A total of 1103 clinical charts of patients admitted to 3 teaching hospitals in the state of Rio de Janeiro were reviewed. Most admissions were in non-obstetric specialties (80.5%). The mean age was 46.9 years, and 61.3% of the patients admitted were women (Table ). The proportions of principal diagnoses grouped according to the chapters of the ICD-10 revealed that 44.7% of the cases analyzed were admitted for problems associated with pregnancy, childbirth and postpartum, diseases of the circulatory system, and diseases of the digestive system. The proportion of admissions with a secondary diagnosis recorded in the charts was 54.2%, while in cases of death this proportion was 87.2% (Table ). More than 50% of the cases were emergency admissions; more than 70% of the cases underwent some procedure. Of the 94 deaths analyzed, 34% occurred in cases with an adverse event, and 26.6% of the deaths occurred in cases involving adverse events classified as preventable (Table ).
Study population characteristics: sampled admissions and deaths
Analysis of the relationship between death and patient risk factors (age, gender, Charlson index) showed a statistically significant association (Table ). Except for gender, the correlations were around 0.20. Type of admission had a correlation of 0.21 and unadjusted odds ratio of 5.14 (Table ). Among the variables related to the process of care (specialty, procedure, and length of stay), only the type of procedure was not statistically significant.
Measures of association between death and patient characteristics, process of care, preventable and non-preventable adverse events
The overall hospital mortality rate was 8.5%, but this rate increased to 38.1% in the subset of cases with the occurrence of an adverse event, and to 44.6% in the subset of cases with a preventable adverse event (Table ). The correlation between death and adverse event showed a statistically significant association, with odds ratio of 9.50 (Table ). There was also a significant association between death and preventable adverse event, with an even higher odds ratio (11.43). The mortality rate related to adverse events was 2.9% (32/1103), while that related to preventable adverse events was 2.3% (25/1103).
The mean length of stay, which may reflect a consequence of the adverse event and the severity of the case, was 25.1 days in cases with a fatal outcome (SD: 33.4; 95% CI: 18.3-32.0 days), more than twice as much as cases without death (11.1 days - SD: 22.2; 95% CI: 9.7-12.5 days). A similar pattern emerged when comparing cases with and without an adverse event: the mean length of stay tripled in cases with adverse events (32.4 days - SD: 36.0; 95% CI: 24.6-40.2 days) compared to those without adverse events (10.6 days - SD: 21.5; 95% CI: 9.3-12.0 days).
None of the tested models showed any adjustment problems, as confirmed by the Hosmer-Lemeshow test (Table ). The three models presented good predictive capacity, as measured by the C statistic (Table ). The introduction of the variable related to the occurrence of an adverse event impacted the model's performance. Among the variables related to the process of care, length of stay was the only one statistically significant, but it did not impact the baseline model's discriminatory capacity (Table ; model 2). In the second modeling step, the introduction of the clinical specialty variable (obstetrics, yes/no) was not statistically significant, besides slightly decreasing the model's predictive capacity (C statistic = 0.84; 95% CI 0.80-0.88).
Discriminatory capacity and adjustment of models for predicting death
With the exception of gender, the odds ratios for the other variables were greater than 1.5. The application of the Charlson index to the primary diagnosis yielded an odds ratio of 2.41 for cases with score greater than or equal to 1, as compared to score equal to 0. This index also displayed an upward gradient when applied to comorbidities (Table , baseline model). Age greater than 79 years (OR: 8.18) and unplanned admissions had the highest odds ratios in the baseline model (Table ). In the baseline and final models, score 1 in the Charlson index applied to comorbidities was not statistically significant (Table ). In the final model, risk of death adjusted by case severity was high in patients with non-preventable adverse events (OR 6.23), compared to patients without any adverse event. However, patients with an adverse event classified as preventable showed an even higher odds ratio (8.23) (Table ). Regarding patient risk variables in the final model, after the occurrence of adverse events was included, the odds ratio for elderly patients (> 79 years) presented the biggest decrease. For the other variables the odds ratio remained quite similar, being slightly lower for patients between 50 and 59 years old (Table ).
Logistic regression for prediction of hospital death: baseline model and final model