with Drug-Resistant Tuberculosis in the Philippines: A Mixed-Methods Study

Tuberculosis is still one of the most severe progressive diseases; it severely limits the social and economic development of many countries. In the present study, the topic trend of scientific publications on tuberculosis has been examined using text mining techniques and co-word analysis with an analytical approach. The statistical population of the study is all global publications related to tuberculosis. In order to extract the data, the Scopus citation database was used for the period 1900 to 2022. The main keywords for the search strategy were chosen through consultation with thematic specialists and using MESH. Python programming language and VOSviewer software were applied to analyze data. The results showed four main topics as follows: &#x201C;Clinical symptoms&#x201D; (41.8&#x0025;), &#x201C;Diagnosis and treatment&#x201D; (28.1&#x0025;), &#x201C;Bacterial structure, pathogenicity and genetics&#x201D; (22.3&#x0025;), and &#x201C;Prevention&#x201D; (7.84&#x0025;). The results of this study can be helpful in the decision of this organization and knowledge of the process of studies on tuberculosis and investment and development of programs and guidelines against this disease.

Meisam Dastani

Alireza Mohammadzadeh

Jalal Mardaneh

Reza Ahmadi

Topic Analysis and Mapping of Tuberculosis Research Using Text Mining and Co-Word Analysis

<i>Background.</i> Active case finding (ACF) for tuberculosis (TB) is a key strategy to reduce diagnostic delays, expedite treatment, and prevent transmission. <i>Objective.</i> Our objective was to identify the populations, settings, screening and diagnostic approaches that optimize coverage (proportion of those targeted who were screened) and yield (proportion of those screened who had active TB) in ACF programs. <i>Methods.</i> We performed a comprehensive search to identify studies published from 1980-2016 that reported the coverage and yield of different ACF approaches. For each outcome, we conducted meta-analyses of single proportions to produce estimates across studies, followed by meta-regression to identify predictors. <i>Findings.</i> Of 3,972 publications identified, 224 met criteria after full-text review. Most individuals who were targeted successfully completed screening, for a pooled coverage estimate of 93.5&#x0025;. The pooled yield of active TB across studies was 3.2&#x0025;. Settings with the highest yield were internally-displaced persons camps (15.6&#x0025;) and healthcare facilities (6.9&#x0025;). When compared to symptom screening as the reference standard, studies that screened individuals regardless of symptoms using microscopy, culture, or GeneXpert&#x00AE;MTB/RIF (Xpert) had 3.7&#x0025; higher case yield. In particular, microbiological screening (usually microscopy) as the initial test, followed by culture or Xpert for diagnosis had 3.6&#x0025; higher yield than symptom screening followed by microscopy for diagnosis. In a model adjusted for use of Xpert testing, approaches targeting persons living with HIV (PLWH) had a 4.9&#x0025; higher yield than those targeting the general population. In all models, studies targeting children had higher yield (4.8&#x0025;-5.7&#x0025;) than those targeting adults. <i>Conclusion.</i> ACF activities can be implemented successfully in various populations and settings. Screening yield was highest in internally-displaced person and healthcare settings, and among PLWH and children. In high-prevalence settings, ACF approaches that screen individuals with laboratory tests regardless of symptoms have higher yield than approaches focused on symptomatic individuals.

Ruth W. Deya

Linnet N. Masese

Walter Jaoko

Jeremiah Chakaya Muhwa

Lilian Mbugua

David J. Horne

Susan M. Graham

Yield and Coverage of Active Case Finding Interventions for Tuberculosis Control:A Systematic Review and Meta-analysis

<i>Background.</i> Ethiopia is one of the highest tuberculosis burden countries globally, and tuberculosis is one of the most pressing health problems nationally. Weight gain during treatment is the main indicator of good treatment outcome, but there is no adequate information regarding the factors that affect weight gain in Ethiopia. <i>Objective.</i> The objective of this study was to identify determinants of weight gain among adult tuberculosis patients during the intensive phase, in Debre Markos town public health institutions Northwest Ethiopia, 2020. <i>Methods</i>. Unmatched case-control study was conducted in Debre Markos town public health facilities with a total sample size of 236. Cases (clients who got weight) and controls (clients who did not get weight) were enrolled in the study consecutively, and data were collected using standardized questionnaires. Data were entered through Epi-Data version 4.2 and exported to SPSS version 25 for analysis. Bivariable analysis was done, and all independent variables that had <span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="18.973pt" style="vertical-align:-3.42938pt" id="M1" height="11.7782pt" version="1.1" viewBox="-0.0498162 -8.34882 18.973 11.7782"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-113" d="M570 304C570 398 525 448 414 448C385 448 343 445 312 434L329 511L321 518C297 504 262 482 244 460L233 411C195 397 159 381 128 358L135 332C160 347 189 360 224 373L111 -147C97 -210 84 -218 17 -231L13 -257L254 -247L259 -218L233 -216C183 -212 177 -202 189 -142L218 -1C238 -10 266 -12 283 -12C351 3 429 48 483 105C543 168 570 242 570 304ZM482 289C482 161 380 33 304 33C278 33 248 51 233 69L303 396C326 400 352 403 369 403C428 403 482 380 482 289Z"/></g><g transform="matrix(.013,0,0,-0.013,11.342,0)"><path id="g117-91" d="M512 -3V55L134 254V256L512 456V514L75 281V230L512 -3Z"/></g></svg><span class="irelop"/><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="21.921pt" style="vertical-align:-3.42938pt" height="11.7782pt" version="1.1" viewBox="22.555183800000002 -8.34882 21.921 11.7782"><g transform="matrix(.013,0,0,-0.013,22.605,0)"><path id="g113-49" d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"/></g><g transform="matrix(.013,0,0,-0.013,28.845,0)"><path id="g113-47" d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z"/></g><g transform="matrix(.013,0,0,-0.013,31.809,0)"><path id="g113-51" d="M412 140C382 77 369 73 315 73H129L270 222C362 320 402 379 402 466C402 571 322 635 234 635C177 635 130 609 99 576L42 495L64 475C90 514 133 568 201 568C274 568 318 519 318 435C318 349 255 267 193 193C144 135 87 78 32 23V0H405C417 45 427 89 440 131L412 140Z"/></g><g transform="matrix(.013,0,0,-0.013,38.049,0)"><path id="g113-54" d="M153 550H386L412 615L406 623H120L82 318C104 327 142 338 184 338C294 338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z"/></g></svg></span> were entered into multivariable binary logistic regression analysis. Finally, independent variables which were significantly associated with weight gain at <span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="18.973pt" style="vertical-align:-3.42938pt" id="M2" height="11.7782pt" version="1.1" viewBox="-0.0498162 -8.34882 18.973 11.7782"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g113-113"/></g><g transform="matrix(.013,0,0,-0.013,11.342,0)"><use xlink:href="#g117-91"/></g></svg><span class="irelop"/><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="21.921pt" style="vertical-align:-3.42938pt" height="11.7782pt" version="1.1" viewBox="22.555183800000002 -8.34882 21.921 11.7782"><g transform="matrix(.013,0,0,-0.013,22.605,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,28.845,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,31.809,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,38.049,0)"><use xlink:href="#g113-54"/></g></svg></span> were considered determinant factors of weight gain. <i>Result</i>. Pulmonary tuberculosis (AOR: 5 (95% CI: 2.3, 11.2)), monitoring by health professionals (AOR: 3.7 (1.6, 8.4)), ≥18.5 baseline body mass index (AOR: 3.4 (95% CI: 1.6, 7.3)), parasitic disease (AOR: 3.2 (95% CI: 1.3, 7.99)), &lt;30 days duration of illness before start of treatment (AOR: 2.8 (95% CI: 1.2, 6.1)), and human immune virus/acquired immune deficiency syndrome (AOR: 3.3 (95% CI: 1.2, 9.1)) were independently associated with weight gain compared to their counterpart. <i>Conclusion</i>. Type of tuberculosis, monitoring by health professionals, baseline status, parasitic disease, duration of illness before start of treatment, and human immune virus/acquired immune deficiency syndrome were with the determinants of weight gain. Therefore, early detection, support and supervision, and attention for comorbidity are mandatory during antituberculosis treatment.

Belsity Temesgen Meselu

Birhanu Barud Demelie

Tigist Adeb Shedie

Determinants of Weight Gain among Adult Tuberculosis Patients during Intensive Phase in Debre Markos Town Public Health Facilities, Northwest Ethiopia, 2020: Unmatched Case-Control Study

<i>Background</i>. Advancing a research agenda designed to meet the specific needs of children is critical to ending pediatric TB epidemic. Systematic reviews are increasingly informing policies in pediatric tuberculosis (TB) care and control. However, there is a paucity of information on pediatric TB research priorities. <i>Methodology</i>. We searched MEDLINE, EMBASE, Web of Science, and the Cochrane Library for systematic reviews and meta-analyses on any aspect related to pediatric TB published between 2015 and 2021. We used the UK Health Research Classification System (HRCS) to help us classify the research questions and priorities. <i>Findings</i>. In total, 29 systematic reviews, with 84 research questions, were included in this review. The four most common research topics in the area of detection were 43.33&#x0025; screening and diagnosis of TB, 23.33&#x0025; evaluation of treatments and therapeutic interventions, 13.34&#x0025; TB etiology and risk factors, and 13.34&#x0025; prevention of disease and conditions and promotion of well-being. The research priorities focused mainly on evaluating TB diagnosis by improving yield through enhanced in specimen collection or preparation and evaluating of bacteriological TB diagnostic tests. Other topics of future research were developing a treatment for TB in children, assessing the use of IPT in reducing TB-associated morbidity, evaluating the prioritization of an IPT-friendly healthcare environment, and providing additional guidance for the use of isoniazid in the prevention of TB in HIV-infected children. <i>Conclusion</i>. There is a need for more systematic reviews on pediatric TB. The review identified several key priorities for future pediatric TB research mainly in the domain of (1) &#x201C;Detection, screening and diagnosis,&#x201D; &#x201C;Development of Treatments and Therapeutic Interventions,&#x201D; and &#x201C;Prevention of Disease and Conditions, and Promotion of Well-Being.&#x201D; These domains are very relevant in the research component of the roadmap towards ending TB in children. It also will serve as an additional action in the WHO End TB strategy.

Thomas Achombwom Vukugah

Vera Nyibi Ntoh

Derick Akompab Akoku

Simo Leonie

Amed Jacob

Research Questions and Priorities for Pediatric Tuberculosis: A Survey of Published Systematic Reviews and Meta-Analyses

<i>Background</i>. Tuberculosis remains to be a public health threat in Ethiopia. However, the use of ill diagnostic methods and the lack of enough epidemiological information in the country contributed to the diagnostic delay and development of anti-TB drug resistance. Therefore, the present study is aimed at assessing the prevalence of pulmonary TB (PTB) and the development of drug resistance using GeneXpert MTB/RIF assay in Merhabete district, Central Ethiopia. <i>Methods</i>. A cross-sectional, health facility-based study was conducted from December 2019 to June 2020. Bacteriological examination and GeneXpert molecular diagnostic methods were used for the detection of <i>M</i>. <i>tuberculosis</i> and rifampicin resistance (RR). Descriptive statistics and logistic regression analysis were used to determine the possible association of risk factors with the occurrence of PTB and RR. <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.0498209pt" id="M1" height="8.68572pt" version="1.1" viewBox="-0.0498162 -8.6359 8.15071 8.68572" width="8.15071pt"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-81" d="M600 480C600 590 528 650 384 650H143L137 622C222 614 225 607 210 531L130 127C113 41 106 36 23 28L17 0H294L300 28C204 36 195 42 212 127L243 284L314 263C327 263 339 263 352 264C465 271 600 337 600 480ZM508 481C508 351 402 304 329 304C289 304 265 311 250 317L295 559C302 594 310 606 323 611C335 616 350 619 367 619C455 619 508 573 508 481Z"/></g></svg> values of &lt;0.05 were considered statistically significant. <i>Results</i>. The overall prevalence rates of PTB and RR <i>M</i>. <i>tuberculosis</i> were 11.2% and 15.8%, respectively. The logistic regression analysis revealed that being in the age group of 49-64 years was significantly associated with the occurrence of TB (<span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="19.289pt" style="vertical-align:-0.2064009pt" id="M2" height="8.8423pt" version="1.1" viewBox="-0.0498162 -8.6359 19.289 8.8423"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g113-81"/></g><g transform="matrix(.013,0,0,-0.013,11.658,0)"><path id="g117-34" d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z"/></g></svg><span class="irelop"/><span class="nowrap"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="21.918pt" style="vertical-align:-0.2064009pt" height="8.8423pt" version="1.1" viewBox="22.8711838 -8.6359 21.918 8.8423"><g transform="matrix(.013,0,0,-0.013,22.921,0)"><path id="g113-49" d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"/></g><g transform="matrix(.013,0,0,-0.013,29.161,0)"><path id="g113-47" d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z"/></g><g transform="matrix(.013,0,0,-0.013,32.125,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,38.365,0)"><path id="g113-50" d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z"/></g></svg>).</span></span> The odds of HIV-positive and retreatment study participants to be infected by <i>M</i>. <i>tuberculosis</i> were much more than those of HIV-negative and newly treated cases, respectively (<span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="19.289pt" style="vertical-align:-0.6370001pt" id="M3" height="9.2729pt" version="1.1" viewBox="-0.0498162 -8.6359 19.289 9.2729"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g113-81"/></g><g transform="matrix(.013,0,0,-0.013,11.658,0)"><path id="g117-91" d="M512 -3V55L134 254V256L512 456V514L75 281V230L512 -3Z"/></g></svg><span class="irelop"/><span class="nowrap"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="21.918pt" style="vertical-align:-0.6370001pt" height="9.2729pt" version="1.1" viewBox="22.8711838 -8.6359 21.918 9.2729"><g transform="matrix(.013,0,0,-0.013,22.921,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,29.161,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,32.125,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,38.365,0)"><path id="g113-54" d="M153 550H386L412 615L406 623H120L82 318C104 327 142 338 184 338C294 338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z"/></g></svg>).</span></span> However, none of the sociodemographic and clinical patient characteristics was significantly associated with the development of RR-TB (<span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="19.289pt" style="vertical-align:-0.6370001pt" id="M4" height="9.2729pt" version="1.1" viewBox="-0.0498162 -8.6359 19.289 9.2729"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g113-81"/></g><g transform="matrix(.013,0,0,-0.013,11.658,0)"><path id="g117-92" d="M512 230V281L75 514V456L453 256V254L75 55V-3L512 230Z"/></g></svg><span class="irelop"/><span class="nowrap"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="21.918pt" style="vertical-align:-0.6370001pt" height="9.2729pt" version="1.1" viewBox="22.8711838 -8.6359 21.918 9.2729"><g transform="matrix(.013,0,0,-0.013,22.921,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,29.161,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,32.125,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,38.365,0)"><use xlink:href="#g113-54"/></g></svg>).</span></span> <i>Conclusion</i>. In the present study, high prevalence rates of PTB and RR <i>M</i>. <i>tuberculosis</i> were observed. The findings, which were attributed to different risk factors, suggested an urgent need for appropriate intervention measures to reduce the transmission of PTB and the development of anti-TB drug resistance in the study area.

Sebsib Selfegna

Amir Alelign

Detection of <i>Mycobacterium tuberculosis</i> and Rifampicin Resistance Using GeneXpert MTB/RIF Assay at Enat Hospital, Central Ethiopia

About this journal

<p><em>Tuberculosis Research and Treatment</em> publishes original research articles and&nbsp;review articles related to all aspects of tuberculosis, from the immunological basis of disease to translational and clinical research.</p>


Journal profile

Meet the editorial board

<p><em>Tuberculosis Research and Treatment&nbsp;</em>maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.</p>


Editor spotlight

Submit your proposal

Do you think there is an emerging area of research that really needs to be highlighted? Or an existing research area that has been overlooked or would benefit from deeper investigation? Raise the profile of a research area by leading a Special Issue.

Special Issues

Author guidelines

Editorial board

Databases and indexing

Tuberculosis Research and Treatment - Table of contents 2022

Tuberculosis Research and Treatment | Hindawi

title

Tuberculosis Research and Treatment publishes original research articles and review articles related to all aspects of tuberculosis, from the immunological basis of disease to translational and clinical research.

Tuberculosis Research and Treatment