What is the clinical evidence from this study?

Study design: Cohort. Population: Critically ill patients (n=3778). Intervention: Charlson Index Score vs. APACHE II. Primary outcome: Discriminative ability for all-cause hospital mortality (C-statistic).

July 30, 2009BMC Health Services Research120 citationsOpen Access

A comparison between the APACHE II and Charlson Index Score for predicting hospital mortality in critically ill patients

SQSusan QuachHospital for Sick Children DHDeirdre HennessyStatistics Canada PFPeter FarisAlberta Health Services

Key Result

The Charlson index demonstrated poor discriminative ability for predicting hospital mortality (C-statistic = 0.626) compared to the APACHE II score (C-statistic = 0.808) in critically ill patients.

Study Design

Type

Cohort (n=3,778)

Multicenter

Yes

Structured PICO

Does the Charlson Index Score predict hospital mortality as well as the APACHE II score in adult multisystem ICU patients?

Population

3,778 adult (>17 years of age) residents of the Calgary Health Region admitted to a multisystem ICU between April 2002 and March 2004. Cardiovascular surgery patients were excluded. Mean age 56.9 years, 57.0% male.

Intervention

Charlson Index Score (derived from administrative hospital discharge data)

Comparator

APACHE II score (collected prospectively at the time of ICU admission)

Outcome

All cause hospital mortalityhard clinical

The Charlson index is inferior to the APACHE II score for predicting hospital mortality in ICU patients, but may serve as a viable alternative for risk adjustment when physiological acuity scores are unavailable.

Main Result

Absolute Event Rate: 0.626% vs 0.808%

Limitations

Potential selection bias if critically ill patients were refused ICU admission based on underlying co-morbidities and probability for death.
Small number of ICU patients with high Charlson index scores resulted in a highly skewed distribution and potentially unstable estimates in that subset.
The original Charlson weights may not be appropriate for critically ill patients, as advances in treatment have changed mortality risks for some co-morbidities.
Potential selection bias if critically ill patients were refused admission to ICU based on underlying co-morbidities and probability for death
Small number of ICU patients with high Charlson index scores, making estimates unstable in this subset

Abstract

BACKGROUND: Risk adjustment and mortality prediction in studies of critical care are usually performed using acuity of illness scores, such as Acute Physiology and Chronic Health Evaluation II (APACHE II), which emphasize physiological derangement. Common risk adjustment systems used in administrative datasets, like the Charlson index, are entirely based on the presence of co-morbid illnesses. The purpose of this study was to compare the discriminative ability of the Charlson index to the APACHE II in predicting hospital mortality in adult multisystem ICU patients. METHODS: This was a population-based cohort design. The study sample consisted of adult (>17 years of age) residents of the Calgary Health Region admitted to a multisystem ICU between April 2002 and March 2004. Clinical data were collected prospectively and linked to hospital outcome data. Multiple regression analyses were used to compare the performance of APACHE II and the Charlson index. RESULTS: The Charlson index was a poor predictor of mortality (C = 0.626). There was minimal difference between a baseline model containing age, sex and acute physiology score (C = 0.74) and models containing either chronic health points (C = 0.76) or Charlson index variations (C = 0.75, 0.76, 0.77). No important improvement in prediction occurred when the Charlson index was added to the full APACHE II model (C = 0.808 to C = 0.813). CONCLUSION: The Charlson index does not perform as well as the APACHE II in predicting hospital mortality in ICU patients. However, when acuity of illness scores are unavailable or are not recorded in a standard way, the Charlson index might be considered as an alternative method of risk adjustment and therefore facilitate comparisons between intensive care units.

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