Time to Hemostasis (TTH) after Needle Removal in ESRD Patients (pts) on Hemodialysis (HD) Treatment
Bibliographic record
Abstract
Prolonged bleeding after needle removal post-HD sessions results in increased blood loss and prolongs waiting time between shifts in HD treatment centers. We sought to identify factors that contribute to lengthening TTH after needle removal in ESRD patients on HD in an outpatient treatment facility. TTH was determined as the average of 4 measurements in 4 separate treatment sessions. Of 163 patients consecutively studied, 120 patients had TTH < 8 min, defined as short TTH, whereas in 43 patients TTH was > or = 8 min, defined as long TTH. Clinical and laboratory variables were analyzed by the Cox's proportional hazard model. The age of long TTH pts was 62 ± 15, similar to 58 ± 13 yr in short TTH pts. Long TTH pts had been on HD for 3.0 ± 1.6 yr, significantly longer than 2.2 ± 1.7 yr in short TTH pts. Blood pressure (BP) in long TTH pts was 139 ± 19/72 ± 11, significantly higher than 129 ± 16/68 ± 9 mmHg in short TTH pts. In long TTH pts, blood flow through the HD circuit (indicated by blood pump readings), and mean venous pressure (measured at the venous bubble trap) were 448 ± 36 and 241 ± 33, respectively, significantly greater than 436 ± 30 ml/min and 220 ± 35 mmHg in short TTH pts, and positively correlated with TTH (P < 0.001). AV graft was more likely than fistula to be associated with long TTH (P < 0.0001), as was an upper arm angioaccess compared with a forearm graft or fistula (P < 0.002). In pts with long TTH, the Hct was 34 ± 4, lower thn 38 ± 4% in short TTH pts (P < 0.0001), while the platelet count and the dose of heparin used during HD were similar in both groups. In the multivariate analysis, Hct, systolic BP, and AV graft were associated with long TTH. Conclusion: Higher levels of Hct, lower BP, use of an AV fistula and placement of a forearm access decrease TTH, leading to a decrease in post-HD blood loss as well as an increase in the efficiency of the HD unit.
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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 | 0.004 |
| 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 | 0.001 |
| 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".