Painless Gastrointestinal Endoscopy Assisted with Computed Tomography Image Information Data Monitoring in Postoperative Neurocognitive Dysfunction in Patients with Combined Anesthesia of Propofol and Butorphanol Tartrate under Electronic Health
Bibliographic record
Abstract
The aim of this study was to explore the value of computed tomography (CT) images based on electronic health (E-health) combined with painless gastrointestinal endoscopy (PGE) in the diagnosis of neurocognitive function in patients with combined anesthesia of propofol and butorphanol tartrate. 126 patients undergoing PGE were selected as the research objects, and all were performed with CT perfusion imaging before and after anesthesia to obtain the cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT), and time to peak (TTP). The Montreal Cognitive Assessment (MoCA) was adopted to evaluate the cognitive function of patients. The results showed that after anesthesia, the levels of CBF and CBV in the left and right thalami, frontal lobe, and temporal lobe of the patients were lower than those before anesthesia, while TTP and MTT were higher than those before anesthesia ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi>P</a:mi> <a:mo><</a:mo> <a:mn>0.05</a:mn> </a:math> ). The MoCA score after anesthesia was lower than that before anesthesia ( <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"> <c:mi>P</c:mi> <c:mo><</c:mo> <c:mn>0.05</c:mn> </c:math> ). After anesthesia, the CBF, CBV, TTP, and MTT values of the left and right frontal lobes and left and right temporal lobes were significantly positively correlated with MoCA ( <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M3"> <e:mi>P</e:mi> <e:mo><</e:mo> <e:mn>0.05</e:mn> </e:math> ). In conclusion, the brain CT image parameters based on E-health can clearly display the blood perfusion in the lesion area of the patient, which was beneficial to the PGE-assisted judgment of cognitive dysfunction in patients with propofol tartrate and butorphanol tartrate anesthesia. Therefore, CT-assisted PGE examination based on E-health had a certain clinical value in evaluating the neurocognitive function of 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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".