Seasonal variation in emergent hemodialysis initiation in the late elderly: A single‐center study
Bibliographic record
Abstract
BACKGROUND: The number of new dialysis patients, particularly among the elderly population, has been globally increasing. In Japan, patients aged ≥65 years and ≥75 years comprised 72% and 45% of patients on dialysis in 2018, respectively. Few studies have reported seasonal variations in the initiation of dialysis. We investigated the seasonal prevalence of the emergent hemodialysis initiation in the elderly. METHODS: We reviewed 479 elderly patients who initiated hemodialysis between January 2006 and December 2018. Early elderly patients were defined as patients aged between 65 and 74 years, and late elderly patients were defined as those aged ≥75 years. Emergent hemodialysis initiation was defined as initiation with a temporary vascular catheter without elective permanent vascular access or unplanned hemodialysis initiation due to patients requiring critical care regardless of elective permanent vascular access. The information collected included age, sex, and details of the initiation of hemodialysis. RESULTS: The early elderly group consisted of 199 patients, and the late elderly group consisted of 279 patients. In the late elderly group, hemodialysis initiation was most frequent in winter, followed by spring, autumn, and summer (p = 0.018). Moreover, emergent hemodialysis initiation was most frequent in winter, followed by spring, autumn, and summer (p = 0.009). Emergent hemodialysis initiation due to fluid overload was most frequent in winter, followed by autumn, spring, and summer (p < 0.001). Among late elderly patients who initiated hemodialysis, 78% did not have permanent hemodialysis access at the time of the initiation of hemodialysis. CONCLUSION: In the late elderly group, hemodialysis initiation and emergent hemodialysis initiation were significantly more frequent in the winter than in the remaining seasons. In addition, emergent hemodialysis initiation due to fluid overload was most frequent in winter in the late elderly group.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".