Gabapentin for Neuropathic Pain: An application to the 21st meeting of the WHO Expert Committee on Selection and Use of Essential Medicines for the inclusion of gabapentin on the WHO Model List of Essential Medicines
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABOUTThis repository contains all the files required to generate the application (and supporting documents) the International Association for the Study of Pain (IASP) and the International Association of Hospice and Palliative Care (IAHPC) made to the 21st meeting of the WHO Expert Committee on Selection and Use of Essential Medicines (2017) for the inclusion of gabapentin on the WHO Model List of Essential Medicines for the treatment of neuropathic pain.For a brief summary of why we have applied for the inclusion of an additional medicine to treat neuropathic pain on the WHO Model List, see:Neuropathic pain: so many people, but where are the drugs?World Health Organization essential medicines lists: where are the drugs to treat neuropathic pain? <em>PAIN</em>156:793-797, 2015. DOI: 10.1097/01.j.pain.0000460356.94374.a1, PMC: 4670621CITATIONKamerman PR, Finnerup NB, De Lima L, Haroutounian S, Raja SN, Rice ASC, Smith BH, Treede RD. Gabapentin for neuropathic pain: An application to the 21st meeting of the WHO Expert Committee on Selection and Use of Essential Medicines for the inclusion of gabapentin on the WHO Model List of Essential Medicines. DOI: 10.6084/m9.figshare.3814206.v2, 2016ACKNOWLEGEMENTSWe are indebted to our four external reviewers for their constructive comments:Michael I Bennett (UK)Daniel Ciampi de Andrada (Brazil)G Allen Finley (Canada)Telesphore B Nguelefack (Cameroon)We also thank Dr Nicola Magrini (Secretary of the Expert Committee on the Selection and Use of Essential Medicines) and Dr Tarun Dua (Department of Mental Health and Substance Abuse) for their assistance and constructive feedback.INSTRUCTIONSDownload a complete copyClick on this link to access a PDF of the complete document (application and appendices).Build the documentFollow the steps below to compile the application, appendices, and the executive summary.Windows users must first download and install:<em>Git for Windows</em> or any other <em>Bash</em>-like shell for Windows.<em>GNU Make</em>.If you use Git/GitHub:<em>Fork</em> the repository to your GitHub account.<em>Clone</em> the repository to your computer.Open a <em>terminal</em> and change the path to the directory of the respository.Type <em>'make'</em>.If you do not use Git/GitHub:<em>Download</em> the repository as a zip file.<em>Unzip</em> the repository on your computer.Open a <em>terminal</em> and change the path to the directory you unzipped the repository into.Type <em>'make'</em>.The following set-up was used to generate all filesR version 3.3.1 (2016-06-21) running on RStudio v1.0.44 for macOS SierraPackages used (inclusive of: <em>application.Rmd</em>, <em>appendices.Rmd</em>, <em>summary.Rmd</em>, and all other analysis scripts):cowplot 0.7.0dplyr 0.5.0ggplot2 2.2.0gridExtra 2.2.1knitr 1.15pander 0.6.0readr 1.0.0rmeta 2.16scales 0.4.1stringr 1.1.0tidyr 0.6.0xtable 1.8-2LICENSEGabapentin for neuropathic pain: An application to the 21st meeting of the WHO Expert Committee on Selection and Use of Essential Medicines for the inclusion of gabapentin on the WHO Model List of Essential Medicines by the International Association for the Study of Pain (IASP) and the International Association of Hospice and Palliative Care (IAHPC) is licensed under a Creative Commons Attribution 4.0 International License.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it