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Record W3042434630 · doi:10.1371/journal.pntd.0008294

The data are inadequate to assess safety and efficacy of mass chemotherapy for Taenia solium taeniasis

2020· letter· en· W3042434630 on OpenAlexaff
A. Clinton White, Seth E. O’Neal, Andrea Sylvia Winkler, Annette Abraham, Hélène Carabin

Bibliographic record

VenuePLoS neglected tropical diseases · 2020
Typeletter
Languageen
FieldMedicine
TopicParasitic infections in humans and animals
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsTaenia soliumTaeniasisMedicineAlbendazolePublic healthPraziquantelNeglected tropical diseasesNeurocysticercosisCysticercosisIntensive care medicineEnvironmental healthSurgeryPsychiatryPathologyImmunologySchistosomiasisHelminthsCestode infections

Abstract

fetched live from OpenAlex

As members of the Pan American Health Organization (PAHO) and World Health Organization (WHO) guidelines development group on chemotherapy strategies for the control of Taenia solium taeniasis, we are very disappointed at the systematic review by Haby and colleagues. With respect to the analysis of efficacy, the authors did not account for differences in the methods used to ascertain the outcome in the studies analyzed. There are also major concerns regarding the safety analyses. Few of the included studies used carefully designed active surveillance protocols to detect epileptic seizures and/or chronic progressive headaches. These neurologic side effects, due the inadvertent killing of viable brain cysts, have been noted after mass therapy with praziquantel and albendazole. We wholeheartedly agree with the authors' statement in their discussion that control programs applying chemotherapy using mass drug administration "need to be informed by evidence of the best drug and dose in terms of efficacy and side-effects." Unfortunately, the flawed analysis that was published is contrary to that goal.

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)0.048
metaresearch head score (Gemma)0.302
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.048
Threshold uncertainty score0.254

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.302
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0040.004
Science and technology studies0.0020.004
Scholarly communication0.0040.007
Open science0.0030.003
Research integrity0.0210.017
Insufficient payload (model declined to judge)0.0050.005

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 head0.074
GPT teacher head0.327
Teacher spread0.253 · 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
GenreCommentary

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

Citations5
Published2020
Admission routes1
Has abstractyes

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