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Evaluation of the Effects of Insulin Therapy on peripheral Nervous System in Diabetic Patients

2019· article· en· W2930084035 on OpenAlexaboutno aff
Mufeed Akram Taha

Bibliographic record

VenueIndian Journal of Public Health Research & Development · 2019
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPeripheralPeripheral nervous systemInsulinMedicineDiabetes mellitusInternal medicineBioinformaticsEndocrinologyBiologyCentral nervous system

Abstract

fetched live from OpenAlex

Peripheral neuropathy is common diabetic complication that associated with high rates of morbidity and mortality. Insulin therapy is essential in treatment of diabetic peripheral neuropathy; however, rapid strict glycemic control may lead to many complications such as neuropathy. This study performed to evaluate the effect of insulin therapy on peripheral nervous system in patients with type 2 diabetes. This study was conducted in outpatient clinics of Neurology departments of “Azadi Teaching Hospital in Kirkuk city-Iraq” during the period from the 1st of October, 2015 to 30th of September, 2017 included 50 type 2 diabetic patients treated with insulin therapy. Patients followed up at 3rd and 6th months after first examination by evaluating fasting blood sugar, hemoglobin A1c, Toronto scoring and nerve conduction study. Findings revealed predominance of females. There was a significant decline in overnight fasting blood sugar and hemoglobin A1c levels after 6 months follow up (p<0.001). The mean Toronto score increased from 5.9 at baseline to 10.6 after 3 months and 12.1 after 6 months. In conclusion the rapid strict glycemic control of blood sugar level is obviously considered to be a risk factor for peripheral neuropathy development among type 2 diabetic 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 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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.113
GPT teacher head0.395
Teacher spread0.282 · 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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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