Development and validation of prediction scores for nosocomial infections, reoperations, and adverse events in the daily clinical setting of neurosurgical patients with cerebral and spinal tumors.
Adolescent
Adult
Aged
Aged, 80 and over
Brain Neoplasms
/ complications
Cohort Studies
Cross Infection
/ diagnosis
Female
Humans
Incidence
Inflammation
/ complications
Male
Middle Aged
Neurosurgical Procedures
/ adverse effects
Postoperative Complications
/ epidemiology
Predictive Value of Tests
ROC Curve
Reoperation
/ statistics & numerical data
Risk Assessment
Spinal Neoplasms
/ complications
Treatment Outcome
Young Adult
brain tumor
infection
quality indicators
risk assessment
risk score
Journal
Journal of neurosurgery
ISSN: 1933-0693
Titre abrégé: J Neurosurg
Pays: United States
ID NLM: 0253357
Informations de publication
Date de publication:
20 Mar 2020
20 Mar 2020
Historique:
received:
25
11
2019
accepted:
13
01
2020
pubmed:
21
3
2020
medline:
31
7
2021
entrez:
21
3
2020
Statut:
epublish
Résumé
Various quality indicators are currently under investigation, aiming at measuring the quality of care in neurosurgery; however, the discipline currently lacks practical scoring systems for accurately assessing risk. The aim of this study was to develop three accurate, easy-to-use risk scoring systems for nosocomial infections, reoperations, and adverse events for patients with cerebral and spinal tumors. The authors developed a semiautomatic registry with administrative and clinical data and included all patients with spinal or cerebral tumors treated between September 2017 and May 2019. Patients were further divided into development and validation cohorts. Multivariable logistic regression models were used to develop risk scores by assigning points based on β coefficients, and internal validation of the scores was performed. In total, 1000 patients were included. An unplanned 30-day reoperation was observed in 6.8% of patients. Nosocomial infections were documented in 7.4% of cases and any adverse event in 14.5%. The risk scores comprise variables such as emergency admission, nursing care level, ECOG performance status, and inflammatory markers on admission. Three scoring systems, NoInfECT for predicting the incidence of nosocomial infections (low risk, 1.8%; intermediate risk, 8.1%; and high risk, 26.0% [p < 0.001]), LEUCut for 30-day unplanned reoperations (low risk, 2.2%; intermediate risk, 6.8%; and high risk, 13.5% [p < 0.001]), and LINC for any adverse events (low risk, 7.6%; intermediate risk, 15.7%; and high risk, 49.5% [p < 0.001]), showed satisfactory discrimination between the different outcome groups in receiver operating characteristic curve analysis (AUC ≥ 0.7). The proposed risk scores allow efficient prediction of the likelihood of adverse events, to compare quality of care between different providers, and further provide guidance to surgeons on how to allocate preoperative care.
Identifiants
pubmed: 32197255
doi: 10.3171/2020.1.JNS193186
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM