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Record W2516721032 · doi:10.12688/f1000research.9323.2

Collecting clinical data in primary ciliary dyskinesia- challenges and opportunities

2016· preprint· en· W2516721032 on OpenAlexaff
Israel Amirav, Mary Roduta Roberts, Huda Mussaffi, Avigdor Mandelberg, Yehudah Roth, Revital Abitbul, Anthony Luder, Hannah Blau, Soliman Alkrinawi, Micha Aviram, Marta Ben-Ami, Moshe Rotschild, Lea Bentur, David Shoseyov, Malena Cohen‐Cymberknoh, Eitan Kerem, Avraham Avital, Chaim Springer, Avigdor Hevroni, Husein Dabbah, Arnon Elizur, Elie Picard, Shmuel Goldberg, Joseph Rivlin, Galit Livnat, Moran Lavie, Nael Alias, Ruth Soferman, Heike Olbrich, Johanna Raidt, Julia Wallmeier, Claudius Werner, Niki T. Loges, Heymut Omran

Bibliographic record

VenueF1000Research · 2016
Typepreprint
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPrimary ciliary dyskinesiaMedicineConsistency (knowledge bases)DyskinesiaData collectionOpen peer reviewInternal consistencyPathologyPlant biologyComputer sciencePsychometricsInternal medicineClinical psychologyBronchiectasis

Abstract

fetched live from OpenAlex

<ns4:p> <ns4:bold>Rationale:</ns4:bold> Primary ciliary dyskinesia (PCD) is under diagnosed and underestimated. Most clinical research has used some form of questionnaires to capture data but none has been critically evaluated particularly with respect to its end-user feasibility and utility. </ns4:p> <ns4:p/> <ns4:p> <ns4:bold>Objective:</ns4:bold> To critically appraise a clinical data collection questionnaire for PCD used in a large national PCD consortium in order to apply conclusions in future PCD research. </ns4:p> <ns4:p/> <ns4:p> <ns4:bold>Methods:</ns4:bold> We describe the development, validation and revision process of a clinical questionnaire for PCD and its evaluation during a national clinical PCD study with respect to data collection and analysis, initial completion rates and user feedback. </ns4:p> <ns4:p/> <ns4:p> <ns4:bold>Results:</ns4:bold> 14 centers participating in the consortium successfully completed the revised version of the questionnaire for 173 patients with various completion rates for various items. While content and internal consistency analysis demonstrated validity, there were methodological deficiencies impacting completion rates and end-user utility. These deficiencies were addressed resulting in a more valid questionnaire. </ns4:p> <ns4:p/> <ns4:p> <ns4:bold>Conclusions:</ns4:bold> Our experience may be useful for future clinical research in PCD. Based on the feedback collected on the questionnaire through analysis of completion rates, judgmental analysis of the content, and feedback from experts and end users, we suggest a practicable framework for development of similar tools for various future PCD research. </ns4:p>

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.910
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.011
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.469
GPT teacher head0.494
Teacher spread0.025 · 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 teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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
Published2016
Admission routes1
Has abstractyes

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