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Prediction model of in-hospital death for AECOPD patients admitted to ICU: the PD-ICU score.
Respiration ; : 1-25, 2024 Sep 11.
Article en En | MEDLINE | ID: mdl-39260355
ABSTRACT

INTRODUCTION:

Patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) admitted to intensive care unit (ICU) are exposed to poor clinical outcomes, and no specific prognostic models are available among these population. We aimed to develop and validate a risk score for prognosis prediction for these patients.

METHODS:

This was a multicenter observation study. AECOPD patients admitted to ICU were included for model derivation from a prospective, multicenter cohort study. Logistic regression analysis was applied to identify independent predictors for in-hospital death and establish the prognostic risk score. The risk score was further validated and compared with DECAF, BAP-65, CURB-65 and APACHE Ⅱ score in another multicenter cohort.

RESULTS:

Five variables were identified as independent predictors for in-hospital death in APCOPD patients admitted to ICU, and a corresponding risk score (PD-ICU score) was established, which was composed of Procalcitonin>0.5ug/L, Diastolic Blood Pressure<60mmHg, Need for Invasive Mechanical Ventilation, Disturbance of Consciousness and Blood Urea Nitrogen>7.2mmol/L. Patients were classified into three risk categories according to PD-ICU score. The in-hospital mortality of low-risk, intermediate-risk, and high-risk patients were 0.3%, 7.3%, and 27.9%, respectively. PD-ICU score displayed excellent discrimination ability with an area under the receiver operating characteristic curve (AUC) of 0.815 in the derivation cohort and 0.754 in the validation cohort which outperformed other prognostic models.

CONCLUSION:

We derived and validated a simple and clinician-friendly prediction model (PD-ICU score) for in-hospital mortality among AECOPD patients admitted to ICU. With good performance and clinical practicability, this model may facilitate early risk stratification and optimal decision-making among these patients.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Respiration Año: 2024 Tipo del documento: Article Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Respiration Año: 2024 Tipo del documento: Article Pais de publicación: Suiza