Evidence-based clinical practice guidelines on postdural puncture headache: a consensus report from a multisociety international working group
Bibliographic record
Abstract
INTRODUCTION: 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 or management of this condition is, however, currently lacking. This multisociety guidance aims to fill this void and provide practitioners with comprehensive information and patient-centric recommendations to prevent, diagnose and manage patients with PDPH. METHODS: Based on input from committee members and stakeholders, the committee cochairs developed 10 review questions deemed important for the prevention, diagnosis and management of PDPH. A literature search for each question was performed in MEDLINE (Ovid) on 2 March 2022. The results from each search were imported into separate Covidence projects for deduplication and screening, followed by data extraction. Additional relevant clinical trials, systematic reviews and research studies published through March 2022 were also considered for the development of guidelines and shared with contributors. Each group submitted a structured narrative review along with recommendations graded according to the US Preventative Services Task Force grading of evidence. The interim draft was shared electronically, with each collaborator requested to vote anonymously on each recommendation using two rounds of a modified Delphi approach. RESULTS: Based on contemporary evidence and consensus, the multidisciplinary panel generated 50 recommendations to provide guidance regarding risk factors, prevention, diagnosis and management of PDPH, along with their strength and certainty of evidence. After two rounds of voting, we achieved a high level of consensus for all statements and recommendations. Several recommendations had moderate-to-low certainty of evidence. CONCLUSIONS: These clinical practice guidelines for PDPH provide a framework to improve identification, evaluation and delivery of evidence-based care by physicians performing neuraxial procedures to improve the quality of care and align with patients' interests. Uncertainty remains regarding best practice for the majority of management approaches for PDPH due to the paucity of evidence. Additionally, opportunities for future research are identified.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.181 | 0.292 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.012 |
| Bibliometrics | 0.034 | 0.024 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.014 | 0.015 |
| Research integrity | 0.015 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".