The Battle of the Pneumonia Predictors: A Comprehensive Meta-Analysis Comparing the Pneumonia Severity Index (PSI) and the CURB-65 Score in Predicting Mortality and the Need for ICU Support

Abstract

The CURB-65 (confusion, uremia, respiratory rate, blood pressure, age ≥ 65 years) score and the pneumonia severity index (PSI) are widely used and recommended in predicting 30-day mortality and the need for intensive care support in community-acquired pneumonia. This study aims to compare the performance of these two severity scores in both mortality prediction and the need for intensive care support. A systematic review and meta-analysis was carried out, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) 2020 guidelines, and PubMed, Scopus, ScienceDirect, and Google Scholar were searched for articles published from 2012 to 2022. The reference lists of the included studies were also searched to retrieve possible additional studies. Twenty-five studies reporting prognostic information for CURB 65 and PSI were identified. ReviewManager (RevMan) 5.4.1 was used to produce risk ratios, and a random effects model was used to pool them. Both PSI and CURB-65 showed a high strength in identifying high-risk patients. However, CURB-65 was slightly better in early mortality prediction and had more sensitivity (96.7%) and specificity (89.3%) in predicting admission to intensive care support. Thus, CURB-65 seems to be the preferred tool in predicting mortality and the need for admission into intensive care support.

Septic pulmonary embolism arising from a small temporal boil in a patient with diabetes mellitus type 2: A rare case report

“…2,3 Early identification of such patients could lead to better results, fewer incorrect nonadmissions, and possibly shorter ICU stays. 4 We present a remarkable case of SPE originating from a small boil on the right temporal region, an atypical source of infection. This case underscores the importance of considering rare diagnostic possibilities, especially in the context of underlying medical conditions.…”

“…These manifestations can overlap with those of respiratory or other conditions, further complicating the diagnostic process 2,3 . Early identification of such patients could lead to better results, fewer incorrect nonadmissions, and possibly shorter ICU stays 4 …”

An explainable machine learning-based model to predict intensive care unit admission among patients with community-acquired pneumonia and connective tissue disease

“…Therefore, apart from timely initiations of appropriate antibiotics and respiratory support, predicting the likelihood of ICU admission is another important issue in the management of CAP patients. Traditional risk score systems such as pneumonia severity index (PSI) and CURB-65 (confusion, uremia, increased respiratory rate, hypotension, and age 65 years or older) have been widely used to facilitate choosing appropriate site-of-care and predicting the prognosis for patients with CAP [ 13 , 14 ]. Meanwhile, the 2007 Infectious Diseases Society of America / American Thoracic Society criteria for defining severe community-acquired pneumonia (IDSA/ATS 2007 criteria) remains the most pragmatic tool to predict ICU admission in CAP [ 15 ].…”