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Record W3161701439 · doi:10.1101/2021.05.04.21255000

COVID-19 Compromises in the Medical Practice and the Consequential Effect on Endometriosis Patients

2021· preprint· en· W3161701439 on OpenAlexaff
Matilda Shaked Ashkenazi, Ole Linvåg Huseby, Gard Kroken, Adrián Soto-Mota, Marius Pents, Alessandra Loschiavo, Roksana Lewandowska, Grace Tran, Sebastian Kwiatkowski

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEndometriosisPandemicMedicineCoronavirus disease 2019 (COVID-19)DiseaseInfertilityQuality of life (healthcare)Pelvic painCross-sectional studyGynecologyInternal medicineSurgeryPathologyNursingPregnancyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

ABSTRACT Background and purpose In response to the ongoing coronavirus disease 2019 (COVID-19) pandemic, self-isolation practices aimed to curb the spread of COVID-19 have severely complicated the medical management of patients suffering from endometriosis and their physical and mental well- being. Endometriosis, the main cause for chronic pelvic pain (CPP), is a highly prevalent disease characterized by the presence of endometrial tissue in locations outside the uterine cavity that affects up to 10% of women in their reproductive age. This study aimed to explore the effects of the global COVID-19 pandemic on patients suffering from endometriosis across multiple countries, and to investigate the different approaches to the medical management of these patients based on their self-reported experiences. Methods A cross-sectional survey, partially based on validated quality of life questionnaires for endometriosis patients, was initially created in English, which was then reviewed by experts. Through the process of assessing face and content validity, the questionnaire was then translated to fifteen different languages following the WHO recommendations for medical translation. After evaluation, the questionnaire was converted into a web form and distributed across different platforms. An analysis of 2964 responses of participants from 59 countries suffering from self-reported endometriosis was then conducted. Results The data shows an association between COVID-19 imposed compromises with the reported worsening of the mental state of the participants, as well as with the aggravation of their symptoms. For the 1174 participants who had their medical appointments cancelled, 43.7% (n=513) reported that their symptoms had been aggravated, and 49.3% (n=579) reported that their mental state had worsened. In comparison, of the 1180 participants who kept their appointments, only 29.4% (n=347) stated that their symptoms had been aggravated, and 27.5% (n=325) stated their mental health had worsened. 610 participants did not have medical appointments scheduled, and these participants follow a similar pattern as the participants who kept their appointments, with 29.0% (n=177) reporting aggravation of symptoms and 28.2% (n=172) reporting that their mental state had worsened. Conclusions These findings suggest that COVID-19 pandemic has had a clinically significant negative effect on the mental and physical well-being of participants suffering from endometriosis based on their self-reported experiences. Thus, they show the importance of further assessment and reevaluation of the current and future management of this condition in medical practices worldwide.

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)0.002
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.002
Research integrity0.0000.001
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 head0.034
GPT teacher head0.373
Teacher spread0.339 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

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