Clinical epidemiology and CKD 1-5
Bibliographic record
Abstract
Introduction and Aims: To examine the relationship of birthweight, and prematurity, to risk factors and markers for chronic kidney disease (CKD) in postnatal life.Methods: The AusDiab study is a longitudinal study where baseline data on 11,247 participants, aged = 25 years, were collected in 1999-2000.During the 2004-05 follow-up AusDiab survey, questions about birthweight were included.Also, we approached four hundred and twelve CKD patients, and 339 agreed to participate in the study.The patients filled the same questionnaire as was included in the AusDiab study.Medical records were reviewed to check the diagnoses, causes of kidney disease and SCr levels.Two control subjects, matched for gender and age, were selected for each CKD patient from participants in the AusDiab study who reported their birthweight.Also, we studied children and teenage subjects of a cohort, of VLBW due to prematurity.This cohort and a control group were enrolled in our study.Data were collected from participants, their medical records and clinical examination and laboratory investigations.Results: eGFR was strongly and positively associated with birthweight, with a predicted increase of 2.6 ml/min (CI 2.1, 3.2) and 3.8 (3.0, 4.5) for each kg of birthweight for females and males, respectively.The OR (CI) for low eGFR (<61.0 ml/min for females and < 87.4 males) in people of LBW compared with those of NBW was 2.04 (1.45, 2.88) for females and 3.4 (2.11, 5.36) for males.189 chronic kidney disease (CKD) patients reported their birthweight; 106 were male.Their age was 60.3(15) years.Their mean birthweight was 3.27 (0.62) kg, vs 3.46 (0.6) kg for their AusDiab controls, p<0.001 and the proportions with birthweight<2.5 kg were 12.17% and 4.44%, p<0.001.Among CKD patients, 22.8%, 21.7%, 18% and 37.6% were in CKD stages 2, 3, 4 and 5 respectively.Birthweights by CKD stage and their AusDiab controls were as follows: 3.38 (0.52) vs 3.49 (0.52), p=0.251 for CKD2; 3.28 (0.54) vs 3.44 (0.54), p=0.121 for CKD3; 3.19 (0.72) vs 3.43 (0.56), p= 0.112 for CKD4 and 3.09 (0.65) vs 3.47 (0.67), p=<0.001 for CKD5.37 premature children (17 girls) of premature cohort children and 23 full term children (9 girls) were consented for clinical examination, urine, blood and ultrasound examinations of their children.Kidney volume was calculated using the ellipsoid formula: volume (ml) = [length x widthx (depth1+depth2)/2)] × 0.523.The gestational age for preterm cohort was 26.7 (2.6) and ranged from 23 to 35 weeks.Their birthweight was 867 (248) grams vs. 3433 (285) for full term babies.The age of premature children was 12.1(3.8)years vs. 11.5 (3.5) years for full term children.Children born prematurely had lower lower kidney volumes (99.7 ml (89.3, 110) vs. 131 (111, 151), P=0.01 and lower eGFR (87.0 (78.5, 113) vs. 113 (99.1, 128), p<0.001.Kidney volume correlated well with eGFR (0.83).Conclusions: In an affluent Western country with a good adult health profile, LBW people were predisposed to higher rates of lower eGFR in later life.In all instances it would be prudent to adopt policies of intensified whole of life surveillance of lower birthweight people, anticipating this risk.The general public awareness of the effect of LBW on development of chronic diseases in later life is of vital importance.The general public, in addition to the awareness of people in medical practice of the role of LBW, will set a trend towards a better management of this group of our population that is increasingly surviving into adulthood.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".