Hospitalizations before and after initiation of chronic hemodialysis
Bibliographic record
Abstract
Hospitalization rate is high in patients on chronic hemodialysis (HD). We investigated whether initiation of HD changes the rate and length of hospitalization. We analyzed hospitalizations in HD patients in one hospital over 15 years. We compared annual rate and length of hospitalizations, both presented as mean (95% confidence interval [CI]) between the pre-HD and HD period. Three hundred ninety-two patients, 98% men, 59% diabetic, and 66.3 ± 11.2 years old at the onset of HD, had 1016 hospitalizations in the pre-HD period (60.0 ± 42.9 months) and 1627 hospitalizations in the HD period (32.5 ± 25.9 months). Higher values were found in the HD than the pre-HD period for rate, (pre-HD 0.557 [95% CI 0.473-0.611], HD 2.198 [95% CI 1.997-2.399] admissions/[patient-year], P<0.001) and length (pre-HD 4.63 [95% CI 3.71-5.55], HD 28.07 [95% CI 23.55-32.59] days/patient-year], P<0.001) of hospitalizations for all causes, cardiac disease, infections, vascular access, peripheral vascular disease, metabolic disturbances, gastrointestinal diseases, and miscellaneous conditions, mainly respiratory illness and malignancy. Similar differences were found when we compared the year before and the year after the start of HD. Diabetics had higher all cause rate and length of hospitalizations than non-diabetics in the pre-HD and HD periods. The rate and length of hospitalizations was higher in the HD than the pre-HD period for both HD-specific conditions and conditions encountered in both HD and general populations. Study of factors specific to HD that may affect these conditions should constitute the first step toward improving the morbidity of patients on HD.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 0.001 |
| 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".