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Effect of red light combined with hot compress on peripheral neuropathy of diabetes

2019· article· en· W3031514218 on OpenAlexaboutno aff
Hongmei Zhou, Xiaochun Yang

Bibliographic record

VenueZhongguo jiceng yiyao · 2019
Typearticle
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNerve conduction velocityPeripheral neuropathyDiabetes mellitusInternal medicineMedian nerveGastroenterologySurgeryEndocrinology

Abstract

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Objective To investigate the effect of red light combined with hot compress on diabetic peripheral neuropathy (DPN). Methods From June 2017 to June 2018, 110 patients with DPN admitted to the Department of Endocrinology, Hangzhou Hospital of Traditional Chinese Medicine were selected in the study.The patients were divided into study group (55 cases) and control group (55 cases) according to the random number table method.All patients were given DPN basic care and treatment, with red light in the control group, and red light combined with hot compress in the study group.The motor nerve conduction velocity (MCV) and the sensory nerve conduction velocity (SCV) of the ulnar nerve, median nerve and common peroneal nerve were compared between the two groups before and after treatment.The total scores of the Toronto clinical scoring system (TCSS) were compared between the two groups before and after treatment.The efficacy of the two groups was compared. Results Before treatment, there were no statistically significant differences in MCV [(40.45±5.33)m/s vs.(40.14±5.08)m/s, t=0.312, P=0.755; (41.15±5.51)m/s vs.(40.86±5.23)m/s, t=0.283, P=0.778; (42.27±5.84)m/s vs.(41.94±5.75)m/s, t=0.299, P=0.766] and SCV [(39.38±4.82)m/s vs.(39.08±4.60)m/s, t=0.334, P=0.739; (40.13±5.45)m/s vs.(39.86±5.15)m/s, t=0.267, P=0.790; (41.18±5.78)m/s vs.(40.89±5.46)m/s, t=0.278, P=0.782] between the ulnar nerve, median nerve and common peroneal nerve in the two groups.After treatment, the ulnar nerve, median nerve and common peroneal nerve of the two groups were treated.The MCV[(48.77±7.25)m/s vs.(44.62±6.30)m/s, t=3.204, P=0.002; (49.35±7.46)m/s vs.(45.36±6.45)m/s, t=3.001, P=0.003; (49.26±7.13)m/s vs.(46.35±6.22)m/s, t=2.281, P=0.025] and SCV[(47.67±6.52)m/s vs.(43.57±5.61)m/s, t=3.535, P=0.001; (47.77±6.63)m/s vs.(44.31±5.14)m/s, t=3.059, P=0.003; (48.33±7.17)m/s vs.(45.12±6.41)m/s, t=2.475, P=0.015] of the two groups were increased, while which of the study group increased more significantly.Before treatment, there was no statistically significant difference in the total scores of TCSS between the two groups [(10.15±1.23)points vs.(10.45±1.51)points, t=1.142, P=0.256]. After treatment, the total scores of TCSS decreased in the two groups, while which of the study group decreased more significantly[(7.22±0.85)points vs.(8.15±0.96)points, t=5.379, P=0.000]. After treatment, the effective rate of the study group was 87.27%, which of the control group was 63.64%, the difference was statistically significant(χ2=8.295, P=0.004). Conclusion The combination of red light and hot compress on DPN has a more prominent clinical effect, which is worthy of wide application. Key words: Diabetic neuropathies; Red light; Hot compress; Ulnar nerve; Median nerve; Common peroneal nerve; Motor nerve conduction velocity; Sensory nerve conduction velocity

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.004
GPT teacher head0.240
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2019
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