Variables influencing the likelihood of cardiac dysrhythmias during extracorporeal shock wave lithotripsy
Bibliographic record
Abstract
INTRODUCTION: Extracorporeal shock wave lithotripsy (ESWL) is a safe and effective treatment of upper urinary tract calculi. While serious side effects are rare, transient cardiac dysrhythmias (CD) may be associated with ESWL. The exact etiology of these events, which are often unpredictable, is poorly understood. Awareness of CD during ESWL and identification of risk factors for developing them could help clinicians predict and manage them safely and effectively. The current study examines selected variables to determine whether they may predispose individuals to developing CD during ESWL. METHODS: We compared 16 patients who experienced CD during ESWL to 56 control patients. Cases and controls were compared with respect to several continuous and discrete variables, including age, pre-treatment heart rate, number of shocks received during treatment, energy setting of the lithotripter, gender, presence of a ureteric stent, previous ESWL and side being treated. RESULTS: Cardiac dysrhythmias occurred more frequently in younger patients and in those being treated for right-sided stones. The other variables did not influence the likelihood of CD. All CD resolved promptly following conversion to electrocardiogram (ECG)-gating. CONCLUSION: Younger age and right-sided treatment predisposed individuals to developing CD during ESWL. Careful ECG monitoring should be performed during treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".