Barriers faced by patients in the diagnosis of multidrug-resistant tuberculosis in Brazil

OBJECTIVE To understand patients’ narratives about the barriers they faced in the diagnosis and treatment of multidrug-resistant tuberculosis, and their consequences in Rio de Janeiro State, Brazil. METHODS This is a qualitative cross-sectional study with non-probabilistic sampling. A theoretical saturation criterion was considered for composing the number of interviewees. Semi-structured interviews were conducted from August to December 2019 with 31 patients undergoing treatment for multidrug-resistant tuberculosis at an outpatient referral center in Rio de Janeiro. Data were transcribed and processed with the aid of the NVIVO software. Interviews were evaluated by content analysis, and their themes, cross-referenced with participants’ characterization data. RESULTS Our main findings were: a) participants show a high proportion of primary drug resistance, b) patients experience delays in the diagnosis and effective treatment of multidrug-resistant tuberculosis ; c) healthcare providers fail to value or seek the diagnosis of drug-resistant tuberculosis, thus beginning the inadequate treatment for drug-susceptible tuberculosis, d) primary health units show low report rates of active case-finding and contact monitoring, and e) patients show poor knowledge about the disease. CONCLUSIONS We need to improve referral systems, and access to the diagnosis and effective treatment of multidrug-resistant tuberculosis; conduct an active investigation of contacts; intensify the training of healthcare providers, in collaboration with medical and nursing schools, in both public and private systems; and promote campaigns to educate the population on tuberculosis signs and symptoms

Predictive factors for unfavourable treatment in MDR-TB and XDR-TB patients in Rio de Janeiro State, Brazil, 2000-2016.

SettingThe State of Rio de Janeiro stands out as having the second highest incidence and the highest mortality rate due to TB in Brazil. This study aims at identifying the factors associated with the unfavourable treatment of MDR/XDR-TB patients in that State.MethodData on 2269 MDR-TB cases reported in 2000-2016 in Rio de Janeiro State were collected from the Tuberculosis Surveillance System. Bivariate and multivariate logistic regressions were run to estimate the factors associated with unfavourable outcomes (failure, default, and death) and, specifically, default and death.ResultsThe proportion of unfavourable outcomes was 41.9% among MDR-TB and 81.5% among XDR-TB. Having less than 8 years of schooling, and being an Afro-Brazilian, under 40 years old and drug user were associated with unfavourable outcome and default. Bilateral disease, HIV positive, and comorbidities were associated with death. XDR-TB cases had a 4.7-fold higher odds of an unfavourable outcome, with 29.3% of such cases being not treated for multidrug resistance in the past.ConclusionAbout 30% of XDR-TB cases may have occurred by primary transmission. The high rates of failure and death in this category reflect the limitation of treatment options. This highlights the urgency to incorporate new drugs in the treatment

ABC₂-SPH risk score for in-hospital mortality in COVID-19 patients

Objectives: The majority of available scores to assess mortality risk of coronavirus disease 2019 (COVID-19) patients in the emergency department have high risk of bias. Therefore, this cohort aimed to develop and validate a score at hospital admission for predicting in-hospital mortality in COVID-19 patients and to compare this score with other existing ones. Methods: Consecutive patients (≥ 18 years) with confirmed COVID-19 admitted to the participating hospitals were included. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients admitted between March–July, 2020. The model was validated in the 1054 patients admitted during August–September, as well as in an external cohort of 474 Spanish patients. Results: Median (25–75th percentile) age of the model-derivation cohort was 60 (48–72) years, and in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. Seven significant variables were included in the risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO2/FiO2 ratio, platelet count, and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829–0.859), which was confirmed in the Brazilian (0.859 [95% CI 0.833–0.885]) and Spanish (0.894 [95% CI 0.870–0.919]) validation cohorts, and displayed better discrimination ability than other existing scores. It is implemented in a freely available online risk calculator (https://abc2sph.com/). Conclusions: An easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation was designed and validated for early stratification of in-hospital mortality risk of patients with COVID-19.</p