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Record W4363678407 · doi:10.1002/osp4.672

Association of body mass index with the development of metabolic acidosis in patients with chronic kidney disease

2023· article· en· W4363678407 on OpenAlexaff
Vandana Mathur, Nancy L. Reaven, Susan E. Funk, Thomas W. Ferguson, Navdeep Tangri

Bibliographic record

VenueObesity Science & Practice · 2023
Typearticle
Languageen
FieldMedicine
TopicRenal function and acid-base balance
Canadian institutionsUniversity of ManitobaAlberta Health
Fundersnot available
KeywordsMedicineMetabolic acidosisBody mass indexKidney diseaseInternal medicineAcidosisRenal functionHazard ratioIncidence (geometry)Risk factorEndocrinologyConfidence interval

Abstract

fetched live from OpenAlex

Abstract Aims Higher body mass index (BMI) is associated with higher bone mass and bone serves as a buffer during the development of metabolic acidosis. The authors sought to examine the relationship between BMI and metabolic acidosis in patients with chronic kidney disease (CKD). Materials and Methods The study utilized a large US longitudinal data repository including over 103 million patients from healthcare provider organizations to evaluate the relationship between the exposure variable (BMI) and the prevalence and incidence of metabolic acidosis among patients with estimated glomerular filtration rate <60 ml/min/1.73 m2. Incident metabolic acidosis was identified at the first of two consecutive post‐index serum bicarbonate values, 10–365 days apart, between 12 and <22 mEq/L in patients with normal index serum bicarbonate. Cox proportional hazard models were adjusted for multiple variables including demographics, comorbidities, income, education, and kidney function. Results 103,766 patients qualified for this study; 6472 (6.2%) had metabolic acidosis at index. An inverse association between BMI category and metabolic acidosis was observed for both baseline (prevalence) and new‐onset (incidence) metabolic acidosis. Compared to BMI category of 18.5 to <25 kg/m2, each category of incrementally higher BMI was associated with a decreasing risk of incident metabolic acidosis; the adjusted hazard ratios (95% confidence interval) were 0.866 (0.824–0.911), 0.770 (0.729–0.813), 0.664 (0.622–0.709), and 0.612 (0.571–0.655) for BMI 25 to <30, 30 to <35, 35 to <40, and 40+ kg/m2, respectively. Conclusions Among patients with CKD, an incremental increase in BMI was inversely associated with both the prevalence and incidence of metabolic acidosis. These associations suggest that increased body weight may protect against the development of metabolic acidosis, a risk factor for progressive loss of kidney function.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.006
GPT teacher head0.252
Teacher spread0.246 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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