MétaCan
Menu
Back to cohort
Record W4396612951 · doi:10.4103/cjrm.cjrm_20_23

Does proximity to a fertility centre increase the chance of achieving pregnancy in Northeastern Ontario?

2024· article· en· W4396612951 on OpenAlexaffvenueabout
A Wallace, Karen Splinter

Bibliographic record

VenueCanadian Journal of Rural Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsHealth Sciences NorthNOSM University
Fundersnot available
KeywordsFertilityDemographyPregnancyMedicinePopulationGeographyHealth careEnvironmental healthPolitical scienceSociology

Abstract

fetched live from OpenAlex

INTRODUCTION: Northern Ontario has a population of approximately 800,000 people distributed over 806,707 km2. Before 2018, the only fertility treatment centre in Northern Ontario was located in Thunder Bay; many patients travelled south for care. In 2018, the Northeastern Ontario Women's Health Network (NEOWHN) opened in Sudbury, providing fertility treatments to people living in Northeastern Ontario. The goal of this study was to determine if proximity to this new fertility centre increases one's chance of achieving pregnancy when undergoing fertility treatment. Secondary outcomes included the quantity and types of fertility investigations and treatments completed by patients. MATERIALS AND METHODS: A retrospective chart review was performed for all patients seeking fertility treatment at NEOWHN between January 2019 and December 2020. Traveling >100 km to access healthcare was considered to be a clinically significant determinant of health. RESULTS: Seven hundred and 5 patients were seen in consultation for fertility services at NEOWHN during the study period. One hundred eighty-one of 478 (37.9%) patients living <100 km from NEOWHN achieved pregnancy compared to 39 of 227 (17.2%) patients living >100 km from NEOWHN (P < 0.01). CONCLUSION: Living in proximity (<100 km) to NEOWHN increased the likelihood that individuals in Northeastern Ontario would seek fertility services and would achieve pregnancy. Financial constraints and inaccessibility likely play a role in this, but further studies are needed to explain this difference. INTRODUCTION: Le Nord de l'Ontario compte une population d'environ 800,000 personnes réparties sur 806,707 km2. Avant 2018, le seul centre de traitement de la fertilité du Nord de l'Ontario était situé à Thunder Bay; de nombreux patients SE rendaient dans le sud pour recevoir des soins. En 2018, le Northeastern Ontario Women's Health Network (NEOWHN-le Réseau de santé des femmes du Nord-Est de l'Ontario) a ouvert ses portes à Sudbury, offrant des traitements de fertilité aux personnes vivant dans le Nord-Est de l'Ontario. L'objectif de cette étude était de déterminer si la proximité de ce nouveau centre de fertilité augmente les chances d'obtenir une grossesse lors d'un traitement de fertilité. Les résultats secondaires comprenaient la quantité et les types d'examens et de traitements de fertilité effectués par les patients. MTHODES: Une étude rétrospective des dossiers a été réalisée pour tous les patients cherchant un traitement de fertilité au NEOWHN entre janvier 2019 et décembre 2020. Le fait de voyager >100 km pour accéder aux soins de santé a été considéré comme un déterminant de la santé cliniquement significatif. RSULTATS: Seven hundred and 5 patients ont été vus en consultation pour des services de fertilité au NEOWHN pendant la période d'étude. One hundred eighty-one des 478 (37.9%) patientes vivant à moins de 100 km du NEOWHN ont obtenu une grossesse, contre 39 des 227 (17.2%) patientes vivant à plus de 100 km du NEOWHN (P < 0.01). CONCLUSION: Le fait de vivre à proximité (<100 km) du NEOWHN augmente la probabilité que les habitants du Nord-Est de l'Ontario aient recours à des services de fertilité et obtiennent une grossesse. Les contraintes financières et l'inaccessibilité jouent probablement un rôle à cet égard, mais d'autres études sont nécessaires pour expliquer cette différence.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.403
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.021
GPT teacher head0.292
Teacher spread0.271 · 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

Citations1
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Rural MedicineSame topicMaternal and Perinatal Health InterventionsFrench-language works237,207