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Liao R, Hu L, Yu J, Chen Y, Chen M, Yan J, Li X, Han X, Jike C, Yu G, Wang J, Liao Q, Xia L, Bai X, Shi J, Jiang T, Du L, Zhang T. Association between TB delay and TB treatment outcomes in HIV-TB co-infected patients: a study based on the multilevel propensity score method. BMC Infect Dis 2024; 24:457. [PMID: 38689228 PMCID: PMC11061920 DOI: 10.1186/s12879-024-09328-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 04/16/2024] [Indexed: 05/02/2024] Open
Abstract
BACKGROUND HIV-tuberculosis (HIV-TB) co-infection is a significant public health concern worldwide. TB delay, consisting of patient delay, diagnostic delay, treatment delay, increases the risk of adverse anti-TB treatment (ATT) outcomes. Except for individual level variables, differences in regional levels have been shown to impact the ATT outcomes. However, few studies appropriately considered possible individual and regional level confounding variables. In this study, we aimed to assess the association of TB delay on treatment outcomes in HIV-TB co-infected patients in Liangshan Yi Autonomous Prefecture (Liangshan Prefecture) of China, using a causal inference framework while taking into account individual and regional level factors. METHODS We conducted a study to analyze data from 2068 patients with HIV-TB co-infection in Liangshan Prefecture from 2019 to 2022. To address potential confounding bias, we used a causal directed acyclic graph (DAG) to select appropriate confounding variables. Further, we controlled for these confounders through multilevel propensity score and inverse probability weighting (IPW). RESULTS The successful rate of ATT for patients with HIV-TB co-infection in Liangshan Prefecture was 91.2%. Total delay (OR = 1.411, 95% CI: 1.015, 1.962), diagnostic delay (OR = 1.778, 95% CI: 1.261, 2.508), treatment delay (OR = 1.749, 95% CI: 1.146, 2.668) and health system delay (OR = 1.480 95% CI: (1.035, 2.118) were identified as risk factors for successful ATT outcome. Sensitivity analysis demonstrated the robustness of these findings. CONCLUSIONS HIV-TB co-infection prevention and control policy in Liangshan Prefecture should prioritize early treatment for diagnosed HIV-TB co-infected patients. It is urgent to improve the health system in Liangshan Prefecture to reduce delays in diagnosis and treatment.
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Affiliation(s)
- Rujun Liao
- Center of Infectious Diseases, Research Center of Clinical Epidemiology and Evidence-Based Medicine, Innovation Insititute for Integration of Medicine and Engineering, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, People's Republic of China
- Sichuan Center for Disease Control and Prevention, Chengdu, 610041, Sichuan, People's Republic of China
| | - Lin Hu
- Department of Epidemiology and Health Statistics, West China School of Public Health, West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, People's Republic of China
| | - Jie Yu
- Department of Epidemiology and Health Statistics, West China School of Public Health, West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, People's Republic of China
| | - Ying Chen
- Department of Epidemiology and Health Statistics, West China School of Public Health, West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, People's Republic of China
| | - Miaoshuang Chen
- Department of Epidemiology and Health Statistics, West China School of Public Health, West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, People's Republic of China
| | - Jingmin Yan
- Department of Epidemiology and Health Statistics, West China School of Public Health, West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, People's Republic of China
| | - Xin Li
- Department of Epidemiology and Health Statistics, West China School of Public Health, West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, People's Republic of China
| | - Xinyue Han
- Department of Epidemiology and Health Statistics, West China School of Public Health, West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, People's Republic of China
| | - Chunnong Jike
- Liangshan Center for Disease Control and Prevention, Xichang, 615000, Sichuan, People's Republic of China
| | - Gang Yu
- Liangshan Center for Disease Control and Prevention, Xichang, 615000, Sichuan, People's Republic of China
| | - Ju Wang
- Liangshan Center for Disease Control and Prevention, Xichang, 615000, Sichuan, People's Republic of China
| | - Qiang Liao
- Liangshan Center for Disease Control and Prevention, Xichang, 615000, Sichuan, People's Republic of China
| | - Lan Xia
- Sichuan Center for Disease Control and Prevention, Chengdu, 610041, Sichuan, People's Republic of China
| | - Xuefei Bai
- Sichuan Center for Disease Control and Prevention, Chengdu, 610041, Sichuan, People's Republic of China
| | - Jinhong Shi
- Sichuan Center for Disease Control and Prevention, Chengdu, 610041, Sichuan, People's Republic of China
| | - Tian Jiang
- Editorial department of Journal of Sichuan University (Medical Sciences), Sichuan University, Chengdu, CN, People's Republic of China
| | - Liang Du
- Center of Infectious Diseases, Research Center of Clinical Epidemiology and Evidence-Based Medicine, Innovation Insititute for Integration of Medicine and Engineering, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, People's Republic of China.
| | - Tao Zhang
- Department of Epidemiology and Health Statistics, West China School of Public Health, West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, People's Republic of China.
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Dinh LV, Vo LNQ, Wiemers AMC, Nguyen HB, Vu HQ, Mo HTL, Nguyen LP, Nguyen NTT, Dong TTT, Tran KT, Dang TMH, Nguyen LH, Pham AT, Codlin AJ, Forse RJ. Ensuring Continuity of Tuberculosis Care during Social Distancing through Integrated Active Case Finding at COVID-19 Vaccination Events in Vietnam: A Cohort Study. Trop Med Infect Dis 2024; 9:26. [PMID: 38276637 PMCID: PMC10819868 DOI: 10.3390/tropicalmed9010026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 01/15/2024] [Accepted: 01/18/2024] [Indexed: 01/27/2024] Open
Abstract
COVID-19 significantly disrupted tuberculosis (TB) services in Vietnam. In response, the National TB Program (NTP) integrated TB screening using mobile chest X-rays into COVID-19 vaccination events. This prospective cohort study evaluated the integrated model's yield, treatment outcomes, and costs. We further fitted regressions to identify risk factors and conduct interrupted time-series analyses in the study area, Vietnam's eight economic regions, and at the national level. At 115 events, we conducted 48,758 X-ray screens and detected 174 individuals with TB. We linked 89.7% to care, while 92.9% successfully completed treatment. The mean costs per person diagnosed with TB was $547. TB risk factors included male sex (aOR = 6.44, p < 0.001), age of 45-59 years (aOR = 1.81, p = 0.006) and ≥60 years (aOR = 1.99, p = 0.002), a history of TB (aOR = 7.96, p < 0.001), prior exposure to TB (aOR = 3.90, p = 0.001), and symptomatic presentation (aOR = 2.75, p < 0.001). There was a significant decline in TB notifications during the Delta wave and significant increases immediately after lockdowns were lifted (IRR(γ1) = 5.00; 95%CI: (2.86, 8.73); p < 0.001) with a continuous upward trend thereafter (IRR(γ2) = 1.39; 95%CI: (1.22, 1.38); p < 0.001). Similar patterns were observed at the national level and in all regions but the northeast region. The NTP's swift actions and policy decisions ensured continuity of care and led to the rapid recovery of TB notifications, which may serve as blueprint for future pandemics.
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Affiliation(s)
- Luong Van Dinh
- National Lung Hospital, Ha Noi 100000, Vietnam; (L.V.D.); (H.B.N.); (H.Q.V.)
| | - Luan Nguyen Quang Vo
- Friends for International Tuberculosis Relief (FIT), Ha Noi 100000, Vietnam; (A.M.C.W.); (H.T.L.M.); (N.T.T.N.); (T.T.T.D.); (K.T.T.); (A.J.C.); (R.J.F.)
- Department of Global Health, WHO Collaboration Centre on Tuberculosis and Social Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Anja Maria Christine Wiemers
- Friends for International Tuberculosis Relief (FIT), Ha Noi 100000, Vietnam; (A.M.C.W.); (H.T.L.M.); (N.T.T.N.); (T.T.T.D.); (K.T.T.); (A.J.C.); (R.J.F.)
| | - Hoa Binh Nguyen
- National Lung Hospital, Ha Noi 100000, Vietnam; (L.V.D.); (H.B.N.); (H.Q.V.)
| | - Hoa Quynh Vu
- National Lung Hospital, Ha Noi 100000, Vietnam; (L.V.D.); (H.B.N.); (H.Q.V.)
| | - Huong Thi Lan Mo
- Friends for International Tuberculosis Relief (FIT), Ha Noi 100000, Vietnam; (A.M.C.W.); (H.T.L.M.); (N.T.T.N.); (T.T.T.D.); (K.T.T.); (A.J.C.); (R.J.F.)
| | - Lan Phuong Nguyen
- IRD VN Social Enterprise Company Limited, Ho Chi Minh City 700000, Vietnam;
| | - Nga Thi Thuy Nguyen
- Friends for International Tuberculosis Relief (FIT), Ha Noi 100000, Vietnam; (A.M.C.W.); (H.T.L.M.); (N.T.T.N.); (T.T.T.D.); (K.T.T.); (A.J.C.); (R.J.F.)
| | - Thuy Thi Thu Dong
- Friends for International Tuberculosis Relief (FIT), Ha Noi 100000, Vietnam; (A.M.C.W.); (H.T.L.M.); (N.T.T.N.); (T.T.T.D.); (K.T.T.); (A.J.C.); (R.J.F.)
| | - Khoa Tu Tran
- Friends for International Tuberculosis Relief (FIT), Ha Noi 100000, Vietnam; (A.M.C.W.); (H.T.L.M.); (N.T.T.N.); (T.T.T.D.); (K.T.T.); (A.J.C.); (R.J.F.)
| | - Thi Minh Ha Dang
- Pham Ngoc Thach Hospital, Ho Chi Minh City 700000, Vietnam; (T.M.H.D.); (L.H.N.)
| | - Lan Huu Nguyen
- Pham Ngoc Thach Hospital, Ho Chi Minh City 700000, Vietnam; (T.M.H.D.); (L.H.N.)
| | | | - Andrew James Codlin
- Friends for International Tuberculosis Relief (FIT), Ha Noi 100000, Vietnam; (A.M.C.W.); (H.T.L.M.); (N.T.T.N.); (T.T.T.D.); (K.T.T.); (A.J.C.); (R.J.F.)
- Department of Global Health, WHO Collaboration Centre on Tuberculosis and Social Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Rachel Jeanette Forse
- Friends for International Tuberculosis Relief (FIT), Ha Noi 100000, Vietnam; (A.M.C.W.); (H.T.L.M.); (N.T.T.N.); (T.T.T.D.); (K.T.T.); (A.J.C.); (R.J.F.)
- Department of Global Health, WHO Collaboration Centre on Tuberculosis and Social Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden
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Mohebbi Z, Dehbozorgi R, Setoodeh G, Momennasab M, Heydari N, Shaygan M. Lived Experience of Iranian Family Caregivers of Tubercular Patients: A Qualitative Study. INVESTIGACION Y EDUCACION EN ENFERMERIA 2022; 40:e02. [PMID: 36867775 PMCID: PMC10017139 DOI: 10.17533/udea.iee.v40n3e02] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 10/03/2022] [Indexed: 06/18/2023]
Abstract
OBJECTIVES To investigate the lived experience of family caregivers of persons with tuberculosis. METHODS In this study, the method of hermeneutic phenomenology. Data were collected through online in-depth semi-structured interviews with nine family caregivers of TB patients. The obtained data were thematically analyzed to explain the concept of home care for TB patients through van Manen's 6-step methodology. RESULTS After the thematic analysis, three main themes of caregivers' mental distresses, quality care stasis, and facilitated care were obtained from 944 primary codes and 11 categories. CONCLUSIONS Family caregivers of these patients suffer from mental distress. This issue affects the quality and ease of caregiving for these patients. Therefore, policymakers of this area should pay attention to the family caregivers of these patients and attempt to provide support; they should try to improve their quality of life.
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Affiliation(s)
- Zinat Mohebbi
- School of Nursing and Midwifery, Shiraz University of Medical Sciences, Shiraz, Iran.
| | - Raziye Dehbozorgi
- Nursing and Midwifery School, Isfahan University of Medical Sciences, Isfahan, Iran. Ph.D. Candidate.
| | - Giti Setoodeh
- School of Nursing and Midwifery, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Marzieh Momennasab
- School of Nursing and Midwifery, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Naval Heydari
- School of Nursing and Midwifery, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Maryam Shaygan
- School of Nursing and Midwifery, Shiraz University of Medical Sciences, Shiraz, Iran
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Chakma B, Gomes D, Filipe PA, Soares P, de Sousa B, Nunes C. A temporal analysis on patient and health service delays in pulmonary tuberculosis in Portugal: inter and intra‑regional differences and in(equalities) between gender and age. BMC Public Health 2022; 22:1830. [PMID: 36171570 PMCID: PMC9517984 DOI: 10.1186/s12889-022-14216-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 09/21/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Tuberculosis (TB) diagnosis and treatment delays increase the period of infectiousness, making TB control difficult and increasing the fatality rates. This study aimed to determine the evolution of health care service delay (time between the patient's first contact with the health service and the diagnosis/start of treatment) and patient delay (time between onset symptoms date and the date of first contact with health services) for Pulmonary Tuberculosis (PTB) in Portugal between 2008 and 2017 across different regions, age groups and gender. METHODS An exploratory analysis was performed, trends of both delays were studied, and 36 months forecasts were generated. We used the permutation test to test differences between groups and the Seasonal and Trend decomposition using Loess (STL) method and Autoregressive Integrated Moving Average (ARIMA) models for forecasting for both Health and Patient delays. We used data from notified PTB cases in mainland Portugal between 2008 and 2017, provided by the national surveillance system. RESULTS Health delays remained relatively constant while patient delays increased. Females had significantly higher health delays in some regions. Individuals older than 64 had higher health delays than younger individuals, while patient delay for working-age individuals between 15 and 64 years old, presents higher patient delay. CONCLUSIONS Forecasts presage that the upward trend of the delays is unlikely to fall in the coming years. It is important to understand the evolution of the delays and predict how these will evolve. Our understanding of the delays behaviours will contribute to better health policies and resources allocation.
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Affiliation(s)
- Bhaswar Chakma
- Research Centre for Mathematics and Applications, Institute for Advanced Studies and Research, University of Évora, Évora, Portugal
| | - Dulce Gomes
- Research Centre for Mathematics and Applications, Institute for Advanced Studies and Research, University of Évora, Évora, Portugal. .,Department of Mathematics, School of Science and Technology, University of Évora, Évora, Portugal.
| | - Patrícia A Filipe
- Research Centre for Mathematics and Applications, Institute for Advanced Studies and Research, University of Évora, Évora, Portugal.,Quantitative Methods for Management and Economics Department, Iscte Business School, Iscte - University Institute of Lisbon, Lisboa, Portugal
| | - Patrícia Soares
- Public Health Research Centre, NOVA National School of Public Health, Universidade NOVA de Lisboa, Lisboa, Portugal.,Comprehensive Health Research Center, Universidade NOVA de Lisboa, Lisboa, Portugal
| | - Bruno de Sousa
- CINEICC, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal
| | - Carla Nunes
- Public Health Research Centre, NOVA National School of Public Health, Universidade NOVA de Lisboa, Lisboa, Portugal.,Comprehensive Health Research Center, Universidade NOVA de Lisboa, Lisboa, Portugal
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Soares P, Aguiar A, Leite A, Duarte R, Nunes C. Ecological factors associated with areas of high tuberculosis diagnosis delay. Public Health 2022; 208:32-39. [DOI: 10.1016/j.puhe.2022.04.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 04/04/2022] [Accepted: 04/27/2022] [Indexed: 10/18/2022]
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Pilot study to identify missed opportunities for prevention of childhood tuberculosis. Eur J Pediatr 2022; 181:3299-3307. [PMID: 35771355 PMCID: PMC9395448 DOI: 10.1007/s00431-022-04537-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Revised: 03/03/2022] [Accepted: 06/19/2022] [Indexed: 11/23/2022]
Abstract
UNLABELLED Tuberculosis (TB) in exposed children can be prevented with timely contact tracing and preventive treatment. This study aimed to identify potential barriers and delays in the prevention of childhood TB in a low-incidence country by assessing the management of children subsequently diagnosed with TB. A pilot retrospective cohort study included children (< 15 years) treated for TB between 2009 and 2016 at a tertiary care hospital in Berlin, Germany. Clinical data on cases and source cases, information on time points of the diagnostic work up, and preventive measures were collected and analyzed. Forty-eight children (median age 3 years [range 0.25-14]) were included; 36 had been identified through contact tracing, the majority (26; 72.2%) being < 5 years. TB source cases were mostly family members, often with advanced disease. Thirty children (83.3%) did not receive prophylactic or preventive treatment, as TB was already prevalent when first presented. Three cases developed TB despite preventive or prophylactic treatment; in three cases (all < 5 years), recommendations had not been followed. Once TB was diagnosed in source cases, referral, assessment, TB diagnosis, and treatment were initiated in most children in a timely manner with a median duration of 18 days (interquartile range 6-60, range 0-252) between diagnosis of source case and child contact (information available for 35/36; 97.2%). In some cases, notable delays in follow-up occurred. CONCLUSION Prompt diagnosis of adult source cases appears to be the most important challenge for childhood TB prevention. However, improvement is also needed in the management of exposed children. WHAT IS KNOWN • Following infection with Mycobacterium tuberculosis, young children have a high risk of progression to active and severe forms of tuberculosis (TB). • The risk of infection and disease progression can be minimized by prompt identification of TB-exposed individuals and initiation of prophylactic or preventive treatment. WHAT IS NEW • We could show that there are avoidable time lags in diagnosis in a relevant proportion of children with known TB exposure. • Delayed diagnosis of adult source cases, losses in follow-up examinations, and delay in referral to a specialized TB clinic of TB-exposed children, especially among foreign-born children, appear to be the main issue in this German pediatric study cohort.
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Miller AC, Arakkal AT, Koeneman S, Cavanaugh JE, Gerke AK, Hornick DB, Polgreen PM. Incidence, duration and risk factors associated with delayed and missed diagnostic opportunities related to tuberculosis: a population-based longitudinal study. BMJ Open 2021; 11:e045605. [PMID: 33602715 PMCID: PMC7896623 DOI: 10.1136/bmjopen-2020-045605] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
OBJECTIVES Missed opportunities to diagnose tuberculosis are costly to patients and society. In this study, we (1) estimate the frequency and duration of diagnostic delays among patients with active pulmonary tuberculosis and (2) determine the risk factors for experiencing a diagnostic delay. DESIGN A retrospective cohort study of patients with tuberculosis using longitudinal healthcare encounters prior to diagnosis. SETTING Commercially insured enrollees from the Commercial Claims and Encounters or Medicare Supplemental IBM Marketscan Research Databases, 2001-2017. PARTICIPANTS All patients diagnosed with, and receiving treatment for, pulmonary tuberculosis, enrolled at least 365 days prior to diagnosis. PRIMARY AND SECONDARY OUTCOME MEASURES We estimated the number of visits with tuberculosis-related symptoms prior to diagnosis that would be expected to occur in the absence of delays and compared this estimate to the observed pattern. We computed the number of visits representing a delay and used a simulation-based approach to estimate the number of patients experiencing a delay, number of missed opportunities per patient and duration of delays (ie, time between diagnosis and earliest missed opportunity). We also explored risk factors for missed opportunities. RESULTS We identified 3371 patients diagnosed and treated for active tuberculosis that could be followed up for 1 year prior to diagnosis. We estimated 77.2% (95% CI 75.6% to 78.7%) of patients experienced at least one missed opportunity; of these patients, an average of 3.89 (95% CI 3.65 to 4.14) visits represented a missed opportunity, and the mean duration of delay was 31.66 days (95% CI 28.51 to 35.11). Risk factors for delays included outpatient or emergency department settings, weekend visits, patient age, influenza season presentation, history of chronic respiratory symptoms and prior fluoroquinolone use. CONCLUSIONS Many patients with tuberculosis experience multiple missed diagnostic opportunities prior to diagnosis. Missed opportunities occur most commonly in outpatient settings and numerous patient-specific, environment-specific and setting-specific factors increase risk for delays.
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Affiliation(s)
| | | | - Scott Koeneman
- Biostatistics, The University of Iowa, Iowa City, Iowa, USA
| | | | - Alicia K Gerke
- Internal Medicine, The University of Iowa, Iowa City, Iowa, USA
| | | | - Philip M Polgreen
- Epidemiology, University of Iowa, Iowa City, Iowa, USA
- Internal Medicine, The University of Iowa, Iowa City, Iowa, USA
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