Systematic Review And Meta-Analysis
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Transcript of Systematic Review And Meta-Analysis
Cellular Phone-Based Technologies For Monitoring Of Patients With Diabetes: a Systematic Review and Meta Analysis
Systematic Review And Meta-Analysis
Class 3Professor Doutor João FonsecaIntrodução à Medicina II
Mobile phone based
tecnhologies
Chronic diseases
Applied in management of diseases [3]
60% of all deaths [1]
Slow progression
Introduction
Increasing international interest[2]
[1]http://www.who.int/en/, available on 1-11-2007
[2] Hilary Pinnock, Roger Slack, Claudia Pagliari, David Price, Aziz Sheikh; Understanding the potential role of mobile phone-based monitoring on asthma self-management: qualitative study; Clinical and Experimental Allergy. 2007 May;Kollmann et al., 20077(5):794-802; Available at: www.pubmed.com 26-10-2007.
[3] Ryan D, Cobern W, Wheeler J, Price D, Tarassenko L; Mobile Phone Technology in the Management of Asthma; Journal of Telemedicine and Telecare 2005; 11 Suppl 1:4Kollmann et al., 2007-6; Available at: www.pubmed.com 26-10-2007
Patient with diabetes
Quickly communication of symptoms (4]
Healthcare professional
Communication of adapted treatment
Fig. 1_ The role of CPT in the monitoring of patients with chronic diseases
[4] Morak J, Kollmann A, Schreier G; Feasibility and usability of a home monitoring concept based on mobile phones and near field communication (NFC) technology; Medinfo. 2007; 12 (Pt 1):112-6; Available at: www.pubmed.com 26-10-2007.
Diabetes
High mortality
High morbidity
Increasing prevalence in society [5]
Selection of one disease
Clear and structured article
Focused article
[5] AMOS A. F; MCCARTY D. J.; ZIMMET P., The rising global burden of diabetes and its implications: estimates and projections to the year 2010 ;Diabetic medicine ; 1997, vol.14, pp S7-S84, SUP5
Outcome
Patients’ medical state
Glycosylated haemoglobin
Fasting plasmatic glycemia
Research question
“Does cellular phone based tecnhologies monitoring
improve diabetes patients’ clinical outcomes?”
Systematic review and meta-analysis
search present summarize
Evidence collected from
articles
((monitoring) OR (telemonitoring)) AND ((cellular phone-based technologies) OR (mobile phone-based technologies) OR (cellular phone) OR (mobile phone)) AND ((chronic diseases) OR (chronic patients) OR (cancer)
OR (nephrologic diseases) OR (kidney insufficiency) OR (asthma) OR (respiratory chronic diseases) OR (COPD) OR (diabetes) OR (cardiovascular
disease)).
Query
PubmedIsi Web of knowledge Scopus
51 45 64
160Total
Articles Obtained
Inclusion/exclusion criteria
21 articles
applied
selected
50 repeatedarticles among databases
9 articles without abstract
Groups of two people read the abstracts
Articles per disease
Graphic 1_ Distribuition of diseases among obtained articles
Inclusion criteria Exclusion criteria Articles published in the last 10 years
Articles containing original data
Cellular phone-based technologies
(CPT)
Articles about the application of CPT
in patients
Articles regarding diabetes
Articles regarding comparison studies
Articles regarding the evolution of the
clinical state of the patient
Articles in English, Spanish and
French
Use of cellular-phone for interviewing
patients about other issues unrelated
to disease monitoring
Articles that describe technologies
and their development
Reading of full texts
21 articles
8 articles were obtained
applied Inclusion/exclusion
criteria
6 articles without full-text
A group of two people
5 articlesselected
read
8 articles3 were
repeated within
databases
Reading of full texts
5 articles
Extraction of variables
Statistical analysis
for
Followed by
year of publication
country of origin
type of study
n intervention
n controls
age group
glycosylated hemoglobinControl/intervention
Fasting plasmatic glycemiaControl/intervention
Variables
Children : 0-14Youth: 15-17Adults: 18-65Elderly: +65
Article Section Subsection Quality Criteria
Introduction --------------- Objectives and/or hypotheses of the study
Methods
InterventionPrecise details of the interventions intended for each group and
how they were actually administered
Outcomes Clearly defined primary and secondary outcome measures
Statistical methods Statistical methods used to compare groups for primary outcome(s)
Recruitment Duration of recruitment and follow-up
Baseline data Not existence of different characteristics in each group
Numbers analyzedNumber of participants in each group included in each analysis and
whether analysis was by “intention-to-treat”
Outcomes and estimation
For each primary and secondary outcome, a summary of results for
each group and the estimated effect size and its precision (e.g., 95%
confidence interval)
Discussion
Generalizability
Generalizability (external validity) of the trial findings according to
the intervention, comparators, patients, and care providers and
centers involved in the trial
Overall evidenceGeneral interpretation of the results in the context of current
evidence
Table 1. _ Quality Criteria used to evaluate the final articles included, adapted from “Extending the CONSORT Statement to Randomized Trials of Nonpharmacologic Treatment: Explanation and Elaboration ”
Studies
TotalKollmann
et al.,2007
Kim
et al.,
2006
Kim
et al.,
2006
Benhamou
et al., 2007
Vahatalo et
al., 2004
Criteria
1 1 1 1 1 1 5
2 1 1 1 1 1 5
3 1 0 1 1 1 4
4 1 1 1 1 1 5
5 1 1 1 1 1 5
6 1 1 1 1 0 4
7 1 1 1 1 1 5
8 1 1 1 1 0 4
9 0 1 0 0 0 1
10 1 1 1 1 1 5
Total 9 9 9 9 7
Table 2_Classification according to quality criteria
Article Year of publication Country Type of study n
intervention n control Age group
Vahatalo et al.,2004 2004 Finland Quasi-
experimental 102 101 adults
Kollmann et al., 2007 2007 Austria Clinical trial 10 adults
Kim et al.,2007 2007 South korea Clinical trial 25 26 adults
Kim et al.,2006 2006 South korea
Quasi-experimental 33 adults
Benhamou et al., 2007 2007 France Randomized
crossover study30(29
glycemia)30 (28
glycemia) adults
Table 3_ Included articles characteristics
Table 4_Secundary variables.
Articlen
int. group
n control group
Glycosylated hemoglobin % intervention
Glycosylated haemoglobin %
control
Fasting plasma glycemia (mg/dl)
intervention
Fasting plasma glycemia (mg/dl)
control
posttest pretest posttest pretest posttest pretest Posttest pretest
Vahatalo et al.,2004 102 101
7.7±1.3 7.9± 1.5
0.45±1.2 0.375±1 .0
Kollmann et al., 2007 10 7,5± 0,9 7,9± 1,1 141,2±
23,1 141,8± 22,5
Kim et al.,2007 25 26 7,04±
1,398,09± 1,72
7,70± 0,90 7,59± 1,09 145,7± 3 151,1± 25,7 149,5±
39,3142,2±
24,1
Kim et al.,2006 33
7,0± 1,1 8,1± 2,1
-1,1± 2,1
Benhamou et al., 2007
30(29 glic)
30 (28 glic)
8.18 ± 0.59
8.31± 0.65
8.34 ± 0.67
8.22 ± 0.72 160 ± 20 166 ± 23 167 ± 21 162 ± 22
–0.14 ± 0.53 0.12 ± 0.65 –5 ± 17 4 ± 18
Table 5_ Extracted variables
Article n int. group
n control group
Glycosylated haemoglobin
% intervention
Glycosylated haemoglobin
% control
Fasting plasma
glycemia (mg/dl)
intervention
Fasting plasma
glycemia (mg/dl) control
Vahatalo et al.,2004 102 101
Kollmann et al., 2007 10 10 7,5±0,9 7,9± 1,1 141,2±23.1 141,8± 22,5
Kim et al.,2007 25 26 7,04±1,39 7,70±0,90 145,7±39.7 149,5±39,3
Kim et al.,2006 33 33 7,0±1,1 8,1± 2,1
Benhamou et al., 2007
30 (29
glyc)
30 (28 glyc) 8.18 ± 0.59 8.34± 0.67 160 ± 20 167 ± 21
Table 6_ data regarding dependent variables used to perform the meta-analysis. The values were extracted from the included articles and analysed using RevMan. Some data is absent due to lack of information in the articles
Graphic 2_ Glycosilated haemoglobin forest plot
Graphic 3_ Fasting plasmatic glycemia forest plot.
References
[1]http://www.who.int/en/, available on 1-11-2007
[2] Hilary Pinnock, Roger Slack, Claudia Pagliari, David Price, Aziz Sheikh; Understanding the potential role of mobile phone-based monitoring on asthma self-management: qualitative study; Clinical and Experimental Allergy. 2007 May;Kollmann et al., 20077(5):794-802; Available at: www.pubmed.com 26-10-2007.
[Kollmann et al., 2007] Ryan D, Cobern W, Wheeler J, Price D, Tarassenko L; Mobile Phone Technology in the Management of Asthma; Journal of Telemedicine and Telecare 2005; 11 Suppl 1:4Kollmann et al., 2007-6; Available at: www.pubmed.com 26-10-2007
[4] Morak J, Kollmann A, Schreier G; Feasibility and usability of a home monitoring concept based on mobile phones and near field communication (NFC) technology; Medinfo. 2007; 12 (Pt 1):112-6; Available at: www.pubmed.com 26-10-2007.
[5] AMOS A. F; MCCARTY D. J.; ZIMMET P., The rising global burden of diabetes and its implications: estimates and projections to the year 2010; Diabetic medicine ; 1997, vol.14, pp S7-S84, SUP5
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