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Consensus Practice Guidelines on Postdural Puncture Headache From a Multisociety, International Working Group

2023· article· en· W4385827826 on OpenAlexaff
Vishal Uppal, Robin Russell, Rakesh V. Sondekoppam, Jessica Ansari, Zafeer Baber, Kathryn DelPizzo, Dan Sebastian Dîrzu, Hari Kalagara, Narayan Kissoon, Peter G. Kranz, Lisa Leffert, Grace Lim, Clara Lobo, D. N. Lucas, Εleni Μoka, Stephen E. Rodriguez, Herman Sehmbi, Manuel C. Vallejo, Thomas Volk, Samer Narouze

Bibliographic record

VenueJAMA Network Open · 2023
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsWestern UniversityDalhousie University
FundersAmerican Society of Regional Anesthesia and Pain Medicine
KeywordsMedicineGuidelineMEDLINEGrading (engineering)Delphi methodEvidence-based medicineLumbar punctureSystematic reviewAlternative medicine

Abstract

fetched live from OpenAlex

Importance: Postdural puncture headache (PDPH) can follow unintentional dural puncture during epidural techniques or intentional dural puncture during neuraxial procedures, such as a lumbar puncture or spinal anesthesia. Evidence-based guidance on the prevention, diagnosis, and management of this condition is, however, currently lacking. Objective: To fill the practice guidelines void and provide comprehensive information and patient-centric recommendations for preventing, diagnosing, and managing PDPH. Evidence Review: With input from committee members and stakeholders of 6 participating professional societies, 10 review questions that were deemed important for the prevention, diagnosis, and management of PDPH were developed. A literature search for each question was performed in MEDLINE on March 2, 2022. Additional relevant clinical trials, systematic reviews, and research studies published through March 2022 were also considered for practice guideline development and shared with collaborator groups. Each group submitted a structured narrative review along with recommendations that were rated according to the US Preventive Services Task Force grading of evidence. Collaborators were asked to vote anonymously on each recommendation using 2 rounds of a modified Delphi approach. Findings: After 2 rounds of electronic voting by a 21-member multidisciplinary collaborator team, 47 recommendations were generated to provide guidance on the risk factors for and the prevention, diagnosis, and management of PDPH, along with ratings for the strength and certainty of evidence. A 90% to 100% consensus was obtained for almost all recommendations. Several recommendations were rated as having moderate to low certainty. Opportunities for future research were identified. Conclusions and Relevance: Results of this consensus statement suggest that current approaches to the treatment and management of PDPH are not uniform due to the paucity of evidence. The practice guidelines, however, provide a framework for individual clinicians to assess PDPH risk, confirm the diagnosis, and adopt a systematic approach to its management.

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)0.116
metaresearch head score (Gemma)0.251
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.116
Threshold uncertainty score0.611

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1160.251
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0050.008
Bibliometrics0.0180.012
Science and technology studies0.0030.003
Scholarly communication0.0080.007
Open science0.0120.011
Research integrity0.0170.013
Insufficient payload (model declined to judge)0.0090.008

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 head0.091
GPT teacher head0.377
Teacher spread0.286 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations63
Published2023
Admission routes1
Has abstractyes

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