Conservative Kidney Management in the Middle East and North Africa: Attitudes, Practices, and Implementation Barriers
Bibliographic record
Abstract
Introduction: Conservative kidney management (CKM) is poorly developed and not easily accessible globally, especially in middle- and low-income countries. This study aimed to understand the perspectives of nephrologists on CKM and the barriers to its implementation in the Middle East and North Africa (MENA) region. Methods: We conducted an online survey. Nephrologists were contacted through their local nephrology societies. Responses were divided into the following 3 groups as per the country's income classification by the World Bank: high-, middle-, and low-income. Results: A total of 336 surveys were analyzed (response rate: 34.28%). The mean age of participants was 43.3 ± 9.8 years; 50% were male, 91% practiced in urban settings, and 18% were affiliated with academic centers. Of the participants, 76% were from middle-income countries. Nearly 80% of the participants were aware of CKM, and 65% accepted CKM as a treatment modality for kidney failure. However, only 20% consistently offered CKM to their patients and only 16% had a formal CKM program at their institution. Among these, 12% had a multidisciplinary team and only 6% had formal CKM training. The major perceived barriers to CKM implementation were financial and resource constraints (37.7% and 32.7%, respectively). Cultural and religious barriers constituted 18.3% and 8.6%, respectively, and were similar among the 3 income groups. Conclusion: Despite the significant awareness of CKM in the MENA region, its implementation remains poor. Key barriers include financial limitations, resource shortages, and a lack of training. Regional and national research is required to address these challenges and guide policies to improve CKM accessibility and implementation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".