Prevalence, predictors, and outcomes of acute respiratory distress syndrome in severe stroke.

OBJECTIVES: Patients with severe stroke are at high risk of developing acute respiratory distress syndrome (ARDS), but this severe complication was often under-diagnosed and rarely explored in stroke patients. We aimed to investigate the prevalence, early predictors, and outcomes of ARDS in severe stroke. METHODS: This prospective study included consecutive patients admitted to neurological intensive care unit (neuro-ICU) with severe stroke, including acute ischemic stroke, intracerebral hemorrhage, and subarachnoid hemorrhage. The incidence of ARDS was examined, and baseline characteristics and severity scores on admission were investigated as potential early predictors for ARDS. The in-hospital mortality, length of neuro-ICU stay, the total cost in neuro-ICU, and neurological functions at 90 days were explored. RESULTS: Of 140 patients included, 35 (25.0%) developed ARDS. Over 90% of ARDS cases occurred within 1 week of admission. Procalcitonin (OR 1.310 95% CI 1.005-1.707, P = 0.046) and PaO2/FiO2 on admission (OR 0.986, 95% CI 0.979-0.993, P < 0.001) were independently associated with ARDS, and high brain natriuretic peptide (OR 0.994, 95% CI 0.989-0.998, P = 0.003) was a red flag biomarker warning that the respiratory symptoms may be caused by cardiac failure rather than ARDS. ARDS patients had longer stays and higher expenses in neuro-ICU. Among patients with ARDS, 25 (62.5%) were moderate or severe ARDS. All the patients with moderate to severe ARDS had an unfavorable outcome at 90 days. CONCLUSIONS: ARDS is common in patients with severe stroke, with most cases occurring in the first week of admission. Procalcitonin and PaO2/FiO2 on admission are early predictors of ARDS. ARDS worsens both short-term and long-term outcomes. The conflict in respiratory support strategies between ARDS and severe stroke needs to be further studied.

The clinical value of neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR) and systemic inflammation response index (SIRI) for predicting the occurrence and severity of pneumonia in patients with intracerebral hemorrhage.

Background: Inflammatory mechanisms play important roles in intracerebral hemorrhage (ICH) and have been linked to the development of stroke-associated pneumonia (SAP). The neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR) and systemic inflammation response index (SIRI) are inflammatory indexes that influence systemic inflammatory responses after stroke. In this study, we aimed to compare the predictive value of the NLR, SII, SIRI and PLR for SAP in patients with ICH to determine their application potential in the early identification of the severity of pneumonia. Methods: Patients with ICH in four hospitals were prospectively enrolled. SAP was defined according to the modified Centers for Disease Control and Prevention criteria. Data on the NLR, SII, SIRI and PLR were collected at admission, and the correlation between these factors and the clinical pulmonary infection score (CPIS) was assessed through Spearman's analysis. Results: A total of 320 patients were enrolled in this study, among whom 126 (39.4%) developed SAP. The results of the receiver operating characteristic (ROC) analysis revealed that the NLR had the best predictive value for SAP (AUC: 0.748, 95% CI: 0.695-0.801), and this outcome remained significant after adjusting for other confounders in multivariable analysis (RR=1.090, 95% CI: 1.029-1.155). Among the four indexes, Spearman's analysis showed that the NLR was the most highly correlated with the CPIS (r=0.537, 95% CI: 0.395-0.654). The NLR could effectively predict ICU admission (AUC: 0.732, 95% CI: 0.671-0.786), and this finding remained significant in the multivariable analysis (RR=1.049, 95% CI: 1.009-1.089, P=0.036). Nomograms were created to predict the probability of SAP occurrence and ICU admission. Furthermore, the NLR could predict a good outcome at discharge (AUC: 0.761, 95% CI: 0.707-0.8147). Conclusions: Among the four indexes, the NLR was the best predictor for SAP occurrence and a poor outcome at discharge in ICH patients. It can therefore be used for the early identification of severe SAP and to predict ICU admission.