Validation and Comparison of Seven Mortality Prediction Models for Hospitalized Patients With Acute Decompensated Heart Failure

Abstract

Background Heart failure (HF) inpatient mortality prediction models can help clinicians make treatment decisions and researchers conduct observational studies. Published models have not been validated in external populations, however. Methods and Results We compared the performance of seven models that predict inpatient mortality in patients hospitalized with acute decompensated heart failure (ADHF): Four HF-specific mortality prediction models developed from three clinical databases (Acute Decompensated HF National Registry [ADHERE], Enhanced Feedback for Effective Cardiac Treatment [EFFECT] Study, Get with the Guidelines-HF [GWTG-HF] Registry); two administrative HF mortality prediction models (Premier, Premier+); and a model that uses clinical data but is not specific for HF (Laboratory-Based Acute Physiology Score [LAPS2]). Using a multi-hospital electronic health record-derived (EHR) dataset (HealthFacts [Cerner Corp], 2010–2012), we identified patients ≥18 years admitted with HF. Of 13,163 eligible patients, median age was 74 years; half were women; and 27% were black. In-hospital mortality was 4.3%. Model predicted mortality ranges varied: Premier+ (0.8–23.1%), LAPS2 (0.7–19.0%), ADHERE (1.2–17.4%), EFFECT (1.0–12.8%), GWTC-Eapen (1.2–13.8%), and GWTG-Peterson (1.1–12.8%). The LAPS2 and Premier models outperformed the clinical models (c-statistics: LAPS2 0.80 [95% CI: 0.78–0.82], Premier models 0.81 [95% CI: 0.79–0.83]) and 0.76 [95% CI: 0.74–0.78]; clinical models 0.68–0.70). Conclusions Four clinically-derived inpatient HF mortality models exhibited similar performance, with c-statistics near 0.70. Three other models, one developed in EHR data and two developed in administrative data, also were predictive, with c-statistics from 0.76–0.80. Because every model performed acceptably, the decision to use a given model should depend on practical concerns and intended use.

Regional Validation and Recalibration of Clinical Predictive Models for Patients With Acute Heart Failure

“…Consistent with a recent report limited only to North America,15 The GWTG‐HF CPM showed a moderate drop in discrimination in our North American validation cohort. CPM discrimination across different world regions was generally considerably worse for each of the 3 models compared with performance reported in the initial derivation samples and the decrement in discrimination varied substantially across different world regions.…”

Derivation and Validation of an In‐Hospital Mortality Prediction Model Suitable for Profiling Hospital Performance in Heart Failure

“…First, we validated the model for use at the hospital level in a separate population with different demographic characteristics. Second, we previously demonstrated the patient‐level performance of the Premier model compared with published clinical HF mortality prediction models 16. Third, our model is one of only 2 clinical prediction models in the HF literature aimed specifically at benchmarking hospitals and is potentially more broadly applicable than the CMS model for the reasons stated.…”

“…We used a broad set of diagnosis codes to identify patients (with both HF and respiratory failure as principal diagnoses), but also required the presence of at least 1 HF‐specific treatment early in the hospitalization as a proxy for clinical findings of HF. Although many prior studies and CMS quality metrics use diagnosis codes alone to identify patients hospitalized with HF,10, 30, 31, 32 we believe that using criteria that combine the principal diagnosis code with early therapies is a more specific method for identifying hospitalizations for which the primary issue is HF 16. Furthermore, the high percentage of patients treated with diuretics provides additional evidence that these were hospitalizations for which the primary issue was HF.…”

Short‐Term Safety of Nicotine Replacement in Smokers Hospitalized With Coronary Heart Disease

“…Similarly, we also tracked the use of several critical care therapies in the first 2 days of hospitalization and included them as baseline characteristics. This included recording the use of inotropes, vasopressors, invasive and noninvasive ventilation, intra‐aortic balloon pump, and/or arterial line, as has previously been done 20, 21. We also included location in an intensive care or intermediate care unit as a marker of illness severity.…”