Role of magnesium in the risk of intradialytic hypotension among maintenance hemodialysis patients
Bibliographic record
Abstract
INTRODUCTION: Intradialytic hypotension (IDH) is a common complication in end-stage renal disease patients on hemodialysis (HD). It has been documented that several factors contribute to IDH. However, the relationship between serum electrolytes and the occurrence of IDH remains unclear. Our study aims to investigate the role of serum magnesium (Mg) for the risk of IDH in maintenance HD patients. METHODS: The retrospective study included adults starting HD before January 2009 in the blood purification center, Zhongshan Hospital, Fudan University, and treated thrice weekly with standard bicarbonate dialysate by low-flux HD. Patients' characteristics including age and sex, laboratory test results were collected. IDH was defined according to kidney disease outcomes quality initiative (K/DOQI) guidelines as a decrease in systolic blood pressure (SBP) by ≥20 mmHg or a decrease in mean arterial pressure (MAP) by ≥10 mmHg associated with clinical symptoms during HD. Multivariate logistic regression was employed to explore independent risk factors for IDH. FINDINGS: Among 423 patients recruited, 175 patients (41.4%) suffered from IDH. Compared with those with non-IDH, patients with IDH presented higher predialysis serum Mg levels. Univariate correlation analysis showed that predialysis serum Mg level was negatively correlated with SBP at 3 hours, 4 hours after dialysis (3 hours SBP r = -0.134 P = 0.006, 4 hours SBP r = -0.142 P = 0.003) and was positively correlated with the differences of blood pressure (BP) (SBP and MAP) (△SBP r = 0.195 P < 0.001, △MAP r = 0.155, P = 0.001). After adjustment for predialysis blood urea nitrogen, platelet distribution width, cardiac troponin T, fasting blood glucose, β2-microglobulin, and predialysis MAP, multivariate logistic regression analysis demonstrated that predialysis serum Mg level was one of the independent risk factors for IDH (odds ratio [95% confidence interval-CI]: 7.154 (1.568-32.637); P = 0.011). In addition, Mg levels of 1.15 mmol/L or higher were associated with a high incidence of IDH. DISCUSSION: Our findings suggested that higher predialysis serum Mg level was one of the independent risk factors for IDH among maintenance hemodialysis (MHD patients).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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) | 0.001 | 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".