Bibliographic record
Abstract
We present a case of a 47-year-old female with a history of anxiety, depression, and alcohol dependence with history of alcohol withdrawal seizures, who presented after a witnessed seizure episode. She admitted to drinking only copious amounts of black tea 1 week prior to presentation in an attempt to quit alcohol. She was subsequently found to be severely hyponatremic with a serum sodium level of 112 mEq/L and was admitted to the intensive care unit. Approximately 48 h after admission, she experienced sudden-onset of dizziness, diaphoresis, and nausea, with a heart rate of 42 beats/min and blood pressure of 70/40 mm Hg. STAT EKG revealed new T-wave inversions in the lateral and precordial leads and troponin was elevated to 5.99 ng/mL. Treatment was initiated for NSTEMI with continuous heparin infusion, aspirin, clopidogrel, carvedilol, and lisinopril. Transthoracic echocardiogram revealed apical and mid ventricular dyskinesia with hyperkinesis of the basal walls, with an estimated left ventricular ejection fraction of 35%. Cardiac catheterization revealed no significant coronary disease with ejection fraction 30-35% and similar areas of hypo and hyperkinesis, classic for apical ballooning syndrome. This case not only illustrates the rare phenomenon of hyponatremia-induced Takotsubo cardiomyopathy, but is one of the only incidents caused by primary polydipsia. J Med Cases. 2018;9(5):147-150 doi: https://doi.org/10.14740/jmc3050e
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".