Evaluating unplanned readmission and prolonged length of stay following minimally invasive surgery for endometrial cancer

All Wales Ovarian Cancer Prehabilitation Project (AWOCPP)

Over 50% of patients with ovarian cancer are diagnosed with advanced disease (stage 3+) in Wales when treatment typically involves chemotherapy, combined with cytoreductive surgery. Postoperative morbidity is common resulting in prolonged hospital stays and delays in returning to chemotherapy. Patients with advanced ovarian cancer commonly have modifiable risk factors that can be targeted for improvement with personalised prehabilitation. Multimodal personalised prehabilitation has been shown to have a positive impact on perioperative outcomes and length of stay (LOS).Quality improvement methods were used to implement a multimodal prehabilitation programme for all patients with advanced ovarian cancer planned for surgery in Wales. A unique approach to determining an individual patient's modifiable risk factors was devised that enabled a personalised prehabilitation programme to be created including exercise, smoking cessation, medical and nutritional optimisation and emotional support. Data were collected to enable future health economic evaluation of the programme in anticipation of national role out as standard of care. To evaluate if the prehabilitation intervention was impacting the quality of care, the following outcome measures were assessed: LOS, postoperative complications and surgery to chemotherapy interval (SCI). These measures were compared with a historical Welsh data set from 2018 to 2019 when access to prehabilitation was not available.Following the implementation of prehabilitation for ovarian cancer, the median LOS reduced from 6 to 5 days (p=0.29). There was a reduction in postoperative complications: from 16.9% to 12.7% (Grade 2), 4.4% to 1.8% (Grade 3), 0.6% to 0% (Grade 4+5). The median SCI following prehabilitation was 43.5 days (range 27-91) compared with 40 days (range 15-182 (p=0.65)).Prehabilitation has had a positive impact on the treatment pathways for advanced ovarian cancer in Wales. Means of improving patient engagement and establishing cost-effective delivery need to be developed to make this intervention standard of care.

Development and comparison of machine-learning models for predicting prolonged postoperative length of stay in lung cancer patients following video-assisted thoracoscopic surgery

Objective

This study aimed to develop models for predicting prolonged postoperative length of stay (PPOLOS) in lung cancer patients undergoing video-assisted thoracoscopic surgery (VATS) by utilizing machine-learning techniques. These models aim to offer valuable insights for clinical decision-making.

Methods

This retrospective cohort study analyzed a dataset of lung cancer patients who underwent VATS, identifying 25 numerical features and 45 textual features. Three classification machine-learning models were developed: XGBoost, random forest, and neural network. The performance of these models was evaluated based on accuracy (ACC) and area under the receiver operating characteristic curve, whereas the importance of variables was assessed using the feature importance parameter from the random forest model.

Results

Of the 6767 lung cancer patients, 1481 patients (21.9%) experienced a postoperative length of stay of > 4 days. The majority were male (4111, 60.8%), married (6246, 92.3%), and diagnosed with adenocarcinoma (4145, 61.3%). The Random Forest classifier exhibited superior prediction performance with an area under the curve (AUC) of 0.792 and ACC of 0.804. The calibration plot revealed that all three classifiers were in close alignment with the ideal calibration line, indicating high calibration reliability. The five most critical features identified were the following: surgical duration (0.116), age (0.066), creatinine (0.062), hemoglobin (0.058), and total protein (0.054).

Conclusions

This study developed and evaluated three machine-learning models for predicting PPOLOS in lung cancer patients undergoing VATS. The findings revealed that the Random Forest model is most accurately predicting the PPOLOS. Findings of this study enable the identification of crucial determinants and the formulation of targeted interventions to shorten the length of stay among lung cancer patients after VATS, which contribute to optimize the allocation of healthcare resources.

Predicting unplanned readmission due to cardiovascular disease in hospitalized patients with cancer: a machine learning approach

Cardiovascular disease (CVD) in cancer patients can affect the risk of unplanned readmissions, which have been reported to be costly and associated with worse mortality and prognosis. We aimed to demonstrate the feasibility of using machine learning techniques in predicting the risk of unplanned 180-day readmission attributable to CVD among hospitalized cancer patients using the 2017-2018 Nationwide Readmissions Database. We included hospitalized cancer patients, and the outcome was unplanned hospital readmission due to any CVD within 180 days after discharge. CVD included atrial fibrillation, coronary artery disease, heart failure, stroke, peripheral artery disease, cardiomegaly, and cardiomyopathy. Decision tree (DT), random forest, extreme gradient boost (XGBoost), and AdaBoost were implemented. Accuracy, precision, recall, F2 score, and receiver operating characteristic curve (AUC) were used to assess the model's performance. Among 358,629 hospitalized patients with cancer, 5.86% (n = 21,021) experienced unplanned readmission due to any CVD. The three ensemble algorithms outperformed the DT, with the XGBoost displaying the best performance. We found length of stay, age, and cancer surgery were important predictors of CVD-related unplanned hospitalization in cancer patients. Machine learning models can predict the risk of unplanned readmission due to CVD among hospitalized cancer patients.

Calculating surgical readmission rates in gynecologic oncology: The impact of patient factors

OBJECTIVE

To determine the 30-day surgical readmission rate after major gynecologic oncology surgeries at a high-volume academic institution and correlated risk factors.

METHODS

Retrospective cohort study was conducted of surgical admissions from January 2016 - December 2019 at a single institution. Data were extracted from patient charts, including reason for readmission and length of stay. A readmission rate was calculated. Nested case control design was used to identify correlations between readmission and patient specific risk-factors. Multivariable logistic regression models were used to determine risk factors with readmission.

RESULTS

A total of 2152 patients were included. The readmission rate was 3.5%, most commonly due to GI disturbance and surgical site infection. Average readmission length was 5 days. Prior to adjusting for covariates, insurance status, primary diagnosis, index admission length, and disposition at discharge differed between patients who were and were not readmitted. After adjusting for co-variates, younger patients, index admission >2 days, and higher Charlson co-morbidity index were associated with readmission.

CONCLUSIONS

Our surgical readmission rate was lower than previously reported rates in gynecologic oncology patients. Patient factors associated with readmission included younger age, longer index hospital admission, and higher medical co-morbidity index scores. Provider factors and institutional practice patterns could contribute to the decreased readmission rate. These findings underscore the importance of standardizing how we calculate readmission rate and interpret these data. Varying readmission rates and institutional practice patterns deserve closer scrutiny to inform best practice and future policies.

Clavien-Dindo classification and risk prediction model of complications after robot-assisted radical hysterectomy for cervical cancer

Although significant progress has been made with surgical methods, the incidence of complications after minimally invasive surgery in patients with cervical cancer remains high. Established as a standardized system, Clavien-Dindo classification (CDC) has been applied in a variety of surgical fields. This study is designed to evaluate the complications after robot-assisted radical hysterectomy (RRH) for cervical cancer using CDC and further establish a prediction model. This is a study on the development of prediction model based on retrospective data. Patients with cervical cancer who received RRH treatment in our hospital from January 2016 to April 2019 were invited to participate in the study. The demographic data, laboratory and imaging examination results and postoperative complications were collected, and the logistic regression model was applied to analyze the risk factors possibly related to complications to establish a prediction model. 753 patients received RRH. The overall incidence of complications was 32.7%, most of which were grade I and grade II (accounting for 30.6%). The results of multivariate analysis showed that the preoperative neoadjuvant chemotherapy (OR = 1.693, 95%CI: 1.210-2.370, P = 0.002), preoperative ALT (OR = 1.028, 95%CI: 1.017-1.039, P < 0.001), preoperative urea nitrogen (OR = 0.868, 95%CI: 0.773-0.974, P = 0.016), preoperative total bilirubin (OR = 0.958, 95%CI: 0.925-0.993, P = 0.0.018), and preoperative albumin (OR = 0.937, 95%CI: 0.898-0.979, P = 0.003) were related to the occurrence of postoperative complications. The area under the curve (AUC) of receiver-operating characteristic (ROC) in the prediction model of RRH postoperative complications established based on these five factors was 0.827 with 95% CI of 0.794-0.860. In patients undergoing robot-assisted radical hysterectomy for cervical cancer, preoperative ALT level, urea nitrogen level, total bilirubin level, albumin level, and neoadjuvant chemotherapy were significantly related to the occurrence of postoperative complications. The regression prediction model established on this basis showed good prediction performance with certain clinical promotion and reference value.

Feasibility of combining pelvic reconstruction with gynecologic oncology-related surgery

INTRODUCTION AND HYPOTHESIS

At our institution, every patient seen by the gynecologic oncology service is screened for pelvic floor dysfunction. This study was aimed at determining if a combined surgical approach by gynecologic oncology and urogynecology services at our institution was feasible and safe for this patient population.

METHODS

We performed a retrospective review of patients undergoing combined surgery by gynecologic oncology and urogynecology services at our institution from 2013 to 2021. Perioperative variables, postoperative adverse events, and long-term outcomes were assessed, and descriptive statistics were performed.

RESULTS

From 20 December 2013 to 29 January 2021, a total of 102 patients underwent concurrent surgical repair of pelvic organ prolapse and/or stress urinary incontinence. Seventy-three patients (71.6%) had normal/benign pathologic conditions, and 29 (28.4%) had premalignant/malignant pathologic conditions. Ten patients (9.8%) had a postoperative complication, including reoperation for exposed midurethral sling (4.9%), urinary retention requiring midurethral sling release (2.9%), reoperation for hemoperitoneum (1.0%), and anemia requiring blood transfusion (1.0%). Nine complications occurred in patients with benign/normal pathologic conditions (12.3%), and one complication occurred in patients with pre-malignant/malignant pathologic conditions (3.4%).

CONCLUSIONS

In our single-institution experience, concurrent gynecologic oncology and pelvic floor reconstructive surgery were safe and feasible in combination with no reported major morbidity events.

Prehabilitation to Improve Outcomes of Patients with Gynaecological Cancer: A New Window of Opportunity?

The literature evaluating the effect of prehabilitation programmes on postoperative outcomes and quality of life of patients with gynaecological cancer undergoing surgery was reviewed. Databases including Pubmed, Medline, EMBASE (Ovid) and PsycINFO were systematically searched to identify studies evaluating the effect of prehabilitation programmes on patients with gynaecological cancer. Both unimodal and multimodal prehabilitation programmes were included encompassing physical exercise and nutritional and psychological support. Primary outcomes were surgical complications and quality of life. Secondary outcomes were anthropometric changes and adherence to the prehabilitation programme. Seven studies fulfilled the inclusion criteria, comprising 580 patients. Included studies were nonrandomised prospective studies (n = 4), retrospective studies (n = 2) and one case report. Unimodal programmes and multimodal programmes were included. In patients with ovarian cancer, multimodal prehabilitation resulted in significantly reduced hospital stay and time to chemotherapy. In patients with endometrial and cervical cancer, prehabilitation was associated with significant weight loss, but had no significant effects on surgical complications or mortality. No adverse events of the programmes were reported. Evidence on the effect of prehabilitation for patients with gynaecological cancer is limited. Future studies are needed to determine the effects on postoperative complications and quality of life.

Predictors of prolonged admission after outpatient female pelvic reconstructive surgery

OBJECTIVES

This study aimed to determine factors associated with prolonged hospital admission following outpatient female pelvic reconstructive surgery (FPRS) and associated adverse clinical outcomes.

METHODS

Using the National Surgical Quality Improvement Program database, we identified outpatient FPRS performed 2011-2016. Isolated hysterectomy without concurrent prolapse repair was excluded. Surgeries were classified as major or minor for analysis. The primary outcome was prolonged length of stay (LOS), defined as admission of ≥2 days. Secondary outcomes included complications, readmission and reoperation associated with prolonged LOS. We abstracted data on covariates, and following univariable analysis, performed backward stepwise regression analysis.

RESULTS

A total of 29645 women were included: 12311 (41.5%) major and 17334 (58.5%) minor procedures. A total of 6.9% (2033) had a prolonged LOS. On full cohort multivariable regression analysis, patient characteristics associated with prolonged LOS were older age (odds ratio [OR]: 1.1 per 10 years, confidence interval [CI]: 1.06-1.1, p < 0.001), frailty (OR: 1.8, 95% CI: 1.3-2.6, p = 0.001), and Caucasian race (OR: 1.2, CI: 1.02-1.3, p = 0.024). Associated surgical factors included having a major surgical procedure (OR: 1.3, CI: 1.2-1.4, p < 0.001), use of general anesthesia (OR: 2.0, CI: 1.5-2.6, p < 0.001) and longer operative time (OR: 2.0, CI: 1.8-2.2, p < 0.001). The occurrence of any complication (10.3% vs. 4.7%, p < 0.001), hospital readmission (4.3% vs. 1.7%, p < 0.001), and reoperation (2.7% vs. 1.0%, p < 0.001) were more likely with prolonged LOS.

CONCLUSIONS

After outpatient FPRS, 6.9% of patients experience an admission of ≥2 days. Prolonged LOS is more common in patients who are older, frail and Caucasian, and in those who have major surgery with long operative time and general anesthesia.

Permanent stoma: a quality outcome in treatment of rectal cancer and its impact on length of stay

BACKGROUND

This study aimed to identify socioeconomic predictors of permanent stoma in rectal cancer treatment and examine its association with length of stay at the treatment facility.

METHODS

Rectal cancer patients who underwent elective surgery between January 2015 and December 2018 were identified from the Agency for Health Care Administration Florida Hospital Inpatient Discharge Dataset. Multivariate regression models were utilized to identify demographic and socioeconomic factors associated with receiving a permanent stoma as well as the associated length of stay of these patients.

RESULTS

Of 2630 rectal cancer patients who underwent surgery for rectal cancer, 21% had a permanent stoma. The odds of receiving permanent stoma increased with higher Elixhauser score, metastatic disease, advanced age, having open surgery, residence in Southwest Florida, and having Medicaid insurance or no insurance/self-payers (p < 0.05). Patients with a permanent stoma had a significantly extended stay after surgery (p < 0.001).

CONCLUSIONS

Patients with a permanent stoma following cancer resection were more likely to have open surgery, had more comorbidities, and had a longer length of stay. Having permanent stoma was higher in patients living in South West Florida, patients with Medicaid insurance, and in the uninsured. Additionally, the payer type significantly affected the length of stay.