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Record W3037735708 · doi:10.1111/head.12246

The <scp>CARE</scp> Guidelines: Consensus‐Based Clinical Case Reporting Guideline Development

2013· editorial· en· W3037735708 on OpenAlexaff
Joel Gagnier, Gunver S. Kienle, Douglas G. Altman, David Moher, Harold C. Sox, D. Riley

Bibliographic record

VenueHeadache The Journal of Head and Face Pain · 2013
Typeeditorial
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersUniversity of Michigan
KeywordsGuidelineChecklistTimelinePsychological interventionTransparency (behavior)MedicineMedical educationSystematic reviewMEDLINEHealth careBest practiceFamily medicinePsychologyNursingComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Background A case report is a narrative that describes, for medical, scientific, or educational purposes, a medical problem experienced by one or more patients. Case reports written without guidance from reporting standards are insufficiently rigorous to guide clinical practice or to inform clinical study design. Objective Develop, disseminate, and implement systematic reporting guidelines for case reports. Methods We used a three‐phase consensus process consisting of (1) pre‐meeting literature review and interviews to generate items for the reporting guidelines, (2) a face‐to‐face consensus meeting to draft the reporting guidelines, and (3) post‐meeting feedback, review, and pilot testing, followed by finalization of the case report guidelines. Results This consensus process involved 27 participants and resulted in a 13‐item checklist—a reporting guideline for case reports. The primary items of the checklist are title, key words, abstract, introduction, patient information, clinical findings, timeline, diagnostic assessment, therapeutic interventions, follow‐up and outcomes, discussion, patient perspective, and informed consent. Conclusions We believe the implementation of the CARE (CAse REport) guidelines by medical journals will improve the completeness and transparency of published case reports and that the systematic aggregation of information from case reports will inform clinical study design, provide early signals of effectiveness and harms, and improve healthcare delivery.

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)0.138
metaresearch head score (Gemma)0.476
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.862
Threshold uncertainty score0.730

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1380.476
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0060.007
Bibliometrics0.0200.018
Science and technology studies0.0030.005
Scholarly communication0.0090.006
Open science0.0120.006
Research integrity0.0140.016
Insufficient payload (model declined to judge)0.0080.009

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 head0.666
GPT teacher head0.568
Teacher spread0.097 · 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.

Study designNot applicable
DomainReporting
GenreEditorial

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

Citations1,261
Published2013
Admission routes1
Has abstractyes

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