Högskolan i Skövde

his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Preoperative Prediction of Body Mass Index of Patients with Type 2 Diabetes at 1 Year After Laparoscopic Sleeve Gastrectomy: Cross-Sectional Study
University of Skövde, School of Health Sciences. University of Skövde, Digital Health Research (DHEAR). Department of Surgery, Hamad Medical Corporation, Doha, Qatar ; College of Medicine, Qatar University, Doha, Qatar ; Weill Cornell Medicine-Qatar, Doha, Qatar. (Medborgarcentrerad hälsa MeCH, Research on Citizen Centered Health, University of Skövde (Reacch US))ORCID iD: 0000-0003-0961-1302
Department of Bariatric Surgery/Bariatric Medicine, Hamad Medical Corporation, Doha, Qatar.
2022 (English)In: Metabolic Syndrome and Related Disorders, ISSN 1540-4196, E-ISSN 1557-8518, Vol. 20, no 6, p. 360-366Article in journal (Refereed) Published
Abstract [en]

Background: Very few models predict weight loss among type 2 diabetes mellitus (T2D) patients after laparoscopic sleeve gastrectomy (LSG). This retrospective study undertook such a task. Materials and Methods: We identified all patients >18 years old with T2D who underwent primary LSG at our institution and had complete data. The training set comprised 107 patients operated upon during the period April 2011 to June 2014; the validation set comprised 134 patients operated upon during the successive chronological period, July 2014 to December 2015. Sex, age, presurgery BMI, T2D duration, number of T2D medications, insulin use, hypertension, and dyslipidemia were utilized as independent predictors of 1-year BMI. We employed regression analysis, and assessed the goodness of fit and "Residuals versus Fits" plot. Paired sample t-tests compared the observed and predicted BMI at 1 year. Results: The model comprised preoperative BMI (β = 0.757, P = 0.026) + age (β = 0.142, P < 0.0001) with adjusted R2 of 0.581 (P < 0.0001), and goodness of fit showed an unbiased model with accurate prediction. The equation was: BMI value 1 year after LSG = 1.777 + 0.614 × presurgery BMI (kg/m2) +0.106 × age (years). For validation, the equation exhibited an adjusted R2 0.550 (P < 0.0001), and the goodness of fit indicated an unbiased model. The BMI predicted by the model fell within -3.78 BMI points to +2.42 points of the observed 1-year BMI. Pairwise difference between the mean 1-year observed and predicted BMI was not significant (-0.41 kg/m2, P = 0.225). Conclusions: This predictive model estimates the BMI 1 year after LSG. The model comprises preoperative BMI and age. It allows the forecast of patients' BMI after surgery, hence setting realistic expectations which are critical for patient satisfaction after bariatric surgery. An attainable target motivates the patient to achieve it.

Place, publisher, year, edition, pages
Mary Ann Liebert, 2022. Vol. 20, no 6, p. 360-366
Keywords [en]
body mass index, laparoscopic sleeve gastrectomy, model, prediction at 1 year, type 2 diabetes mellitus, weight loss
National Category
Surgery Health Care Service and Management, Health Policy and Services and Health Economy Bio Materials
Research subject
Research on Citizen Centered Health, University of Skövde (Reacch US)
Identifiers
URN: urn:nbn:se:his:diva-21742DOI: 10.1089/met.2021.0153ISI: 000876255500001PubMedID: 35506900Scopus ID: 2-s2.0-85136342905OAI: oai:DiVA.org:his-21742DiVA, id: diva2:1692129
Available from: 2022-09-01 Created: 2022-09-01 Last updated: 2023-08-23Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records

El Ansari, Walid

Search in DiVA

By author/editor
El Ansari, Walid
By organisation
School of Health SciencesDigital Health Research (DHEAR)
In the same journal
Metabolic Syndrome and Related Disorders
SurgeryHealth Care Service and Management, Health Policy and Services and Health EconomyBio Materials

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 192 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf