Assessing Global Kidney Nutrition Care
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Nutrition intervention is an essential component of kidney disease management. This study aimed to understand current global availability and capacity of kidney nutrition care services, interdisciplinary communication, and availability of oral nutrition supplements. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: The International Society of Renal Nutrition and Metabolism (ISRNM), working in partnership with the International Society of Nephrology (ISN) Global Kidney Health Atlas Committee, developed this Global Kidney Nutrition Care Atlas. An electronic survey was administered among key kidney care stakeholders through 182 ISN-affiliated countries between July and September 2018. RESULTS: Overall, 160 of 182 countries (88%) responded, of which 155 countries (97%) answered the survey items related to kidney nutrition care. Only 48% of the 155 countries have dietitians/renal dietitians to provide this specialized service. Dietary counseling, provided by a person trained in nutrition, was generally not available in 65% of low-/lower middle-income countries and "never" available in 23% of low-income countries. Forty-one percent of the countries did not provide formal assessment of nutrition status for kidney nutrition care. The availability of oral nutrition supplements varied globally and, mostly, were not freely available in low-/lower middle-income countries for both inpatient and outpatient settings. Dietitians and nephrologists only communicated "sometimes" on kidney nutrition care in ≥60% of countries globally. CONCLUSIONS: This survey reveals significant gaps in global kidney nutrition care service capacity, availability, cost coverage, and deficiencies in interdisciplinary communication on kidney nutrition care delivery, especially in lower-income countries.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".