Skip to main content
Top
Published in: Acta Neurochirurgica 2/2019

01-02-2019 | Nosocomial Infection | Original Article - Brain Tumors

Adverse events in brain tumor surgery: incidence, type, and impact on current quality metrics

Authors: Stephanie Schipmann, Tobias Brix, Julian Varghese, Nils Warneke, Michael Schwake, Benjamin Brokinkel, Christian Ewelt, Martin Dugas, Walter Stummer

Published in: Acta Neurochirurgica | Issue 2/2019

Login to get access

Abstract

Background

The aim of the study was to determine pre-operative factors associated with adverse events occurring within 30 days after neurosurgical tumor treatment in a German center, adjusting for their incidence in order to prospectively compare different centers.

Methods

Adult patients that were hospitalized due to a benign or malignant brain were retrospectively assessed for quality indicators and adverse events. Analyses were performed in order to determine risk factors for adverse events and reasons for readmission and reoperation.

Results

A total of 2511 cases were enrolled. The 30 days unplanned readmission rate to the same hospital was 5.7%. The main reason for readmission was tumor progression. Every 10th patient had an unplanned reoperation. The incidence of surgical revisions due to infections was 2.3%. Taking together all monitored adverse events, male patients had a higher risk for any of these complications (OR 1.236, 95%CI 1.025–1.490, p = 0.027). Age, sex, and histological diagnosis were predictors of experiencing any complication. Adjusted by incidence, the increased risk ratios greater than 10.0% were found for male sex, age, metastatic tumor, and hemiplegia for various quality indicators.

Conclusions

We found that most predictors of outcome rates are based on preoperative underlying medical conditions and are not modifiable by the surgeon. Comparing our results to the literature, we conclude that differences in readmission and reoperation rates are strongly influenced by standards in decision making and that comparison of outcome rates between different health-care providers on an international basis is challenging. Each health-care system has to develop own metrics for risk adjustment that require regular reassessment.
Appendix
Available only for authorised users
Literature
7.
go back to reference Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373–383CrossRefPubMed Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373–383CrossRefPubMed
8.
go back to reference Charlson M, Szatrowski TP, Peterson J, Gold J (1994) Validation of a combined comorbidity index. J Clin Epidemiol 47:1245–1251CrossRefPubMed Charlson M, Szatrowski TP, Peterson J, Gold J (1994) Validation of a combined comorbidity index. J Clin Epidemiol 47:1245–1251CrossRefPubMed
17.
go back to reference Fukamachi A, Koizumi H, Nukui H (1985) Postoperative intracerebral hemorrhages: a survey of computed tomographic findings after 1074 intracranial operations. Surg Neurol 23:575–580CrossRefPubMed Fukamachi A, Koizumi H, Nukui H (1985) Postoperative intracerebral hemorrhages: a survey of computed tomographic findings after 1074 intracranial operations. Surg Neurol 23:575–580CrossRefPubMed
23.
go back to reference Kalfas IH, Little JR (1988) Postoperative hemorrhage: a survey of 4992 intracranial procedures. Neurosurgery 23:343–347CrossRefPubMed Kalfas IH, Little JR (1988) Postoperative hemorrhage: a survey of 4992 intracranial procedures. Neurosurgery 23:343–347CrossRefPubMed
24.
go back to reference Khuri SF, Daley J, Henderson W, Hur K, Demakis J, Aust JB, Chong V, Fabri PJ, Gibbs JO, Grover F, Hammermeister K, Irvin G 3rd, McDonald G, Passaro E Jr, Phillips L, Scamman F, Spencer J, Stremple JF (1998) The Department of Veterans Affairs’ NSQIP: the first national, validated, outcome-based, risk-adjusted, and peer-controlled program for the measurement and enhancement of the quality of surgical care. National VA surgical quality improvement program. Ann Surg 228:491–507CrossRefPubMedPubMedCentral Khuri SF, Daley J, Henderson W, Hur K, Demakis J, Aust JB, Chong V, Fabri PJ, Gibbs JO, Grover F, Hammermeister K, Irvin G 3rd, McDonald G, Passaro E Jr, Phillips L, Scamman F, Spencer J, Stremple JF (1998) The Department of Veterans Affairs’ NSQIP: the first national, validated, outcome-based, risk-adjusted, and peer-controlled program for the measurement and enhancement of the quality of surgical care. National VA surgical quality improvement program. Ann Surg 228:491–507CrossRefPubMedPubMedCentral
27.
go back to reference Levin ML (1953) The occurrence of lung cancer in man. Acta Unio Int Contra Cancrum 9:531–541PubMed Levin ML (1953) The occurrence of lung cancer in man. Acta Unio Int Contra Cancrum 9:531–541PubMed
29.
go back to reference McCutcheon BA, Ubl DS, Babu M, Maloney P, Murphy M, Kerezoudis P, Bydon M, Habermann EB, Parney I (2016) Predictors of surgical site infection following craniotomy for intracranial neoplasms: an analysis of prospectively collected data in the American College of Surgeons National Surgical Quality Improvement Program Database. World Neurosurg 88:350–358. https://doi.org/10.1016/j.wneu.2015.12.068 CrossRefPubMed McCutcheon BA, Ubl DS, Babu M, Maloney P, Murphy M, Kerezoudis P, Bydon M, Habermann EB, Parney I (2016) Predictors of surgical site infection following craniotomy for intracranial neoplasms: an analysis of prospectively collected data in the American College of Surgeons National Surgical Quality Improvement Program Database. World Neurosurg 88:350–358. https://​doi.​org/​10.​1016/​j.​wneu.​2015.​12.​068 CrossRefPubMed
34.
go back to reference Palmer JD, Sparrow OC, Iannotti F (1994) Postoperative hematoma: a 5-year survey and identification of avoidable risk factors. Neurosurgery 35:1061–1064 discussion 1064-1065 CrossRefPubMed Palmer JD, Sparrow OC, Iannotti F (1994) Postoperative hematoma: a 5-year survey and identification of avoidable risk factors. Neurosurgery 35:1061–1064 discussion 1064-1065 CrossRefPubMed
39.
go back to reference Senders JT, Muskens IS, Cote DJ, Goldhaber NH, Dawood HY, Gormley WB, Broekman MLD, Smith TR (2018) Thirty-day outcomes after craniotomy for primary malignant brain tumors: a National Surgical Quality Improvement Program Analysis. Neurosurgery. https://doi.org/10.1093/neuros/nyy001 Senders JT, Muskens IS, Cote DJ, Goldhaber NH, Dawood HY, Gormley WB, Broekman MLD, Smith TR (2018) Thirty-day outcomes after craniotomy for primary malignant brain tumors: a National Surgical Quality Improvement Program Analysis. Neurosurgery. https://​doi.​org/​10.​1093/​neuros/​nyy001
44.
go back to reference Wolters U, Wolf T, Stutzer H, Schroder T (1996) ASA classification and perioperative variables as predictors of postoperative outcome. Br J Anaesth 77:217–222CrossRefPubMed Wolters U, Wolf T, Stutzer H, Schroder T (1996) ASA classification and perioperative variables as predictors of postoperative outcome. Br J Anaesth 77:217–222CrossRefPubMed
46.
go back to reference Zhang J, Yu KF (1998) What’s the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA 280:1690–1691CrossRefPubMed Zhang J, Yu KF (1998) What’s the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA 280:1690–1691CrossRefPubMed
Metadata
Title
Adverse events in brain tumor surgery: incidence, type, and impact on current quality metrics
Authors
Stephanie Schipmann
Tobias Brix
Julian Varghese
Nils Warneke
Michael Schwake
Benjamin Brokinkel
Christian Ewelt
Martin Dugas
Walter Stummer
Publication date
01-02-2019
Publisher
Springer Vienna
Published in
Acta Neurochirurgica / Issue 2/2019
Print ISSN: 0001-6268
Electronic ISSN: 0942-0940
DOI
https://doi.org/10.1007/s00701-018-03790-4

Other articles of this Issue 2/2019

Acta Neurochirurgica 2/2019 Go to the issue