It is well known that air pollution causes respiratory morbidity and mortality by inducing airway inflammation. However, whether long-term exposure to air pollution is associated with increased incidence of chronic obstructive pulmonary disease (COPD) is controversial. We conducted a systematic review and meta-analysis with a random-effects model to calculate the pooled risk estimates of COPD development per 10 μg/m3 increase in individual air pollutants. PubMed, Embase, and Cochrane Library were searched from the date of their inception to August 2019 to identify long-term (at least three years of observation) prospective longitudinal studies that reported the risk of COPD development due to exposure to air pollutants. The air pollutants studied included particulate matter (PM2.5 and PM10) and nitrogen dioxide (NO2). Of the 436 studies identified, seven met our eligibility criteria. Among the seven studies, six, three, and five had data on PM2.5, PM10, and NO2, respectively. The meta-analysis results showed that a 10 μg/m3 increase in PM2.5 is associated with increased incidence of COPD (pooled HR 1.18, 95% CI 1.13-1.23). We also noted that a 10 μg/m3 increase in NO2 is marginally associated with increased incidence of COPD (pooled HR 1.07, 95% CI 1.00-1.16). PM10 seems to have no significant impact on the incidence of COPD (pooled HR 0.95, 95% CI 0.83-1.08), although the number of studies was too small. Meta-regression analysis found no significant effect modifiers. Long-term exposure to PM2.5 and NO2 can be associated with increased incidence of COPD.

Conventional severity-of-illness scoring systems have shown suboptimal performance for predicting in-intensive care unit (ICU) mortality in patients with severe pneumonia. This study aimed to develop and validate machine learning (ML) models for mortality prediction in patients with severe pneumonia. This retrospective study evaluated patients admitted to the ICU for severe pneumonia between January 2016 and December 2021. The predictive performance was analyzed by comparing the area under the receiver operating characteristic curve (AU-ROC) of ML models to that of conventional severity-of-illness scoring systems. Three ML models were evaluated: (1) logistic regression with L2 regularization, (2) gradient-boosted decision tree (LightGBM), and (3) multilayer perceptron (MLP). Among the 816 pneumonia patients included, 223 (27.3%) patients died. All ML models significantly outperformed the Simplified Acute Physiology Score II (AU-ROC: 0.650 [0.584–0.716] vs 0.820 [0.771–0.869] for logistic regression vs 0.827 [0.777–0.876] for LightGBM 0.838 [0.791–0.884] for MLP; P < 0.001). In the analysis for NRI, the LightGBM and MLP models showed superior reclassification compared with the logistic regression model in predicting in-ICU mortality in all length of stay in the ICU subgroups; all age subgroups; all subgroups with any APACHE II score, PaO₂/FiO₂ ratio < 200; all subgroups with or without history of respiratory disease; with or without history of CVA or dementia; treatment with mechanical ventilation, and use of inotropic agents. In conclusion, the ML models have excellent performance in predicting in-ICU mortality in patients with severe pneumonia. Moreover, this study highlights the potential advantages of selecting individual ML models for predicting in-ICU mortality in different subgroups.

Background: The association between the location of non‐small cell lung cancer (NSCLC) and prognosis is a debated issue. Some studies have provided evidence of better prognosis of upper lobe tumors than lower to middle lobe tumors, while other studies have reported contrasting conclusions. The aim of this study was to further assess this association through a systematic review and meta‐analysis.Methods: Medline, Embase, and the Cochrane Central Register of Controlled Trials were searched up to 27 January 2017. Patients pathologically diagnosed with stage I–III NSCLC with three or five‐year survival data were included. The main meta‐analysis compared differences in survival rates according to the primary tumor location using the Mantel–Haenszel method with a random effect model. Sensitivity analysis was conducted according to lymph node metastasis, tumor node metastasis stage, staging method, and treatment modality.Results: Ten clinical studies and 35 570 patients were recruited. Patients with tumors in the upper lobes had a higher rate of five‐year survival compared to those with tumors in non‐upper lobes (odds ratio [OR] 1.31, 95% confidence interval [CI] 1.15–1.49). Similarly, the three‐year survival rate was high in patients with tumors in the upper lobes (OR 1.99, 95% CI 1.02–3.86) and low in those with lower lobe tumors (OR 0.31, 95% CI 0.12–0.77).Conclusions: Stage I–III NSCLC located in the upper lobes showed higher five‐year survival rates compared to other tumor locations.

This systematic review and meta-analysis aimed to comprehensively evaluate the factors associated with mortality and progressive disease in NTM-LD patients. We conducted a literature search to identify the eligible studies, dated between January 1, 2007, and April 12, 2021. Forty-one studies with total 10,452 patients were included. The overall all-cause mortality rate was 20% (95% CI 17–24%). The overall rates of clinical and radiographic progressive disease were 46% (95% CI 39–53%) and 43% (95% CI 31–55%), respectively. Older age, male sex, history of TB, diabetes, chronic heart disease, malignancy, systemic immunosuppression, chronic liver disease, presence of cavity, consolidative radiologic features, acid-fast bacillus (AFB) smear positivity, hypoalbuminemia, anemia, increasing platelet count, high CRP, and high ESR were significantly associated with increased all-cause mortality, whereas increasing body mass index (BMI), hemoptysis, and treatment with rifamycin regimen (in M. xenopi) were significantly associated with decreased all-cause mortality in multivariable analysis. History of TB, Aspergillus co-infection, cough, increased sputum, weight loss, presence of cavity, and AFB smear positivity were significantly associated with increased clinical progression with treatment, while older age and low BMI were significantly associated with decreased clinical progression in multivariable analysis. Older age, interstitial lung disease, presence of cavity, consolidative radiologic feature, anemia, high CRP, and leukocytosis were significantly associated with increased radiographic progression after adjusting for covariates. Older age, history of tuberculosis, presence of cavity, consolidative radiologic features, AFB smear positivity, anemia, and high C-reactive protein were common significant factors associated with the all-cause mortality and clinical or radiographic progressive disease of NTM-LD. These factors are thought to directly affect NTM-LD related mortality. The future prediction models for the prognosis of NTM-LD should be established considering these factors.