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Record W4255512187 · doi:10.14740/jem564

Dapagliflozin Add-On Therapy Improves Body Composition and Metabolic Parameters in Overweight Type 2 Diabetic Patients: A Pilot Study

2019· article· en· W4255512187 on OpenAlexvenueno aff
Ugo Di Folco, Alessandra Gatti, Maria Rosaria Nardone, Claudio Tubili

Bibliographic record

VenueJournal of Endocrinology and Metabolism · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsDapagliflozinMedicineOverweightInternal medicineBody mass indexEndocrinologyMetforminDiabetes mellitusType 2 diabetesWeight lossType 2 Diabetes MellitusBody waterObesityBody weight

Abstract

fetched live from OpenAlex

Background: Sodium-glucose cotransporter-2 inhibitors (SGLT2-i) inhibit renal glucose reabsorption in the proximal tubules, and reduce plasma glucose, body weight and cardiovascular risk in patients with type 2 diabetes mellitus (T2DM). The data on the effect of SGLT-2i on body composition are conflicting: in some reports, they reduce fat mass, while in other reports, they determine reduction of extra- and intra-cellular fluids. The aim of our pilot study was to investigate the body compartments changes and the effects on glycemia and plasma lipids of add-on SGLT2-i dapagliflozin therapy in poorly controlled overweight/obese T2DM patients. Methods: Fifty-six overweight (body mass index (BMI) > 25) uncontrolled (HbA1c > 53 mmol/mol; 7%) T2DM outpatients were recruited. They were treated with metformin and basal insulin (group A) or metformin (group B). Weight, BMI, waist circumference (WC), fasting blood glucose (FPG), HbA1c, plasma lipids, bioelectric parameters and derived body compartments (phase angle (pA), total body water (TBW), fat free mass (FFM) and fat mass (FM)) were assessed at baseline (T0) and after 16 weeks (T1) of dapagliflozin 10 mg add-on treatment. Student’s t -test and one-way analysis of variance (ANOVA) were used to compare the T0 and T1 data. Results: After 16 weeks, all the patients had weight loss (-3.0 ± 0.6 kg, P < 0.0001) and reduced WC (-2.5 ± 0.6 cm, P < 0.0001). Weight reduction was significant in both groups separately (group A: -2.5 ± 0.3 kg, P <= 0.001; group B: -3.4 ± 0.4 kg, P <= 0.001) and was higher in group B. FFM was not impaired in group A (from 60.2 ± 5.2 to 59.5 ± 8.1 kg; ns) and in group B (from 60.4 ± 6.2 to 59.3 ± 6.6 kg; ns). FM decreased in all the patients (29.9 ± 6.84 kg vs. 26.30 ± 7.4 kg, P < 0.000); a higher reduction was found in group B (-3.6 ± 1.2 kg, P < 0.001) vs. group A (-2.3 ± 1.3 kg, P < 0.001). Metabolic control improved in all the patients: FPG 172 ± 49.4 mg/dL vs. 137 ± 36.8 mg/dL at T1, P < 0.0001; HbA1c 69 ± 9.3 mmol/mol (8.5±1.5%) vs. 60 ± 8.7 mmol/mol (7.6±1.4%), P = 0.000. In group A, insulin dose was reduced by 9.3%. Cholesterol and triglycerides (TG) levels decreased in overall population (181.8 ± 48.8 mg/dL vs. 170.7 ± 40.7, P = 0.003; 172 ± 93 mg/dL vs. 143.2 ± 87.8, P = 0.000). Conclusions: Dapagliflozin add-on therapy induced weight loss and metabolic improvement in overweight and obese T2DM patients. Also insulin-treated patients had weight loss (2.5 kg). Bioelectric impedance analysis (BIA) demonstrated FM loss without FFM impairment and was confirmed to be a simple and effective method to assess body composition in clinical practice. J Endocrinol Metab. 2019;9(4):90-94 doi: https://doi.org/10.14740/jem564

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)0.001
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.261
Teacher spread0.245 · 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 designNon-randomized trial
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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Citations1
Published2019
Admission routes1
Has abstractyes

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