Longitudinal Study of Conservative Kidney Management by Using Tools to Identify Palliative and End-of-Life Care Needs
Bibliographic record
Abstract
Background: Trajectory of end-stage kidney disease (ESKD) patients on conservative care varies. The objective of study was assessing the utility of objective assessment tools and mortality outcome. Methods: This is a single center, prospective study of conservative kidney management patients from April 2021 to February 2024. Palliative trained community nurse performed monthly home visit and assessment. Edmonton symptom assessment system revised (ESASr version 2016), resource utilization groups activities of daily living (RUG-ADL) and palliative performance scale (PPS) were used and monitored longitudinally. SPSS version 27 was used for analysis, p < 0.05 is considered significant. Results: A total of 103 patients with median follow-up of 11.1 months (IQR: 0.4, 15.8). Forty-seven patients passed away during the study. The baseline characteristics including female 64.1%, Chinese 80.6%, mean age 79.6±7.7 years, estimated glomerular filtration rate 10.5±3.4ml/min and Charlson comorbidity index 8.4±1.9. No significant difference between the survived versus demised group. However, those demised patients had higher ESASr (4.4 vs 2.0), RUG-ADL (6.3 vs 4.9) but lower PPS (59 vs 67) at baseline. Mixed model using repeated measurements for ESASr, RUG-ADL and PPS were done. The variance within each time point for RUG-ADL, ESASr and PPS were 1.5, 6.5 and 27.4, whereas covariance between any 2 time-points were 7.2, 11.3 and 136.9 respectively. There was no interaction with PPS model. The CKM patients have relative stable PPS until last few weeks of life (figure1). Conclusion: This study demonstrated the high degree of symptom burden and functional decline toward the end of life for CKD patients managed conservatively. Optimal community care allow close monitoring of symptoms with optimization of care and timely referral to hospice service to reduce hospitalization for end-of-life care. Funding: Government Support – Non-U.S.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".