Outcome of Hospitalized Cancer Patients with Hypernatremia: A Retrospective Case-Control Study
Bibliographic record
Abstract
Hypernatremia (>145 mmol/L) is a relatively rare event, and the data regarding its role in the outcome of inpatients on an oncology ward are weak. The aim of this study was to describe the prevalence, prognosis, and outcome of hospitalized cancer patients with hypernatremia. We performed a retrospective case-control study of data obtained from inpatients with a solid tumor at the St. Claraspital, Basel, Switzerland, who were admitted between 2017 and 2020. The primary endpoint was overall survival. Hypernatremia was found in 93 (3.16%) of 2945 inpatients bearing cancer or lymphoma. From 991 eligible normonatremic control patients, 93 were matched according to diagnosis, age, and sex. The median overall survival time (OS) of patients with hypernatremia was 1.5 months compared to 11.7 months of the normonatremic controls (HR 2.69, 95% CI 1.85–3.90, p < 0.0001). OS of patients with irreversible compared to reversible hypernatremia was significantly shorter (23 versus 88 days, HR 4.0, 95% CI 2.04–7.70, p < 0.0001). The length of hospital stay was significantly longer for the hypernatremic than for the normonatremic group (p < 0.0001). Significantly more patients with hypernatremia died in the hospital (30.1% versus 8.6%, p < 0.001). These results suggest hypernatremia to be associated with an unfavorable outcome and a very short OS.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".