METHODS AND ANALYSIS: A total of 294 eligible participants will be recruited and allocated into 3 groups comprising of mHealth intervention alone, mHealth intervention integrated with personal medical nutrition therapy and a control group. Pretested structured questionnaires are used to obtain the respondents' personal information, anthropometry data, prenatal knowledge, physical activity, psychosocial well-being, dietary intake, quality of life, sleep quality and GWG. There will be at least three time points of data collection, with all participants recruited during their first or second trimester will be followed up prospectively (after 3 months or/and after 6 months) until delivery. Generalised linear mixed models will be used to compare the mean changes of outcome measures over the entire study period between the three groups.
ETHICS AND DISSEMINATION: Ethical approvals were obtained from the ethics committee of human subjects research of Universiti Putra Malaysia (JKEUPM-2022-072) and medical research & ethics committee, Ministry of Health Malaysia: NMRR ID-22-00622-EPU(IIR). The results will be disseminated through journals and conferences targeting stakeholders involved in nutrition research.
TRIAL REGISTRATION NUMBER: Clinicaltrial.gov ID: NCT05377151.
OBJECTIVE: The goal of this study was to gain insight into (1) access and utilization of communication technology (eg, landline phone, internet, mobile phone), (2) acceptability of mHealth-based interventions for HIV prevention services, and (3) preferences regarding the format and frequency of mHealth interventions among Malaysian men who have sex with men.
METHODS: We conducted a cross-sectional survey with Malaysian men who have sex with men between July 2018 and March 2020. Participants were recruited using respondent-driven sampling in the Greater Kuala Lumpur region of Malaysia. We collected information on demographic characteristics, HIV risk-related behaviors, access to and the frequency of use of communication technology, and acceptability of using mHealth for HIV prevention using a self-administered questionnaire with a 5-point scale (1, never; 2, rarely; 3, sometimes; 4, often; 5, all the time).
RESULTS: A total of 376 men participated in the survey. Almost all respondents owned or had access to a smartphone with internet access (368/376, 97.9%) and accessed the internet daily (373/376, 99.2%), mainly on a smartphone (334/376, 88.8%). Participants on average used smartphones primarily for social networking (mean 4.5, SD 0.8), followed by sending or receiving emails (mean 4.0, SD 1.0), and searching for health-related information (mean 3.5, SD 0.9). There was high acceptance of the use of mHealth for HIV prevention (mean 4.1, SD 1.5), including for receiving HIV prevention information (345/376, 91.8%), receiving medication reminders (336/376, 89.4%), screening and monitoring sexual activity (306/376, 81.4%) or illicit drug use (281/376, 74.7%), and monitoring drug cravings (280/376, 74.5%). Participants overwhelmingly preferred a smartphone app over other modalities (eg, text, phone call, email) for engaging in mHealth HIV prevention tools. Preference for app notifications ranged from 186/336 (53.9%), for receiving HIV prevention information, to 212/336 (69.3%), for screening and monitoring sexual activity. Acceptance of mHealth was higher for those who were university graduates (P=.003), living in a relationship with a partner (P=.04), engaged in sexualized drug use (P=.01), and engaged in receptive anal sex (P=.006).
CONCLUSIONS: Findings from this study provide support for developing and deploying mHealth strategies for HIV prevention using a smartphone app in men who have sex with men-a key population with suboptimal engagement in HIV prevention and treatment.
OBJECTIVES: To compare techniques of blood glucose monitoring and their impact on maternal and infant outcomes among pregnant women with pre-existing diabetes.
SEARCH METHODS: We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (30 November 2016), searched reference lists of retrieved studies and contacted trial authors.
SELECTION CRITERIA: Randomised controlled trials (RCTs) and quasi-RCTs comparing techniques of blood glucose monitoring including SMBG, continuous glucose monitoring (CGM) or clinic monitoring among pregnant women with pre-existing diabetes mellitus (type 1 or type 2). Trials investigating timing and frequency of monitoring were also included. RCTs using a cluster-randomised design were eligible for inclusion but none were identified.
DATA COLLECTION AND ANALYSIS: Two review authors independently assessed study eligibility, extracted data and assessed the risk of bias of included studies. Data were checked for accuracy. The quality of the evidence was assessed using the GRADE approach.
MAIN RESULTS: This review update includes at total of 10 trials (538) women (468 women with type 1 diabetes and 70 women with type 2 diabetes). The trials took place in Europe and the USA. Five of the 10 included studies were at moderate risk of bias, four studies were at low to moderate risk of bias, and one study was at high risk of bias. The trials are too small to show differences in important outcomes such as macrosomia, preterm birth, miscarriage or death of baby. Almost all the reported GRADE outcomes were assessed as being very low-quality evidence. This was due to design limitations in the studies, wide confidence intervals, small sample sizes, and few events. In addition, there was high heterogeneity for some outcomes.Various methods of glucose monitoring were compared in the trials. Neither pooled analyses nor individual trial analyses showed any clear advantages of one monitoring technique over another for primary and secondary outcomes. Many important outcomes were not reported.1. Self-monitoring versus standard care (two studies, 43 women): there was no clear difference for caesarean section (risk ratio (RR) 0.78, 95% confidence interval (CI) 0.40 to 1.49; one study, 28 women) or glycaemic control (both very low-quality), and not enough evidence to assess perinatal mortality and neonatal mortality and morbidity composite. Hypertensive disorders of pregnancy, large-for-gestational age, neurosensory disability, and preterm birth were not reported in either study.2. Self-monitoring versus hospitalisation (one study, 100 women): there was no clear difference for hypertensive disorders of pregnancy (pre-eclampsia and hypertension) (RR 4.26, 95% CI 0.52 to 35.16; very low-quality: RR 0.43, 95% CI 0.08 to 2.22; very low-quality). There was no clear difference in caesarean section or preterm birth less than 37 weeks' gestation (both very low quality), and the sample size was too small to assess perinatal mortality (very low-quality). Large-for-gestational age, mortality or morbidity composite, neurosensory disability and preterm birth less than 34 weeks were not reported.3. Pre-prandial versus post-prandial glucose monitoring (one study, 61 women): there was no clear difference between groups for caesarean section (RR 1.45, 95% CI 0.92 to 2.28; very low-quality), large-for-gestational age (RR 1.16, 95% CI 0.73 to 1.85; very low-quality) or glycaemic control (very low-quality). The results for hypertensive disorders of pregnancy: pre-eclampsia and perinatal mortality are not meaningful because these outcomes were too rare to show differences in a small sample (all very low-quality). The study did not report the outcomes mortality or morbidity composite, neurosensory disability or preterm birth.4. Automated telemedicine monitoring versus conventional system (three studies, 84 women): there was no clear difference for caesarean section (RR 0.96, 95% CI 0.62 to 1.48; one study, 32 women; very low-quality), and mortality or morbidity composite in the one study that reported these outcomes. There were no clear differences for glycaemic control (very low-quality). No studies reported hypertensive disorders of pregnancy, large-for-gestational age, perinatal mortality (stillbirth and neonatal mortality), neurosensory disability or preterm birth.5.CGM versus intermittent monitoring (two studies, 225 women): there was no clear difference for pre-eclampsia (RR 1.37, 95% CI 0.52 to 3.59; low-quality), caesarean section (average RR 1.00, 95% CI 0.65 to 1.54; I² = 62%; very low-quality) and large-for-gestational age (average RR 0.89, 95% CI 0.41 to 1.92; I² = 82%; very low-quality). Glycaemic control indicated by mean maternal HbA1c was lower for women in the continuous monitoring group (mean difference (MD) -0.60 %, 95% CI -0.91 to -0.29; one study, 71 women; moderate-quality). There was not enough evidence to assess perinatal mortality and there were no clear differences for preterm birth less than 37 weeks' gestation (low-quality). Mortality or morbidity composite, neurosensory disability and preterm birth less than 34 weeks were not reported.6. Constant CGM versus intermittent CGM (one study, 25 women): there was no clear difference between groups for caesarean section (RR 0.77, 95% CI 0.33 to 1.79; very low-quality), glycaemic control (mean blood glucose in the 3rd trimester) (MD -0.14 mmol/L, 95% CI -2.00 to 1.72; very low-quality) or preterm birth less than 37 weeks' gestation (RR 1.08, 95% CI 0.08 to 15.46; very low-quality). Other primary (hypertensive disorders of pregnancy, large-for-gestational age, perinatal mortality (stillbirth and neonatal mortality), mortality or morbidity composite, and neurosensory disability) or GRADE outcomes (preterm birth less than 34 weeks' gestation) were not reported.
AUTHORS' CONCLUSIONS: This review found no evidence that any glucose monitoring technique is superior to any other technique among pregnant women with pre-existing type 1 or type 2 diabetes. The evidence base for the effectiveness of monitoring techniques is weak and additional evidence from large well-designed randomised trials is required to inform choices of glucose monitoring techniques.
METHODS: A random pair of neurosurgery resident and specialist conducted consecutive virtual and physical ward rounds on neurocritical patients. A virtual ward round was first conducted remotely by a specialist who received real-time audiovisual information from a resident wearing smart glasses integrated with telemedicine. Subsequently, a physical ward round was performed together by the resident and specialist on the same patient. The management plans of both ward rounds were compared, and the intrarater reliability was measured. On study completion a qualitative survey was performed.
RESULTS: Ten paired ward rounds were performed on 103 neurocritical care patients with excellent overall intrarater reliability. Nine out of 10 showed good to excellent internal consistency, and 1 showed acceptable internal consistency. Qualitative analysis indicated wide user acceptance and high satisfaction rate with the alternative method.
CONCLUSIONS: Virtual ward rounds using telemedicine via smart glasses on neurosurgical patients in critical care were feasible, effective, and widely accepted as an alternative to physical ward rounds during the coronavirus disease 2019 pandemic.
OBJECTIVE: The aim of this study was to investigate current telemedicine usage by urologists, urologists' perceptions on the necessity of in-person clinic appointments, the usability of telemedicine, and the current barriers to its implementation.
METHODS: We conducted a global, cross-sectional, web-based survey to investigate the use of telemedicine before and after the COVID-19 pandemic. Urologists' perceived usability of telemedicine was assessed using a modified Delphi approach to create questions based on a modified version of the validated Telehealth Usability Questionnaire (TUQ). For the purposes of this study, telemedicine was defined as video calls only.
RESULTS: A total of 620 urologists from 58 different countries and 6 continents participated in the survey. Prior to COVID-19, 15.8% (n=98) of urologists surveyed were using telemedicine in their clinical practices; during the pandemic, that proportion increased to 46.1% (n=283). Of the urologists without telemedicine experience, interest in telemedicine usage increased from 43.7% (n=139) to 80.8% (n=257) during the COVID-19 pandemic. Among urologists that used telemedicine during the pandemic, 80.9% (n=244) were interested in continuing to use it in their practice. The three most commonly used platforms were Zoom, Doxy.me, and Epic, and the top three barriers to implementing telemedicine were patients' lack of technological comprehension, patients' lack of access to the required technology, and reimbursement concerns.
CONCLUSIONS: This is the first study to quantify the use, usability, and pervading interest in telemedicine among urologists during the COVID-19 pandemic. In the face of this pandemic, urologists' usage of telemedicine nearly tripled, demonstrating their ability to adopt and adapt telemedicine into their practices, but barriers involving the technology itself are still preventing many from utilizing it despite increasing interest.