Predictive models-assisted diagnosis of AIDS-associated Pneumocystis jirovecii pneumonia in the emergency room, based on clinical, laboratory, and radiological data.

Autor: Chagas OJ; Laboratório de Micologia Médica (LIM53), Instituto de Medicina Tropical (IMT), Faculdade de Medicina (FMUSP), Universidade de São Paulo, São Paulo, SP, Brazil. oscarchagasf@hotmail.com., Gonçalves FAR; Laboratório de Medicina Laboratorial (LIM03), Hospital das Clínicas da Faculdade de Medicina (HCFMUSP), Universidade de São Paulo, São Paulo, SP, Brazil., Nagatomo PP; Laboratório de Micologia Médica (LIM53), Instituto de Medicina Tropical (IMT), Faculdade de Medicina (FMUSP), Universidade de São Paulo, São Paulo, SP, Brazil., Buccheri R; Instituto de Infectologia Emílio Ribas, São Paulo, SP, Brazil.; Vitalant Research Institute, San Francisco, CA, USA., Pereira-Chioccola VL; Laboratório de Biologia Molecular de Parasitas e Fungos do Centro de Parasitologia e Micologia, Instituto Adolfo Lutz, São Paulo, SP, Brazil., Del Negro GMB; Laboratório de Micologia Médica (LIM53), Instituto de Medicina Tropical (IMT), Faculdade de Medicina (FMUSP), Universidade de São Paulo, São Paulo, SP, Brazil., Benard G; Laboratório de Micologia Médica (LIM53), Instituto de Medicina Tropical (IMT), Faculdade de Medicina (FMUSP), Universidade de São Paulo, São Paulo, SP, Brazil.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2024 May 16; Vol. 14 (1), pp. 11247. Date of Electronic Publication: 2024 May 16.
DOI: 10.1038/s41598-024-61174-4
Abstrakt: We assessed predictive models (PMs) for diagnosing Pneumocystis jirovecii pneumonia (PCP) in AIDS patients seen in the emergency room (ER), aiming to guide empirical treatment decisions. Data from suspected PCP cases among AIDS patients were gathered prospectively at a reference hospital's ER, with diagnoses later confirmed through sputum PCR analysis. We compared clinical, laboratory, and radiological data between PCP and non-PCP groups, using the Boruta algorithm to confirm significant differences. We evaluated ten PMs tailored for various ERs resource levels to diagnose PCP. Four scenarios were created, two based on X-ray findings (diffuse interstitial infiltrate) and two on CT scans ("ground-glass"), incorporating mandatory variables: lactate dehydrogenase, O2 sat , C-reactive protein, respiratory rate (> 24 bpm), and dry cough. We also assessed HIV viral load and CD4 cell count. Among the 86 patients in the study, each model considered either 6 or 8 parameters, depending on the scenario. Many models performed well, with accuracy, precision, recall, and AUC scores > 0.8. Notably, nearest neighbor and naïve Bayes excelled (scores > 0.9) in specific scenarios. Surprisingly, HIV viral load and CD4 cell count did not improve model performance. In conclusion, ER-based PMs using readily available data can significantly aid PCP treatment decisions in AIDS patients.
(© 2024. The Author(s).)
Databáze: MEDLINE
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