Clinical characteristics and risk factors associated with mortality in patients with severe community-acquired pneumonia and type 2 diabetes mellitus

Abstract

Background The present study was performed to investigate the impacts of type 2 diabetes mellitus (T2DM) on severe community-acquired pneumonia (SCAP) and to develop a novel prediction model for mortality in SCAP patients with T2DM. Methods This was a retrospective observational study conducted in consecutive adult patients with SCAP admitted to the intensive care unit (ICU) of West China Hospital, Sichuan University, China, between September 2011 and September 2019. The primary outcome was hospital mortality. A propensity score matching (PSM) analysis model with a 1:2 ratio was used for the comparisons of clinical characteristics and outcomes between T2DM and nondiabetic patients. The independent risk factors were identified via univariate and then multivariable logistic regression analysis and were then used to establish a nomogram. Results In total, 1262 SCAP patients with T2DM and 2524 matched patients without T2DM were included after PSM. Patients with T2DM had longer ICU length of stay (LOS) (13 vs. 12 days, P = 0.016) and higher 14-day mortality (15% vs. 10.8%, P < 0.001), 30-day mortality (25.7% vs. 22.7%, P = 0.046), ICU mortality (30.8% vs. 26.5%, P = 0.005), and hospital mortality (35.2% vs. 31.0%, P = 0.009) than those without T2DM. In SCAP patients with T2DM, the independent risk factors for hospital mortality were increased numbers of comorbidities and diabetes-related complications; elevated C-reactive protein (CRP), neutrophil to lymphocyte ratio (NLR), brain natriuretic peptide (BNP) and blood lactate; as well as decreased blood pressure on admission. The nomogram had a C index of 0.907 (95% CI: 0.888, 0.927) in the training set and 0.873 (95% CI: 0.836, 0.911) in the testing set, which was superior to the pneumonia severity index (PSI, AUC: 0.809, 95% CI: 0.785, 0.833). The calibration curve and decision curve analysis (DCA) also demonstrated its accuracy and applicability. Conclusions SCAP patients with T2DM had worse clinical outcomes than nondiabetic patients. The nomogram has good predictive performance for hospital mortality and might be generally applied after more external validations.

Braden scale for predicting pneumonia after spontaneous intracerebral hemorrhage

“…Diabetic patients are more prone to pulmonary infection 33 , but we did not observe an association of diabetes with SAP after ICH in the multivariable analysis. However, we found that there is a correlation between fasting blood glucose and SAP, which may suggest that it is the blood sugar control at the onset of ICH rather than the history of diabetes that affects SAP.…”

The landscape of lung microbiota predicts the outcome of severe community-acquired pneumonia by interacting with the host immune response

“…In our study, although no signi cant difference in the microbiome diversity and richness was observed between SOFA-decreased and SOFA-nondecreased patients, the univariate and multivariate ORs of ΔSOFA in the model were signi cantly associated with 28-day mortality, indicating ΔSOFA a potential independent indicator of outcome in the early days after admission. In addition, previous model studies mainly focused on a single variable [25][26][27][28]. Our study innovatively combined the clinical indicators, lung microbiota, and the early changed SOFA scores in predicting the mortality of SCAP patients, which outperformed the previous prediction models, suggesting the validity of the predicted model that takes into account the lung microbiota and host indicators.…”

Use of infection biomarkers in the emergency department

“…[ 38 ] In prospective studies, the risk of mortality in CAPs increased in correlation with CRP levels (for CRP 10–99 mg/L OR: 3.756 (2.320, 6.080), for CRP >200 mg/L, OR: 23.348 (13.304, 40.975), P < 0.001). [ 39 40 ] There are clinical studies that reach different results in urinary system infections. CRP did not help predict treatment failure in febrile urinary tract infections.…”