Shortcoming of Measuring Patient Satisfaction’s Association With Anemia-Based Cardiovascular Risk in End-Stage Kidney Disease Patients
Bibliographic record
Abstract
Background: Patient-reported humanistic outcomes like patient satisfaction are becoming more important in clinical practice, but their use has limitations. Improvements are needed to better demonstrate how patient satisfaction and clinical outcomes are associated. The objective of the study was to observe the correlation between patient’s hemoglobin and patient satisfaction. Methods: A cross-sectional study was conducted at a University Hospital hemodialysis unit among end-stage kidney disease (ESKD) patients on maintenance hemodialysis in February and March, 2021. During this time period patient satisfaction was measured using an instrument from the Choices for Healthy Outcomes in Caring for End-Stage Renal Disease (CHOICE) study. Spearman’s correlation coefficient was used to find a correlation between patient satisfaction domains and hemoglobin. P value was set at 0.05, and SPSS version 26 was used for the analysis. Results: Out of 41 patients studied, their satisfaction on care by interprofessional staff was 77.3%, information received was 68.8%, and effectiveness of care was 71.3% for “very good” and “excellent” responses combined. Out of 40 patients, hemoglobin levels were lower in 17 (42.5%) and higher in seven (17.5%) patients than the optimal range of 10 - 12 g/dL. Spearman’s correlation coefficients were not statistically significant for anemia and any patient satisfaction domain (r s : 0.244, 0.101, 0.048, respectively for the three domains). Spearman’s correlation coefficients were high or moderate between patient satisfaction domains; interprofessional staff with information (r s : 0.745, P value < 0.001) and interprofessional staff with the effectiveness of care (r s : 0.619, P value < 0.001). Information domain had a moderate correlation with the effectiveness of care (r s : 0.527, P value < 0.001). Conclusions: No correlation was observed between patient satisfaction with hemoglobin. Although patient satisfaction among hemodialysis patients was mostly “very good” or “excellent”, nearly half of the patients were anemic, and some had higher hemoglobin than the target. Since both of these groups have higher cardiovascular risk this provides an opportunity for the development of patient satisfaction tools with greater sensitivity to awareness of patients’ cardiovascular risk. Cardiol Res. 2021;12(6):344-350 doi: https://doi.org/10.14740/cr1332
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".