Development and external validation of a clinical prediction model for predicting quality of recovery up to 1 week after surgery.

The Quality of Recovery Score-40 (QoR-40) has been increasingly used for assessing recovery after patients undergoing surgery. However, a prediction model estimating quality of recovery is lacking. The aim of the present study was to develop and externally validate a clinical prediction model that predicts quality of recovery up to one week after surgery. The modelling procedure consisted of two models of increasing complexity (basic and full model). To assess the internal validity of the developed model, bootstrapping (1000 times) was applied. At external validation, the model performance was evaluated according to measures for overall model performance (explained variance (R2)) and calibration (calibration plot and slope). The full model consisted of age, sex, previous surgery, BMI, ASA classification, duration of surgery, HADS and preoperative QoR-40 score. At model development, the R2 of the full model was 0.24. At external validation the R2 dropped as expected. The calibration analysis showed that the QoR-40 predictions provided by the developed prediction models are reliable. The presented models can be used as a starting point for future updating in prediction studies. When the predictive performance is improved it could be implemented clinically in the future.

Evolution of Making Clinical Predictions in Neurosurgery.

Prediction of clinical outcomes is an essential task for every physician. Physicians may base their clinical prediction of an individual patient on their intuition and on scientific material such as studies presenting population risks and studies reporting on risk factors (prognostic factors). A relatively new and more informative approach for making clinical predictions relies on the use of statistical models that simultaneously consider multiple predictors that provide an estimate of the patient's absolute risk of an outcome. There is a growing body of literature in the neurosurgical field reporting on clinical prediction models. These tools have high potential in supporting (not replacing) neurosurgeons with their prediction of a patient's outcome. If used sensibly, these tools pave the way for more informed decision-making with or for individual patients. Patients and their significant others want to know their risk of the anticipated outcome, how it is derived, and the uncertainty associated with it. Learning from these prediction models and communicating the output to others has become an increasingly important skill neurosurgeons have to master. This article describes the evolution of making clinical predictions in neurosurgery, synopsizes key phases for the generation of a useful clinical prediction model, and addresses some considerations when deploying and communicating the results of a prediction model. The paper is illustrated with multiple examples from the neurosurgical literature, including predicting arachnoid cyst rupture, predicting rebleeding in patients suffering from aneurysmal subarachnoid hemorrhage, and predicting survival in glioblastoma patients.

Development and Internal Validation of the ARISE Prediction Models for Rebleeding After Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND: Aneurysmal rerupture is one of the most important determents for outcome after aneurysmal subarachnoid hemorrhage and still occurs frequently because individual risk assessment is challenging given the heterogeneity in patient characteristics and aneurysm morphology. OBJECTIVE: To develop and internally validate a practical prediction model to estimate the risk of aneurysmal rerupture before aneurysm closure. METHODS: We designed a multinational cohort study of 2 prospective hospital registries and 3 retrospective observational studies to predict the risk of computed tomography confirmed rebleeding within 24 and 72 hours after ictus. We assessed predictors with Cox proportional hazard regression analysis. RESULTS: Rerupture occurred in 269 of 2075 patients. The cumulative incidence equaled 7% and 11% at 24 and 72 hours, respectively. Our base model included hypertension, World Federation of Neurosurgical Societies scale, Fisher grade, aneurysm size, and cerebrospinal fluid drainage before aneurysm closure and showed good discrimination with an optimism corrected c-statistic of 0.77. When we extend the base model with aneurysm irregularity, the optimism-corrected c-statistic increased to 0.79. CONCLUSION: Our prediction models reliably estimate the risk of aneurysm rerupture after aneurysmal subarachnoid hemorrhage using predictor variables available upon hospital admission. An online prognostic calculator is accessible at https://www.evidencio.com/models/show/2626 .

Structural damage burden and hypertrophic olivary degeneration in pediatric postoperative cerebellar mutism syndrome.

Cerebellar mutism syndrome (CMS) occurs in one out of four children after posterior fossa tumor surgery, with open questions regarding risk factors, pathophysiology, and prevention strategies. Because of similarities between several cerebellar syndromes, a common pathophysiology with damage to the dentato-thalamo-cortical and dentato-rubro-olivary pathways has been proposed. Hypertrophic olivary degeneration (HOD) is an imaging correlate of cerebellar injury observed for instance in stroke patients. Aim of this study was to investigate whether the occurrence and severity of CMS correlates with the extent of damage to the relevant anatomical structures and whether HOD is a time-dependent postoperative neuroimaging correlate of CMS. We performed a retrospective single center study of CMS patients compared with matched non-CMS controls. CMS occurred in 10 children (13% of the overall cohort) with a median age of 8 years. Dentate nucleus (DN) injury significantly correlated with CMS, and superior cerebellar peduncle (SCP) injury was associated by tendency. HOD was observed as a dynamic neuroimaging phenomenon in the postoperative course and its presence significantly correlated with CMS and DN injury. Children who later developed HOD had an earlier onset and tended to have longer persistence of CMS. These findings can guide surgical measures to protect the DN and SCP during posterior fossa tumor resections and to avoid a high damage burden (i.e., bilateral damage). Development of intraoperative neuromonitoring of the cerebellar efferent pathways as well as improved preoperative risk stratification could help to establish a patient-specific strategy with optimal balance between degree of resection and functional integrity.

Development and external validation of a clinical prediction model for survival in patients with IDH wild-type glioblastoma.

OBJECTIVE: Prognostication of glioblastoma survival has become more refined due to the molecular reclassification of these tumors into isocitrate dehydrogenase (IDH) wild-type and IDH mutant. Since this molecular stratification, however, robust clinical prediction models relevant to the entire IDH wild-type glioblastoma patient population are lacking. This study aimed to provide an updated model that predicts individual survival prognosis in patients with IDH wild-type glioblastoma. METHODS: Databases from Germany and the Netherlands provided data on 1036 newly diagnosed glioblastoma patients treated between 2012 and 2018. A clinical prediction model for all-cause mortality was developed with Cox proportional hazards regression. This model included recent glioblastoma-associated molecular markers in addition to well-known classic prognostic variables, which were updated and refined with additional categories. Model performance was evaluated according to calibration (using calibration plots and calibration slope) and discrimination (using a C-statistic) in a cross-validation procedure by country to assess external validity. RESULTS: The German and Dutch patient cohorts consisted of 710 and 326 patients, respectively, of whom 511 (72%) and 308 (95%) had died. Three models were developed, each with increasing complexity. The final model considering age, sex, preoperative Karnofsky Performance Status, extent of resection, O6-methylguanine DNA methyltransferase (MGMT) promoter methylation status, and adjuvant therapeutic regimen showed an optimism-corrected C-statistic of 0.73 (95% confidence interval 0.71-0.75). Cross-validation between the national cohorts yielded comparable results. CONCLUSIONS: This prediction model reliably predicts individual survival prognosis in patients with newly diagnosed IDH wild-type glioblastoma, although additional validation, especially for long-term survival, may be desired. The nomogram and web application of this model may support shared decision-making if used properly.

Updating Clinical Prediction Models: An Illustrative Case Study.

The performance of clinical prediction models tends to deteriorate over time. Researchers often develop a new prediction if an existing model performs poorly at external validation. Model updating is an efficient technique and promising alternative to the de novo development of clinical prediction models. Model updating has been recommended by the TRIPOD guidelines. To illustrate several model updating techniques, a case study is provided for the development and updating of a clinical prediction model assessing postoperative anxiety in data coming from two double-blinded placebo-controlled randomized controlled trials with a very similar methodological framework. Note that the developed model and updated model are for didactic purposes only. This paper discusses some common considerations and caveats for researchers to be aware of when planning or applying updating of a prediction model.

Is My Clinical Prediction Model Clinically Useful? A Primer on Decision Curve Analysis.

Decision curve analysis is an increasingly popular method to assess the impact of a prediction model on medical decision making. The analysis provides a graphical summary. A basic understanding of a decision curve is needed to interpret these graphics. This short introduction addresses the common features of a decision curve. Furthermore, using a glioblastoma patient set provided by the Machine Intelligence in Clinical Neuroscience Lab from the Department of Neurosurgery and Clinical Neuroscience Center, University Hospital Zurich a decision curve is plotted for two prediction models. The corresponding R code is provided.

Predictive Analytics in Clinical Practice: Advantages and Disadvantages.

Predictive analytics are increasingly reported by clinicians. These tools aim to improve patient outcomes in terms of quality, safety, and efficiency. However, deploying predictive analytics in clinical practice remains challenging today. We highlight several advantages and disadvantages of the application of predictive analytics in clinical practice. To flourish and reach its potential, predictive analytics need data that is of adequate quantity and quality, ideally tailored to clinical scenarios in equipoise regarding optimal management. Adequate reporting of predictive analytic tools is incumbent for uptake into clinical workflows. At least for now, the clinicians' knowledge, experience, and vigilance remain imperative for applying predictive analytics in clinical practice.

The rupture of an anterior communicating artery aneurysm does not associate with an asymmetry in the A1 or A2 arteries: a retrospective study of radiological features.

BACKGROUND AND OBJECTIVES: Although the formation and rupture risk of an anterior communicating artery (ACoA) aneurysm has been the subject of many studies, no previous study has primarily searched for the relationship of the parent and daughter vessels and the impact of their size/diameter ratio on the potential rupture risk of an AcoA aneurysm. The objective of this study is to explore this link and to further analyse the surrounding vasculature of the anterior communicating artery aneurysm. MATERIALS AND METHODS: We conducted a retrospective analysis of 434 patients: 284 patients with an ACoA aneurysm (121 unruptured and 162 ruptured) and 150 control patients without an ΑCoA aneurysm. Radiological angiography investigations were used to assess the diameter ratios of the parent vessels in addition to ACoA aneurysm morphology parameters. RESULTS: When comparing the ruptured to the unruptured cases, we observed no significant difference in the parent or daughter vessel diameter ratios. Younger patient age (OR 0.96, p = 0.00) and a higher aneurysm size ratio (OR 1.10, p = 0.02) were of prognostic importance concerning the rupture risk of the aneurysm. The A1 diameter ratio and the A2 diameter were not statistically significant (OR 1.00, p = 0.99, and OR 3.38, p = 0.25 respectively). CONCLUSIONS: In our study, we focused on asymmetry in the parent and daughter vessels as well as traditional ACoA aneurysm morphological characteristics. We were able to label younger patient age and a greater size ratio as independent prognostic factors for ACoA aneurysm rupture. We were unable to label parent and daughter vessel asymmetry as prognostic factors. To validate our findings, parent and daughter vessel asymmetry should be subjected to future prospective studies.

Proposed definition of competencies for surgical neuro-oncology training.

OBJECTIVE: The aim of this work is to define competencies and entrustable professional activities (EPAs) to be imparted within the framework of surgical neuro-oncological residency and fellowship training as well as the education of medical students. Improved and specific training in surgical neuro-oncology promotes neuro-oncological expertise, quality of surgical neuro-oncological treatment and may also contribute to further development of neuro-oncological techniques and treatment protocols. Specific curricula for a surgical neuro-oncologic education have not yet been established. METHODS: We used a consensus-building approach to propose skills, competencies and EPAs to be imparted within the framework of surgical neuro-oncological training. We developed competencies and EPAs suitable for training in surgical neuro-oncology. RESULT: In total, 70 competencies and 8 EPAs for training in surgical neuro-oncology were proposed. EPAs were defined for the management of the deteriorating patient, the management of patients with the diagnosis of a brain tumour, tumour-based resections, function-based surgical resections of brain tumours, the postoperative management of patients, the collaboration as a member of an interdisciplinary and/or -professional team and finally for the care of palliative and dying patients and their families. CONCLUSIONS AND RELEVANCE: The present work should subsequently initiate a discussion about the proposed competencies and EPAs and, together with the following discussion, contribute to the creation of new training concepts in surgical neuro-oncology.

Application of clinical prediction modeling in pediatric neurosurgery: a case study.

There has been an increasing interest in articles reporting on clinical prediction models in pediatric neurosurgery. Clinical prediction models are mathematical equations that combine patient-related risk factors for the estimation of an individual's risk of an outcome. If used sensibly, these evidence-based tools may help pediatric neurosurgeons in medical decision-making processes. Furthermore, they may help to communicate anticipated future events of diseases to children and their parents and facilitate shared decision-making accordingly. A basic understanding of this methodology is incumbent when developing or applying a prediction model. This paper addresses this methodology tailored to pediatric neurosurgery. For illustration, we use original pediatric data from our institution to illustrate this methodology with a case study. The developed model is however not externally validated, and clinical impact has not been assessed; therefore, the model cannot be recommended for clinical use in its current form.

Age-stratified clinical performance and survival of patients with IDH-wildtype glioblastoma homogeneously treated by radiotherapy with concomitant and maintenance temozolomide.

OBJECTIVE: Isocitrate dehydrogenase (IDH)-wildtype glioblastomas are the most malignant glial tumours. Median survival is only 14-16 months after diagnosis, with patients aged ≥ 65 years reportedly showing worse outcome. This study aimed to further evaluate the prognostic role of age in a homogenously treated patient cohort. METHODS: The study includes 132 IDH-wildtype glioblastoma patients treated between 2013 and 2017 with open resection followed by radiotherapy with concomitant and maintenance temozolomide. Patients were dichotomized into a non-elderly (< 65 years) and an elderly (≥ 65 years) group. Extent of resection and the O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status were determined for each tumour. Clinical and radiological follow-up data were obtained at 6 weeks after the end of radiation therapy and thereafter in 3-month intervals. Progression-free survival (PFS) and overall survival (OS) were evaluated in univariate and multivariate cox regression analyses. RESULTS: The elderly group consisted of 58 patients (median age: 70.5 years) and the non-elderly group of 74 patients (median age: 55 years). Median pre- and postoperative operative Karnofsky Performance Scale (KPS), Eastern Cooperative Oncology Group (ECOG) score and National Institutes of Stroke Scale (NIHSS) were not significantly different between the groups, but KPS and ECOG scores became significantly worse in the elderly group at 6 weeks after termination of radiation therapy. Neither PFS nor OS differed significantly between the age groups. Patients with MGMT promoter-methylated tumours survived longer. CONCLUSION: Elderly patients in good pre- and postoperative clinical conditions may show similar outcome as younger patients when treated according to standard of care. However, elderly patients may suffer more frequently from clinical deterioration following chemoradiotherapy. In both age groups, MGMT promoter methylation was linked to longer PFS and OS.

Asymmetry of P1 and vertebral arteries is not related to basilar tip aneurysm development or rupture.

OBJECTIVE: Lately, morphological parameters of the surrounding vasculature aside from aneurysm size, specific for the aneurysm location, e.g., posterior cerebral artery angle for basilar artery tip aneurysms, could be identified to correlate with the risk of rupture. We examined further image-based morphological parameters of the aneurysm surrounding vasculature that could correlate with the growth or the risk of rupture of basilar artery tip aneurysms. METHODS: Data from 83 patients with basilar tip aneurysms (27 not ruptured; 56 ruptured) and 100 control patients were assessed (50 without aneurysms and 50 with aneurysms of the anterior circle of Willis). Anatomical parameters of the aneurysms were assessed and analyzed, as well as of the surrounding vasculature, namely the asymmetry of P1 and the vertebral arteries. RESULTS: Patients with basilar tip aneurysm showed no significant increase in P1 or vertebral artery asymmetry compared with the control patients or patients with aneurysms of the anterior circulation, neither was there a significant difference in asymmetry between cases with ruptured and unruptured aneurysms. Furthermore, we observed no significant correlations between P1 asymmetry and the aneurysm size or number of lobuli in the aneurysms. CONCLUSION: We observed no significant difference in aneurysm size, rupture, or lobulation associated with P1 or vertebral artery (surrounding vasculature) asymmetry. Therefore, the asymmetry of the surrounding vessels does not seem to be a promising morphological parameter for the evaluation of probability of rupture and growth in basilar tip aneurysms in future studies.

Association between health insurance status and malignant glioma.

BACKGROUND: Prior studies have suggested an association between patient socioeconomic status and brain tumors. In the present study we attempt to indirectly validate the findings, using health insurance status as a proxy for socioeconomic status. METHODS: There are 2 types of health insurance in Germany: statutory and private. Owing to regulations, low- and middle-income residents are typically statutory insured, whereas high-income residents have the option of choosing a private insurance. We compared the frequencies of privately insured patients suffering from malignant neoplasms of the brain with the corresponding frequencies among other neurosurgical patients at our hospital and among the German population. To correct for age, sex, and distance from the hospital, we included these variables as predictors in logistic and binomial regression. RESULTS: A significant association (odds ratio [OR] = 1.59, CI = 1.45-1.74, P < .001) between health insurance status and brain tumors was found. The association is independent of patients' sex or age. Whereas privately insured patients generally tend to come from farther away, such a relationship was not observed for patients suffering from brain tumors. Comparing the out of house and in-house brain tumor patients showed no selection bias on our side. CONCLUSION: Previous studies have found that people with a higher income, level of education, or socioeconomic status are more likely to suffer from malignant brain tumors. Our findings are in line with these studies. Although the reason behind the association remains unclear, the probability that our results are due to some random effect in the data is extremely low.

Endovascular aneurysm closure during out of office hours is not related to complications or outcome.

PURPOSE: A possible disadvantage of endovascular occlusion outside work hours is that complex procedures might expose patients to additional risk when performed in a suboptimal setting. In this prospective cohort study, we evaluated whether treatment during out of office hours is a risk factor for per-procedural complications and clinical outcome. METHODS: We included 471 endovascular-treated, consecutive aneurysmal subarachnoid hemorrhage patients (56.6 ± 13.1, 69% female), from two prospective observational databases which were retrospectively analyzed. Primary outcome was the occurrence of per-procedural complications. Secondary outcomes were good clinical outcome (modified ranking scale ≤ 2) and death at 6-month follow-up. We determined odds ratios (OR) with 95% confidence intervals (CI) by ordered polytomous logistic regression analysis and adjusted odds ratios (aOR) for age, World Federation of Neurosurgical Societies grade, and time to treatment. RESULTS: Most patients were treated during office hours (363/471; 77.1%). Treatment during out of office hours did not result in an increased risk of per-procedural complications (OR 0.85 (95% CI 0.53-1.37; p = 0.51). Patients treated during out of office hours displayed similar odds of good clinical outcome and death after 6 months (OR 1.14, 95% CI 0.68-1.97 and 1.16 95% CI 0.56-2.29, respectively) compared to patients treated during office hours. CONCLUSION: In our study, endovascular coil embolization during out of office hours did not expose patients to an increased risk of procedural complications or affect functional outcome after 6 months.

Association between aneurysm hemodynamics and wall enhancement on 3D vessel wall MRI.

OBJECTIVE: Aneurysm wall enhancement (AWE) on 3D vessel wall MRI (VWMRI) has been suggested as an imaging biomarker for intracranial aneurysms (IAs) at higher risk of rupture. While computational fluid dynamics (CFD) studies have been used to investigate the association between hemodynamic forces and rupture status of IAs, the role of hemodynamic forces in unruptured IAs with AWE is poorly understood. The authors investigated the role and implications of abnormal hemodynamics related to aneurysm pathophysiology in patients with AWE in unruptured IAs. METHODS: Twenty-five patients who had undergone digital subtraction angiography (DSA) and VWMRI studies from September 2016 to September 2017 were included, resulting in 22 patients with 25 IAs, 9 with and 16 without AWE. High-resolution CFD models of hemodynamics were created from DSA images. Univariate and multivariate analyses were performed to investigate the association between AWE and conventional morphological and hemodynamic parameters. Normalized MRI signal intensity was quantified and quantitatively associated with wall shear stresses (WSSs) for the entire aneurysm sac, and in regions of low, intermediate, and high WSS. RESULTS: The AWE group had lower WSS (p < 0.01) and sac-averaged velocity (p < 0.01) and larger aneurysm size (p < 0.001) and size ratio (p = 0.0251) than the non-AWE group. From multivariate analysis of both hemodynamic and morphological factors, only low WSS was found to be independently associated with AWE. Sac-averaged normalized MRI signal intensity correlated with WSS and was significantly different in regions of low WSS compared to regions of intermediate (p = 0.018) and high (p < 0.001) WSS. CONCLUSIONS: The presence of AWE was associated with morphological and hemodynamic factors related to rupture risk. Low WSS was found to be an independent predictor of AWE. Our findings support the hypothesis that low WSS in IAs with AWE may indicate a growth and remodeling process that may predispose such aneurysms to rupture; however, a causality between the two cannot be established.

The effect of midazolam as premedication on the quality of postoperative recovery after laparotomy: a randomized clinical trial.

PURPOSE: Despite the uncertain effects of anxiolytic premedication with benzodiazepines on the quality of postoperative recovery, perioperative benzodiazepine administration is still a common practice in many hospitals. We evaluated the effect of premedication with midazolam on the quality of recovery in hospitalized patients undergoing a laparotomy. METHODS: We conducted a single-centre randomized placebo-controlled, double-blinded clinical trial from July 2014 to September 2015. We included 192 patients aged > 18 yr scheduled for elective laparotomy with a planned postoperative stay of ≥ three days. Participants were randomized into two groups to receive either midazolam 3 mg or sodium chloride 0.9% intravenously as premedication prior to surgery. Patients were followed up for up to one week after surgery. The primary outcome was the Quality of Recovery-40 (QoR-40) score on postoperative day (POD) 3. The secondary outcomes included the QoR-40 score on POD 7, and the State-Trait Anxiety Inventory, State-Trait Anger Scale, Multidimensional Fatigue Inventory, and the Hospital Anxiety and Depression Scale scores. RESULTS: The mean (standard deviation) postoperative QoR-40 scores on POD 3 were not significantly different in the midazolam group compared with controls [166.4 (17.0) vs 163.9 (19.8), respectively; mean difference, 2.3; 95% confidence interval, - 2.9 to 8.4; P = 0.35]. There were no between-group differences in any of the secondary outcomes. CONCLUSIONS: Administration of midazolam as premedication for laparotomy patients did not improve the quality of recovery up to one week after surgery. General prescription of midazolam as premedication can be questioned and might only suit some patients. TRIAL REGISTRATION: www.clinicaltrials.gov (NCT01993459); registered 29 October, 2013.

Meteorological factors for subarachnoid hemorrhage in the greater Düsseldorf area revisited: a machine learning approach to predict the probability of admission of patients with subarachnoid hemorrhage.

BACKGROUND: Reported data regarding the relation between the incidence of spontaneous subarachnoid hemorrhage (SAH) and weather conditions are conflicting and do so far not allow prognostic models. METHODS: Admissions for spontaneous SAH (ICD I60.*) 2009-2018 were retrieved form our hospital data base. Historical meteorological data for the nearest meteorological station, Düsseldorf Airport, was retrieved from the archive of the Deutsche Wetterdienst (DWD). Airport is in the center of our catchment area with a diameter of approximately 100 km. Pearson correlation matrix between mean daily meteorological variables and the daily admissions of one or more patients with subarachnoid hemorrhage was calculated and further analysis was done using deep learning algorithms. RESULTS: For the 10-year period from January 1, 2009 until December 31, 2018, a total of 1569 patients with SAH were admitted. No SAH was admitted on 2400 days (65.7%), 1 SAH on 979 days (26.7%), 2 cases on 233 days (6.4%), 3 SAH on 37 days (1.0%), 4 in 2 days (0.05%), and 5 cases on 1 day (0.03%). Pearson correlation matrix suggested a weak positive correlation of admissions for SAH with precipitation on the previous day and weak inverse relations with the actual mean daily temperature and the temperature change from the previous days, and weak inverse correlations with barometric pressure on the index day and the day before. Clustering with admission of multiple SAH on a given day followed a Poisson distribution and was therefore coincidental. The deep learning algorithms achieved an area under curve (AUC) score of approximately 52%. The small difference from 50% appears to reflect the size of the meteorological impact. CONCLUSION: Although in our data set a weak correlation of the probability to admit one or more cases of SAH with meteorological conditions was present during the analyzed time period, no helpful prognostic model could be deduced with current state machine learning methods. The meteorological influence on the admission of SAH appeared to be in the range of only a few percent compared with random or unknown factors.