FP530KT/V ACHIEVEMENT AND SURVIVAL IN HEMODIALYSIS PATIENTS IN THE GULF COOPERATION COUNCIL (GCC) COUNTRIES: INTERNATIONAL RESULTS FROM DOPPS 5 & 6 (2012-2018)
Bibliographic record
Abstract
INTRODUCTION: Dialysis adequacy, as measured by Kt/V, is an important practice for maintaining the good health of hemodialysis (HD) patients (pts). Guidelines have recommended single pool Kt/V >1.2 as the minimum dose for pts receiving thrice weekly HD. Using data from the Dialysis Outcomes and Practice Patterns Study (DOPPS), we describe: (1) the prevalence of low Kt/V (<1.2) in the GCC (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) compared to other regions, (2) predictors of low Kt/V, (3) relationship of low Kt/V with mortality, and (4) percent of low Kt/V cases attributed to particular practices of treatment time (TT) and blood flow rate (BFR) in different patient subgroups. METHODS: Data were from DOPPS 5 (2012-2015) and 6 (2015-2018) HD and hemodiafiltration (HDF) pts (N=1544) on dialysis >180 days at 40 randomly selected GCC HD units. Logistic regression was used to estimate the proportion of low Kt/V cases attributable to various treatment practices, and multivariable Cox regression used to estimate hazard ratios (HR) for low Kt/V on all-cause mortality with adjustments as indicated in Table 1. RESULTS: 34% of GCC HD pts had a low Kt/V (<1.2) versus 17%, 14%, 10%, and 6% in Japan, Canada, Europe, and US, respectively. In the GCC, low Kt/V was 27% for females vs 39% for males, and ranged from 10% in Qatar to 54% in Kuwait. In multivariable logistic models, low Kt/V was more common (p<0.05) with larger body weight and height, being male, lower TT, lower BFR, greater comorbidity burden, and using HD vs HDF. In the GCC, low Kt/V was strongly related to higher mortality in women (HR 1.86, 95% CI 1.11-3.14) whereas a weak mortality association was seen in men (HR 1.12, 95% CI 0.68-1.85). BFR <350 mL/min and TT <4 hours were common (80 and 43% of pts, respectively); 40% of low Kt/V cases were attributable to having either a BFR <350 or TT <4 hrs (52% for women, 36% for men). Table 1 reports the full attributable fraction analysis. CONCLUSIONS: Relatively large proportions of HD GCC pts have low Kt/V – with 52% attributed to low BFR and TT in females. Low Kt/V is strongly associated with higher female mortality. Increasing BFR to 350 ml/min and TT to 4 hours thrice weekly will reduce low Kt/V prevalence and, in turn, may further improve survival in GCC HD pts – particularly female pts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".