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P.14: Islet transplantation in type 1 DM: The perception gap in India

2023· article· en· W4387877229 on OpenAlexaboutno aff
Ravindra Shukla, Nagaraj Balasubramanian, Neelesh Agarwal

Bibliographic record

VenueTransplantation · 2023
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineImmunosuppressionIsletTransplantationType 1 diabetesIslet cell transplantationGlycemicDiabetes mellitusHypoglycemiaInternal medicineIntensive care medicineFamily medicineEndocrinology

Abstract

fetched live from OpenAlex

Association of Endocrine and Diabetes Researchers. Introduction: Recent studies have attested long term safety and efficacy of islet transplantation in Type 1 DM. (1) Our own studies have shown only limited benefit in escalating DSME in those with Hypoglycemic Unawareness (HA). (2) These would be likely islet allotransplant candidates. However, distorted perceptions among clinicians may hamper willingness of T1DM patients to agree to islet Tx Methods: Association of Endocrine and Diabetes Researchers (AEDR) conducted a google form based survey (through email) of those of our members with a degree of MD and above and an experience of at least 5 years in managing diabetes. Results:Of 281 eligible members 234 consented for the survey. About 201 (85%) agreed hypoglycemia to be major impediment in achieving glycemic targets.156 (66.7%) had >10% of their T1DM experiencing HA. This shows HA to be a significant problem recognized by clinicians. Yet when asked about possible intervention which can be offered to their patients, only 31 (13.6%) were aware of islet Tx. Majority would intensify DSME.73% would offer stem cell therapy, despite the fact that its not yet approved. When asked about concerns with islet tx, 84% were concerned with morbidity and mortality while 65% feared adverse effects of immunosuppression. Up to 84% were of the opinion that less than <10% of islet tx recipients will survive more than five years Conclusion: Recent advances in transplantation has not percolated among diabetologists and endocrinologists for obvious reasons. Islet transplant is often equated with solid organ transplant and hence perceived to have similar mortality As stem cell based therapies are being touted as holy grail for diabetes, islet transplantation no longer hogs limelight. This may explain the absurd optimism with stem cell therapy we found in the survey. It is also a grim reminder that Islet allo transplantation as therapy may die untimely death, and in places like India -never become available to those who need it- not because of economic or scientific reason; but because of sheer perception among those who care for type 1 DM subjects References: 1. Marfil-Garza BA et al Pancreatic islet transplantation in type 1 diabetes: 20-year experience from a single-centre cohort in Canada. Lancet Diabetes Endocrinol. 2022 Jul;10(7):519-532. 2. Gupta P et al Whatsapp for diabetes self management education (DSME) in type 1 diabetes mellitus: A randomized controlled trial. Indian J Endocrinol Metab. 2022 Mar;26(Suppl 1):S39.

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)0.004
metaresearch head score (Gemma)0.010
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: none
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0030.003
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0110.001

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 head0.029
GPT teacher head0.286
Teacher spread0.257 · 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
Published2023
Admission routes1
Has abstractyes

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