Development and Validation of a Multivariate Prediction Model of Perioperative Mortality in Neurosurgery: The New Zealand Neurosurgical Risk Tool (NZRISK-NEURO)

Abstract

BACKGROUND Multivariate risk prediction models individualize prediction of adverse outcomes, assisting perioperative decision-making. There are currently no models specifically designed for the neurosurgical population. OBJECTIVE To develop and validate a neurosurgical risk prediction model, with 30-d, 1-yr, and 2-yr mortality endpoints. METHODS We accessed information on all adults in New Zealand who underwent neurosurgery or spinal surgery between July 1, 2011, and June 30, 2016, from an administrative database. Our dataset comprised of 18 375 participants, split randomly into derivation (75%) and validation (25%) datasets. Previously established covariates tested included American Society of Anesthesiologists physical status grade (ASA-PS), surgical acuity, operative severity, cancer status, and age. Exploratory covariates included anatomical site, gender, diabetes, trauma, ethnicity, and socioeconomic status. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct 30-d, 1-yr, and 2-yr mortality models. RESULTS Our final models included 8 covariates: age, ASA-PS grade, surgical acuity, cancer status, anatomical site, diabetes, ethnicity, and trauma. The area under the receiver operating curve for the 30-d, 1-yr, and 2-yr mortality models was 0.90, 0.91, and 0.91 indicating excellent discrimination, respectively. Calibration also showed excellent performance with McFadden's pseudo R2 statistics of 0.28, 0.37, and 0.41 and calibration plot slopes of 0.93, 0.95, and 0.94, respectively. The strongest predictors of mortality were ASA-PS 4 and 5 (30 d) and cancer (1 and 2 yr). CONCLUSION NZRISK-NEURO is a robust multivariate calculator created specifically for neurosurgery, enabling physicians to generate data-driven individualized risk estimates, assisting shared decision-making and perioperative planning.

Incidence of postoperative delirium in surgical patients: An observational retrospective cohort study

“…However, our previous experience with using NMDS data is that data completeness, accuracy and integrity for demographic and process datapoints is greater than 99%. 15,[27][28][29] Our results were consistent with previously identified risk factors for POD, including increasing age, acute surgery, comorbidity and association with invasive surgery. 1 Perioperative outcomes were also worse in patients diagnosed with POD as previously observed.…”

A scoping review of complication prediction models in spinal surgery: An analysis of model development, validation and impact

“… [67] 2020 None Retrospective 4046 Single centre Posterior spine fusion Surgical site infection MD and IV AUC: 0.78 No Clark et al. [68] 2020 NZRISK-Neuro Retrospective 18,375 New Zealand registry Neuro or spinal surgery Mortality MD and IV AUC: 0.9 (30-day), 0.91 (1 year) 0.91 (2 year) Yes MD: model development; IV: internal validation; EV: external validation, LR: logistic regression, ML: machine learning, AUC: area under the curve, AUROC: area under the receiver operating characteristic ASD: adult spinal deformity, NZRISK-Neuro: The New Zealand Neurosurgical Risk Tool. …”

The Japan Neurosurgical Database: Statistics Update 2018 and 2019

“…Various studies involving 40,000 patients have suggested that outcomes are improved when patients who have neurocritical conditions (e.g., stroke and traumatic brain injury) are cared for in specialized neurointensive care units, especially with the involvement of neurointensivists. 5) A previous study using data from the Japan Neurotrauma Data Bank showed that the management and monitoring of intracranial pressure are both important for the management and care of severe brain injury. 6) Further studies are required to investigate the effect of neurocritical care and quality assessment on patient outcomes, especially after stroke and neurotrauma.…”

“…1) Regarding medical treatment in neurosurgical admission, antiplatelet and anticoagulation treatment and neuroprotective therapy (e.g., edaravone 4) ) are performed mainly for cerebrovascular diseases, whereas other medical treatments such as anti-edema therapy and for in specialized neurointensive care units, especially with the involvement of neurointensivists. 5) A previous study using data from the Japan Neurotrauma Data Bank showed that the management and monitoring of intracranial pressure are both important for the management and care of severe brain injury. 6) Further studies are required to investigate the effect of neurocritical care and quality assessment on patient outcomes, especially after stroke and neurotrauma.…”