High prevalence of subclinical hypothyroidism and nodular thyroid disease in patients on hemodialysis
Bibliographic record
Abstract
Chronic kidney disease has been known to affect thyroid hormone metabolism. Low serum levels of T3 and T4 are the most remarkable laboratorial findings. A high incidence of goiter and nodules on thyroid ultrasonography has been reported in patients with end-stage renal disease (ESRD). Our objective is to evaluate the prevalence of laboratorial and morphologic alterations in the thyroid gland in a cohort of patients with ESRD on hemodialysis (HD). Sixty-one patients with ESRD on HD were selected and compared with 43 healthy subjects matched by age, gender, and weight. Patients were submitted to thyroid ultrasonography. T3, free T4 (FT4), thyroid-stimulating hormone, antithyroglobulin, and antithyroperoxidase antibodies were measured. The mean age of patients with ESRD was 47.4 ± 12.3 and 61% were women. ESRD was mainly caused by hypertensive nephrosclerosis and diabetic nephropathy. Mean thyroid volume, as determined by ultrasonography, was similar in both groups. Patients with ESRD had more hypoechoic nodules when compared with the control group (24.1% vs. 7.9%, P = 0.056). Mean serum FT4 and T3 levels were significantly lower in patients with ESRD, and subclinical hypothyroidism was more prevalent in patients with ESRD (21.82% vs. 7.14% control group, P = 0.04). Titers of antithyroid antibodies were similar in both groups. ESRD was associated with a higher prevalence of subclinical hypothyroidism and lower levels of T3 and FT4. Almost a quarter of patients showed thyroid nodules >10 mm. Periodic ultrasound evaluation and assessment of thyroid function are recommended in patients with ESRD on HD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".