Feasibility and safety of same-day home discharge after radiofrequency catheter ablation

Interventional cardiology in a day-case setting might reduce logistic constraints on hospital resources. However, in contrast with coronary angioplasty, few data support the feasibility and safety of radiofrequency catheter ablation (RCA). The aim of this prospective, multicenter cohort study was to evaluate the feasibility and safety of RCA in 1,342 patients (814 men; mean age 57 +/- 17 years) considered eligible for ambulatory RCA, according to specific set of criteria, for common atrial flutter (n = 632), atrioventricular nodal reentrant tachycardia (n = 436), accessory pathways (n = 202), and atrial tachycardia (n = 72). Patients suitable for early discharge (4 to 6 hours after uncomplicated RCA) were scheduled for 1-month follow-up. Predictive factors for delayed complications were studied by multivariate analysis. Of the 1,342 enrolled patients, 1,270 (94.6%) were discharged the same day and followed for 1 month; no deaths occurred, and the readmission rate was 0.79% (95% confidence interval 0.30% to 1.27%). Six patients had significant puncture complications, 2 presented with symptomatic delayed pulmonary embolism, and 2 had new onset of poorly tolerated atrial flutter. None of these complications was life threatening. Multivariate analysis did not identify any significant independent predictors for delayed complications. In conclusion, these data suggest that same-day discharge after uncomplicated RCA for routine supraventricular arrhythmias is safe and may be applicable in clinical practice. This approach is known to be associated with significant patient satisfaction and cost savings and can be considered a first-line option in most patients who undergo routine ablation procedures.

Potentially avoidable 30-day hospital readmissions in medical patients: derivation and validation of a prediction model

IMPORTANCE Because effective interventions to reduce hospital readmissions are often expensive to implement, a score to predict potentially avoidable readmissions may help target the patients most likely to benefit. OBJECTIVE To derive and internally validate a prediction model for potentially avoidable 30-day hospital readmissions in medical patients using administrative and clinical data readily available prior to discharge. DESIGN Retrospective cohort study. SETTING Academic medical center in Boston, Massachusetts. PARTICIPANTS All patient discharges from any medical services between July 1, 2009, and June 30, 2010. MAIN OUTCOME MEASURES Potentially avoidable 30-day readmissions to 3 hospitals of the Partners HealthCare network were identified using a validated computerized algorithm based on administrative data (SQLape). A simple score was developed using multivariable logistic regression, with two-thirds of the sample randomly selected as the derivation cohort and one-third as the validation cohort. RESULTS Among 10 731 eligible discharges, 2398 discharges (22.3%) were followed by a 30-day readmission, of which 879 (8.5% of all discharges) were identified as potentially avoidable. The prediction score identified 7 independent factors, referred to as the HOSPITAL score: h emoglobin at discharge, discharge from an o ncology service, s odium level at discharge, p rocedure during the index admission, i ndex t ype of admission, number of a dmissions during the last 12 months, and l ength of stay. In the validation set, 26.7% of the patients were classified as high risk, with an estimated potentially avoidable readmission risk of 18.0% (observed, 18.2%). The HOSPITAL score had fair discriminatory power (C statistic, 0.71) and had good calibration. CONCLUSIONS AND RELEVANCE This simple prediction model identifies before discharge the risk of potentially avoidable 30-day readmission in medical patients. This score has potential to easily identify patients who may need more intensive transitional care interventions.

Depressive Symptoms at Discharge from Rehabilitation Predict Future Cardiovascular-Related Hospitalizations

Objectives: Depression is associated with poor prognosis in patients with cardiovascular disease (CVD). We hypothesized that depressive symptoms at discharge from a cardiac rehabilitation program are associated with an increased risk of future CVD-related hospitalizations. Methods: We examined 486 CVD patients (mean age = 59.8 ± 11.2) who enrolled in a comprehensive 3-month rehabilitation program and completed the depression subscale of the Hospital Anxiety and Depression Scale (HADS-D). At follow-up we evaluated the predictive value of depressive symptoms for CVD-related hospitalizations, controlling for sociodemographic factors, cardiovascular risk factors, and disease severity. Results: During a mean follow-up of 41.5 ± 15.6 months, 63 patients experienced a CVD-related hospitalization. The percentage of depressive patients (HADS-D ≥ 8) decreased from 16.9% at rehabilitation entry to 10.7% at discharge. Depressive symptoms at discharge from rehabilitation were a significant predictor of outcome (HR 1.32, 95% CI 1.09–1.60; p =0.004). Patients with clinically relevant depressive symptoms at discharge had a 2.5-fold increased relative risk of poor cardiac prognosis compared to patients without clinically relevant depressive symptoms independently of other prognostic variables. Conclusion: In patients with CVD, depressive symptoms at discharge from rehabilitation indicated a poor cardiac prognosis.