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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