When to discharge patients following a neuronavigation-assisted brain biopsy for supratentorial lesion? A single-center experience

OBJECTIVE

Most brain biopsies are performed using the frame-based stereotactic technique and several studies describe the time taken and rate of complications, often allowing an early discharge. In comparison, neuronavigation-assisted biopsies are performed under general anesthesia and their complications have been poorly described. We examined the complication rate and determined which patients will worsen clinically.

METHODS

All adults who underwent a neuronavigation-assisted brain biopsy for a supratentorial lesion from Jan, 2015, to Jan, 2021, in the Neurosurgical Department of the University Hospital Center of Bordeaux, France, were analyzed retrospectively in accordance with the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) statement. The primary outcome of interest was short-term (7 days) clinical deterioration. The secondary outcome of interest was the complication rate.

RESULTS

The study included 240 patients. The median postoperative Glasgow score was 15. Thirty patients (12.6 %) showed acute postoperative clinical worsening, including 14 (5.8 %) with permanent neurological worsening. The median delay was 22 h after the intervention. We examined several clinical combinations that allowed early postoperative discharge. A preoperative Glasgow prognostic score of 15, Charlson Comorbidity Index ≤ 3, preoperative World Health Organization Performance Status ≤ 1, and no preoperative anticoagulation or antiplatelet treatment predicted postoperative worsening (negative predictive value, 96.3 %).

CONCLUSION

Optical neuronavigation-assisted brain biopsies might require longer postoperative observation than frame-based biopsies. Based on strict preoperative clinical criteria, we consider to plan postoperative observation for 24 h a sufficient hospital stay for patients who undergo these brain biopsies.

Dynamic individual vital sign trajectory early warning score (DyniEWS) versus snapshot national early warning score (NEWS) for predicting postoperative deterioration

Aims

International early warning scores (EWS) including the additive National Early Warning Score (NEWS) and logistic EWS currently utilise physiological snapshots to predict clinical deterioration. We hypothesised that a dynamic score including vital sign trajectory would improve discriminatory power.

Methods

Multicentre retrospective analysis of electronic health record data from postoperative patients admitted to cardiac surgical wards in four UK hospitals. Least absolute shrinkage and selection operator-type regression (LASSO) was used to develop a dynamic model (DyniEWS) to predict a composite adverse event of cardiac arrest, unplanned intensive care re-admission or in-hospital death within 24 h.

Results

A total of 13,319 postoperative adult cardiac patients contributed 442,461 observations of which 4234 (0.96%) adverse events in 24 h were recorded. The new dynamic model (AUC = 0.80 [95% CI 0.78−0.83], AUPRC = 0.12 [0.10−0.14]) outperforms both an updated snapshot logistic model (AUC = 0.76 [0.73−0.79], AUPRC = 0.08 [0.60−0.10]) and the additive National Early Warning Score (AUC = 0.73 [0.70−0.76], AUPRC = 0.05 [0.02−0.08]). Controlling for the false alarm rates to be at current levels using NEWS cut-offs of 5 and 7, DyniEWS delivers a 7% improvement in balanced accuracy and increased sensitivities from 41% to 54% at NEWS 5 and 18% to –30% at NEWS 7.

Conclusions

Using an advanced statistical approach, we created a model that can detect dynamic changes in risk of unplanned readmission to intensive care, cardiac arrest or in-hospital mortality and can be used in real time to risk-prioritise clinical workload.