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Record W4385398369 · doi:10.1136/jnis-2023-snis.21

O-021 Concurrent middle meningeal artery embolization for treatment of chronic subdural hematomas

2023· article· en· W4385398369 on OpenAlexfundno aff
W. Salah, Cordell M. Baker, J. T. Scoville, J Hunsaker, Christopher S. Ogilvy, Justin M. Moore, Howard A. Riina, Elad I. Levy, Alejandro M Spiotta, Brian T. Jankowitz, C. Michael Cawley, Alex A Khalessi, O Tanweer, Ricardó A. Hanel, Bradley A. Gross, O Kuybu, Alex Nguyen Hoang, Ammad A. Baig, M Khorasanizadeh, A. Méndez, Gustavo M Cortez, Jason M. Davies, Sandra Narayanan, Brian M. Howard, Michael J. Lang, Adnan H. Siddiqui, Ajith J. Thomas, Peter Kan, Jan‐Karl Burkhardt, Mohamed M. Salem, Ramesh Grandhi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicNeurosurgical Procedures and Complications
Canadian institutionsnot available
FundersUniversity of California, San DiegoSchool of Medicine, New York UniversityYork UniversityUniversity of South CarolinaUniversity of WashingtonEmory University
KeywordsMedicinePerioperativeSurgeryModified Rankin ScaleEmbolizationNeurosurgeryHematomaCohortInternal medicine

Abstract

fetched live from OpenAlex

<h3></h3> Non-acute subdural hematomas (NASHs) are expected to be the most common cranial neurosurgery pathology encountered by the year 2030. Treatment with surgical evacuation may be necessary, but the rate of recurrence after surgical intervention has been reported to be as high as 30%. Minimally invasive middle meningeal artery embolization (MMAe) during the perioperative period has been posited as an adjunctive treatment to decrease recurrence after surgical evacuation of NASH. The authors evaluated the safety and efficacy of MMAe in a multi-institutional cohort. Data from 145 patients with NASH who underwent surgical evacuation and concurrent MMA embolization in the perioperative period were retrospectively collected from 15 institutions. The primary outcome was rates of NASH recurrence requiring repeat surgical intervention. We collected clinical data including use of anticoagulants and/or antiplatelets, prior treatment of NASH, and perioperative platelet counts; treatment data including anesthesia type, type of embolic agent, length of hospital stay, and access type; and radiographic data including laterality of the NASH, presence of subdural membranes, MMA size, presence of dangerous collaterals, and median width of the NASH at initial presentation, after evacuation, and at 90-day follow-up. This data can be seen in table 1. Radiographic features of the NASHs at last follow-up were included size reductions/improvements. Radiographic features at last follow-up are summarized in table 2. Outcomes data collected included: mortality, adverse events, and modified Rankin Scale (mRS) score at last follow-up, results can be seen in table 3. The median preoperative hematoma width was 18 mm, and subdural membranes were present on imaging in 87% of patients. At 90-day follow-up, the median NASH width was 6 mm, and 51% of patients had at least a 50% decrease of NASH size. At last clinical follow up, 87% had the same or improved mRS score. Eight percent of treated NASHs had recurrence requiring additional surgery. The total all-cause mortality was 6%. This study provides evidence from a multi-institutional cohort that performing concurrent MMAe in the perioperative period as an adjunct to surgical evacuation is a safe and effective means to reduce surgical recurrence in patients with NASHs. <h3>Disclosures</h3> <b>W. Salah:</b> None. <b>C. Baker:</b> None. <b>J. Scoville:</b> None. <b>J. Hunsaker:</b> None. <b>C. Ogilvy:</b> None. <b>J. Moore:</b> None. <b>H. Riina:</b> None. <b>E. Levy:</b> None. <b>A. Spiotta:</b> None. <b>B. Jankowitz:</b> None. <b>C. Cawley:</b> None. <b>A. Khalessi:</b> None. <b>O. Tanweer:</b> None. <b>R. Hanel:</b> None. <b>B. Gross:</b> None. <b>O. Kuybu:</b> None. <b>A. Nguyen Hoang:</b> None. <b>A. Baig:</b> None. <b>M. Khorasanizadeh:</b> None. <b>A. Mendez:</b> None. <b>G. Cortez:</b> None. <b>J. Davies:</b> None. <b>S. Narayanan:</b> None. <b>B. Howard:</b> None. <b>M. Lang:</b> None. <b>A. Siddiqui:</b> None. <b>A. Thomas:</b> None. <b>P. Kan:</b> None. <b>J. Burkhardt:</b> None. <b>M. Salem:</b> None. <b>R. Grandhi:</b> None.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.090
GPT teacher head0.339
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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