CoChat
Sign Up
Cited by 284Diabetes Management and ResearchDiabetes Treatment and ManagementDiabetes Management and Education

The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.

Self-monitoring of blood glucose in type 2 diabetes and long-term outcome: an epidemiological cohort study

Open access
Martin, S., Schneider, B., Heinemann, L., Lodwig, V., Kurth, H.-J., Kolb, H., Scherbaum, W. A., for the ROSSO Study Group·2006·Diabetologia
DOI 10.1007/s00125-005-0083-5
Open this paper in CoChat — free accountOpen PDF

Abstract

Aims/hypothesis The aim of this study was to obtain epidemiological data on self-monitoring of blood glucose (SMBG) in type 2 diabetes and to investigate the relationship of SMBG with disease-related morbidity and mortality.Methods The German multicentre Retrolective Study 'Self-monitoring of Blood Glucose and Outcome in Patients with Type 2 Diabetes' (ROSSO) followed 3,268 patients from diagnosis of type 2 diabetes between 1995 and 1999 until the end of 2003. Endpoints were diabetes-related morbidity (non-fatal myocardial infarction, stroke, foot amputation, blindness or haemodialysis) and all-cause mortality. SMBG was defined as self-measurement of blood glucose for at least 1 year.Results During a mean follow-up period of 6.5 years, 1,479 patients (45.3%) began SMBG prior to an endpoint and an additional 64 patients started SMBG after a non-fatal endpoint. Interestingly, many patients used SMBG while being treated with diet or oral hypoglycaemic drugs (808 of 2,515, 32%). At baseline, the SMBG cohort had higher mean fasting blood glucose levels than the non-SMBG cohort (p<0.001), suggesting that insufficient metabolic control was one reason for initiating SMBG. This was associated with a higher rate of microvascular endpoints. However, the total rate of non-fatal events, micro- and macrovascular, was lower in the SMBG group than in the non-SMBG group (7.2 vs 10.4%, p=0.002). A similar difference was found for the rate of fatal events (2.7 vs 4.6%, p=0.004). Cox regression analysis identified SMBG as an independent predictor of morbidity and mortality, with adjusted hazard ratios of 0.68 (95% CI 0.51-0.91, p=0.009) and 0.49 (95% CI 0.31-0.78, p=0.003), respectively. A better outcome for both endpoints was also observed in the SMBG cohort when only those patients who were not receiving insulin were analysed.Conclusions/interpretation SMBG was associated with decreased diabetes-related morbidity and all-cause mortality in type 2 diabetes, and this association remained in a subgroup of patients who were not receiving insulin therapy. SMBG may be associated with a healthier lifestyle and/or better disease management.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s00125-005-0083-5

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Cited by

Sorted by citations

See all 284

Related

See all

Metadata

Authors
Martin, S., Schneider, B., Heinemann, L., Lodwig, V., Kurth, H.-J., Kolb, H., Scherbaum, W. A., & for the ROSSO Study Group
Affiliations
  • Deutsches Diabetes-Zentrum e.V. (DE)
  • Medizinische Hochschule Hannover (DE)
  • Profil Institute for Metabolic Research (DE)
  • Institute for Medical Informatics and Biostatistics (CH)
Corresponding author
Martin, S.
ORCID
Venue
Diabetologia
Publisher
Springer Science and Business Media LLC
Published
2005-12-17
Volume
49
Issue
2
Pages
271-278
ISSN
  • 0012-186X (ISSN-L)
  • 1432-0428
DOI
10.1007/s00125-005-0083-5
OpenAlex
W2142280025
Cited by
284
References
40
Citations by year
2026: 2 · 2025: 3 · 2024: 8 · 2023: 7 · 2022: 8 · 2021: 5 · 2020: 11 · 2019: 11 · 2018: 6 · 2017: 16 · 2016: 7 · 2015: 13 · 2014: 19 · 2013: 13 · 2012: 21
FWCI
14.69
Type
journal article
Language
en
Open access
Licence
www.springer.com/tdm (tdm)
Locations
  • Diabetologia (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Bundesministerium für Bildung und Forschung
  • Bundesministerium für Gesundheit
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
Keywords
self-monitoring of blood glucose, type 2 diabetes, all-cause mortality, microvascular complications, macrovascular complications, glycemic control, fasting blood glucose, insulin therapy, oral antidiabetic drugs, myocardial infarction, stroke, foot amputation, blindness
MeSH terms
Aged, Blood Glucose, Diabetes Mellitus, Type 2, Female, Follow-Up Studies, Humans, Hypoglycemic Agents, Insulin, Longitudinal Studies, Male, Middle Aged, Regression Analysis, Retrospective Studies, Blood Glucose Self-Monitoring, Cohort Studies, Survival Analysis, Outcome Assessment, Health Care, Disease Management, Diabetes Complications

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review