Predictors of Reoperation in 30 days in Subdural Hematoma Evacuation

Author:

Sayed Rahman1,Zamarud Aroosa2,Gross Suzanne1,Ramos Rafael De La Garza1,Holland Ryan1,Eikermann Matthias1,Rupp Samuel1,Kim Jinu1,Babar Mustufa1,Basam Mudaser1,Yassari Reza1,Gelfand Yaroslav1

Affiliation:

1. Montefiore Medical Center

2. Stanford school of medicine

Abstract

Abstract Introduction: Subdural hematoma (SDH) represents one of the most common types of intracranial hemorrhages, particularly in the elderly. Despite a long history of diagnoses and procedures, there is conflicting data on predictive parameters to predict outcomes. Methods We conducted a large retrospective review of patients that underwent a SDH evacuation at a single urban institution between 2015–2022. Data were collected from the electronic medical record on prior comorbidities, anticoagulation use, mental status on presentation, pre-op labs, and pre/post-op imaging parameters. Univariate and multivariate analyses were conducted to analyze predictors of reoperation. Results Of the 329 patients, 35 patients were excluded due to missing data in the EMR. 10% of the patients underwent reoperation with the average time to reoperation being 17 days. Univariate analysis showed that a prior history of chronic kidney disease was associated with higher rates of reoperation. Lab data showed that those presenting with elevated PTT were more likely to undergo reoperation. Analysis of the imaging data showed that patients with a post-op shift of 6 mm or greater were more likely to undergo reoperation. Multivariate analysis showed that only having a post-op shift of greater than 6 mm was a significant predictor of reoperation. Twenty-two percent of patients with post-op shifts over 6 mm needed re-op. We briefly compared those below and above 65 and found no increase in instances of persistent shift over 6 mm in the older group. Interestingly, having a higher PTT lead to lower rates of reoperation Conclusion On multivariate analysis, a post-op shift of over 6 mm is the only independent predictor of re-operations. Further analysis would be beneficial to better understand predictors of reoperation. A review of the current literature showed that this is one of the largest series from a single institution with granular data available for analysis.

Publisher

Research Square Platform LLC

Reference18 articles.

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