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Record W4399919097 · doi:10.1016/j.heliyon.2024.e33460

Association of C-reactive protein/albumin ratio with mortality in patients with Traumatic Brain Injury: A systematic review and meta-analysis

2024· review· en· W4399919097 on OpenAlexaboutno aff
Yuyang Liu, Yaheng Tan, Jun Wan, Qiwen Chen, Yuxin Zheng, Wenhao Xu, Peng Wang, Weelic Chong, Xueying Yu, Yu Zhang

Bibliographic record

VenueHeliyon · 2024
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsnot available
FundersChengdu UniversitySichuan UniversityTangshan Science and Technology BureauWest China Hospital, Sichuan UniversityChongqing Municipal Education CommissionNational Natural Science Foundation of China
KeywordsMedicineOdds ratioTraumatic brain injuryMeta-analysisConfidence intervalInternal medicineSubgroup analysisCochrane LibraryC-reactive proteinInflammationPsychiatry

Abstract

fetched live from OpenAlex

Objective: This study examines the C-reactive protein (CRP)/albumin ratio (CAR) as an inflammation-based prognostic score for predicting mortality in patients with Traumatic Brain Injury (TBI). Methods: We systematically searched the electronic databases PubMed, Embase, and Cochrane up to February 2024. Our inclusion criteria encompassed studies investigating CAR-predicted mortality in patients with TBI. We calculated the Odds Ratio (OR) and associated 95 % confidence intervals (95 % CI) using a random-effects model. Quality assessment of the included studies was appraised using a Newcastle-Ottawa scale. Results: A total of five studies comprising 1040 patients were included in this meta-analysis. The pooled results indicated that CAR was associated with mortality in patients with TBI (OR = 1.88, 95 % CI: 1.05-3.36, P < 0.0001). The findings of subgroup analysis indicated that the relationship between CAR and mortality in patients with TBI did not vary with the severity of the condition. Conclusions: CAR emerges as a valuable prognostic tool for mortality in patients with TBI, underscoring its potential role in early risk stratification and management strategies.

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)0.001
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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.591
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0100.001
Bibliometrics0.0000.002
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 head0.058
GPT teacher head0.338
Teacher spread0.279 · 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 designSystematic review
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

Citations6
Published2024
Admission routes1
Has abstractyes

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