Digital Diabetes Care System Observations from a Pilot Evaluation Study in Vietnam.
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ABSTRACT:
SUBMITTER: Khanh TQ
PROVIDER: S-EPMC7037177 | biostudies-literature | 2020 Feb
REPOSITORIES: biostudies-literature
Publications
Digital Diabetes Care System Observations from a Pilot Evaluation Study in Vietnam.
Khanh Tran Quang TQ Hao Pham Nhu PN Roitman Eytan E Raz Itamar I Marganitt Baruch B Cahn Avivit A
International journal of environmental research and public health 20200203 3
Digital technologies are gaining an important role in the management of patients with diabetes. We assessed clinical outcomes and user satisfaction of incorporating a digital diabetes care system in diabetes clinics of a developing country. The system integrated a wireless blood glucose monitor that communicates data to any smartphone utilizing a patented acoustic data transfer method, a mobile-app, and cloud-based software that stores, analyzes, and presents data. Five hospital endocrinology cl ...[more]
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Project description:IntroductionThe prevalence of type 2 diabetes is rising steeply. National Health Service England (NHSE) is exploring the potential of a digital diabetes prevention programme (DDPP) and has commissioned a pilot with embedded evaluation.Methods and analysisThis study aims to determine whether, and if so, how, should NHSE implement a national DDPP, using a mixed-methods pretest and post-test design, underpinned by two theoretical frameworks: the Coventry, Aberdeen and London - Refined (CALO-RE) taxonomy of behavioural change techniques for the digital interventions and the Consolidated Framework for Implementation Research (CFIR) for implementation processes. In eight pilot areas across England, adults with non-diabetic hyperglycaemia (NDH) (glycated haemoglobin (HbA1c) 42-47 mmol/mol or fasting plasma glucose 5.5-6.9 mmol/L) and adults without NDH who are overweight (body mass index (BMI) >25 kg/m2) or obese (BMI >30 kg/m2) will be referred to one of five digitally delivered diabetes prevention interventions. The primary outcomes are reduction in HbA1c and weight (for people with NDH) and reduction in weight (for people who are overweight or obese) at 12 months. Secondary outcomes include use of the intervention, satisfaction, physical activity, patient activation and resources needed for successful implementation. Quantitative data will be collected at baseline, 6 months and 12 months by the digital intervention providers. Qualitative data will be collected through semistructured interviews with commissioners, providers, healthcare professionals and patients. Quantitative data will be analysed descriptively and using generalised linear models to determine whether changes in outcomes are associated with demographic and intervention factors. Qualitative data will be analysed using framework analysis, with data pertaining to implementation mapped onto the CFIR.Ethics and disseminationThe study has received ethical approval from the Public Health England Ethics and Research Governance Group (reference R&D 324). Dissemination will include a report to NHSE to inform future policy and publication in peer-reviewed journals.
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Project description:Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of results related to diabetes care challenging. We developed a diabetes-specific clinical decision support system (Diabetes Dashboard) interface for displaying glycemic, lipid and renal function results, in an integrated form with decision support capabilities, based on local clinical practice guidelines. The clinical decision support system included a dashboard feature that graphically summarized all relevant laboratory results and displayed them in a color-coded system that allowed quick interpretation of the metabolic control of the patients. An alert module informs the user of tests that are due for repeat testing. An interactive graph module was also developed for better visual appreciation of the trends of the laboratory results of the patient. In a pilot study involving case scenarios administered via an electronic questionnaire, the Diabetes Dashboard, compared to the existing laboratory reporting interface, significantly improved the identification of abnormal laboratory results, of the long-term trend of the laboratory tests and of tests due for repeat testing. However, the Diabetes Dashboard did not significantly improve the identification of patients requiring treatment adjustment or the amount of time spent on each case scenario. In conclusion, we have developed and shown that the use of the Diabetes Dashboard, which incorporates several decision support features, can improve the management of diabetes. It is anticipated that this dashboard will be most helpful when deployed in an outpatient setting, where physicians can quickly make clinical decisions based on summarized information and be alerted to pertinent areas of care that require additional attention.
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Project description:Patient Selection: Three hospitals were involved in the study: Dong Thap Provincial and An Giang Provincial hospitals, both located in the Mekong Delta Region of Vietnam where most of the Typhoid patients were admitted, and the Hospital for Tropical Diseases, Ho Chi Minh City, where the malarial patients were admitted. Infection status of each patient was determined by blood culture for the Typhoid patients and by microscopic examination of stained thick and thin peripheral-blood slides for the patients suspected of having Malaria. Patients with blood cultures positive for S. Typhi or S. enterica serovar Paratyphi A (S. Paratyphi A) (samples designated ST) or peripheral blood smears positive for Plasmodium falciparum or Plasmodium vivax (samples designated PF) were consented and enrolled in the study. A total of 28 S. Typhi positive patients and one S. Paratyphi A positive patient were enrolled in the first phase of the study and a further 9 S. Typhi and one S. Paratyphi A positive patient were enrolled in the second phase. Nine patients with Malaria caused by P. falciparum and one caused by P. vivax were enrolled. Sixteen uninfected healthy individuals (samples designated HC) were also enrolled in the study (one sample each). The Typhoid patients were randomly chosen to receive either Azithromycin or Gatifloxicin (20mg/kg/day for 7 days) antibiotics. Uncomplicated malaria patients were treated for 3 days with Artekin (dihydroartemisinin with piperaquine phosphate). Venous blood (2.5ml) was collected for total RNA extraction into PaxGene RNA collection tubes (Qiagen) at various times. The first sample (T1) was taken immediately on admission or entry into the study, then samples were collected, 3 (T3), 6-9 (T9 for Typhoid, T7 for Malaria), and 28-45 (T28) days following entry into the study and an average of 9 months (T9M) later. The PaxGene tubes were stored at 4degC until RNA was extracted as per the manufacturers instructions. Purified RNA was shipped on dry ice to Stanford University, CA for use in Microarray analyses. Microarrays: Experimental and reference samples (Human Universal RNA reference {Stratagene}) were amplified using the MessageAmp II aRNA Kit (Ambion) as per the manufacturer's instructions. Four micrograms amplified RNA was labeled through indirect incorporation of Cy5 (experimental) and Cy3 (reference) dyes (protocols can be found at http://cmgm.stanford.edu/pbrown/protocols/index.html). The labeled probes were then mixed and hybridized to Stanford Human cDNA arrays with 42 K features. Arrays were scanned using a Genepix 4000A laser scanner and data extracted with Genepix Pro Software version 5.1 (Axon Instruments). The data were then uploaded into the Stanford Microarray Database (SMD). A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Compound Based Treatment: Drugs used for treatment Disease State: Malaria, Typhoid or Healthy Controls Keywords: disease_state_design
2010-01-04 | GSE7000 | GEO
Project description:ObjectiveThere are few standardized neonatal neurobehavioral instruments available for longitudinal child development research. We adapted an established clinical tool, the Newborn Behavioral Observations (NBO) system, for research by standardizing the administration protocol and expanding the 3-point coding scale to 5 points.MethodsWe administered the 5-point NBO to 144 racially/ethnically diverse late preterm or term infants born to low-income women (average age 5 weeks). Cronbach's alphas were calculated to determine internal consistency reliability of Autonomic, Motor, Organization of State, and Responsivity subscales. We examined concurrent validity using subscale associations with infant salivary cortisol reactivity to the NBO and maternally reported infant temperament.ResultsTwo of the 4 NBO subscales, Organization of State and Responsivity, had excellent (0.91) and good (0.76) reliability, respectively, and were retained for further analyses. Infants with higher Organization of State scores (more optimal regulation) demonstrated lower cortisol reactivity (r = -0.30, p < 0.01) and temperamental negativity (r = -0.16, p < 0.05). Responsivity was unrelated to cortisol reactivity or temperament.ConclusionsState regulation, as measured by the 5-point NBO, was associated with a biologic marker of infant stress response to the NBO administration and reported temperament. Poor reliability of the NBO's 3-item Autonomic and 7-item Motor subscales suggests that further psychometric research in other samples and likely refinement are needed. Given the paucity of neurobehavioral assessment tools for infants, these findings justify such research as next steps in the incremental progression toward the development of a practical, reliable, and predictive measure of early neurobehavioral development.
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Project description:BackgroundThe use of remote data capture for monitoring blood glucose and supporting digital apps is becoming the norm in diabetes care. One common goal of such apps is to increase user awareness and engagement with their day-to-day health-related behaviors (digital engagement) in order to improve diabetes outcomes. However, we lack a deep understanding of the complicated association between digital engagement and diabetes outcomes.ObjectiveThis study investigated the association between digital engagement (operationalized as tagging of behaviors alongside glucose measurements) and the monthly average blood glucose level in persons with type 2 diabetes during the first year of managing their diabetes with a digital chronic disease management platform. We hypothesize that during the first 6 months, blood glucose levels will drop faster and further in patients with increased digital engagement and that difference in outcomes will persist for the remainder of the year. Finally, we hypothesize that disaggregated between- and within-person variabilities in digital engagement will predict individual-level changes in blood glucose levels.MethodsThis retrospective real-world analysis followed 998 people with type 2 diabetes who regularly tracked their blood glucose levels with the Dario digital therapeutics platform for chronic diseases. Subjects included "nontaggers" (users who rarely or never used app features to notice and track mealtime, food, exercise, mood, and location, n=585) and "taggers" (users who used these features, n=413) representing increased digital engagement. Within- and between-person variabilities in tagging behavior were disaggregated to reveal the association between tagging behavior and blood glucose levels. The associations between an individual's tagging behavior in a given month and the monthly average blood glucose level in the following month were analyzed for quasicausal effects. A generalized mixed piecewise statistical framework was applied throughout.ResultsAnalysis revealed significant improvement in the monthly average blood glucose level during the first 6 months (t=-10.01, P<.001), which was maintained during the following 6 months (t=-1.54, P=.12). Moreover, taggers demonstrated a significantly steeper improvement in the initial period relative to nontaggers (t=2.15, P=.03). Additional findings included a within-user quasicausal nonlinear link between tagging behavior and glucose control improvement with a 1-month lag. More specifically, increased tagging behavior in any given month resulted in a 43% improvement in glucose levels in the next month up to a person-specific average in tagging intensity (t=-11.02, P<.001). Above that within-person mean level of digital engagement, glucose levels remained stable but did not show additional improvement with increased tagging (t=0.82, P=.41). When assessed alongside within-person effects, between-person changes in tagging behavior were not associated with changes in monthly average glucose levels (t=1.30, P=.20).ConclusionsThis study sheds light on the source of the association between user engagement with a diabetes tracking app and the clinical condition, highlighting the importance of within-person changes versus between-person differences. Our findings underscore the need for and provide a basis for a personalized approach to digital health.
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Project description:Patient Selection: Three hospitals were involved in the study: Dong Thap Provincial and An Giang Provincial hospitals, both located in the Mekong Delta Region of Vietnam where most of the Typhoid patients were admitted, and the Hospital for Tropical Diseases, Ho Chi Minh City, where the malarial patients were admitted. Infection status of each patient was determined by blood culture for the Typhoid patients and by microscopic examination of stained thick and thin peripheral-blood slides for the patients suspected of having Malaria. Patients with blood cultures positive for S. Typhi or S. enterica serovar Paratyphi A (S. Paratyphi A) (samples designated ST) or peripheral blood smears positive for Plasmodium falciparum or Plasmodium vivax (samples designated PF) were consented and enrolled in the study. A total of 28 S. Typhi positive patients and one S. Paratyphi A positive patient were enrolled in the first phase of the study and a further 9 S. Typhi and one S. Paratyphi A positive patient were enrolled in the second phase. Nine patients with Malaria caused by P. falciparum and one caused by P. vivax were enrolled. Sixteen uninfected healthy individuals (samples designated HC) were also enrolled in the study (one sample each). The Typhoid patients were randomly chosen to receive either Azithromycin or Gatifloxicin (20mg/kg/day for 7 days) antibiotics. Uncomplicated malaria patients were treated for 3 days with Artekin (dihydroartemisinin with piperaquine phosphate). Venous blood (2.5ml) was collected for total RNA extraction into PaxGene RNA collection tubes (Qiagen) at various times. The first sample (T1) was taken immediately on admission or entry into the study, then samples were collected, 3 (T3), 6-9 (T9 for Typhoid, T7 for Malaria), and 28-45 (T28) days following entry into the study and an average of 9 months (T9M) later. The PaxGene tubes were stored at 4degC until RNA was extracted as per the manufacturers instructions. Purified RNA was shipped on dry ice to Stanford University, CA for use in Microarray analyses. Microarrays: Experimental and reference samples (Human Universal RNA reference {Stratagene}) were amplified using the MessageAmp II aRNA Kit (Ambion) as per the manufacturer's instructions. Four micrograms amplified RNA was labeled through indirect incorporation of Cy5 (experimental) and Cy3 (reference) dyes (protocols can be found at http://cmgm.stanford.edu/pbrown/protocols/index.html). The labeled probes were then mixed and hybridized to Stanford Human cDNA arrays with 42 K features. Arrays were scanned using a Genepix 4000A laser scanner and data extracted with Genepix Pro Software version 5.1 (Axon Instruments). The data were then uploaded into the Stanford Microarray Database (SMD). A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Compound Based Treatment: Drugs used for treatment Disease State: Malaria, Typhoid or Healthy Controls Keywords: disease_state_design Complex
2010-01-03 | E-GEOD-7000 | biostudies-arrayexpress
Project description:To evaluate retinopathy of prematurity (ROP) screening practice in reverse Kangaroo Mother Care (R-KMC) with respect to stress and pain to the infant.In a pilot study we evaluated ROP screening practice in R-KMC in 20 babies at risk of ROP. The R-KMC differed from the conventional KMC with respect to the baby position where the baby lay supine on mother's chest. With the mother lying supine and the baby in R-KMC position, screening examinations were done with indirect ophthalmoscope. The outcome measures included stress (quantified by pulse, respiration, and oxygen saturation) and pain to the baby by observing facial expression (eye squeezing, crying, and brow bulge). The heart rate, respiratory rate, and SpO2 (%) were compared before and immediately after the procedure using paired t-test.Mean (±SD) gestational age and birth weight were 30.8±2.3 weeks and 1362.5±253.9 g, respectively. During examination in R- KMC position 8 babies (40%) were completely relaxed (no eye squeezing and crying), 10 (50%) were partially relaxed (no brow bulge) and 2 babies (10%) were not relaxed. A change in heart and respiration rate both by 10 per minute was recorded in 12 (60%) and 10 (50%) babies, respectively. Five babies (25%) had reduction in blood oxygen concentration below 92%. The majority of the mothers (19 of 20) were relaxed.ROP screening in R-KMC can be a baby friendly screening practice with respect to stress and pain to the infant and needs further evaluation in a larger cohort.
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