Barreiras e facilitadores à integração dos serviços de depressão e tuberculose na rede de atenção primária no Brasil

Mental disorders can affect up to 70% of individuals with tuberculosis (TB). The World Health Organization (WHO) End TB Strategy explicitly calls for TB and mental health service integration. The goal of this study was to explore the barriers and facilitators to integrating depression treatment in the TB Control Program and primary care system in the municipality of Itaboraí - Rio de Janeiro, using Interpersonal Counseling (IPC). IPC is an evidence-based treatment for depression that can be delivered by non-mental health specialists with expert supervision. This study was conducted between 2016 and 2017 in the municipality of Itaboraí. Data collection consisted of six focus groups (n = 42) with health professionals (n = 29), program coordinators (n = 7) and TB patients (n = 6). The main potential barriers identified were poverty, political instability, an overburdened and under-resourced health system, high levels of distress among professionals, violence in the community and stigma related to mental health and TB. Potential facilitators included a high receptivity to, and demand for, mental health training; strong community relationships through the Community Health Workers (CHW); overall acceptability of IPC delivered by non-specialists for the treatment of depression among individuals with and without comorbid TB. Despite many challenges, integrating depression treatment into primary care in Itaboraí using IPC was perceived as an acceptable and feasible option.Os transtornos mentais podem afetar até 70% dos indivíduos com tuberculose (TB). A Organização Mundial da Saúde (OMS), como estratégia para o fim da TB, exige a integração do seu tratamento com a saúde mental. O objetivo deste estudo foi explorar as barreiras e facilitadores para integrar serviços de saúde mental no Programa de Controle de Tuberculose (PCT) e em Unidades de Saúde da Família (USF) do município de Itaboraí – Rio de Janeiro, com a aplicação do Aconselhamento Interpessoal (AIP). O AIP é um tratamento para depressão baseado em evidências que pode ser aplicado por não especialistas em saúde mental com supervisão especializada. Seis grupos focais foram realizados entre 2016 e 2017 no município de Itaboraí. A amostra (n=42) incluiu profissionais de saúde (n=29), coordenadores de programas (n=7) e pacientes com TB (n=6). Os grandes desafios encontrados foram: pobreza, instabilidade política, um sistema de saúde sobrecarregado e com poucos recursos, alta frequência de estresse entre os profissionais, violência na comunidade e estigma relacionado à saúde mental e à TB. Os facilitadores potenciais incluíram uma grande receptividade e demanda para capacitações em saúde mental; boa relação com a comunidade pelos Agentes Comunitários de Saúde (ACS) e; aceitação geral do AIP aplicado por não especialistas em saúde mental para o tratamento de depressão em pessoas com e sem TB. Apesar de muitos desafios, integrar o tratamento de depressão na atenção primária de Itaboraí aplicando o AIP foi percebido como uma alternativa aceitável e factível

Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients

Background: Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Methods: Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. Results: We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. Conclusions: The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in countries with limited resources.Fogarty/NIHFogarty/NIH [3 D43 TW000018-16S3, 5 U2R TW006883-02]CNPq [504162/2008-0, 308889/2007-0]CNP

The presence of a booster phenomenon among contacts of active pulmonary tuberculosis cases: a retrospective cohort

Abstract\ud \ud \ud \ud Background\ud \ud Assuming a higher risk of latent tuberculosis (TB) infection in the population of Rio de Janeiro, Brazil, in October of 1998 the TB Control Program of Clementino Fraga Filho Hospital (CFFH) routinely started to recommend a two-step tuberculin skin test (TST) in contacts of pulmonary TB cases in order to distinguish a boosting reaction due to a recall of delayed hypersensitivity previously established by infection with Mycobacterium tuberculosis (M.tb) or BCG vaccination from a tuberculin conversion. The aim of this study was to assess the prevalence of boosted tuberculin skin tests among contacts of individuals with active pulmonary tuberculosis (TB).\ud \ud \ud \ud Methods\ud \ud Retrospective cohort of TB contacts ≥ 12 years old who were evaluated between October 1st, 1998 and October 31st 2001. Contacts with an initial TST ≤ 4 mm were considered negative and had a second TST applied after 7–14 days. Boosting reaction was defined as a second TST ≥ 10 mm with an increase in induration ≥ 6 mm related to the first TST. All contacts with either a positive initial or repeat TST had a chest x-ray to rule out active TB disease, and initially positive contacts were offered isoniazid preventive therapy. Contacts that boosted did not receive treatment for latent TB infection and were followed for 24 months to monitor the development of TB. Statistical analysis of dichotomous variables was performed using Chi-square test. Differences were considered significant at a p < 0.05.\ud \ud \ud \ud Results\ud \ud Fifty four percent (572/1060) of contacts had an initial negative TST and 79% of them (455/572) had a second TST. Boosting was identified in 6% (28/455). The mean age of contacts with a boosting reaction was 42.3 ± 21.1 and with no boosting was 28.7 ± 21.7 (p = 0.01). Fifty percent (14/28) of individuals whose test boosted met criteria for TST conversion on the second TST (increase in induration ≥ 10 mm). None of the 28 contacts whose reaction boosted developed TB disease within two years following the TST.\ud \ud \ud \ud Conclusion\ud \ud The low number of contacts with boosting and the difficulty in distinguishing boosting from TST conversion in the second TST suggests that the strategy of two-step TST testing among contacts of active TB cases may not be useful. However, this conclusion must be taken with caution because of the small number of subjects followed.The authors are grateful to Anne Efron and Dr. Richard Chaisson for their assistance and support to this manuscript. Cristiane G Salles and Michelle Cailleaux-Cesar were recipients of a scholarship from Cornell/Fogarty/NIH project # 3 D43 TW000018-16S3.The authors are grateful to Anne Efron and Dr. Richard Chaisson for their assistance and support to this manuscript. Cristiane G Salles and Michelle CailleauxCesar were recipients of a scholarship from Cornell/Fogarty/NIH project # 3 D43 TW00001816S3

Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients

Abstract Background Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Methods Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. Results We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. Conclusions The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in countries with limited resources.</p