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Record W6990472242

Do Case Reports and Case Series Generate Clinical Discoveries About Preeclampsia? A Systematic Review

2023· article· en· W6990472242 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Ecology and Soil Science
Canadian institutionsnot available
Fundersnot available
KeywordsEpidemiologyPublic healthGovernment (linguistics)Obstetrics and gynaecologyPreeclampsiaUniversity hospitalHealth careClinical epidemiology
DOInot available

Abstract

fetched live from OpenAlex

Ghayath Janoudi,1,2 Mara Uzun (Rada),3 Stephanie T Boyd,1 Deshayne B Fell,2,4 Joel G Ray,5 Angel M Foster,6 Randy Giffen,7 Tammy J Clifford,2,8 Mark C Walker1,2,9– 12 1Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada; 2School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada; 3Independent Researcher, Ottawa, ON, Canada; 4Children’s Hospital of Eastern Ontario (CHEO) Research Institute, Children’s Hospital of Eastern Ontario, Ottawa, ON, Canada; 5Departments of Medicine, Health Policy Management and Evaluation, and Obstetrics and Gynecology, St Michael’s Hospital, University of Toronto, Toronto, ON, Canada; 6Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada; 7IBM Canada, IBM, Toronto, ON, Canada; 8Canadian Institute of Health Research, Government of Canada, Ottawa, ON, Canada; 9International and Global Health Office, University of Ottawa, Ottawa, ON, Canada; 10Department of Obstetrics and Gynecology, University of Ottawa, Ottawa, ON, Canada; 11Department of Obstetrics, Gynecology & Newborn Care, The Ottawa Hospital, Ottawa, ON, Canada; 12BORN Ontario, Children’s Hospital of Eastern Ontario, Ottawa, ON, CanadaCorrespondence: Mark C Walker, Clinical Epidemiology Program, Ottawa Hospital Research Institute, Centre for Practice Changing Research, Box 241, 501 Smyth Road, Ottawa, ON, K1H 8L6, Canada, Tel +1 613-798-5555 x76655, Email mwalker@toh.caBackground: Preeclampsia is a leading cause of maternal and perinatal mortality and morbidity. The management of preeclampsia has not changed much in more than two decades, and its aetiology is still not fully understood. Case reports and case series have traditionally been used to communicate new knowledge about existing conditions. Whether this is true for preeclampsia is not known.Objective: To determine whether recent case reports or case series have generated new knowledge and clinical discoveries about preeclampsia.Methods: A detailed search strategy was developed in consultation with a medical librarian. Two bibliographic databases were searched through Ovid: Embase and MEDLINE. We selected case reports or case series published between 2015 and 2020, comprising pregnant persons diagnosed with hypertensive disorders of pregnancy, including preeclampsia. Two reviewers independently screened all publications. One reviewer extracted data from included studies, while another conducted a quality check of extracted data. We developed a codebook to guide our data extraction and outcomes assessment. The quality of each report was determined based on Joanna Briggs Institute (JBI) critical appraisal checklist for case reports and case series.Results: We included 104 case reports and three case series, together comprising 118 pregnancies. A severe presentation or complication of preeclampsia was reported in 81% of pregnancies, and 84% had a positive maternal outcome, free of death or persistent complications. Only 8% of the case reports were deemed to be of high quality, and 53.8% of moderate quality; none of the case series were of high quality. A total of 26 of the 107 publications (24.3%) included a novel clinical discovery as a central theme.Conclusion: Over two-thirds of recent case reports and case series about preeclampsia do not appear to present new knowledge or discoveries about preeclampsia, and most are of low quality.Keywords: hypertensive disorders of pregnancy, eclampsia, HELLP syndrome, study design

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.227
GPT teacher head0.540
Teacher spread0.313 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2023
Admission routes1
Has abstractyes

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