Prevalence of hypothyroidism and thyroid nodule in chronic hemodialysis Iranian patients
Bibliographic record
Abstract
INTRODUCTION: End stage renal disease (ESRD) reasons several changes in the function of thyroid gland as; lower levels of thyroid hormones, altered hormone metabolism, and increased iodine storage. The aim of this study was to evaluate the prevalence of nodular goiter and hypothyroidism in hemodialysis (HD) patients compared with normal population. METHODS: This cross-sectional study was conducted among HD patients and healthy people as the control group for thyroid function evaluation. Thyroid gland was evaluated by physical examination and ultrasonography. Blood level of FT3, FT4, TSH, TPO Ab, and urinary iodine excretion were checked in both groups. Data were analyzed using SPSS-17 and P-value less than 0.05 was considered as the significance level. FINDINGS: Eighty six HD patients (57.2 ± 17.2 mean age, 48 men) and 86 healthy people (56.6 ± 16.8 mean age, 48 men) were enrolled in this study. Goiter was confirmed by physical examination in 29.0% of the HD patients and 12.8% of the control group (P = 0.04). Nodular goiter that was shown by ultrasonography was found in 27.9% and 3.5% of the HD and control groups, respectively (P = 0.01). HD patients had a higher frequency of reduced FT3 (40.9% vs. 4.6%, P < 0.01) and increased TSH (18.6% vs. 8.1%, P < 0.03(. TPO Ab was positive in 15.1% of the HD and 11.6% of the control groups (P = 0.14). DISCUSSION: The high incidence of nodular goiter and hypothyroidism in ESRD patients shows that screening for thyroid dysfunction and goiter, using appropriate laboratory tests, should be considered in evaluations of ESRD patients.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".