Echocardiogram changes following parathyroidectomy for primary hyperparathyroidism
Bibliographic record
Abstract
The aim of the study is to systematically review the evidence on post parathyroidectomy (PTX) changes as measured by echocardiogram (ECHO) in patients with primary hyperparathyroidism (PHPT).PHPT may increase risk of cardiovascular morbidity/mortality. Conclusions of studies assessing ECHO changes, pre versus post PTX, are inconsistent.A systematic literature search was conducted to locate published and unpublished studies. Randomized control trials, nonrandomized control trials, and observational studies were included. Variables were reported as means and standard deviations. An inverse variance statistical method, with random-effects analysis model, was applied to continuous data. The effect measure was standardized mean difference, confidence interval of 95%. Primary outcome measure was left ventricular ejection fraction (LVEF). Secondary outcome measures were left ventricular mass index (LVMI), peak early over peak late diastolic velocity ratio (E/A ratio), isovolumetric relaxation time (IVRT), intraventricular septal thickness (IVST), and posterior wall thickness (PWT).Fourteen studies were included. Follow-up time ranged 3 to 67 months. No significant differences (P > .05) in primary outcome measure LVEF (SMD = -0.03, CI = -0.24, 0.19), or secondary outcome measures E/A Ratio (SMD = -0.05, CI = -0.24, 0.14), IVST (SMD = 0, CI = 0.31, 0.32), PWT (SMD = 0.01, CI = -0.38, 0.39), LVMI (SMD = -0.18, CI = -0.74, 0.38), and IVRT (SMD = -0.84, CI = -1.83, 0.14) were observed.There was no significant difference in LVEF pre to post PTX. Due to heterogeneity of current literature, we were unable to determine if other outcome measures of cardiac function are affected after PTX in patients with PHPT. We recommend a randomized control trial be conducted to make concrete conclusions.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".