Prognosis of Hyponatremia in Elderly Patients With Fragility Fractures
Bibliographic record
Abstract
BACKGROUND: Hyponatremia (serum sodium < 135 mmol/L) is the commonest electrolyte imbalance encountered in clinical practice. It is associated with multiple poor clinical outcomes including increased length of hospital stay, institutionalization and mortality. Prevalence of hyponatremia is higher in frail patient groups, and elderly patients with fragility fractures (EPFF) are particularly susceptible. This study aimed to establish the impact of hyponatremia on total length of inpatient stay (TLOS), need for inpatient rehabilitation and mortality in EPFF. METHODS: Prospective observational study of consenting adults aged ≥ 65 years admitted with a fragility fracture to a university hospital between January 7, and April 4, 2013. Demographic and clinical data, length of hospital stay, discharge destination and any participant deaths were recorded. Prevalence of hyponatremia on admission and incidence of cases developing in hospital were reported. Basic demographic data and serum sodium results were included in multivariate linear regression models for TLOS. Difference in mortality rate and proportion of individuals discharged to inpatient rehabilitation between the hyponatremic and normonatremic group were tested using Chi-squared and Fisher's exact tests. Unadjusted odds ratios (ORs) and 95% confidence intervals (CIs) were also calculated. RESULTS: Of 212 cases, 127 (60%) EPFF were recruited (mean age 79 years, 78% female). Of those not recruited, 66 had incapacity to consent and 19 refused participation. Thirty-three cases of hyponatremia were identified; point prevalence on admission was 13.4% and a further 12.6% developed hyponatremia during admission. There were no statistically significant differences in patient characteristics between the hyponatremic and normonatremic group. Hyponatremic participants had a 66.7% increased time from admission to surgery (P = 0.014) and a 51.5% increased length of index hospital stay (P = 0.006). Factors independently associated with increased TLOS were age (P = 0.03) and drop in sodium during admission (P < 0.001). Mortality rate and proportion of participants discharged to inpatient rehabilitation were higher in the hyponatremic group (OR 4.2 (95% CI: 0.9 - 19.8) and 2.2 (95% CI: 0.9 - 5.1), respectively), but figures did not reach statistical significance. CONCLUSIONS: Hyponatremia is highly prevalent in EPFF, seen in 33/127 cases (26%), and is associated with increased length of index hospital stay. Drop in serum sodium during admission was independently associated with increased TLOS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".