A method to estimate urinary electrolyte excretion in patients at risk for developing cerebral salt wasting
Bibliographic record
Abstract
OBJECT: Two major criteria are necessary to diagnose cerebral salt wasting (CSW): a cerebral lesion and a large urinary excretion of Na+ and Cl- at a time when the extracellular fluid (ECF) volume is contracted. Nevertheless, it is difficult for the physician to confirm from bedside observation that a patient has a contracted ECF volume. Hyponatremia, although frequently present, should not be a criterion for a diagnosis of salt wasting. A contracted ECF volume is unlikely if there are positive balances of Na+ and Cl-. The goal of this study was to assess the accuracy of calculating balances for Na+ plus K+ and of Cl- over 1 to 10 days in an intensive care unit (ICU) setting. METHODS: A prospective comparison of measured and estimated quantities of Na+ plus K+ and of Cl- excreted over 1 to 10 days in 10 children and 12 adults who had recently received a traumatic brain injury or undergone recent neurosurgery. Plasma concentrations of electrolytes were recorded at the beginning and end of the study period. The total volumes infused and excreted and the concentrations of Na+, K+, and Cl- in the infusate were obtained from each patient's ICU chart. The electrolytes in the patients' urine were measured and calculated. Correlations between measured and calculated values for excretions of Cl- and of Na+ plus K+ were excellent. CONCLUSIONS: Mass balances for Na+ plus K+ and for Cl- can be accurately estimated. These data provide information to support or refute a clinical diagnosis of CSW. The danger of relying on balances for these electrolytes measured within a single day to diagnose CSW is illustrated.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".