Causes and characteristics associated with early and late readmission after open-heart valve surgery

Predicting the risk of hospital readmissions using a machine learning approach: a case study on patients undergoing skin procedures

Introduction

Even with modern advancements in medical care, one of the persistent challenges hospitals face is the frequent readmission of patients. These recurrent admissions not only escalate healthcare expenses but also amplify mental and emotional strain on patients.

Methods

This research delved into two primary areas: unraveling the pivotal factors causing the readmissions, specifically targeting patients who underwent dermatological treatments, and determining the optimal machine learning algorithms that can foresee potential readmissions with higher accuracy.

Results

Among the multitude of algorithms tested, including logistic regression (LR), support vector machine (SVM), random forest (RF), Naïve Bayesian (NB), artificial neural network (ANN), xgboost (XG), and k-nearest neighbor (KNN), it was noted that two models-XG and RF-stood out in their prediction prowess. A closer inspection of the data brought to light certain patterns. For instance, male patients and those between the ages of 21 and 40 had a propensity to be readmitted more frequently. Moreover, the months of March and April witnessed a spike in these readmissions, with ~6% of the patients returning within just a month after their first admission.

Discussion

Upon further analysis, specific determinants such as the patient's age and the specific hospital where they were treated emerged as key indicators influencing the likelihood of their readmission.

The effect of early follow-up after open cardiac surgery in a student clinic

Objectives. Readmission rates following open cardiac surgery are high, affecting patients and the cost of care. This study aimed to investigate the effect of early additional follow-up after open cardiac surgery when 5th-year medical students conducted follow-ups under the supervision of physicians. The primary endpoint was unplanned cardiac-related readmissions within one year. The secondary outcomes were the detection of impending complications and health-related quality of life (HRQOL). Methods. Patients undergoing open cardiac surgery were prospectively included. For intervention, additional follow-up visits, including point-of-care ultrasound, were conducted by supervised 5th-year medical students on postoperative days 3, 14 and 25. Unplanned cardiac-related readmissions, including emergency department visits, were registered within the first year of surgery. Danish National Health Survey 2010 questionnaire was used for HRQOL. In standard follow-up, all patients were seen 4-6 weeks postoperative. Results. For data analysis, 100 of 124 patients in the intervention group and 319 of 335 patients in the control group were included. The 1-year unplanned readmission rates did not differ; 32% and 30% in the intervention and control groups, respectively (p = 0.71). After discharge, 1% of patients underwent pericardiocentesis. The additional follow-up initiated scheduled drainage, contrary to more unscheduled/acute drainages in the control group. Pleurocentesis was more common in the intervention group (17% (n = 17) vs 8% (n = 25), p = 0.01) and performed earlier. There was no difference between groups on HRQOL. Conclusion. Supervised student-led follow-up of newly cardiac-operated patients did not alter readmission rates or HRQOL but may detect complications earlier and initiate non-emergent treatment of complications.

A Retrospective Review of 30-Day Hospital Readmission Risk After Open Heart Surgery in Patients With Atrial Fibrillation

Introduction Readmission rates after open heart surgery (OHS) remain an important clinical issue. The causes are varied, with identifying risk factors potentially providing valuable information to reduce healthcare costs and the rate of post-operative complications. This study aimed to characterize the reasons for 30-day hospital readmission rates of patients after open heart surgery. Methods All patients over 18 years of age undergoing OHS at a community hospital from January 2020 through December 2020 were identified. Demographic data, medical history, operative reports, post-operative complications, and telehealth interventions were obtained through chart review. Descriptive statistics and readmission rates were calculated, along with a logistic regression model, to understand the effects of medical history on readmission. Results A total of 357 OHS patients met the inclusion criteria for the study. Within the population, 8.68% of patients experienced readmission, 10.08% had an emergency department (ED) visit, and 95.80% had an outpatient office visit. A history of atrial fibrillation (AFib) significantly predicted 30-day hospital readmissions but not ED or outpatient office visits. Telehealth education was delivered to 66.11% of patients. Conclusion The study investigated factors associated with 30-day readmission following OHS. AFib patients were more likely to be readmitted than patients without atrial fibrillation. No other predictors of readmission, ED visits, or outpatient office visits were found. Patients reporting symptoms of tachycardia, pain, dyspnea, or "other" could be at increased risk for readmission.

Occurrence and predictors of pericardial effusion requiring invasive treatment following heart valve surgery

OBJECTIVES

To describe the occurrence of significant pericardial effusion, and to investigate characteristics associated with pericardial effusion within three months following heart valve surgery.

METHODS

A retrospective, observational cohort study including adult patients undergoing heart valve surgery at Odense University Hospital from August 2013 to November 2017. Data were gathered from The Western Denmark Heart Registry and electronic patient records.Cox proportional hazard models were used to investigate the associations between characteristics associated with significant pericardial effusion during index admission and within 3 months. Results are presented as HR with 95% CI.

RESULTS

In total, 1460 patients were included (70% men, median age 71 years (IQR 63-76)) and of those, n=230 patients (16%) developed significant pericardial effusion.EuroScore II was significantly associated with an increased risk of pericardial effusion during index admission and associated with a lower risk following discharge (index admission HR 1.05, 95% CI 1.02 to 1.08, after discharge HR 0.80, 95% CI 0.69 to 0.92). Increasing age (HR 0.97, 95% CI 0.95 to 0.98 per year) and concomitant coronary artery bypass grafting versus isolated valve surgery (HR 0.58, 95% CI 0.35 to 0.97) were significantly associated with a reduced risk of pericardial effusions in both periods. Being a man (HR 2.30, 95% CI 1.32 to 4.01) and aortic valve disease versus mitral valve disease (HR 2.16, 95% CI 1.20 to 3.90) were significantly associated with an increased risk after discharge.

CONCLUSION

Significant pericardial effusions requiring drainage were present in 16% of cases following heart valve surgery, and different clinical characteristics were associated with the development of effusion.