Bibliographic record
Abstract
Background: Rhabdomyolysis is a clinical and biochemical syndrome that occurs when skeletal muscle cells disrupt and release creatine phosphokinase and myoglobin into the interstitial space and plasma. The causes of rhabdomyolysis are legion, but the most important and the classical form is the crush syndrome. Acute kidney injury occurs in 33-50% of patients with rhabdomyolysis. Here we report nine cases with acute kidney injury due to crush injury with rhabdomyolysis after the Al-Aema bridge catastrophe in Baghdad, in September 2005.Methods: Nine patients presented to the nephrology department of the Baghdad Teaching Hospital with a suggestive history of crush and laboratory evidence of rhabdomyolysis and acute kidney injury within the first three weeks of this tragic event. All patients were treated initially with aggressive fluid resuscitation with isotonic normal saline and bicarbonate. However, eight patients required acute peritoneal dialysis that was followed by intermittent hemodialysis, while only one received watchful conservative treatment with intravenous fluid support.Results: All patients achieved complete recovery of their clinical status and renal function and discharged within a period of 8 to 30 days.Conclusion: Crush syndrome is common. Early detection, aggressive fluid support still the main aspect of management. Correction of electrolytes abnormalities beside the judicious decision of dialysis initiation are also important in the management of this potentially life threatening situation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".