Improving prognostication of pneumonia among elderly patients: usefulness of suPAR.

PURPOSE: Elderly patients with suspected pneumonia represent a significant proportion of hospital admissions, which is a prognostic challenge for physicians. Our research aimed to assess the prognosis of patients with pneumonia using soluble urokinase plasminogen activator receptor (suPAR) combined with clinical data. METHODS: In a prospective observational study including 164 patients > 65 years (mean age 84.2 (+/-7.64) years) who were hospitalized for a suspicion of pneumonia, suPAR was assessed for each patient, as was the prognosis score (PSI, CURB65) and inflammatory biomarkers (C-reactive protein, procalcitonin, white blood cells). The prognostic value of the suPAR for 30-day mortality was assessed using receiver operating characteristic (ROC) curve analyses. Optimal cut-offs with corresponding sensitivity (SE) and specificity (SP) were determined using the Youden index. RESULTS: A suPAR > 5.1 ng/mL was predictive of 30-day mortality with a sensitivity of 100% and a specificity of 40.4%. A combination of the following parameters exhibited an SE of 100% (95% CI, 100-100) for an SP value of 64.9% (95% CI, 57.6-72.2) when at least two of them were above or below the following cut-off threshold values: suPAR > 9.8 ng/mL, BMI < 29.3 kg/m2 and PSI > 106.5. CONCLUSION: The suPAR seems to be a promising biomarker that can be combined with the PSI and BMI to improve the prognosis of pneumonia among elderly patients. Prospective studies with larger populations are needed to confirm whether this new approach can improve patient outcomes. TRIAL REGISTRATION: ClinicalTrials.gov (NCT02467192), 27th may 2015.

The prognosis of pneumonia in geriatric patients remain challenging, can the dosage of suPAR help clinicians determine the prognosis of pneumonia among geriatric patients? The use of individual or clinical parameters should be improved for a better prediction of respiratory complications and mortality. Adding suPAR dosage with PSI and BMI provides the best sensitivity and specificity for 30-day mortality.

Diagnostic Accuracy of Vascular Ultrasonography for Postanesthesia Induction Hypotension: A Systematic Review and Network Meta-Analysis.

BACKGROUND: Arterial hypotension commonly occurs after anesthesia induction and is associated with negative clinical outcomes. Point-of-care ultrasound examination has emerged as a modality to predict postinduction hypotension (PIH). We performed a systematic review and network meta-analysis of the predictive performance of point-of-care ultrasound tests for PIH in noncardiac, nonobstetrical routine adult surgery. METHODS: Online databases were searched for diagnostic test accuracy studies of point-of-care ultrasound for predicting PIH up to March 30, 2023. The systematic review followed the Cochrane methodology. A Bayesian diagnostic test accuracy network meta-analysis model was used, with PIH as defined by study authors as the main outcome. Risk of bias and applicability were examined through the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies) score. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework was used to assess evidence certainty. RESULTS: A total of 32 studies with 2631 participants were eligible for systematic review. Twenty-six studies with 2258 participants representing 8 ultrasound tests were included in the meta-analysis. Inferior vena cava collapsibility index (22 studies) sensitivity was 60% (95% credible interval [CrI], 49%-72%) and specificity was 83% (CrI, 74%-89%). Carotid artery corrected flow time (2 studies) sensitivity was 91% (CrI, 76%-98%) and specificity was 90% (CrI, 59%-98%). There were serious bias and applicability concerns due to selection bias and inappropriate blinding. The certainty of evidence was very low for all tests. CONCLUSIONS: The predictive performance of point-of-care ultrasound for PIH is uncertain. There is a need for high-quality randomized controlled trials with appropriate blinding and void of selection bias.