Derivation and validation of pragmatic clinical models to predict hospital length of stay after cardiac surgery in Ontario, Canada: a population-based cohort study.

BACKGROUND: Cardiac surgery is resource intensive and often requires multidisciplinary involvement to facilitate discharge. To facilitate evidence-based resource planning, we derived and validated clinical models to predict postoperative hospital length of stay (LOS). METHODS: We used linked, population-level databases with information on all Ontario residents and included patients aged 18 years or older who underwent coronary artery bypass grafting, valvular or thoracic aorta surgeries between October 2008 and September 2019. The primary outcome was hospital LOS. The models were derived by using patients who had surgery before Sept. 30, 2016, and validated after that date. To address the rightward skew in LOS data and to identify top-tier resource users, we used logistic regression to derive a model to predict the likelihood of LOS being more than the 98th percentile (> 30 d), and γ regression in the remainder to predict continuous LOS in days. We used backward stepwise variable selection for both models. RESULTS: Among 105 193 patients, 2422 (2.3%) had an LOS of more than 30 days. Factors predicting prolonged LOS included age, female sex, procedure type and urgency, comorbidities including frailty, high-risk acute coronary syndrome, heart failure, reduced left ventricular ejection fraction and psychiatric and pulmonary circulatory disease. The C statistic was 0.92 for the prolonged LOS model and the mean absolute error was 2.4 days for the continuous LOS model. INTERPRETATION: We derived and validated clinical models to identify top-tier resource users and predict continuous LOS with excellent accuracy. Our models could be used to benchmark clinical performance based on expected LOS, rationally allocate resources and support patient-centred operative decision-making.

Association of frailty with days alive at home after cardiac surgery: a population-based cohort study.

BACKGROUND: Frailty is a geriatric syndrome that leaves people vulnerable to adverse outcomes. In cardiac surgery, minimal data describe associations between frailty and patient-centred outcomes. Our objective was to estimate the association between frailty and days alive at home after cardiac surgery. METHODS: We conducted a population-based cohort study using linked health administrative data in the Canadian province of Ontario. All individuals >65 yr at the time of cardiac surgery were assigned a frailty score using a validated frailty index. Days alive and at home in the 30 and 365 days after surgery were calculated. The unadjusted and adjusted associations between frailty and days alive at home were calculated. RESULTS: We identified 61 389 patients from 2009 to 2015. Frailty was associated with reduced days at home within 30 days (adjusted ratio of means for every 10% increase in frailty=0.79; 95% confidence interval [CI], 0.78-0.81; P<0.0001) and 365 days (adjusted ratio of means for every 10% increase in frailty=0.92; 95% CI, 0.91-0.93; P<0.0001) of surgery. Results were consistent in sensitivity analyses (5.0 fewer days alive at home [95% CI, 4.8-5.2] within 30 days and 9.0 fewer days alive at home [95% CI, 8.7-9.2] within 365 days after surgery). CONCLUSION: Frailty is associated with a reduction in days alive at home after major cardiac surgery. This information should be considered in prognostic discussions before surgery and in care planning for vulnerable older patient groups. Days alive at home may be a useful outcome for routine measurement in quality, reporting, and studies using routinely collected data.