Publication | Open Access
Compensated cirrhosis: Natural history and prognostic factors
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Citations
36
References
1987
Year
PrognosisGastroenterologyPathologyFatty Liver DiseaseCirrhosisSplit SampleHepatology FibrosisLiver PhysiologyNatural HistoryCompensated CirrhosisEpidemiologyHepatologyLiver HistologyHepatitisComplications Of CirrhosisLiver DiseaseLiver CancerLiverMedicine
The study examined the natural history of compensated cirrhosis in 293 consecutive patients without prior major complications, evaluating morbidity and survival. Patients, diagnosed by liver histology between 1968 and 1980, were followed for a median of 63 months, with decompensation defined as the first major complication, and a multivariate Cox regression identified prognostic factors that were used to build and validate a prognostic index. At ten years, 58 % of patients developed decompensated cirrhosis and 47 % survived, and the prognostic index based on seven clinical, biochemical, and histological variables accurately predicted outcomes.
To investigate the natural history of compensated cirrhosis, 293 consecutive patients without previous major complications (ascites, jaundice, encephalopathy or gastrointestinal hemorrhage) were studied in terms of morbidity (probability of developing decompensated cirrhosis during follow-up) and survival. Patients were diagnosed by liver histology between 1968 and 1980. Median follow-up was 63 months. Decompensation of cirrhosis was considered when a patient first developed one of the major complications of the disease. Ten years after diagnosis, the probability of developing decompensated cirrhosis and the survival probability rate were 58 and 47%, respectively. A multivariate survival analysis (Cox's regression model) using clinical, biochemical and histological data obtained at diagnosis disclosed seven factors that predicted prognosis: serum bilirubin; serum gamma-globulin concentration; hepatic stigmata; prothrombin time; sex; age, and alkaline phosphatase. According to the contribution of each one of these factors to the final model, a prognostic index was constructed that allows calculation of the estimated survival probability. The predicting value of this index was validated by a split sample testing technique.
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