MétaCan
Menu
Back to cohort
Record W4317488760 · doi:10.2337/db22-0696

Association Between Obesity and Chronic Kidney Disease: Multivariable Mendelian Randomization Analysis and Observational Data From a Bariatric Surgery Cohort

2023· article· en· W4317488760 on OpenAlexafffund
Anthony Nguyen, Rana Khafagy, Yiding Gao, Ameena Meerasa, Delnaz Roshandel, Mehran Anvari, Boxi Lin, David Z.I. Cherney, Michael E. Farkouh, Baiju R. Shah, Andrew D. Paterson, Satya Dash

Bibliographic record

VenueDiabetes · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsMcMaster UniversitySt. Joseph's HospitalHealth Sciences CentreSunnybrook Health Science CentreSt. Joseph’s Healthcare HamiltonHospital for Sick ChildrenPublic Health OntarioUniversity of TorontoUniversity Health Network
FundersInstitut canadien d'information sur la santéInvention for InnovationUniversity of TorontoOntario Ministry of Health and Long-Term CareDiabetes CanadaBanting and Best Diabetes Centre, University of TorontoInstitute for Clinical Evaluative SciencesHeart and Stroke Foundation of Canada
KeywordsMedicineMendelian randomizationInternal medicineHazard ratioKidney diseaseType 2 diabetesRenal functionOdds ratioObesityDiabetes mellitusEndocrinologyMicroalbuminuriaGastroenterologyConfidence interval

Abstract

fetched live from OpenAlex

Obesity is postulated to independently increase chronic kidney disease (CKD), even after adjusting for type 2 diabetes (T2D) and hypertension. Dysglycemia below T2D thresholds, frequently seen with obesity, also increases CKD risk. Whether obesity increases CKD independent of dysglycemia and hypertension is unknown and likely influences the optimal weight loss (WL) needed to reduce CKD. T2D remission rates plateau with 20-25% WL after bariatric surgery (BS), but further WL increases normoglycemia and normotension. We undertook bidirectional inverse variance weighted Mendelian randomization (IVWMR) to investigate potential independent causal associations between increased BMI and estimated glomerular filtration rate (eGFR) in CKD (CKDeGFR) (<60 mL/min/1.73 m2) and microalbuminuria (MA). In 5,337 BS patients, we assessed whether WL influences >50% decline in eGFR (primary outcome) or CKD hospitalization (secondary outcome), using <20% WL as a comparator. IVWMR results suggest that increased BMI increases CKDeGFR (b = 0.13, P = 1.64 × 10-4; odds ratio [OR] 1.14 [95% CI 1.07, 1.23]) and MA (b = 0.25; P = 2.14 × 10-4; OR 1.29 [1.13, 1.48]). After adjusting for hypertension and fasting glucose, increased BMI did not significantly increase CKDeGFR (b = -0.02; P = 0.72; OR 0.98 [0.87, 1.1]) or MA (b = 0.19; P = 0.08; OR 1.21 [0.98, 1.51]). Post-BS WL significantly reduced the primary outcome with 30 to <40% WL (hazard ratio [HR] 0.53 [95% CI 0.32, 0.87]) but not 20 to <30% WL (HR 0.72 [0.44, 1.2]) and ≥40% WL (HR 0.73 [0.41, 1.30]). For CKD hospitalization, progressive reduction was seen with increased WL, which was significant for 30 to <40% WL (HR 0.37 [0.17, 0.82]) and ≥40% WL (HR 0.24 [0.07, 0.89]) but not 20 to <30% WL (HR 0.60 [0.29, 1.23]). The data suggest that obesity is likely not an independent cause of CKD. WL thresholds previously associated with normotension and normoglycemia, likely causal mediators, may reduce CKD after BS.

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)0.008
metaresearch head score (Gemma)0.012
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 score0.011
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.265
Teacher spread0.238 · 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

Citations23
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueDiabetesSame topicGenetic Associations and EpidemiologyFrench-language works237,207