Preoperative white blood cell count and risk of 30-day readmission after cardiac surgery

Machine Learning Model for Anesthetic Risk Stratification for Gynecologic and Obstetric Patients: Cross-Sectional Study Outlining a Novel Approach for Early Detection

BACKGROUND

Preoperative evaluation is important, and this study explored the application of machine learning methods for anesthetic risk classification and the evaluation of the contributions of various factors. To minimize the effects of confounding variables during model training, we used a homogenous group with similar physiological states and ages undergoing similar pelvic organ-related procedures not involving malignancies.

OBJECTIVE

Data on women of reproductive age (age 20-50 years) who underwent gestational or gynecological surgery between January 1, 2017, and December 31, 2021, were obtained from the National Taiwan University Hospital Integrated Medical Database.

METHODS

We first performed an exploratory analysis and selected key features. We then performed data preprocessing to acquire relevant features related to preoperative examination. To further enhance predictive performance, we used the log-likelihood ratio algorithm to generate comorbidity patterns. Finally, we input the processed features into the light gradient boosting machine (LightGBM) model for training and subsequent prediction.

RESULTS

A total of 10,892 patients were included. Within this data set, 9893 patients were classified as having low anesthetic risk (American Society of Anesthesiologists physical status score of 1-2), and 999 patients were classified as having high anesthetic risk (American Society of Anesthesiologists physical status score of >2). The area under the receiver operating characteristic curve of the proposed model was 0.6831.

CONCLUSIONS

By combining comorbidity information and clinical laboratory data, our methodology based on the LightGBM model provides more accurate predictions for anesthetic risk classification.

TRIAL REGISTRATION

Research Ethics Committee of the National Taiwan University Hospital 202204010RINB; https://www.ntuh.gov.tw/RECO/Index.action.

Abnormal preoperative leukocyte counts and postoperative complications following total shoulder arthroplasty

Background

Total shoulder arthroplasty (TSA) has become the mainstay of treatment for degenerative glenohumeral arthritis, proximal humerus fracture, and rotator cuff arthropathy. The expanding indications for reverse TSA have increased the overall demand for TSA. This necessitates higher quality preoperative testing and risk stratification. White blood cell counts can be obtained from routine preoperative complete blood count testing. The association between abnormal preoperative white blood cell counts and postoperative complications has not been extensively studied. The purpose of this study was to investigate the association between abnormal preoperative leukocyte counts and 30-day postoperative complications following TSA.

Methods

The American College of Surgeons National Surgical Quality Improvement Program database was queried for all patients who underwent TSA between 2015-2020. Patient demographics, comorbidities, surgical characteristics, and 30-day postoperative complication data were collected. Multivariate logistic regression was used to identify postoperative complications associated with preoperative leukopenia and leukocytosis.

Results

In this study, 23,341 patients were included: 20,791 (89.1%) were in the normal cohort, 1307 (5.6%) were in the leukopenia cohort, and 1243 (5.3%) were in the leukocytosis cohort. Preoperative leukopenia was significantly associated with higher rates of bleeding transfusions (P = .011), deep vein thrombosis (P = .037), and non-home discharge (P = .041). After controlling for significant patient variables, preoperative leukopenia was independently associated with higher rates of bleeding transfusions (odds ratios [OR] 1.55, 95% confidence intervals [CI] 1.08-2.23; P = .017) and deep vein thrombosis (OR 2.26, 95% CI 1.07-4.78; P = .033). Preoperative leukocytosis was significantly associated with higher rates of pneumonia (P < .001), pulmonary embolism (P = .004), bleeding transfusions (P < .001), sepsis (P = .007), septic shock (P < .001), readmission (P < .001), and non-home discharge (P < .001). After controlling for significant patient variables, preoperative leukocytosis was independently associated with higher rates of pneumonia (OR 2.20, 95% CI 1.30-3.75; P = .004), pulmonary embolism (OR 2.43, 95% CI 1.17-5.04; P = .017), bleeding transfusions (OR 2.00, 95% CI 1.46-2.72; P < .001), sepsis (OR 2.95, 95% CI 1.20-7.25; P = .018), septic shock (OR 4.91, 95% CI 1.38-17.53; P = .014), readmission (OR 1.36, 95% CI 1.03-1.79; P = .030), and non-home discharge (OR 1.61, 95% CI 1.35-1.92; P < .001).

Conclusion

Preoperative leukopenia is independently associated with higher rates of deep vein thrombosis within 30 days following TSA. Preoperative leukocytosis is independently associated with higher rates of pneumonia, pulmonary embolism, bleeding transfusion, sepsis, septic shock, readmission, and non-home discharge within 30 days following TSA. Understanding the predictive value of abnormal preoperative lab values will aid in perioperative risk stratification and minimize postoperative complications.

Effect of an mHealth self-help intervention on readmission after adult cardiac surgery: Protocol for a pilot randomized controlled trial

Aim

To describe a protocol for the pilot phase of a trial designed to test the effect of an mHealth intervention on representation and readmission after adult cardiac surgery.

Design

A multisite, parallel group, pilot randomized controlled trial (ethics approval: HREC2020.331‐RMH69278).

Methods

Adult patients scheduled to undergo elective cardiac surgery (coronary artery bypass grafting, valve surgery, or a combination of bypass grafting and valve surgery or aortic surgery) will be recruited from three metropolitan tertiary teaching hospitals. Patients allocated to the control group with receive usual care that is comprised of in‐patient discharge education and local paper‐based written discharge materials. Patients in the intervention group will be provided access to tailored ‘GoShare’ mHealth bundles preoperatively, in a week of hospital discharge and 30 days after surgery. The mHealth bundles are comprised of patient narrative videos, animations and links to reputable resources. Bundles can be accessed via a smartphone, tablet or computer. Bundles are evidence‐based and designed to improve patient self‐efficacy and self‐management behaviours, and to empower people to have a more active role in their healthcare. Computer‐generated permuted block randomization with an allocation ratio of 1:1 will be generated for each site. At the time of consent, and 30, 60 and 90 days after surgery quality of life and level of patient activation will be measured. In addition, rates of representation and readmission to hospital will be tracked and verified via data linkage 1 year after the date of surgery.

Discussion

Interventions using mHealth technologies have proven effectiveness for a range of cardiovascular conditions with limited testing in cardiac surgical populations.

Impact

This study provides an opportunity to improve patient outcome and experience for adults undergoing cardiac surgery by empowering patients as end‐users with strategies for self‐help.

Trial registration

Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12621000082808.

Postoperative Neutrophil-to-Lymphocyte Ratio Is Associated with Mortality in Adult Patients After Cardiopulmonary Bypass Surgery: A Cohort Study

Background

Cardiopulmonary bypass (CPB) contributes to the development of systemic inflammatory response after cardiothoracic surgery. As a measure of inflammation and immune reaction, the neutrophil-to-lymphocyte ratio (NLR) has been linked to poor outcomes in a variety of diseases. However, it remains to be seen whether postoperative NLR is associated with CPB patient mortality. The purpose of this research was to explore the prognostic role of the postoperative NLR in adult patients undergoing cardiothoracic surgery with cardiopulmonary bypass.

Material/Methods

This study incorporates data from the MIMIC III database, which includes more than 50 000 critically ill patients. The variable of interest was postoperative NLR. The primary outcome was 30-day mortality and the secondary outcomes were 90-day mortality, length of intensive care unit stay, and length of hospital stay.

Results

We enrolled 575 CPB patients. The ROC curve for the postoperative NLR to estimate mortality was 0.741 (95% confidence interval [CI]: 0.636–0.847, P<0.001), and the critical value was 7.48. There was a significant difference between different postoperative NLR levels in the Kaplan-Meier curve (P=0.045). Furthermore, elevated postoperative NLR was associated with increased hospital mortality (hazard ratio [HR]: 1.1, 95% CI: 1.0–1.1, P=0.021). However, there was no important relationship in these patients between the postoperative NLR levels and 90-day mortality (HR: 1.1, 95% CI: 1.0–1.5, P=0.465).

Conclusions

Our findings suggest that higher postoperative NLR is associated with greater hospital mortality in adult patients undergoing cardiopulmonary bypass surgery.

The Association between Cytokines and 365-Day Readmission or Mortality in Adult Cardiac Surgery

Cardiac surgery results in a multifactorial systemic inflammatory response with inflammatory cytokines, such as interleukin-10 and 6 (IL-10 and IL-6), shown to have potential in the prediction of adverse outcomes including readmission or mortality. This study sought to measure the association between IL-6 and IL-10 levels and 1-year hospital readmission or mortality following cardiac surgery. Plasma biomarkers IL-6 and IL-10 were measured in 1,047 patients discharged alive after isolated coronary artery bypass graft surgery from eight medical centers participating in the Northern New England Cardiovascular Disease Study Group between 2004 and 2007. Readmission status and mortality were ascertained using Medicare, state all-payer claims, and the National Death Index. We evaluated the association between preoperative and postoperative cytokines and 1-year readmission or mortality using Kaplan-Meier estimates and Cox's proportional hazards modeling, adjusting for covariates used in the Society of Thoracic Surgeons 30-day readmission model. The median follow-up time was 1 year. After adjustment, patients in the highest tertile of postoperative IL-6 values had a significantly increased risk of readmission or death within 1 year (HR: 1.38; 95% CI: 1.03-1.85), and an increased risk of death within 1 year of discharge (HR: 4.88; 95% CI: 1.26-18.85) compared with patients in the lowest tertile. However, postoperative IL-10 levels, although increasing through tertiles, were not found to be significantly associated independently with 1-year readmission or mortality (HR: 1.25; 95% CI: .93-1.69). Pro-inflammatory cytokine IL-6 and anti-inflammatory cytokine IL-10 may be postoperative markers of cardiac injury, and IL-6, specifically, shows promise in predicting readmission and mortality following cardiac surgery.

Risk factors for and timing of adverse events after revision total shoulder arthroplasty

BACKGROUND

Despite increasing rates of revision total shoulder arthroplasty (RTSA), there is a paucity of literature on optimizing perioperative outcomes. The purposes of this study were to identify risk factors for unplanned readmission and perioperative complications following RTSA, risk-stratify patients based on these risk factors, and assess timing of complications.

METHODS

Bivariate and multivariate analyses of risk factors were assessed on RTSA patients from the ACS-NSQIP database from 2011 to 2015. Patients were risk-stratified and timing of severe adverse events and cause of readmission were evaluated.

RESULTS

Of 809 RTSA patients, 61 suffered a perioperative complication or readmission within 30 days of discharge. Multivariate analysis identified operative time, BMI > 40, infection etiology, high white blood cell count, and low hematocrit as significant independent risk factors for 30-day complications or readmission after RTSA (p ≤ 0.05). Having at least one significant risk factor was associated with 2.71 times risk of complication or readmission within 15 days compared to having no risk factors (p < 0.001). The majority of unplanned readmission, return to the operating room, open/deep wound infection, and sepsis/septic shock occurred within two weeks of RTSA.

DISCUSSION

Patients at high risk of complications and readmission after RTSA should be identified and optimized preoperatively to improve outcomes and lower costs.

Utility of Biomarkers to Improve Prediction of Readmission or Mortality After Cardiac Surgery

BACKGROUND

Hospital readmission within 30 days is associated with higher risks of complications, death, and increased costs. Accurate statistical models to stratify the risk of 30-day readmission or death after cardiac surgery could help clinical teams focus care on those patients at highest risk. We hypothesized biomarkers could improve prediction for readmission or mortality.

METHODS

Levels of ST2, galectin-3, N-terminal pro-brain natriuretic peptide, cystatin C, interleukin-6, and interleukin-10 were measured in samples from 1,046 patients discharged after isolated coronary artery bypass graft surgery from eight medical centers, with external validation in 1,194 patients from five medical centers. Thirty-day readmission or mortality were ascertained using Medicare, state all-payer claims, and the National Death Index. We tested and externally validated the clinical models and the biomarker panels using area under the receiver-operating characteristics (AUROC) statistics.

RESULTS

There were 112 patients (10.7%) who were readmitted or died within 30 days after coronary artery bypass graft surgery. The Society of Thoracic Surgeons augmented clinical model resulted in an AUROC of 0.66 (95% confidence interval: 0.61 to 0.71). The biomarker panel with The Society of Thoracic Surgeons augmented clinical model resulted in an AUROC of 0.74 (bootstrapped 95% confidence interval: 0.69 to 0.79, p < 0.0001). External validation of the model showed limited improvement with the addition of a biomarker panel, with an AUROC of 0.51 (95% confidence interval: 0.45 to 0.56).

CONCLUSIONS

Although biomarkers significantly improved prediction of 30-day readmission or mortality in our derivation cohort, the external validation of the biomarker panel was poor. Biomarkers perform poorly, much like other efforts to improve prediction of readmission, suggesting there are many other factors yet to be explored to improve prediction of readmission.

Early Rehospitalization After Prolonged Intensive Care Unit Stay Post Cardiac Surgery: Outcomes and Modifiable Risk Factors

Background

Prolonged intensive care unit length of stay (prICULOS) following cardiac surgery (CS) in older adults is increasingly common but rehospitalization characteristics and outcomes are understudied. We sought to describe the rehospitalization characteristics and subsequent non‐institutionalized survival of prICULOS (ICULOS ≥5 days) patients and identify modifiable risk factors to decrease 30‐day rehospitalization.

Methods and Results

Consecutive patients from January 1, 2000 to December 31, 2011 were analyzed utilizing linked clinical and administrative databases. Logistic regression was used to identify risk factors associated with 30‐day rehospitalization. Out of 9210 consecutive patients discharged from the hospital alive, 596 (6.5%) experienced prICULOS. Cumulative incidence of rehospitalization for the prICULOS cohort at 30 and 365 days was 17.5% and 45.6% versus 11.4% and 28.1% for non‐prICULOS (P<0.01). Over 40% of rehospitalizations for the entire cohort occurred within 30 days of discharge costing over $12 million. The most common reasons for rehospitalization were heart failure (in prICULOS) and infection (in non‐prICULOS). Rehospitalization within 30 days was associated with a 2.29‐fold risk of poor 1‐year noninstitutionalized survival for the entire cohort. Potentially modifiable factors affecting 30‐day rehospitalization included lack of physician visits within 30 days of discharge (odds ratio 2.11; P=0.01), and preoperative anxiety diagnosis (odds ratio 2.20; P=0.01).

Conclusions

PrICULOS patients have high rates of rehospitalization that is associated with an increased rate of poor noninstitutionalized survival. Addressing modifiable risk factors including early postdischarge access to physician services, as well as access to mental health services may improve patient outcomes.

Ten-year experience in subclavian revascularisation. A parallel comparative observational study

Introduction

Subclavian stenosis has a prevalence of approximately 2% in the community, and 7% within a clinical population. It is closely linked with hypertension and smoking. There is a relative paucity of published data to inform clinicians on the optimal mode of treatment for subclavian artery stenosis.

Objectives

To compare clinical outcomes of subclavian bypass surgery with that of subclavian endovascular re-vascularisation. Endpoints were survival time, re-intervention-free survival, and symptom-free survival.

Method

In all, 21 subclavian interventions were performed from 2000 to 2010. We compared angioplasty vs angioplasty with stenting vs bypass.

Results

Technical success was 100% in all groups. Symptom-free survival, at 70 months, was 60% in the angioplasty group, 100% in the angioplasty and stenting group and 75% in the bypass group. Re-intervention rate was 40% in the angioplasty group, 0% in the angioplasty and stenting group and 25% in the bypass group. Median time for re-intervention was 9.5 months in angioplasty patients and 36 months in bypass patients ( p = 0.102). Target lesion revascularisation was 20.0% for angioplasty procedures, 16.67% for angioplasty and stenting and 25% for bypass procedures.

Conclusion

Angioplasty with stenting provides improved symptom-free survival and freedom from re-intervention in patients with symptomatic subclavian artery stenosis.