Utility of Acute Physiology and Chronic Health Evaluation (APACHE II) in Predicting Mortality in Patients with Pyogenic Liver Abscess: A Retrospective Study.
Yuan-Ti LeeChi-Chih WangChien-Feng LiHsuan-Yi ChenHsien-Hua LiaoChia-Chun LinPublished in: Journal of clinical medicine (2021)
Pyogenic liver abscess (PLA) is a major life-threatening disease with varied clinical features. This study aimed to determine predictors of mortality in patients with PLA using criteria determined upon admission. We retrospectively examined the data of 324 hospitalized adults in whom liver abscesses were confirmed using abdominal ultrasound and/or computed tomography. The relationship between various risk factors was assessed using multivariate analysis. A total of 109 (33.6%) patients were admitted to the intensive care unit (ICU). The overall mortality rate was 7.4% and was higher among ICU patients than non-ICU patients (21.1% vs. 0.5%, p < 0.001). PLA patients with an Acute Physiology and Chronic Health Evaluation (APACHE) II score ≥18 had a 19.31-fold increased risk, and those with concomitant infections had a 34.33-fold increased risk of 30-day mortality according to multivariate analysis. The estimated area under the receiver operating characteristic curve for predicting 30-day mortality revealed that APACHE II score ≥18 (sensitivity of 75% and specificity of 84%, p < 0.0001) had better discriminative power than Sequential Organ Failure Assessment (SOFA) ≥6 (sensitivity of 81% and specificity of 66%, p < 0.0001). APACHE II has shown better discrimination ability than SOFA in predicting mortality in PLA patients. To improve outcomes in patients with PLA, future management strategies should focus on high-risk patients.
Keyphrases
- end stage renal disease
- risk factors
- ejection fraction
- computed tomography
- newly diagnosed
- chronic kidney disease
- healthcare
- public health
- peritoneal dialysis
- prognostic factors
- magnetic resonance imaging
- intensive care unit
- type diabetes
- magnetic resonance
- patient reported outcomes
- hepatitis b virus
- deep learning
- rare case
- electronic health record
- insulin resistance
- human health