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Correlation of Early Cognitive Impairment in Intracerebral Haemorrhage from Tertiary Care Hospital of North Karnataka

2024· article· en· W4390839394 on OpenAlexaboutno aff
M Dhananjaya, Kiran Hukkeri, Sharankumar Sharankumar, Manoj Manoj

Bibliographic record

VenueSAS Journal of Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsnot available
Fundersnot available
KeywordsCognitive impairmentMedicineMontreal Cognitive AssessmentIntracerebral hemorrhageCognitionRadiological weaponPediatricsInternal medicineSurgeryPsychiatrySubarachnoid hemorrhage

Abstract

fetched live from OpenAlex

Objectives: To identify the correlation of early cognitive impairment following intracerebral haemorrhage. Methods: A total of 30 adult patients (>15 years) with intracerebral hemorrhage were enrolled in the study. Demographic profile, clinical and radiological profile of the patients was noted. Cognitive status at discharge was assessed using Montreal Cognitive Assessment (MoCA). Results: Mean age was 63.53±12.11 years. Majority were males (56.7%). All the patients had cognitive impairment - majority (76.7%) had moderate cognitive impairment followed by severe impairment (16.7%) and mild impairment (6.7%) respectively at time of discharge. History of tobacco use showed a significant association with severe cognitive impairment. Conclusions: Mild to moderate cognitive impairment is quite frequent among intracerebral hemorrhage patients at time of discharge irrespective of the clinical, demographic and radiological profile.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.284
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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