ABSTRACT
PURPOSE: Despite increasing literature on the association between treatment delay and outcomes, cut-off point (1 month or median) selection in almost all studies for treatment delay is too subjective. This study explored more scientific cut-off points of treatment delay for poor treatment outcomes and death at the clinical level. PATIENTS AND METHODS: A total of 18,100 newly confirmed pulmonary tuberculosis (TB) cases in Dalian, China were used in the final analysis. A 3-knotted restricted cubic spline (RCS) fitted for Cox proportional hazard regression models is used to analyse the effects of cut-off points of treatment delay on incident poor treatment outcomes. To explore the moderating effects of age, gender and diabetes, we added the interaction terms of these moderating variables and treatment delay to Cox proportional hazard regression models. RESULTS: The median time of treatment initiation was 30 days (IQR: 14-59 days). The risk of incident poor treatment outcomes increased when the time was greater than cut-off point 1 (53 days; adjusted HR: 1.26; 95% CI: 1.00-1.60) of treatment delay, and the risk of incident death events increased when the time was greater than cut-off point 2 (103 days; adjusted HR: 1.56; 95% CI: 1.00-2.44) of delay. In addition, treatment delay was associated with an increased risk of incident poor treatment outcomes and death, and older age, male sex, and diabetes may increase the risk of treatment delay for poor outcomes. CONCLUSION: This study is the first to identify scientific cut-off points of treatment delay for poor treatment outcomes and death, and this method of exploration should be popularized. In addition, the knowledge of tuberculosis must be spread to every adult. Moreover, the tuberculosis diagnosis level of community level health workers should be enhanced.
ABSTRACT
BACKGROUND: The COVID-19 pandemic seriously threatens general public health services globally. This study aimed to evaluate the impact of the COVID-19 pandemic on the HIV care continuum in Jiangsu province, China. METHODS: Data on newly diagnosed HIV persons for analysis were retrieved from Chinas' web-based Comprehensive Response Information Management System (CRIMS) for HIV/AIDS from 2016 to 2020. We recorded data for the first 3 months (January to March, 2020) of strictly implementing COVID-19 measures from publicly available disease databases of the Jiangsu provincial Health Committee. We used seasonal autoregressive integrated moving average (SARIMA) and exponential smoothing in forecasting the parameters. Subgroup differences were accessed using Chi-square tests. RESULTS: Compared to the estimated proportions, the HIV testing rates decreased by 49.0% (919,938) in the first three months of implementing COVID-19 measures. Of an estimated 1555 new HIV diagnosis expected in the same period, only 63.0% (980) new diagnoses were recorded. According to actual data recorded during the said period, 980 positively tested persons received confirmatory tests, of which 71.4% (700) were reportedly linked to care. And only 49.5% (235) out of the expected 475 newly diagnosed HIV persons received CD4 cell count testing. Meanwhile 91.6% (208) of newly diagnosed HIV persons who received CD4 count tests reportedly initiated antiretroviral therapy (ART) compared to the 227 expected. Compared to the same period from 2016 to 2019, PLWH less than 30 years old and migrants were more likely to be affected by the COVID-19 policies. CONCLUSIONS: The COVID-19 pandemic negatively impacted HIV healthcare systems in Jiangsu, China. Further measures that can counter the impact of the pandemic are needed to maintain the HIV care continuum.