cellular phone-based technologies for monitoring of patients with diabetes: a systematic review and...
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Cellular Phone-Based Technologies for Monitoring Of Patients With Diabetes: a Systematic Review and Meta Analysis
Systematic Review And Meta-Analysis Class 3PhD João FonsecaIntrodução à Medicina II
Overview
IntroductionMotivationResearch questionAims
Methods and ParticipantsSystematic review and Meta-analysisQueryInclusion and Exclusion criteriaSampling methodsData collectionStudies’ quality
Statistical analysis and ResultsDiabetes and the chronic diseasesCharacteristics of the studiesSecondary variablesOutcomesMeta-analysis
DiscussionMain findingsLimitationsCritical comparison with other studiesConclusions
IntroductionMotivationResearch questionAims
Methods and ParticipantsSystematic review and Meta-analysisQueryInclusion and Exclusion criteriaSampling methodsData collectionStudies’ quality
Statistical analysis and ResultsDiabetes and the chronic diseasesCharacteristics of the studiesSecondary variablesOutcomesMeta-analysis
DiscussionMain findingsLimitationsCritical comparison with other studiesConclusions
Chronic diseases
60% of all deaths [1]
Slow progression
Mobile phone based
tecnhologies
Applied in management of diseases [3]
Increasing international interest[2]
[1]http://www.who.int/en/, available at 1-11-2007[2] Pinnock Hilary, Slack Roger, Pagliari Claudia, Price David, Sheikh Aziz. Understanding the potential role of mobile phone-based monitoring on asthma self-
management: qualitative study. Clinical and Experimental Allergy. May 2007. 37(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]-6; Available at: www.pubmed.com 26-10-2007
Motivation
Patient with diabetes
Quick 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] Amosa 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
“Does cellular phone based tecnhologies monitoring
improve diabetes patients’ clinical outcomes?”
Research question
Aims
* To describe the proportion of published studies about CPT regarding major chronic diseases.
* To investigate if CPT improves patients’ medical state
Glycosylated haemoglobin
Fasting plasma glycemia
IntroductionMotivationResearch questionAims
Methods and ParticipantsSystematic review and Meta-analysisQueryInclusion and Exclusion criteriaSampling methodsData collectionStudies’ quality
Statistical analysis and ResultsDiabetes and the chronic diseasesCharacteristics of the studiesSecondary variablesOutcomesMeta-analysis
DiscussionMain findingsLimitationsCritical comparison with other studiesConclusions
Search Collect Summarize
Evidence collected from
articles
Systematic review and Meta-analysis
((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
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
Inclusion and Exclusion criteria
33 14
3
Sampling methods
Fig.2 – Distribution of articles repeated among databases
Read abstract of 160 (inclusion and exclusion criteria) 50 repeated
among databases
Requested by e-mail
6 with no full-text
3 repeated within databases
Read full-text of 21 (inclusion and exclusion criteria)
80 excluded
7 excluded
9 with no abstract
Systematic review
5 articles included
4 excluded (no control group or no postest values)
2 articles included
Meta-analysis
2 answered1 included
* year of publication
* country of origin
* type of study
* n intervention
* n controls
* age group
* Glycosylated haemoglobinControl/intervention
* Fasting plasma glycemiaControl/intervention
Children : 0-14Youth: 15-17Adults: 18-65Elderly: +65
Data collection
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’ quality
Study section Quality criteria
Introduction 1. Objectives and/or hypotheses of the study
Methods
Intervention 2. Precise details of the interventions intended for each group and how they were actually administered
Outcomes 3. Clearly defined primary and secondary outcome measures
Statistical methods 4. Statistical methods used to compare groups for primary outcome(s)
Recruitment 5. Duration of recruitment and follow-up
Baseline data 6. Not existence of different characteristics in each group
Numbers analyzed 7. Number of participants in each group included in each analysis
Outcomes and estimation
8. 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)
DiscussionGeneralizability 9. Generalizability (external validity) of the trial findings according to the intervention,
comparators, patients, and care providers and centers involved in the trial
Overall evidence 10. General interpretation of the results in the context of current evidence
Table 2 – Articles classification according to quality criteria
Criteria
Studies
TotalKollmann et al., 2007 [6]
Kim et al.,2006 [7]
Kim et al., 2007 [8]
Benhamou et al., 2007 [9]
Vahatalo et al., 2004 [10]
Ladyzynski et al. 2001 [11]
1 1 1 1 1 1 1 6
2 1 1 1 1 1 1 6
3 1 0 1 1 1 1 5
4 1 1 1 1 1 1 6
5 1 1 1 1 1 1 6
6 1 1 1 1 0 1 5
7 1 1 1 1 1 1 6
8 1 1 1 1 0 1 5
9 0 1 0 0 0 0 1
10 1 1 1 1 1 1 6
Total 9 9 9 9 7 9
IntroductionMotivationResearch questionAims
Methods and ParticipantsSystematic review and Meta-analysisQueryInclusion and Exclusion criteriaSampling methodsData collectionStudies’ quality
Statistical analysis and ResultsDiabetes and the chronic diseasesCharacteristics of the studiesSecondary variablesOutcomesMeta-analysis
DiscussionMain findingsLimitationsCritical comparison with other studiesConclusions
Graphic 1 - Distribuition of chronic diseases among obtained articles. Total number of articles obtained regarding chronic diseases N= 81
Diabetes and chronic diseases
Table 3 - Included articles characteristics
Characteristics of the studies
Article Year of publication Country Type of study n intervention n control Age group
Ladyzynski et al., 2001 [11] 2001 Poland Quasi-experimental 15 Adults
Vahatalo et al., 2004 [10] 2004 Finland Quasi-experimental 102 101 Adults
Kim et al., 2006 [7] 2006 South
Korea Quasi-experimental 33 Adults
Kollmann et al., 2007 [6] 2007 Austria Clinical trial 10 Adults
Kim et al., 2007 [8] 2007 South
Korea Clinical trial 25 26 Adults
Benhamou et al., 2007 [9] 2007 France Randomized
crossover study30 (29
glycemia)30 (28
glycemia) Adults
Table 4 - Secondary variables
Secondary variables
Secondary Variables
Articles
Kollmann et al., 2007 [6]
Kim et al., 2006 [7]
Kim et al., 2007 [8]
Benhamou et al., 2007 [9]
Vahatalo et al., 2004 [10]
Ladyzynski et al., 2001 [11]
Glycemia above 150 mg/dl p>0,05
Glycemia in normal range (80-150 mg/dl)
p>0,05
Glycemia below 50 mg/dl p>0,05
Two hours post-meal glucose (mg/dl)
p<0,05
Mean blood glucose (mg/dl) P< 0.05
Physical Exercise (d/wk) p<0,05
Diabetic medication taking (d/wk)
p<0,05 p<0,05
Foot Care (d/wk) p<0,05
Diabetic diet (d/wk) p>0,05
DQoL p<0,05
Satisfaction with life p<0,05
Table 5 - Extracted variables
Outcomes
Articles
Glycosylated haemoglobin %
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 [10]
7.7±1.3 7.9± 1.5
0.45±1.2 0.35 ± 1.0
Kollmann et al., 2007 [6] 7,5± 0,9 7,9± 1,1 141,2±
23,1141,8±
22,5
Kim et al., 2007 [8] 7,04± 1,39 8,09± 1,72 7,70±
0,907,59± 1,09
145,7± 39,7
151,1± 25,7
149,5± 39,3
142,2± 24,1
Kim et al., 2006 [7]
7,0± 1,1 8,1± 2,1 -1,1± 2,1
Benhamou et al., 2007 [9]
8.18 ± 0.59 8.31 ± 0.65 8.34 ±
0.678.22 ± 0.72 160 ± 20 166 ± 23 167 ± 21 162 ± 22
– 0.14 ± 0.53 0.12 ± 0.65 – 5 ± 17 4 ± 18
Ladyzynski et al., 2001 [11] 7,1 ± 1,1 8,0 ± 1,1
Fig. 3 - Glycosilated haemoglobin forest plot
Meta-analysis
Glycosilated haemoglobin
Fig.4 - Fasting plasma glycemia forest plot
Fasting plasma glycemia
IntroductionMotivationResearch questionAims
Methods and ParticipantsSystematic review and Meta-analysisQueryInclusion and Exclusion criteriaSampling methodsData collectionStudies’ quality
Statistical analysis and ResultsDiabetes and the chronic diseasesCharacteristics of the studiesSecondary variablesOutcomesMeta-analysis
DiscussionMain findingsLimitationsCritical comparison with other studiesConclusions
Ladyzynski et al., 2001 [11]
Vahatalo et al., 2004 [10]
Kim et al., 2006 [7]
Kollmann et al., 2007 [6]
Benhamou et al., 2007 [9]
Kim et al., 2007 [8]
Clinical State S NS NS S
Adherence S S (Diet NS)
QoL and Satisfaction with life S
Glycosilated haemoglobin (Posttest-Pretest int.) S NS
(increase) S S NS S
Glycosilated haemoglobin (Posttest int. vs control) NS (decrease)
Fasting plasma glycemia (Posttest- Pretest int.) NS NS NS
Fasting plasma glycemia (Posttest int. vs control) NS (decrease)
Quality 9 7 9 9 9 9
Main findings
Table 6 – Summary of obtained results
Ladyzynski et al., 2001 [11]
Vahatalo et al., 2004 [10]
Kim et al., 2006 [7]
Kollmann et al., 2007 [6]
Benhamou et al., 2007 [9]
Kim et al., 2007 [8]
Clinical State S NS NS S
Adherence S S (Diet NS)
QoL and Satisfaction with life S
Quality 9 7 9 9 9 9
Clinical State: Measured in different waysImpossible to compare
Adherence: Significant except for Diabetic dietAdherence seem to increase with the use of CPT
QoL and Satisfaction with life:SignificantThis variable seem to increase with the use of CPT
Table 7 – Summary of results obtained for secondary variables and studies quality classification
Ladyzynski et al., 2001 [11]
Vahatalo et al., 2004 [10]
Kim et al., 2006 [7]
Kollmann et al., 2007 [6]
Benhamou et al., 2007 [9]
Kim et al., 2007 [8]
Glycosilated haemoglobin (Posttest-Pretest int.) S NS
(increase) S S NS S
Glycosilated haemoglobin (Posttest int. vs control) NS (decrease)
Quality 9 7 9 9 9 9
Glycosilated haemoglobin:Increases in Vahatalo et al., 2004 [10] (Quality 7)Decreases significantly in 4 of the studiesMeta-analysis not significant, although decreasesMeasured in different waysIncluded studies are different
Table 8 – Summary of results obtained for glycosilated haemoglobin
Ladyzynski et al., 2001 [11]
Vahatalo et al., 2004 [10]
Kim et al., 2006 [7]
Kollmann et al., 2007 [6]
Benhamou et al., 2007 [9]
Kim et al., 2007 [8]
Fasting plasma glycemia (Posttest- Pretest int.) NS NS NS
Fasting plasma glycemia (Posttest int. vs control) NS (decrease)
Quality 9 7 9 9 9 9
Fasting plasma glycemia:Measured in 3 studiesDecreases not significantly in every studiesMeta-analysis not significant, although decreases
Table 9 – Summary of results obtained for fasting plasma glycemia
Fasting plasma glycemia:Measured in 3 studiesDecreases not significantly in every studiesMeta-analysis not significant, although decreases
Clinical State: Measured in different waysImpossible to compare
Adherence: Significant except for Diabetic dietAdherence seem to increase with the use of CPT
QoL and Satisfaction with life:SignificantThis variable seem to increase with the use of CPT
Glycosilated haemoglobin:Decreases significantly in 4 of the studiesMeta-analysis not significant, although decreases
Limitations and Critical comparison with other studies
Small number of studiesSensitivity of the query?Too restrictive exclusion criteria?Requested articles?Data bases explored?Small number of published articles (recent area of interest)?Published articles have low quality?
Quality of the studiesStudies of short durationNo control groupWays of measuringLow number of participants
Paré et al., 2007 [12] (Systematic review)Bigger number of studies
Criteria applied less restrictive (older articles)Different databases explored
ConclusionsGlycosilated haemoglobin and Fasting plasma glycemia decrease
No meta-analysis found
31% of all articles report to diabetes
No meta-analysis found
Increasing number of patients with chronic diseases
Increasing mortality
Increasing costs for the National Health System
There is no cure, only regular treatments
Systematic review pointing the same conclusions
Increase of the adherence, clinical state and quality of life even if slightly
Older populationChanges in the way of life
Inconclusive results because of the small number of studies
Other chronic diseases are even less studied
Necessity of more studies and with more quality
Conclusions
Susana Carrilho
Sara CoelhoFernando Sá
Diogo Miguel
Alexandra Azevedo Ana Pessoa
Ana Lisboa
Ana Luísa Graça Pedro Lopes
Ana Luísa Padilhó
Joana Carvalho
Maycoll Vieira
Pedro Souteiro
Class 3
[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; 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]-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] Amosa 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 [6] Kollmann A, Riedl M, Kastner P, Schreier G, Ludvik B. Feasibility of a mobile phone-based data service for functional insulin treatment of type 1 diabetes mellitus patients. J Med Internet Res. Dez 2007; 31;9(5):e36.[7] Kim HS. Impact of Web-based nurse's education on glycosylated haemoglobin in type 2 diabetic patients; J Clin Nurs; Jul 2007; 16(7):1361-6.[8] Kim HS; A randomized controlled trial of a nurse short-message service by cellular phone for people with diabetes ; Int J Nurs Stud; Jul 2007; 687-92.[9] Benhamou, P, Melki, V, Boizel R, et al. One-year efficacy and safety of Web-based follow-up using cellular phone in type 1 diabetic patients under insulin pump therapy: the PumpNet study. Diabetes & Metabolism. Jun 2007; 33(2): 220-226.[10] Vahatalo, M.A., Virtamo, H.E., Viikari, J.S., Ronnemaa, T.; Cellular phone transferred self blood glucose monitoring: Prerequisites for positive outcome; Practical Diabetes International; 2004; 21 (5); 192-194.[11] Ladyzynski P, Wojcicki J, Krzymien J, et al. Teletransmission system upporting intensive insulin treatment of out-clinic type 1 diabetic pregnant women: Technical assessment during 3 years’ application. The International Journal of Artificial Organs. 2001. 24(3).[12] Paré G., Jaana M., Sicotte C.; Systematic Review of Home Telemonitoring for Chronic Diseases: The Evidence Base; J Am Med Inform Assoc. May–Jun 2007; 14(3): 269–277.
References