1. Cellular Phone-Based Technologies For Monitoring Of Patients With Diabetes: a Systematic Review and Meta Analysis Systematic Review And Meta-Analysis Class 3 Professor Doutor João Fonseca Introdução à Medicina II

2. 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.www.pubmed.com [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 26-10-2007www.pubmed.com

3. 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. www.pubmed.com

4. 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

5. Outcome Patients’ medical state Glycosylated haemoglobin Fasting plasmatic glycemia

6. Research question “Does cellular phone based tecnhologies monitoring improve diabetes patients’ clinical outcomes?”

8. Systematic review and meta-analysis search presentsummarize Evidence collected from articles

9. ((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

10. Pubmed Isi Web of knowledge Scopus 514564 160 Total Articles Obtained

11. Inclusion/ exclusion criteria 21 articles applied selected 50 repeated articles among databases 9 articles without abstract Groups of two people read the abstracts

12. Articles per disease Graphic 1_ Distribuition of diseases among obtained articles

13. Inclusion criteriaExclusion 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

14. Reading of full texts 21 articles 8 articles were obtained applied Inclusion/ exclusion criteria 6 articles without full-text

15. A group of two people 5 articles selected read 8 articles 3 were repeated within databases

16. Reading of full texts 5 articles Extraction of variables Statistical analysis for Followed by

17. year of publication country of origin type of study n intervention n controls age group glycosylated hemoglobin Control/intervention Fasting plasmatic glycemia Control/intervention Variables Children : 0-14 Youth: 15-17 Adults: 18-65 Elderly: +65

18. Article SectionSubsectionQuality Criteria Introduction---------------Objectives and/or hypotheses of the study Methods Intervention Precise details of the interventions intended for each group and how they were actually administered OutcomesClearly defined primary and secondary outcome measures Statistical methodsStatistical methods used to compare groups for primary outcome(s) RecruitmentDuration of recruitment and follow-up Baseline dataNot existence of different characteristics in each group Numbers analyzed Number 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 evidence General 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 ”

19. Studies Total Kollmann et al.,2007 Kim et al., 2006 Benhamou et al., 2007 Vahatalo et al., 2004 Criteria 1 11111 5 2 11111 5 3 10111 4 4 11111 5 5 11111 5 6 11110 4 7 11111 5 8 11110 4 9 01000 1 10 11111 5 Total99997 Table 2_Classification according to quality criteria

21. Article Year of publication CountryType of study n intervention n controlAge group Vahatalo et al.,2004 2004Finland Quasi- experimental 102101adults Kollmann et al., 2007 2007AustriaClinical trial10 adults Kim et al.,20072007 South korea Clinical trial2526adults Kim et al.,20062006 South korea Quasi- experimental 33 adults Benhamou et al., 2007 2007France Randomized crossover study 30(29 glycemia) 30 (28 glycemia) adults Table 3_ Included articles characteristics

22. Table 4_Secundary variables.

23. Article n int. group n control group Glycosylated hemoglobin % intervention Glycosylated haemoglobin % control Fasting plasma glycemia (mg/dl) intervention Fasting plasma glycemia (mg/dl) control posttestpretestposttestpretestposttestpretestPosttestpretest Vahatalo et al.,2004 102101 7.7±1.3 7.9± 1.5 0.45±1.20.375±1.0 Kollmann et al., 2007 10 7,5± 0,97,9± 1,1 141,2± 23,1 141,8± 22,5 Kim et al.,2007 2526 7,04± 1,39 8,09± 1,72 7,70± 0,90 7,59± 1,09 145,7± 3 151,1± 25,7 149,5± 39,3 142,2± 24,1 Kim et al.,2006 33 7,0± 1,18,1± 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 ± 20166 ± 23167 ± 21162 ± 22 –0.14 ± 0.530.12 ± 0.65–5 ± 174 ± 18 Table 5_ Extracted variables

24. 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 102101 Kollmann et al., 2007 10 7,5±0,97,9± 1,1 141,2±23.1141,8± 22,5 Kim et al.,2007 25267,04±1,397,70±0,90145,7±39.7149,5±39,3 Kim et al.,2006 33 7,0±1,18,1± 2,1 Benhamou et al., 2007 30 (29 glyc) 30 (28 glyc) 8.18 ± 0.598.34± 0.67160 ± 20167 ± 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

26. Graphic 2_ Glycosilated haemoglobin forest plot

27. Graphic 3_ Fasting plasmatic glycemia forest plot.

28. 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.www.pubmed.com [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 26-10-2007www.pubmed.com [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.www.pubmed.com [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

29. Class 3 Susana CarrilhoSara CoelhoFernando SáDiogo MiguelAlexandra AzevedoAna PessoaAna LisboaAna Luísa GraçaPedro LopesAna Luísa PadilhóJoana CarvalhoMaycoll VieiraPedro Souteiro