Publications by authors named "C Casarsa"
Article Synopsis
- - Sepsis is a complicated and serious condition, and this study aimed to improve prognosis and patient grouping by examining specific immune response biomarkers known as regulatory immune checkpoints.
- - Researchers analyzed 12 immune response biomarkers in 113 patients with bacterial sepsis, finding that two biomarkers, IRAK-M and Galectin-1, were strong indicators of short-term (7-day and 30-day) mortality and could help categorize patients based on immune response.
- - The study concluded that IRAK-M and Galectin-1 could serve as prognostic tools to identify different sepsis phenotypes, which may assist in treatment decisions and future clinical trials aimed at targeted therapies.
Coronavirus disease 2019 (COVID-19) is characterized by a distinctive blood leucocyte pattern and B-lines on lung ultrasound (LUS) as marker of alveolar-interstitial syndrome. We aimed to evaluate the accuracy of blood leucocyte count alone or in combination with LUS for COVID-19 diagnosis. We retrospectively enrolled consecutive patients diagnosed with community acquired pneumonia (CAP) at hospital admission to derive and validate cutoff values for blood cell count that could be predictive of COVID-19 before confirmation by the nucleic acid amplification test (NAAT).
View Article and Find Full Text PDFTo assess the usefulness of lung ultrasound (LUS) for identifying community-acquired pneumonia (CAP) among adult patients with suspected lower respiratory tract infection (LRTI) and for discriminating between CAP with different cultural statuses, etiologies, and outcomes. LUS was performed at internal medicine ward admission. The performance of chest X-ray (CXR) and LUS in diagnosing CAP in 410 patients with suspected LRTI was determined.
View Article and Find Full Text PDFArticle Synopsis
- The study critiques the existing qSOFA tool for predicting mortality in sepsis patients outside intensive care units and aims to enhance its effectiveness.
- Researchers developed three new predictive models by combining qSOFA with clinical variables and serum biomarkers from 848 undifferentiated patients and 545 diagnosed with sepsis.
- The new models, especially eqSOFA1 and eqSOFA2+CRP+MR-proADM, showed significantly better predictive ability than qSOFA in identifying mortality risk, proving useful in both initial and validation patient groups.
Article Synopsis
- The study aimed to create and validate a predictive algorithm that combines a nomogram-based assessment with serum biomarker data to effectively distinguish between sepsis/septic shock and noninfectious systemic inflammatory response syndrome in patients.
- Conducted in five university hospitals, the research involved nearly 1,000 adult patients, forming both a training and validation cohort to ensure robustness and accuracy.
- The resulting algorithm, which primarily uses procalcitonin and another biomarker, demonstrated high negative predictive values, making it a reliable tool for emergency department physicians in clinical decision-making.