Hypoalbuminemia is an important risk factor of hypotension during hemodialysis
Bibliographic record
Abstract
Hypotension during hemodialysis (HD) is an important problem in patients on HD. To investigate the risk factors that contribute to the hypotension during HD, we compared background factors of hypotensive (HP) patients during HD. Among 58 patients undergoing HD in Tamura Memorial Hospital, 12 patients could not continue full HD because of hypotension. We compared the data of ultrafiltration volume, cardiothoracic ratio (CTR), total protein (TP), serum albumin, blood urea nitrogen (BUN), serum creatinine, total cholesterol (TC), hemoglobin (Hb), blood glucose (BS), brain natriuretic peptide (BNP), and cardiac function between HP patients (HP group; n=12) and sex- and age-matched control patients (NP group; n=12). There were no significant differences of age, sex, and duration of HD between the 2 groups. Cardiothoracic ratio is bigger and BNP is higher in the HP group compared with the NP group (CTR: HP 55.8+/-2.9% vs. NP 47.7+/-1.1%, p=0.0165; BNP: HP 602+/-171 vs. NP 147+/-38, p=0.0167). Serum albumin in the HP group is significantly lower compared with the NP group (HP 3.2+/-0.1 g/dL vs. NP 3.5+/-0.1 g/dL, p=0.0130). However, there were no significant differences of ultrafiltration rate (UFR), BS, TC, Hb, and cardiac function between the 2 groups. There is a significant negative correlation between changes of systolic blood pressure (delta systolic blood pressure) and serum albumin in these patients (r=-0.598, p=0.0016). From these data, we conclude that hypoalbuminemia is a major risk factor of hypotension during HD.
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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 | 0.000 | 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 | 0.001 |
| 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".