The Journal of infection · 2022
Estimating the risk of bacteraemia in hospitalised patients with pneumococcal pneumonia.
Наблюдательное исследованиеМногоцентровое исследованиеСтатьяНазвание и аннотация: Перевод в очереди
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Serrano Leyre, Ruiz Luis Alberto, Pérez Silvia, España Pedro Pablo, Gomez Ainhoa, Cilloniz Catia, Uranga Ane, Torres Antoni, Zalacain Rafael
Аннотация
OBJECTIVE: To construct a prediction model for bacteraemia in patients with pneumococcal community-acquired pneumonia (P-CAP) based on variables easily obtained at hospital admission.
METHODS: This prospective observational multicentre derivation-validation study was conducted in patients hospitalised with P-CAP between 2000 and 2020. All cases were diagnosed based on positive urinary antigen tests in the emergency department and had blood cultures taken on admission. A risk score to predict bacteraemia was developed.
RESULTS: We included 1783 patients with P-CAP (1195 in the derivation and 588 in the validation cohort). A third (33.3%) of the patients had bacteraemia. In the multivariate analysis, the following were identified as independent factors associated with bacteraemia: no influenza vaccination the last year, no pneumococcal vaccination in the last 5 years, blood urea nitrogen (BUN) ≥30 mg/dL, sodium <130 mmol/L, lymphocyte count <800/µl, C-reactive protein ≥200 mg/L, respiratory failure, pleural effusion and no antibiotic treatment before admission. The score yielded good discrimination (AUC 0.732; 95% CI: 0.695-0.769) and calibration (Hosmer-Lemeshow p-value 0.801), with similar performance in the validation cohort (AUC 0.764; 95% CI:0.719-0.809).
CONCLUSIONS: We found nine predictive factors easily obtained on hospital admission that could help achieve early identification of bacteraemia. The prediction model provides a useful tool to guide diagnostic decisions.
METHODS: This prospective observational multicentre derivation-validation study was conducted in patients hospitalised with P-CAP between 2000 and 2020. All cases were diagnosed based on positive urinary antigen tests in the emergency department and had blood cultures taken on admission. A risk score to predict bacteraemia was developed.
RESULTS: We included 1783 patients with P-CAP (1195 in the derivation and 588 in the validation cohort). A third (33.3%) of the patients had bacteraemia. In the multivariate analysis, the following were identified as independent factors associated with bacteraemia: no influenza vaccination the last year, no pneumococcal vaccination in the last 5 years, blood urea nitrogen (BUN) ≥30 mg/dL, sodium <130 mmol/L, lymphocyte count <800/µl, C-reactive protein ≥200 mg/L, respiratory failure, pleural effusion and no antibiotic treatment before admission. The score yielded good discrimination (AUC 0.732; 95% CI: 0.695-0.769) and calibration (Hosmer-Lemeshow p-value 0.801), with similar performance in the validation cohort (AUC 0.764; 95% CI:0.719-0.809).
CONCLUSIONS: We found nine predictive factors easily obtained on hospital admission that could help achieve early identification of bacteraemia. The prediction model provides a useful tool to guide diagnostic decisions.