Effect of goal-directed fluid therapy on early cognitive function in elderly patients with spinal stenosis: A Case-Control Study
Bibliographic record
Abstract
To explore effect of goal-directed fluid therapy (GDFT) on early cognitive function in elderly patients with spinal stenosis. 83 elderly patients with spinal stenosis were randomly classified into two groups: control group (n = 40) and GDFT group (n = 43). The Montreal Cognitive Assessment (MoCA) score, IL-6 and S100β levels, hemodynamic parameters, cerebral oxygen saturation (rSO2), arterial lactic acid values, output of surgery, operation time and cases of hypotension, intraoperative complications within 7 days were recorded for all patients. The incidence of postoperative cognitive dysfunction (POCD) was about 21.67% in this study. The MoCA scores, inflammatory mediators, perfusion indexes (rSO2 and lactic acid)and intraoperative hemodynamics(HR, MAP, and CI)were not all the same at different time points (P < 0.05). The levels of inflammatory mediators (IL-6 and S100β) in GDFT group were lower than those in the control group (P < 0.05). Total intake, amount of lactated Ringer's solution and cases of hypotension in GDFT group were significantly lower than control group (P < 0.05), but amount of voluven was higher than control group(P < 0.05). Compared with control group, the incidence of postoperative delirium, nausea and vomiting, and hypotension in GDFT group was lower (P < 0.05). GDFT can maintain the stability of perioperative hemodynamics in the prone position of elderly patients with spinal stenosis, improve the balance between perfusion of tissue and organ and supply and demand of oxygen, reduce the inflammatory response, and reduce the incidence of early POCD in this type of surgery.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".