The risks, reasons, and costs for 30- and 90-day readmissions after fusion surgery for adolescent idiopathic scoliosis

Intrawound Vancomycin Powder Reduces Delayed Deep Surgical Site Infections Following Posterior Spinal Fusion for Adolescent Idiopathic Scoliosis

STUDY DESIGN

Retrospective.

OBJECTIVE

Evaluate whether the use of vancomycin powder (VP) placed in the surgical site before wound closure prevents delayed deep surgical site infections (DDI).

SUMMARY OF BACKGROUND DATA

DDI after posterior spinal fusion (PSF) in adolescent idiopathic scoliosis (AIS) patients remains a significant and major complication. The use of VP to prevent acute surgical site infection has been reported, but the impact on DDI is unknown.

MATERIALS AND METHODS

AIS patients treated over the past 20 years with PSF or instrumentation from a large multicenter registry were reviewed. Patients were divided into two groups: intraoperative vancomycin powder placed in the wound (VP) or no antibiotics placed in the wound (NVP). DDI was defined as an infection that occurred >90 days after surgery and required surgical intervention in the operating room. Patients who developed a DDI had secondary verification of VP use or not. χ 2 and Kaplan-Meier (K-M) survivorship analyses were used to compare demographics and the incident rate of DDI between groups.

RESULTS

Totally, 4145 cases met the inclusion criteria for this study. A total of 43 DDI cases were identified (1.0%). The incidence of DDI for the VP group was 0.2% (4/2111), and 1.9% (39/2034) in the NVP group ( P <0.001). Given the difference in follow-up for the two groups, a cumulative survival and Kaplan-Meier analysis revealed the VP group had significantly better "survival" (no DDI) than the NVP group ( P <0.001).

CONCLUSION

DDIs are significant adverse events that can greatly complicate patient recovery after PSF for AIS, including rehospitalization. This study found that patients who received VP intraoperatively were 10 times less likely to develop a DDI than those who did not receive VP. Although other advances and changes in surgical techniques may contribute to the significant decrease in infections found in the more recent VP cohort, VP should be considered as a prophylactic measure.

LEVEL OF EVIDENCE

4.

Superior mesenteric artery syndrome following spine surgery in idiopathic adolescent scoliosis: a systematic review

Superior mesenteric artery syndrome (SMAS) is a rare and unpredictable complication after correction spine surgery for adolescent idiopathic scoliosis (AIS). The management of this condition is poorly investigated, with controversial outcomes. This investigation systematically reviewed current evidence on pathogenesis, risk factors, management, and outcomes of SMAS following correction spine surgery for AIS. The present systematic review was conducted according to the 2020 PRISMA statement. All the included investigations reported SMAS presentation following scoliosis correction surgery in AIS. 29 articles with 61 eligible patients were included in this review. The mean age of the patients was 15.8 ± 7.2 years. The mean weight was 45.3 ± 8.0 kg, the mean height 159.6 ± 13.6 cm, and the mean BMI 16.5 ± 2.9 kg/m2. The mean duration of the treatment for SMAS was 21.6 ± 10.3 days. The mean interval between spine surgery and symptoms of SAMS was 69 days, with high between-studies variability (3 days to 4 years). Prompt identification of risk factors and an early diagnosis are necessary to manage SMAS and reduce the risk of complications. Additional investigations are required to establish risk factors and diagnostic criteria.Level of evidence Level IV, systematic review.

A Neurosurgical Readmissions Reduction Program in an Academic Hospital Leveraging Machine Learning, Workflow Analysis, and Simulation

BACKGROUND

 Predicting 30-day hospital readmissions is crucial for improving patient outcomes, optimizing resource allocation, and achieving financial savings. Existing studies reporting the development of machine learning (ML) models predictive of neurosurgical readmissions do not report factors related to clinical implementation.

OBJECTIVES

 Train individual predictive models with good performance (area under the receiver operating characteristic curve or AUROC > 0.8), identify potential interventions through semi-structured interviews, and demonstrate estimated clinical and financial impact of these models.

METHODS

 Electronic health records were utilized with five ML methodologies: gradient boosting, decision tree, random forest, ridge logistic regression, and linear support vector machine. Variables of interest were determined by domain experts and literature. The dataset was split divided 80% for training and validation and 20% for testing randomly. Clinical workflow analysis was conducted using semi-structured interviews to identify possible intervention points. Calibrated agent-based models (ABMs), based on a previous study with interventions, were applied to simulate reductions of the 30-day readmission rate and financial costs.

RESULTS

 The dataset covered 12,334 neurosurgical intensive care unit (NSICU) admissions (11,029 patients); 1,903 spine surgery admissions (1,641 patients), and 2,208 traumatic brain injury (TBI) admissions (2,185 patients), with readmission rate of 13.13, 13.93, and 23.73%, respectively. The random forest model for NSICU achieved best performance with an AUROC score of 0.89, capturing potential patients effectively. Six interventions were identified through 12 semi-structured interviews targeting preoperative, inpatient stay, discharge phases, and follow-up phases. Calibrated ABMs simulated median readmission reduction rates and resulted in 13.13 to 10.12% (NSICU), 13.90 to 10.98% (spine surgery), and 23.64 to 21.20% (TBI). Approximately $1,300,614.28 in saving resulted from potential interventions.

CONCLUSION

 This study reports the successful development and simulation of an ML-based approach for predicting and reducing 30-day hospital readmissions in neurosurgery. The intervention shows feasibility in improving patient outcomes and reducing financial losses.

Utilization of Machine Learning to Model Important Features of 30-day Readmissions following Surgery for Metastatic Spinal Column Tumors: The Influence of Frailty

STUDY DESIGN

Retrospective cohort study.

OBJECTIVE

The aim of this study was to determine the relative importance and predicative power of the Hospital Frailty Risk Score (HFRS) on unplanned 30-day readmission after surgical intervention for metastatic spinal column tumors.

METHODS

All adult patients undergoing surgery for metastatic spinal column tumor were identified in the Nationwide Readmission Database from the years 2016 to 2018. Patients were categorized into 3 cohorts based on the criteria of the HFRS: Low(<5), Intermediate(5-14.9), and High(≥ 15). Random Forest (RF) classification was used to construct predictive models for 30-day patient readmission. Model performance was examined using the area under the receiver operating curve (AUC), and the Mean Decrease Gini (MDG) metric was used to quantify and rank features by relative importance.

RESULTS

There were 4346 patients included. The proportion of patients who required any readmission were higher among the Intermediate and High frailty cohorts when compared to the Low frailty cohort (Low:33.9% vs. Intermediate:39.3% vs. High:39.2%, P < .001). An RF classifier was trained to predict 30-day readmission on all features (AUC = .60) and architecturally equivalent model trained using only ten features with highest MDG (AUC = .59). Both models found frailty to have the highest importance in predicting risk of readmission. On multivariate regression analysis, Intermediate frailty [OR:1.32, CI(1.06,1.64), P = .012] was found to be an independent predictor of unplanned 30-day readmission.

CONCLUSION

Our study utilizes machine learning approaches and predictive modeling to identify frailty as a significant risk-factor that contributes to unplanned 30-day readmission after spine surgery for metastatic spinal column metastases.

Safety and efficacy of growth-friendly instrumentation for early-onset scoliosis in patients with spinal muscular atrophy type 1 in the disease-modifying treatment era

Purpose

To evaluate the safety of growth-friendly instrumentation for early-onset scoliosis (EOS) in patients with spinal muscular atrophy (SMA) type 1 who received disease-modifying treatment (DMT) and analyze short-term efficacy.

Methods

Retrospective search was conducted between 2017 and 2023. Patients with genetically confirmed SMA type 1 who were surgically treated for spinal deformity and receiving DMTs (nusinersen, risdiplam, or onasemnogene abeparvovec) were included. SMA types 2 and 3 and patients who do not receive DMTs were excluded. Clinical and radiographic data were collected at preoperative, postoperative, and latest follow-up visits.

Results

Twenty-eight patients (mean follow-up: 16 months (range 2-41)) were included. The mean age at surgery was 60 months (range 29-96). Fifteen were treated with dual magnetically controlled growing rods (MCGR), four with unilateral MCGR and a contralateral guided growth system, three with Vertical Expandable Prosthetic Titanium Rib (VEPTR®) implants, five with self-distracting systems, and one with traditional dual growing rods. The mean amount of correction was 57% (44°± 17) for scoliosis and 83% (13°± 11) for pelvic obliquity. The mean T1-12 height gain during surgery was 31 mm (±16 mm), while the mean T1 S1 height gain was 51 mm (±24 mm), and instrumented growth was observed during follow-up. Five patients (18%) developed six serious adverse events: three surgical site infections, two anchor failures, and one rod fracture, and all required unplanned reoperations. No neurologic complication, difficulty during nusinersen injections, or respiratory decline was recorded.

Conclusion

We report that spinal deformity in this population can be safely treated with growth-friendly instrumentation, with similar complication rates when compared with SMA type 2.

Effect of Obesity on Surgical Outcomes and Complication Rates in Pediatric Patients: A Comprehensive Systematic Review and Meta-Analysis

Obesity is one of the primary public health problems faced by children. The increased incidence of obesity in the pediatric population poses significant challenges during and after surgical procedures. This systematic review and meta-analysis aimed to understand to what extent obesity is to surgical complications in pediatric patients. A systematic database search of PubMed, Web of Science, Scopus, and Science Direct was performed in June 2023. According to the inclusion and exclusion criteria, two evaluators independently conducted literature screening, data extraction, and quality evaluation of the retrieved literature. The Newcastle-Ottawa Scale score was used for quality evaluation, and a meta-analysis was performed using Review Manager software 5.4.1. A total of 1,170 relevant articles were initially identified, and 20 articles were finally included for data extraction and meta-analysis. The results of the meta-analysis showed that compared with normal-weight individuals, obese pediatric patients had a higher risk of developing surgical site infection (SSI) (relative risk (RR) = 1.63; 95% confidence interval (CI) = 1.33-2.00), wound dehiscence (RR = 2.01; 95% CI = 1.24-3.23), and underwent procedures that were 11.32 minutes longer (95% CI = 5.36-17.29). There were no differences in bleeding requiring transfusion, deep venous thromboembolism, postoperative abscess rate, and length of stay. Obese pediatric patients have a higher risk of SSI and dehiscence, along with a longer operative time. The established risks in obese adults undergoing surgery suggest a similar risk for obese pediatric patients. The findings of this study hold significant implications for clinical practice, suggesting the potential for additional measures to prevent surgical complications in children.

Previous Emergency Department Admission Is Associated With Increased 90-Day Readmission Following Cervical Spine Surgery: Evidenced Using Propensity Score Matching

STUDY DESIGN

This was a retrospective case-control study.

OBJECTIVE

The objective of this study was to evaluate whether prior emergency department admission was associated with an increased risk for 90-day readmission following elective cervical spinal fusion.

SUMMARY OF BACKGROUND DATA

The incidence of cervical spine fusion reoperations has increased, necessitating the improvement of patient outcomes following surgery. Currently, there are no studies assessing the impact of emergency department visits before surgery on the risk of 90-day readmission following elective cervical spine surgery. This study aimed to fill this gap and identify a novel risk factor for readmission following elective cervical fusion.

METHODS

The 2016-2018 Nationwide Readmissions Database was queried for patients aged 18 years and older who underwent an elective cervical fusion. Prior emergency admissions were defined using the variable HCUP_ED in the Nationwide Readmissions Database database. Univariate analysis of patient demographic details, comorbidities, discharge disposition, and perioperative complication was evaluated using a χ 2 test followed by multivariate logistic regression.

RESULTS

In all, 2766 patients fit the inclusion criteria, and 18.62% of patients were readmitted within 90 days. Intraoperative complications, gastrointestinal complications, valvular, uncomplicated hypertension, peripheral vascular disorders, chronic obstructive pulmonary disease, cancer, and experiencing less than 3 Charlson comorbidities were identified as independent predictors of 90-day readmission. Patients with greater than 3 Charlson comorbidities (OR=0.04, 95% CI 0.01-0.12, P <0.001) and neurological complications (OR=0.29, 95% CI 0.10-0.86, P =0.026) had decreased odds for 90-day readmission. Importantly, previous emergency department visits within the calendar year before surgery were a new independent predictor of 90-day readmission (OR=9.74, 95% CI 6.86-13.83, P <0.001).

CONCLUSIONS

A positive association exists between emergency department admission history and 90-day readmission following elective cervical fusion. Screening cervical fusion patients for this history and optimizing outcomes in those patients may reduce 90-day readmission rates.

Unplanned Readmission After Surgery for Cervical Spine Metastases

OBJECTIVE

Patients undergoing surgery for cervical spine metastases are at risk for unplanned readmission due to comorbidities and chemotherapy/radiation. Our objectives were to: 1) report the incidence of unplanned readmission, 2) identify risk factors associated with unplanned readmission, and 3) determine the impact of an unplanned readmission on long-term outcomes.

METHODS

A single-center, retrospective, case-control study was undertaken of patients undergoing cervical spine surgery for metastatic disease between 02/2010 and 01/2021. The primary outcome of interest was unplanned readmission within 6 months. Survival analysis was performed for overall survival (OS) and local recurrence (LR).

RESULTS

A total of 61 patients underwent cervical spine surgery for metastatic disease with the following approaches: 11 (18.0%) anterior, 28 (45.9%) posterior, and 22 (36.1%) combined. Mean age was 60.9 ± 11.2 years and 38 (62.3%) were males. A total of 9/61 (14.8%) patients had an unplanned readmission, 3 for surgical reasons and 6 for medical reasons. No difference was found in demographics, preoperative Karnofsky Performance Scale (P = 0.992), motor strength (P = 0.477), or comorbidities (P = 0.213) between readmitted patients versus not. Readmitted patients had a higher rate of preoperative radiation (P = 0.009). No statistical differences were found in operative time (P = 0.893), estimated blood loss (P = 0.676), length of stay (P = 0.720), discharge disposition (P = 0.279), and operative approach (P = 0.450). Furthermore, no difference was found regarding complications (P = 0.463), postoperative Karnofsky Performance Scale (P = 0.535), and postoperative Modified McCormick Scale (P = 0.586). Lastly, unplanned readmissions were not associated with OS (log-rank; P = 0.094) or LR (log-rank; P = 0.110).

CONCLUSIONS

In patients undergoing cervical spine metastasis surgery, readmission occurred in 15% of patients, 33% for surgical reasons, and 67% for medical reasons. Preoperative radiotherapy was associated with an increased rate of unplanned readmissions, yet readmission had no association with OS or LR.

Marfan syndrome and adolescent idiopathic scoliosis patients have similar 90-day postoperative outcomes and 5-year reoperation rates after spinal deformity surgery

PURPOSE

Outcomes after spinal deformity surgery in patients with Marfan syndrome (MFS) are poorly characterized given the rarity of the condition. Updated analyses from nationally representative samples, and comparison to outcomes after more commonly performed procedures for conditions such as adolescent idiopathic scoliosis (AIS) could help define the relative risks.

METHODS

Using the 2010-2020 PearlDiver administrative databases, patients who underwent posterior spinal fusion for > 7 segments were extracted. MFS patients were matched 1:4 to AIS patients based on age, sex, and Elixhauer comorbidity index (ECI). Ninety-day outcomes and 5-year reoperation rates were compared. Significance was set at p < 0.05.

RESULTS

In total, 206 MFS patients were matched to 825 AIS patients. After adjusting for age, sex, and ECI, multivariate odds ratios (OR) for 90-day any, serious, and minor adverse events, as well as readmissions, were not significantly different for those with MFS compared to those with AIS (p > 0.05 for each). Five-year reoperation rates were also not significantly different (13.1% for the MFS cohort and 13.0% for the AIS cohort (no difference by log-rank, p = 0.9).

CONCLUSION

While deformity surgery is much less commonly performed for MFS than AIS, it is not uncommonly considered for patients with this condition. Despite some known technical challenges for MFS deformity surgery, the current study leveraged a large, national database to find that 90-day adverse events and 5-year reoperations were not different for matched MFS and AIS patients undergoing deformity surgery. For select patients, these findings should be useful for surgical planning and patient counseling.

Applicability of predictive models for 30-day unplanned hospital readmission risk in paediatrics: a systematic review

OBJECTIVES

To summarise multivariable predictive models for 30-day unplanned hospital readmissions (UHRs) in paediatrics, describe their performance and completeness in reporting, and determine their potential for application in practice.

DESIGN

Systematic review.

DATA SOURCE

CINAHL, Embase and PubMed up to 7 October 2021.

ELIGIBILITY CRITERIA

English or German language studies aiming to develop or validate a multivariable predictive model for 30-day paediatric UHRs related to all-cause, surgical conditions or general medical conditions were included.

DATA EXTRACTION AND SYNTHESIS

Study characteristics, risk factors significant for predicting readmissions and information about performance measures (eg, c-statistic) were extracted. Reporting quality was addressed by the 'Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis' (TRIPOD) adherence form. The study quality was assessed by applying six domains of potential biases. Due to expected heterogeneity among the studies, the data were qualitatively synthesised.

RESULTS

Based on 28 studies, 37 predictive models were identified, which could potentially be used for determining individual 30-day UHR risk in paediatrics. The number of study participants ranged from 190 children to 1.4 million encounters. The two most common significant risk factors were comorbidity and (postoperative) length of stay. 23 models showed a c-statistic above 0.7 and are primarily applicable at discharge. The median TRIPOD adherence of the models was 59% (P₂₅-P₇₅, 55%-69%), ranging from a minimum of 33% to a maximum of 81%. Overall, the quality of many studies was moderate to low in all six domains.

CONCLUSION

Predictive models may be useful in identifying paediatric patients at increased risk of readmission. To support the application of predictive models, more attention should be placed on completeness in reporting, particularly for those items that may be relevant for implementation in practice.