ArticlePloS one2026
A new survival prediction model and exploration of hemodialysis quality control indicators in incident hemodialysis patients.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo develop and internally validate a Cox model predicting 1.5-year adverse outcomes (cardiovascular admission or all-cause mortality) in incident hemodialysis (HD) patients by integrating routinely recorded dialysis-machine parameters with traditional indicators.
methodsWe retrospectively analyzed 74 incident end-stage renal disease (ESRD) patients who commenced thrice-weekly HD at Huashan Hospital, Fudan University, between 2012 and 2018. A total of 83 candidate variables, including demographics, traditional indicators (Kt/V, phosphorus, parathyroid hormone [PTH], albumin, hemoglobin, ultrafiltration volume), and dialysis machine parameters, were evaluated. Univariable and multivariable Cox regression identified predictors of 1.5-year outcomes.
resultsThe mean (± SD) age of the study population was 62 ± 14 years, and 55.4% were male. Independent predictors included serum alkaline phosphatase (ALP) measured at month 3 and machine-derived bicarbonate conductivity (BC) at month 6. A model combining ALP (month 3), bicarbonate conductivity (month 6), and traditional indicators (month 6) showed strong discrimination (AUC = 0.82). Achieving targets in ≥5 of 8 indicators-including ALP and BC-was associated with significantly better outcomes (log-rank p = 0.018).
conclusionIntegrating ALP and machine-derived BC into a Cox model significantly improves risk stratification in incident HD patients and facilitates the implementation of automated quality control.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.