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Assessing illness severity: does clinical judgment work?

作者信息

Charlson M E, Sax F L, MacKenzie C R, Fields S D, Braham R L, Douglas R G

出版信息

J Chronic Dis. 1986;39(6):439-52. doi: 10.1016/0021-9681(86)90111-6.

Abstract

Accurate classification of clinical severity is important for interpreting casemix in clinical studies and for stratifying patients for clinical trials. To evaluate whether clinical judgment might be an effective method of estimating severity, all 604 patients admitted to the medical service in a one month period were rated at the time of admission by the responsible resident as to how sick they were. Within the 13 comorbid disease groups, and within the 15 basic categories of reason for admission, the physicians' severity ratings were the most significant predictor of in-hospital mortality. Death rates rose from 0% in those rated as not ill, to 2% in the mildly ill, to 6% in the moderately ill, to 23% in the severely ill, and to 58% in those rated as moribund (p less than 0.001). Sickness ratings also predicted time to death: mildly ill patients died after prolonged hospitalizations, while the moribund died shortly after admission. The patients' age, sex, race, the number of comorbid diseases or problems did not predict mortality. Patients with serious comorbidity (metastases, AIDS, or cirrhosis) had a higher mortality rate than other patients (p less than 0.001); however, the severity ratings predicted outcomes within this group (p less than 0.001) as well as among those without such serious comorbidity (p less than 0.001). Patients who were admitted with acute neurologic (p less than 0.05) or acute cardiovascular (p less than 0.01) events did have an independently worse prognosis. In conclusion, physicians' estimates or sickness provided an accurate estimate of illness severity, with mortality rates that essentially tripled from one stratum to the next. Clinical judgment may suffice to classify the clinical severity of patients at the time of enrollment in prospective trials and can provide a useful method of controlling for casemix.

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