Feasibility of sustained low efficiency dialysis in critically sick pediatric patients: A multicentric retrospective study
Bibliographic record
Abstract
INTRODUCTION: Sustained low-efficiency dialysis (SLED) has emerged as a cost effective alternative to Continuous Renal Replacement Therapy in the management of hemodynamically unstable adult patients with acute kidney injury. The objective of the study was to document the SLED practices in these centers, and to look at the feasibility, and tolerability of SLED in critically sick pediatric patients. METHODS: It was a retrospective record review from January 2010 to June 2016 done in four tertiary pediatric nephrology centers in India. All pediatric patients undergoing SLED in the collaborating centers were included in the study. Basic demographic data, prescription parameters and outcomes of patients were recorded. FINDINGS: During the study period a total of 68 children received 211 sessions of SLED. PRISM score at admission in patients was 13.33 ± 9.15. Fifty-seven patients were ventilated (84%). Most of the patients had one or more organ system involved in addition to renal (n = 64; 94%). Heparin free sessions were achievable in 153 sessions (72%). Out of 211 sessions, 148 sessions were on at least one inotrope (70.1%). Overall premature terminations had to be done in 27 sessions (13% of all sessions), out of which 7 sessions had to be terminated due to circuit clotting (3.3%). Intradialytic hypotension or need for inotrope escalation was seen in 31 (15%) sessions but termination of the session for drop in BP was required in only 20 (9%) sessions. CONCLUSION: SLED is a feasible method of providing renal replacement in critically ill pediatric patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".