Evidence mapPaperPMID 26645793Full record

Trial reportJournal of diabetes science and technology2016

Integrated Personalized Diabetes Management (PDM): Design of the ProValue Studies: Prospective, Cluster-Randomized, Controlled, Intervention Trials for Evaluation of the Effectiveness and Benefit of PDM in Patients With Insulin-Treated Type 2 Diabetes.

Bernhard Kulzer, Wilfried Daenschel, Ingrid Daenschel, Erhard G Siegel, Wendelin Schramm, Christopher G Parkin, Diethelm Messinger, Joerg Weissmann, Zdenka Djuric, Angelika Mueller and 2 more

Abstract readMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in Journal of diabetes science and technology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Article
  6. Article
  7. A Review of Emerging Technologies in Diabetes Management for Multiple-Dose Insulin-Injecting Patients With Type 2 Diabetes Who Self-monitor Blood Glucose.The Journal of pharmacy technology : jPT : official publication of the Association of Pharmacy Technicians · 2019
    Review
  8. Review
  9. Digital Diabetes Self-Management: A Trilateral Serial.Journal of diabetes science and technology · 2018
    Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Bernhard KulzerForschungsinstitut Diabetes Akademie Bad Mergentheim, Bad Mergentheim, Germany.
Wilfried DaenschelÄrztlicher Leiter Medizinisches Versorgungszentrums am Küchwald GmbH, Chemnitz, Germany.
Ingrid DaenschelHausarztpraxis, Lunzenau, Germany.
Erhard G SiegelSt. Josefskrankenhaus Heidelberg, Heidelberg, Germany.
Wendelin SchrammGECKO Institute for Medicine, Informatics and Economics, Heilbronn University, Heilbronn, Germany.
Christopher G ParkinCGParkin Communications, Inc, Boulder City, NV, USA chris@cgparkin.org.
Diethelm MessingerBiometrics Department, IST GmbH, Mannheim, Germany.
Joerg WeissmannRoche Diabetes Care GmbH, Mannheim, Germany.
Zdenka DjuricRoche Diabetes Care GmbH, Mannheim, Germany.
Angelika MuellerRoche Diabetes Care GmbH, Mannheim, Germany.
Iris VesperRoche Diabetes Care GmbH, Mannheim, Germany.
Lutz HeinemannScience & Co, Düsseldorf, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCollaborative use of structured self-monitoring of blood glucose (SMBG) data and data management software, utilized within a 6-step cycle enables integrated Personalized Diabetes Management (PDM). The 2 PDM-ProValue studies shall assess the effectiveness of this approach in improving patient outcomes and practice efficiencies in outpatient settings.

methodsThe PDM-ProValue studies are 12-month, prospective, cluster-randomized, multicenter, trials to determine if use of integrated PDM in daily life improves glycemic control in insulin-treated type 2 diabetes patients. Fifty-four general medical practices (GPs) and 36 diabetes-specialized practices (DSPs) across Germany will be recruited. The practices will be randomly assigned to the control groups (CNL) or the intervention groups (INT) via cluster-randomization. CNL practices will continue with their usual care; INT practices will utilize integrated PDM. The sample size is 1,014 patients (n = 540 DSP patients, n = 474 GP patients). Each study is designed to detect a between-group difference in HbA1c change of at least 0.4% at 12 months with a power of 90% and 2-sided significance level of .05. Differences in timing and degree of treatment adaptions, treatment decisions, blood glucose target ranges, hypoglycemia, self-management behaviors, quality of life, patients attitudes, clinician satisfaction, practice processes, and resource consumption will be assessed. Study endpoints will be analyzed for the modified intent-to-treat and per protocol populations. Trial results are expected to be available in late 2016. DISCUSSION: Effective and efficient strategies to optimize diabetes management are needed. These randomized studies will help determine if PDM is beneficial.

Indexed as

Blood Glucose Self-MonitoringDiabetes Mellitus, Type 2FemaleHumansMaleMiddle AgedResearch Designdiabetes data managementpersonalized diabetes managementself-monitoring of blood glucoseSMBGtype 2 diabetes

Identifiers

PMID26645793
PMCPMC5038529

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.