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FAT AND NEUROSURGERY

2009· review· en· W2080932502 on OpenAlexaff
Kim E. Schultheiss, Yeon Gyoe Jang, Rachel N. Yanowitch, Jocelyn Tolentino, Daniel J. Curry, Jürgen Lüders, Farbod Asgarzadie-Gadim, R. Loch Macdonald

Bibliographic record

VenueNeurosurgery · 2009
Typereview
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineGlasgow Coma ScaleGlasgow Outcome ScaleNeurosurgerySubarachnoid hemorrhageBody mass indexSurgeryNeurologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Obesity has been linked to increased morbidity and mortality after some surgical procedures. The purpose of this study was to determine whether obesity affects outcome after general neurosurgery and subarachnoid hemorrhage (SAH). METHODS: Three data sets were analyzed, including a retrospective review of 404 patients undergoing cranial and spinal neurosurgical procedures, a prospective collection of 100 patients with aneurysmal SAH, and data from 3567 patients with aneurysmal SAH who were entered into randomized clinical trials of tirilazad. For each data set, outcome was assessed by mortality, postoperative morbidity, and Glasgow Outcome Scale score. Prognostic factors, including body weight and body mass index, were tested for their effect on these outcomes using multivariable logistic regression. RESULTS: For patients undergoing general cranial and spinal neurosurgery, independent predictors of morbidity and mortality were age, American Society of Anesthesia class, disseminated malignancy, emergency surgery, and increased duration of surgery. For patients with SAH, score on the Glasgow Outcome Scale was associated with age and admission Glasgow Coma Scale score. In the tirilazad data set, multiple factors were associated with score on the Glasgow Outcome Scale, but, as with the other 2 data sets, body weight had no relationship to outcome. CONCLUSION: Obesity may have less effect on the outcome of patients with mainly cranial neurosurgical disease and aneurysmal SAH than it does on patients undergoing other types of surgery.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.056
GPT teacher head0.312
Teacher spread0.256 · 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.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations38
Published2009
Admission routes1
Has abstractyes

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