The Effect of Acidosis on Albumin Level in Patients Treated With Regular Hemodialysis (Single Center Study)
Bibliographic record
Abstract
BACKGROUND: Hypoalbuminemia is the most powerful predictor of mortality in end-stage renal disease on hemodialysis. Metabolic acidosis induces net negative nitrogen and total body protein balance. Some patients undergoing maintenance dialysis have low plasma bicarbonate levels due to inadequate dialysis. We aimed to evaluate the role of metabolic acidosis on serum albumin concentration in patients with end stage renal disease on hemodialysis, and to determine differences of serum bicarbonate level before and after hemodialysis in actual situation. METHODS: This cross sectional comparative study was conducted in the Iraqi Center for Hemodialysis/ Baghdad Teaching Hospital from June to December 2015. It included 100 subjects with end stage renal disease on hemodialysis. They were divided equally into cases with low albumin and comparison group with normal albumin level. Serum bicarbonate and the Kt/V were measured for all subjects before, after, and before next hemodialysis session to show the adequacy of dialysis. RESULTS: There was a significant association between low bicarbonate and low albumin level in hemodialysis patient and between numbers and duration of dialysis session with albumin. Low Kt/V was significantly associated with hypoalbuminemia. There was no statistically significant association between age and gender with hypoalbuminemia. CONCLUSION: This study shows that patients with metabolic acidosis had a lower serum albumin concentration and there was a significant correlation between numbers, duration and adequacy of hemodialysis sessions and albumin level. We recommend to increase the numbers of dialysis centers in Iraq and adjust the bicarbonate doses in dialysate according to patient’s bicarbonate levels.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".