[Effect of integrative medical therapy on post-angioplasty arterial restenosis in lower limbs of diabetic patients].
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effect of integrative medical therapy on lower limb post-angioplasty arterial restenosis in diabetes patients. METHODS: Thirty-six patients with lower limb diabetic arterial disease of Fontaine III/IV stage after successful balloon angioplasty were assigned randomly and equally to two groups, the control group and the treatment group, both were treated with basic therapy for 3 months, but Chinese drugs were given to the treatment group additionally. Level of acroesthesia was determined before and after treatment with simplified McGill pain questionnaire (SF-MPQ) scoring, ankle brachial index (ABI), toe brachial index (TBI), mean flow velocity of dorsal artery (MDA) and tibial artery (MTA) were measured by ultrasound Doppler meter, and blood preparation was determined. Moreover, the ulcer remission rate, ulcer cure rate, restenosis rate, and amputation rate were determined in the 6-month and 12-month follow-up studies. RESULTS: Significant improvements of ABI, TBI, MDA and MTA, as well as on blood levels of high-sensitivity C-reactive protein (hs-CRP) and fibrinogen (FIB) were shown in the treatment group after treatment, showing significant difference in comparing with those before treatment (P < 0.05 or P < 0.01), also in comparing with the control group (P < 0.05 or P < 0.01) respectively, while in the control group, although a trend of improvement was seen, these indices were insignificantly changed statistically (P > 0.05). Comparisons between groups after 3-month treatment showed significant difference in ischemia remission rate and pain relief rate (P < 0.05). Outcomes of 6-month follow-up displayed that the differences between groups were insignificant in terms of the ulcer cure rate the and amputation rate (P > 0.05), but did show significance in the ulcer remission rate and the restenosis rate (P < 0.05), while all the 4 parameters were insignificantly different between groups after 12-month follow-up (P > 0.05). Overall incidence of adverse event was somewhat higher in the treatment group, but there was no significant statistically difference. CONCLUSION: Integrative medical therapy could improve the hemodynamic indices and pain symptoms, raise the ulcer cure rate and reduce the incidence of restenosis in patients with diabetic arterial disease after balloon angioplasty.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".