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Record W2142314364 · doi:10.1902/jop.2011.110342

Periodontal Disease is Not Associated With Preeclampsia in Canadian Pregnant Women

2011· article· en· W2142314364 on OpenAlexafffundabout
Nawel Taghzouti, Xu Xiong, Mervyn Gornitsky, Fatiha Chandad, René Voyer, Guy Gagnon, Line Leduc, Hairong Xu, Togas Tulandi, Bin Wei, J Sénécal, Ana Míriam Velly, Mohammad Salah, William D. Fraser

Bibliographic record

VenueJournal of Periodontology · 2011
Typearticle
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsUniversité LavalMcGill UniversityUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsPreeclampsiaMedicineOdds ratioPeriodontitisObstetricsConfoundingConfidence intervalGestationPregnancyPeriodontal diseaseProteinuriaClinical attachment lossInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The findings from the studies on the relationship between periodontal disease and preeclampsia are inconsistent. The objective of this study is to examine the relationship between periodontal disease and preeclampsia. METHODS: A multicenter case-control study was conducted in Quebec, Canada. Preeclampsia was defined as blood pressure ≥140/90 mm Hg and ≥1+ proteinuria after 20 weeks of gestation. Periodontitis was defined as the presence of ≥4 sites with a probing depth ≥5 mm and a clinical attachment loss ≥3 mm at the same sites. RESULTS: A total of 92 preeclamptic women and 245 controls were analyzed. The percentage of periodontal disease was 18.5% in preeclamptic women and 19.2% in normotensive women (crude odds ratio [OR] = 0.96, 95% confidence interval [CI] = 0.52 to 1.77). After adjusting for confounding variables, periodontitis remained not associated with preeclampsia (adjusted OR = 1.13, 95% CI = 0.59 to 2.17). CONCLUSION: This study does not support the hypothesis of an association between periodontal disease and preeclampsia.

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)0.001
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 score0.642
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.032
GPT teacher head0.268
Teacher spread0.235 · 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

Citations25
Published2011
Admission routes3
Has abstractyes

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