Search Results

You are looking at 1 - 2 of 2 items for

  • Author or Editor: Brittany M. Stopa x
Clear All Modify Search
Restricted access

Predicting nonroutine discharge after elective spine surgery: external validation of machine learning algorithms

Presented at the 2019 AANS/CNS Joint Section on Disorders of the Spine and Peripheral Nerves

Brittany M. Stopa, Faith C. Robertson, Aditya V. Karhade, Melissa Chua, Marike L. D. Broekman, Joseph H. Schwab, Timothy R. Smith and William B. Gormley

OBJECTIVE

Nonroutine discharge after elective spine surgery increases healthcare costs, negatively impacts patient satisfaction, and exposes patients to additional hospital-acquired complications. Therefore, prediction of nonroutine discharge in this population may improve clinical management. The authors previously developed a machine learning algorithm from national data that predicts risk of nonhome discharge for patients undergoing surgery for lumbar disc disorders. In this paper the authors externally validate their algorithm in an independent institutional population of neurosurgical spine patients.

METHODS

Medical records from elective inpatient surgery for lumbar disc herniation or degeneration in the Transitional Care Program at Brigham and Women’s Hospital (2013–2015) were retrospectively reviewed. Variables included age, sex, BMI, American Society of Anesthesiologists (ASA) class, preoperative functional status, number of fusion levels, comorbidities, preoperative laboratory values, and discharge disposition. Nonroutine discharge was defined as postoperative discharge to any setting other than home. The discrimination (c-statistic), calibration, and positive and negative predictive values (PPVs and NPVs) of the algorithm were assessed in the institutional sample.

RESULTS

Overall, 144 patients underwent elective inpatient surgery for lumbar disc disorders with a nonroutine discharge rate of 6.9% (n = 10). The median patient age was 50 years and 45.1% of patients were female. Most patients were ASA class II (66.0%), had 1 or 2 levels fused (80.6%), and had no diabetes (91.7%). The median hematocrit level was 41.2%. The neural network algorithm generalized well to the institutional data, with a c-statistic (area under the receiver operating characteristic curve) of 0.89, calibration slope of 1.09, and calibration intercept of −0.08. At a threshold of 0.25, the PPV was 0.50 and the NPV was 0.97.

CONCLUSIONS

This institutional external validation of a previously developed machine learning algorithm suggests a reliable method for identifying patients with lumbar disc disorder at risk for nonroutine discharge. Performance in the institutional cohort was comparable to performance in the derivation cohort and represents an improved predictive value over clinician intuition. This finding substantiates initial use of this algorithm in clinical practice. This tool may be used by multidisciplinary teams of case managers and spine surgeons to strategically invest additional time and resources into postoperative plans for this population.

Restricted access

Alexander F. C. Hulsbergen, Sandra C. Yan, Brittany M. Stopa, Aislyn DiRisio, Joeky T. Senders, Max J. van Essen, Stéphanie M. E. van der Burgt, Timothy R. Smith, William B. Gormley and Marike L. D. Broekman

OBJECTIVE

The value of CT scanning after burr hole surgery in chronic subdural hematoma (CSDH) patients is unclear, and practice differs between countries. At the Brigham and Women’s Hospital (BWH) in Boston, Massachusetts, neurosurgeons frequently order routine postoperative CT scans, while the University Medical Center Utrecht (UMCU) in the Netherlands does not have this policy. The aim of this study was to compare the use of postoperative CT scans in CSDH patients between these hospitals and to evaluate whether there are differences in clinical outcomes.

METHODS

The authors collected data from both centers for 391 age- and sex-matched CSDH patients treated with burr hole surgery between January 1, 2002, and July 1, 2016, and compared the number of postoperative scans up to 6 weeks after surgery, the need for re-intervention, and postoperative neurological condition.

RESULTS

BWH patients were postoperatively scanned a median of 4 times (interquartile range [IQR] 2–5), whereas UMCU patients underwent a median of 0 scans (IQR 0–1, p < 0.001). There was no significant difference in the number of re-operations (20 in the BWH vs 27 in the UMCU, p = 0.34). All re-interventions were preceded by clinical decline and no recurrences were detected on scans performed on asymptomatic patients. Patients’ neurological condition was not worse in the UMCU than in the BWH (p = 0.43).

CONCLUSIONS

While BWH patients underwent more scans than UMCU patients, there were no differences in clinical outcomes. The results of this study suggest that there is little benefit to routine scanning in asymptomatic patients who have undergone surgical treatment of uncomplicated CSDH and highlight opportunities to make practice more efficient.