scholarly journals External validation of type 2 diabetes computer simulation models: definitions, approaches, implications and room for improvement—a protocol for a systematic review

2017 ◽  
Vol 6 (1) ◽  
Author(s):  
Katherine Ogurtsova ◽  
Thomas L. Heise ◽  
Ute Linnenkamp ◽  
Charalabos-Markos Dintsios ◽  
Stefan K. Lhachimi ◽  
...  
Keyword(s):  
Systematic Review ◽  
Type 2 Diabetes ◽  
Computer Simulation ◽  
External Validation ◽  
Simulation Models ◽  
Computer Simulation Models

scholarly journals Computer simulation models of pre-diabetes populations: a systematic review protocol

BMJ Open ◽  
2017 ◽  
Vol 7 (10) ◽  
pp. e014954 ◽  
Author(s):  
Jose Leal ◽  
Waqar Khurshid ◽  
Eva Pagano ◽  
Talitha Feenstra
Keyword(s):  
Systematic Review ◽  
Computer Simulation ◽  
Cost Effectiveness ◽  
Public Health Problem ◽  
Simulation Models ◽  
Decision Models ◽  
Economic Evaluations ◽  
Major Public Health Problem ◽  
Computer Simulation Models ◽  
The Impact

IntroductionDiabetes is a major public health problem and prediabetes (intermediate hyperglycaemia) is associated with a high risk of developing diabetes. With evidence supporting the use of preventive interventions for prediabetes populations and the discovery of novel biomarkers stratifying the risk of progression, there is a need to evaluate their cost-effectiveness across jurisdictions. In diabetes and prediabetes, it is relevant to inform cost-effectiveness analysis using decision models due to their ability to forecast long-term health outcomes and costs beyond the time frame of clinical trials. To support good implementation and reimbursement decisions of interventions in these populations, models should be clinically credible, based on best available evidence, reproducible and validated against clinical data. Our aim is to identify recent studies on computer simulation models and model-based economic evaluations of populations of individuals with prediabetes, qualify them and discuss the knowledge gaps, challenges and opportunities that need to be addressed for future evaluations.Methods and analysisA systematic review will be conducted in MEDLINE, Embase, EconLit and National Health Service Economic Evaluation Database. We will extract peer-reviewed studies published between 2000 and 2016 that describe computer simulation models of the natural history of individuals with prediabetes and/or decision models to evaluate the impact of interventions, risk stratification and/or screening on these populations. Two reviewers will independently assess each study for inclusion. Data will be extracted using a predefined pro forma developed using best practice. Study quality will be assessed using a modelling checklist. A narrative synthesis of all studies will be presented, focussing on model structure, quality of models and input data, and validation status.Ethics and disseminationThis systematic review is exempt from ethics approval because the work is carried out on published documents. The findings of the review will be disseminated in a related peer-reviewed journal and presented at conferences.Reviewregistration numberCRD42016047228.

scholarly journals Prognostic models for predicting the risk of foot ulcer or amputation in people with type 2 diabetes: a systematic review and external validation study

Diabetologia ◽  
2021 ◽  
Author(s):  
Joline W. J. Beulens ◽  
Josan S. Yauw ◽  
Petra J. M. Elders ◽  
Talitha Feenstra ◽  
Ron Herings ◽  
...  
Keyword(s):  
Systematic Review ◽  
Type 2 Diabetes ◽  
Data Extraction ◽  
External Validation ◽  
Foot Ulcer ◽  
Predictive Performance ◽  
Prognostic Models ◽  
Bias Assessment

Abstract Aims/hypothesis Approximately 25% of people with type 2 diabetes experience a foot ulcer and their risk of amputation is 10–20 times higher than that of people without type 2 diabetes. Prognostic models can aid in targeted monitoring but an overview of their performance is lacking. This study aimed to systematically review prognostic models for the risk of foot ulcer or amputation and quantify their predictive performance in an independent cohort. Methods A systematic review identified studies developing prognostic models for foot ulcer or amputation over minimal 1 year follow-up applicable to people with type 2 diabetes. After data extraction and risk of bias assessment (both in duplicate), selected models were externally validated in a prospective cohort with a 5 year follow-up in terms of discrimination (C statistics) and calibration (calibration plots). Results We identified 21 studies with 34 models predicting polyneuropathy, foot ulcer or amputation. Eleven models were validated in 7624 participants, of whom 485 developed an ulcer and 70 underwent amputation. The models for foot ulcer showed C statistics (95% CI) ranging from 0.54 (0.54, 0.54) to 0.81 (0.75, 0.86) and models for amputation showed C statistics (95% CI) ranging from 0.63 (0.55, 0.71) to 0.86 (0.78, 0.94). Most models underestimated the ulcer or amputation risk in the highest risk quintiles. Three models performed well to predict a combined endpoint of amputation and foot ulcer (C statistics >0.75). Conclusions/interpretation Thirty-four prognostic models for the risk of foot ulcer or amputation were identified. Although the performance of the models varied considerably, three models performed well to predict foot ulcer or amputation and may be applicable to clinical practice. Graphical abstract

scholarly journals A review of simulation models for the long-term management of type 2 diabetes in low-and-middle income countries

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Elton Mukonda ◽  
Susan Cleary ◽  
Maia Lesosky
Keyword(s):  
Type 2 Diabetes ◽  
Computer Simulation ◽  
Cost Effectiveness ◽  
Simulation Models ◽  
Simulation Modelling ◽  
Middle Income ◽  
Middle Income Countries ◽  
Low And Middle Income

Abstract Introduction The burden of type 2 diabetes is steadily increasing in low-and-middle-income countries, thereby posing a major threat from both a treatment, and funding standpoint. Although simulation modelling is generally relied upon for evaluating long-term costs and consequences associated with diabetes interventions, no recent article has reviewed the characteristics and capabilities of available models used in low-and-middle-income countries. We review the use of computer simulation modelling for the management of type 2 diabetes in low-and-middle-income countries. Methods A search for studies reporting computer simulation models of the natural history of individuals with type 2 diabetes and/or decision models to evaluate the impact of treatment strategies on these populations was conducted in PubMed. Data were extracted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and assessed using modelling checklists. Publications before the year 2000, from high-income countries, studies involving animals and analyses that did not use mathematical simulations were excluded. The full text of eligible articles was sourced and information about the intervention and population being modelled, type of modelling approach and the model structure was extracted. Results Of the 79 articles suitable for full text review, 44 studies met the inclusion criteria. All were cost-effectiveness/utility studies with the majority being from the East Asia and Pacific region (n = 29). Of the included studies, 34 (77.3%) evaluated the cost-effectiveness of pharmacological interventions and approximately 75% of all included studies used HbA1c as one of the treatment effects of the intervention. 32 (73%) of the publications were microsimulation models, and 29 (66%) were state-transition models. Most of the studies utilised annual cycles (n = 29, 71%), and accounted for costs and outcomes over 20 years or more (n = 38, 86.4%). Conclusions While the use of simulation modelling in the management of type 2 diabetes has been steadily increasing in low-and-middle-income countries, there is an urgent need to invest in evaluating therapeutic and policy interventions related to type 2 diabetes in low-and-middle-income countries through simulation modelling, especially with local research data. Moreover, it is important to improve transparency and credibility in the reporting of input data underlying model-based economic analyses, and studies.

scholarly journals Performance of prediction models for nephropathy in people with type 2 diabetes: systematic review and external validation study

BMJ ◽  
2021 ◽  
pp. n2134
Author(s):  
Roderick C Slieker ◽  
Amber A W A van der Heijden ◽  
Moneeza K Siddiqui ◽  
Marlous Langendoen-Gort ◽  
Giel Nijpels ◽  
...  
Keyword(s):  
Systematic Review ◽  
Type 2 Diabetes ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
General Population ◽  
Diabetic Kidney Disease ◽  
Prediction Models ◽  
External Validation ◽  
Diabetic Kidney

Abstract Objectives To identify and assess the quality and accuracy of prognostic models for nephropathy and to validate these models in external cohorts of people with type 2 diabetes. Design Systematic review and external validation. Data sources PubMed and Embase. Eligibility criteria Studies describing the development of a model to predict the risk of nephropathy, applicable to people with type 2 diabetes. Methods Screening, data extraction, and risk of bias assessment were done in duplicate. Eligible models were externally validated in the Hoorn Diabetes Care System (DCS) cohort (n=11 450) for the same outcomes for which they were developed. Risks of nephropathy were calculated and compared with observed risk over 2, 5, and 10 years of follow-up. Model performance was assessed based on intercept adjusted calibration and discrimination (Harrell’s C statistic). Results 41 studies included in the systematic review reported 64 models, 46 of which were developed in a population with diabetes and 18 in the general population including diabetes as a predictor. The predicted outcomes included albuminuria, diabetic kidney disease, chronic kidney disease (general population), and end stage renal disease. The reported apparent discrimination of the 46 models varied considerably across the different predicted outcomes, from 0.60 (95% confidence interval 0.56 to 0.64) to 0.99 (not available) for the models developed in a diabetes population and from 0.59 (not available) to 0.96 (0.95 to 0.97) for the models developed in the general population. Calibration was reported in 31 of the 41 studies, and the models were generally well calibrated. 21 of the 64 retrieved models were externally validated in the Hoorn DCS cohort for predicting risk of albuminuria, diabetic kidney disease, and chronic kidney disease, with considerable variation in performance across prediction horizons and models. For all three outcomes, however, at least two models had C statistics >0.8, indicating excellent discrimination. In a secondary external validation in GoDARTS (Genetics of Diabetes Audit and Research in Tayside Scotland), models developed for diabetic kidney disease outperformed those for chronic kidney disease. Models were generally well calibrated across all three prediction horizons. Conclusions This study identified multiple prediction models to predict albuminuria, diabetic kidney disease, chronic kidney disease, and end stage renal disease. In the external validation, discrimination and calibration for albuminuria, diabetic kidney disease, and chronic kidney disease varied considerably across prediction horizons and models. For each outcome, however, specific models showed good discrimination and calibration across the three prediction horizons, with clinically accessible predictors, making them applicable in a clinical setting. Systematic review registration PROSPERO CRD42020192831.

Plant-based diet and risk of type 2 diabetes mellitus: a systematic review and meta-analysis

2020 ◽  
pp. 1301-1306
Author(s):  
Arwa Aljabali ◽  
Roaa Maghrabi ◽  
Ahmad Shok ◽  
Ghufran Alshawmali ◽  
Abdullah Alqahtani ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Systematic Review ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Meta Analysis

A grading scale for surgically treated patients with spontaneous supratentorial intracerebral hemorrhage: the Surgical Swedish ICH Score

2020 ◽  
Vol 133 (3) ◽  
pp. 800-807 ◽  
Author(s):  
Andreas Fahlström ◽  
Henrietta Nittby Redebrandt ◽  
Hugo Zeberg ◽  
Jiri Bartek ◽  
Andreas Bartley ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Intracerebral Hemorrhage ◽  
External Validation ◽  
Grading Scale ◽  
Ich Score ◽  
Gcs Score ◽  
Strength Of Association ◽  
Point Type ◽  
Clinical Grading

OBJECTIVEThe authors aimed to develop the first clinical grading scale for patients with surgically treated spontaneous supratentorial intracerebral hemorrhage (ICH).METHODSA nationwide multicenter study including 401 ICH patients surgically treated by craniotomy and evacuation of a spontaneous supratentorial ICH was conducted between January 1, 2011, and December 31, 2015. All neurosurgical centers in Sweden were included. All medical records and neuroimaging studies were retrospectively reviewed. Independent predictors of 30-day mortality were identified by logistic regression. A risk stratification scale (the Surgical Swedish ICH [SwICH] Score) was developed using weighting of independent predictors based on strength of association.RESULTSFactors independently associated with 30-day mortality were Glasgow Coma Scale (GCS) score (p = 0.00015), ICH volume ≥ 50 mL (p = 0.031), patient age ≥ 75 years (p = 0.0056), prior myocardial infarction (MI) (p = 0.00081), and type 2 diabetes (p = 0.0093). The Surgical SwICH Score was the sum of individual points assigned as follows: GCS score 15–13 (0 points), 12–5 (1 point), 4–3 (2 points); age ≥ 75 years (1 point); ICH volume ≥ 50 mL (1 point); type 2 diabetes (1 point); prior MI (1 point). Each increase in the Surgical SwICH Score was associated with a progressively increased 30-day mortality (p = 0.0002). No patient with a Surgical SwICH Score of 0 died, whereas the 30-day mortality rates for patients with Surgical SwICH Scores of 1, 2, 3, and 4 were 5%, 12%, 31%, and 58%, respectively.CONCLUSIONSThe Surgical SwICH Score is a predictor of 30-day mortality in patients treated surgically for spontaneous supratentorial ICH. External validation is needed to assess the predictive value as well as the generalizability of the Surgical SwICH Score.

Sign in / Sign up

Export Citation Format

Share Document