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Adham M. Khalafallah, Sakibul Huq, Adrian E. Jimenez, Henry Brem, and Debraj Mukherjee

OBJECTIVE

Health measures such as the Charlson Comorbidity Index (CCI) and the 11-factor modified frailty index (mFI-11) have been employed to predict general medical and surgical mortality, but their clinical utility is limited by the requirement for a large number of data points, some of which overlap or require data that may be unavailable in large datasets. A more streamlined 5-factor modified frailty index (mFI-5) was recently developed to overcome these barriers, but it has not been widely tested in neuro-oncology patient populations. The authors compared the utility of the mFI-5 to that of the CCI and the mFI-11 in predicting postoperative mortality in brain tumor patients.

METHODS

The authors retrospectively reviewed a cohort of adult patients from a single institution who underwent brain tumor surgery during the period from January 2017 to December 2018. Logistic regression models were used to quantify the associations between health measure scores and postoperative mortality after adjusting for patient age, race, ethnicity, sex, marital status, and diagnosis. Results were considered statistically significant at p values ≤ 0.05. Receiver operating characteristic (ROC) curves were used to examine the relationships between CCI, mFI-11, and mFI-5 and mortality, and DeLong’s test was used to test for significant differences between c-statistics. Spearman’s rho was used to quantify correlations between indices.

RESULTS

The study cohort included 1692 patients (mean age 55.5 years; mean CCI, mFI-11, and mFI-5 scores 2.49, 1.05, and 0.80, respectively). Each 1-point increase in mFI-11 (OR 4.19, p = 0.0043) and mFI-5 (OR 2.56, p = 0.018) scores independently predicted greater odds of 90-day postoperative mortality. Adjusted CCI, mFI-11, and mFI-5 ROC curves demonstrated c-statistics of 0.86 (CI 0.82–0.90), 0.87 (CI 0.83–0.91), and 0.87 (CI 0.83–0.91), respectively, and there was no significant difference between the c-statistics of the adjusted CCI and the adjusted mFI-5 models (p = 0.089) or between the adjusted mFI-11 and the adjusted mFI-5 models (p = 0.82). The 3 indices were well correlated (p < 0.01).

CONCLUSIONS

The adjusted mFI-5 model predicts 90-day postoperative mortality among brain tumor patients as well as our adjusted CCI and adjusted mFI-11 models. The simplified mFI-5 may be easily integrated into clinical workflows to predict brain tumor surgery outcomes in real time.

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Debraj Mukherjee and Chirag G. Patil

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Miriam Nuño, Christine Carico, Debraj Mukherjee, Diana Ly, Alicia Ortega, Keith L. Black, and Chirag G. Patil

OBJECT

The Agency for Healthcare Research and Quality patient safety indicators (PSIs) and the Centers for Medicare and Medicaid Services hospital-acquired conditions (HACs) are administrative data-based metrics. The use of these outcomes as standard performance measures has been discussed in previous studies. With the objective of determining the applicability of these events as performance metrics among patients undergoing brain tumor surgery, this study had 2 aims: 1) to evaluate the association between PSIs, HACs, and in-hospital mortality rates; and 2) to determine a correlation between hospital volume, PSIs, and HACs.

METHODS

Patients with brain tumors treated between 1998 and 2009 were captured in the Nationwide Inpatient Sample database. Hospitals were categorized into groups according to surgical volume. Associations between PSIs, HACs, and in-hospital mortality rates were studied. Factors associated with a PSI, HAC, and mortality were evaluated in a multivariate setting.

RESULTS

A total of 444,751 patients with brain tumors underwent surgery in 1311 hospitals nationwide. Of these, 7.4% of patients experienced a PSI, 0.4% an HAC, and 1.9% died during their hospitalization. The occurrence of a PSI was strongly associated with mortality. Patients were 7.6 times more likely to die (adjusted odds ratio [aOR] 7.6, CI 6.7–8.7) with the occurrence of a PSI in a multivariate analysis. Moderate to strong associations were found between HACs, PSIs, and hospital volume. Patients treated at the highest-volume hospitals compared with the lowest-volume ones had reduced odds of a PSI (aOR 0.9, CI 0.8–1.0) and HAC (aOR 0.5, CI 0.5–0.08).

CONCLUSIONS

Patient safety-related adverse events were strongly associated with in-hospital mortality. Moderate to strong correlations were found between PSIs, HACs, and hospital procedural volume. Patients treated at the highest-volume hospitals had consistently lower rates of mortality, PSIs, and HACs compared with those treated at the lowest-volume facilities.

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Holly Dickinson, Christine Carico, Miriam Nuño, Debraj Mukherjee, Alicia Ortega, Keith L. Black, and Chirag G. Patil

OBJECT

Research on readmissions has been influenced by efforts to reduce hospital cost and avoid penalties stipulated by the Centers for Medicare and Medicaid Services. Less emphasis has been placed on understanding these readmissions and their impact on patient outcomes. This study 1) delineates reasons for readmission, 2) explores factors associated with readmissions, and 3) describes their impact on the survival of glioblastoma patients.

METHODS

The authors conducted a retrospective review of 362 cases involving patients with glioblastoma undergoing biopsy or tumor resection at their institution between 2003 and 2011. Reasons for re-hospitalization were characterized according to whether or not they were related to surgery and considered preventable. Multivariate analyses were conducted to identify the effect of readmission on survival and determine factors associated with re-hospitalizations.

RESULTS

Twenty-seven (7.5%) of 362 patients experienced unplanned readmissions within 30 days of surgery. Six patients (22.2%) were readmitted by Day 7, 14 (51.9%) by Day 14, and 20 (74.1%) by Day 21. Neurological, infectious, and thromboembolic complications were leading reasons for readmission, accounting for, respectively, 37.0%, 29.6%, and 22.2% of unplanned readmissions. Twenty-one (77.8%) of the 27 readmissions were related to surgery and 19 (70.4%) were preventable. The adjusted hazard ratio of mortality associated with a readmission was 2.03 (95% CI 1.3–3.1). Higher-functioning patients (OR 0.96, 95% CI 0.9–1.0) and patients discharged home (OR 0.21, 95% CI 0.1–0.6) were less likely to get readmitted.

CONCLUSIONS

An overwhelming fraction of documented unplanned readmissions were considered preventable and related to surgery. Patients who were readmitted to the hospital within 30 days of surgery had twice the risk of mortality compared with patients who were not readmitted.

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Phillip A. Bonney, Frank J. Attenello, and William J. Mack

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Adham M. Khalafallah, Adrian E. Jimenez, Justin M. Caplan, Cameron G. McDougall, Judy Huang, Debraj Mukherjee, and Rafael J. Tamargo

OBJECTIVE

Although previous studies have explored factors that predict an academic career among neurosurgery residents in general, such predictors have yet to be determined within specific neurosurgical subspecialties. The authors report on predictors they identified as correlating with academic placement among fellowship-trained vascular neurosurgeons.

METHODS

A database was created that included all physicians who graduated from ACGME (Accreditation Council for Graduate Medical Education)–accredited neurosurgery residency programs between 1960 and 2018 using publicly available online data. Neurosurgeons who completed either open vascular or endovascular fellowships were identified. Subsequent employment of vascular or endovascular neurosurgeons in academic centers was determined. A position was considered academic if the hospital of employment was affiliated with a neurosurgery residency program; all other positions were considered non-academic. Bivariate analyses were conducted using Fisher’s exact test or the Mann-Whitney U-test, and multivariate analysis was performed using a logistic regression model.

RESULTS

A total of 83 open vascular neurosurgeons and 115 endovascular neurosurgeons were identified. In both cohorts, the majority of neurosurgeons were employed in academic positions after training. In bivariate analysis, only 2 factors were significantly associated with a career in academic neurosurgery for open vascular neurosurgeons: 1) an h-index of ≥ 2 during residency (OR 3.71, p = 0.016), and 2) attending a top 10 residency program based on U.S. News and World Report rankings (OR 4.35, p = 0.030). In bivariate analysis, among endovascular neurosurgeons, having an h-index of ≥ 2 during residency (OR 4.35, p = 0.0085) and attending a residency program affiliated with a top 10 U.S. News and World Report medical school (OR 2.97, p = 0.029) were significantly associated with an academic career. In multivariate analysis, for both open vascular and endovascular neurosurgeons, an h-index of ≥ 2 during residency was independently predictive of an academic career. Attending a residency program affiliated with a top 10 U.S. News and World Report medical school independently predicted an academic career among endovascular neurosurgeons only.

CONCLUSIONS

The authors report that an h-index of ≥ 2 during residency predicts pursuit of an academic career among vascular and endovascular neurosurgeons. Additionally, attendance of a residency program affiliated with a top research medical school independently predicts an academic career trajectory among endovascular neurosurgeons. This result may be useful to identify and mentor residents interested in academic vascular neurosurgery.

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Adham M. Khalafallah, Adrian E. Jimenez, Rafael J. Tamargo, Timothy Witham, Judy Huang, Henry Brem, and Debraj Mukherjee

OBJECTIVE

Previous authors have investigated many factors that predict an academic neurosurgical career over private practice, including attainment of a Doctor of Philosophy (PhD) and number of publications. Research has yet to demonstrate whether a master’s degree predicts an academic neurosurgical career. This study quantifies the association between obtaining a Master of Science (MS), Master of Public Health (MPH), or Master of Business Administration (MBA) degree and pursuing a career in academic neurosurgery.

METHODS

Public data on neurosurgeons who had graduated from Accreditation Council for Graduate Medical Education (ACGME)–accredited residency programs in the period from 1949 to 2019 were collected from residency and professional websites. Residency graduates with a PhD were excluded to isolate the effect of only having a master’s degree. A position was considered “academic” if it was affiliated with a hospital that had a neurosurgery residency program; other positions were considered nonacademic. Bivariate analyses were performed with Fisher’s exact test. Multivariate analysis was performed using a logistic regression model.

RESULTS

Within our database of neurosurgery residency alumni, there were 47 (4.1%) who held an MS degree, 31 (2.7%) who held an MPH, and 10 (0.9%) who held an MBA. In bivariate analyses, neurosurgeons with MS degrees were significantly more likely to pursue academic careers (OR 2.65, p = 0.0014, 95% CI 1.40–5.20), whereas neurosurgeons with an MPH (OR 1.41, p = 0.36, 95% CI 0.64–3.08) or an MBA (OR 1.00, p = 1.00, 95% CI 0.21–4.26) were not. In the multivariate analysis, an MS degree was independently associated with an academic career (OR 2.48, p = 0.0079, 95% CI 1.28–4.93). Moreover, postresidency h indices of 1 (OR 1.44, p = 0.048, 95% CI 1.00–2.07), 2–3 (OR 2.76, p = 2.01 × 10−8, 95% CI 1.94–3.94), and ≥ 4 (OR 4.88, p < 2.00 × 10−16, 95% CI 3.43–6.99) were all significantly associated with increased odds of pursuing an academic career. Notably, having between 1 and 11 months of protected research time was significantly associated with decreased odds of pursuing academic neurosurgery (OR 0.46, p = 0.049, 95% CI 0.21–0.98).

CONCLUSIONS

Neurosurgery residency graduates with MS degrees are more likely to pursue academic neurosurgical careers relative to their non-MS counterparts. Such findings may be used to help predict residency graduates’ future potential in academic neurosurgery.

Free access

Sakibul Huq, Adham M. Khalafallah, David Botros, Adrian E. Jimenez, Shravika Lam, Judy Huang, and Debraj Mukherjee

Free access

Sandip S. Panesar, Michael Magnetta, Debraj Mukherjee, Kumar Abhinav, Barton F. Branstetter, Paul A. Gardner, Michael Iv, and Juan C. Fernandez-Miranda

OBJECTIVE

Advances in 3-dimensional (3D) printing technology permit the rapid creation of detailed anatomical models. Integration of this technology into neurosurgical practice is still in its nascence, however. One potential application is to create models depicting neurosurgical pathology. The goal of this study was to assess the clinical value of patient-specific 3D printed models for neurosurgical planning and education.

METHODS

The authors created life-sized, patient-specific models for 4 preoperative cases. Three of the cases involved adults (2 patients with petroclival meningioma and 1 with trigeminal neuralgia) and the remaining case involved a pediatric patient with craniopharyngioma. Models were derived from routine clinical imaging sequences and manufactured using commercially available software and hardware.

RESULTS

Life-sized, 3D printed models depicting bony, vascular, and neural pathology relevant to each case were successfully manufactured. A variety of commercially available software and hardware were used to create and print each model from radiological sequences. The models for the adult cases were printed in separate pieces, which had to be painted by hand, and could be disassembled for detailed study, while the model for the pediatric case was printed as a single piece in separate-colored resins and could not be disassembled for study. Two of the models were used for patient education, and all were used for presurgical planning by the surgeon.

CONCLUSIONS

Patient-specific 3D printed models are useful to neurosurgical practice. They may be used as a visualization aid for surgeons and patients, or for education of trainees.