Acute respiratory distress syndrome and outcomes after near hanging.

PURPOSE: The purpose of this study is to assess the case rate of acute respiratory distress syndrome (ARDS) after near hanging and the secondary outcomes of traumatic and/or anoxic brain injury and death. Risk factors for the outcomes were assessed. METHOD: The method is a single-center, statewide retrospective cohort study of consecutive patients admitted between August 2002 and September 2011, with a primary diagnosis of nonjudicial "hanging injury." RESULTS: Of 56 patients, 73% were male. The median age was 31 (Interquartile range (IQR), 16-56). Upon arrival, 9% (5/56) did not have a pulse, and 23% (13/56) patients were intubated. The median Glasgow Coma Scale (GCS) was 13 (IQR, 3-15); 14% (8/56) had a GCS = 3. Acute respiratory distress syndrome developed in 9% (5/56) of patients. Traumatic anoxic brain injury resulted in 9% (5/56) of patients. The in-hospital case fatality was 5% (3/56). Lower median GCS (3 [IQR, 3-7] vs 14 [IQR, 3-15]; P = .0003) and intubation in field or in trauma resuscitation unit (100% [5/5] vs 16% [8/51]; P = .0003) were associated with ARDS development. Risk factors of death were GCS = 3 (100% [3/3] vs 9% [5/53]; P = .002), pulselessness upon arrival of emergency medical services (100% [3/3] vs 4% [2/53]; P < .001], and abnormal neurologic imaging (50% [1/2] vs zero; P = .04). CONCLUSIONS: The ARDS case rate after near hanging is similar to the general trauma population. Low GCS and intubation are associated with increased risk of ARDS development. The rate of traumatic and/or anoxic brain injury in this population is low.

Mobile Technology Care Coordination of Long-Term Services and Support: Cluster Randomized Clinical Trial.

The purpose of the study was to assess whether the effects of a mobile predictive intervention used by Service Coordinators (SCs) reduce hospital utilization in a Medicaid Long-Term Services and Supports (LTSS) population in Baltimore city during a 5-month intervention. SC participants (n = 11) were recruited to treatment or control groups. LTSS clients (n = 420) followed their SC randomization assignment. Utilization data were obtained from the Maryland Chesapeake Regional Information System for our Patients (CRISP) Health Information Exchange (HIE) system and linked to service coordination records. Study groups were similar in age, gender, race, and years receiving LTSS. SCs' satisfaction with use of the mobile tool was surveyed. SC perceptions were neutral (mean scores ranged from 2.3 to 3.3 on a 5-point scale). No significant differences between groups were observed for all utilization metrics. The mobile technology software system used in this study did not improve health care utilization for a LTSS population needing ongoing clinical and social services coordinated care.

Circadian activity rhythms and fatigue of adolescent cancer survivors and healthy controls: a pilot study.

STUDY OBJECTIVES: The primary objective of this study was to compare circadian activity rhythms (CARs) of adolescents within 5 years of completing cancer treatment (survivors) with that of healthy adolescent controls. Secondary objectives were to explore differences in the relationship of CARs and fatigue between survivors and controls and between early survivors (<12 months posttreatment) and late survivors (≥12 months posttreatment). METHODS: Twenty-nine survivors and 30 controls, aged 13-18 years, participated in this prospective, descriptive pilot study. Adolescents and their parents completed a baseline measure of adolescents' fatigue. Adolescents wore a wrist actigraph continuously for 7 days and concurrently kept a sleep diary. Activity data recorded by actigraphy were fitted to an extended cosine model to calculate six CAR variables: acrophase, amplitude, midline estimating statistic of rhythm (MESOR), up-MESOR, down-MESOR, and F-statistic. Linear mixed models explored the relationship between CARs and fatigue. RESULTS: There were no group differences on CAR or fatigue measures. Among survivors, earlier down-MESOR was associated with greater parent-reported fatigue (P = .020), and earlier acrophase (P = .023) and up-MESOR (P = .025) were associated with greater adolescent-reported fatigue. Significant CAR-by-time posttreatment interaction effects were found on fatigue between early and late survivors. Among controls, greater parent-reported fatigue was associated with greater MESOR (P = .0495). CONCLUSIONS: Survivors within the first 5 years posttreatment were similar to controls in CARs and fatigue, suggesting robust recovery of circadian rhythms posttreatment. Different CAR characteristics were associated with fatigue in survivors and controls. Time posttreatment influenced the relationship between CARs and fatigue for survivors, with significant effects only for early survivors.

Gender Differences and Other Factors Associated with Weight Gain Following Initiation of Infliximab: A Post Hoc Analysis of Clinical Trials.

BACKGROUND: In our clinical practice, women often report excess weight gain with infliximab (IFX) use. There are currently no studies investigating weight gain after antitumor necrosis factor therapy in patients with inflammatory bowel disease. The objective of this study was to evaluate the association of clinical factors, with a particular focus on sex and weight gain in patients with moderate to severe Crohn's disease (CD) or ulcerative colitis (UC) initiating IFX. METHODS: Data was extracted from ACCENT I, ACCENT II, ACT 1, and SONIC; included patients received IFX for induction or maintenance of remission of CD or UC. Patients treated with azathioprine (IFX 0 mg/kg) were included as controls. Baseline demographics, clinical characteristics, and weight at each follow-up for the study duration were collected. In addition to descriptive statistics, adjusted mixed effects models were used to test the association between clinical variables and weight gain. RESULTS: There were 1273 patients included for analysis; the majority was white (91%), with CD (81%), and half of patients (50%) were women. Upon univariate analysis, IFX dose, African American race, diagnosis of CD, elevated C-reactive protein, and low hematocrit and albumin were associated with weight gain (P < 0.001). Upon adjusted analysis, sex was significantly associated with weight gain (P = 0.009), with women experiencing a lower percentage increase from baseline weight than men (3.9% increase vs 4.3% increase). CONCLUSIONS: When starting IFX, those with markers of severe disease and with a diagnosis of CD are likely to gain more weight. Adjusting for confounding variables, women actually gain less weight than men after IFX treatment, although this difference is not clinically relevant.

An mHealth Diabetes Intervention for Glucose Control: Health Care Utilization Analysis.

BACKGROUND: Type 2 diabetes (T2D) is a major chronic condition requiring management through lifestyle changes and recommended health service visits. Mobile health (mHealth) is a promising tool to encourage self-management, but few studies have investigated the impact of mHealth on health care utilization. OBJECTIVE: The objective of this analysis was to determine the change in 2-year health service utilization and whether utilization explained a 1.9% absolute decrease in glycated hemoglobin (HbA1c) over 1-year in the Mobile Diabetes Intervention Study (MDIS). METHODS: We used commercial claims data from 2006 to 2010 linked to enrolled patients' medical chart data in 26 primary care practices in Maryland, USA. Secondary claims data analyses were available for 56% (92/163) of participants. In the primary MDIS study, physician practices were recruited and randomized to usual care and 1 of 3 increasingly complex interventions. Patients followed physician randomization assignment. The main variables in the analysis included health service utilization by type of service and change in HbA1c. The claims data was aggregated into 12 categories of utilization to assess change in 2-year health service usage, comparing rates of usage pre- and posttrial. We also examined whether utilization explained the 1.9% decrease in HbA1c over 1 year in the MDIS cluster randomized clinical trial. RESULTS: A significant group by time effect was observed in physician office visits, general practitioner visits, other outpatient services, prescription medications, and podiatrist visits. Physician office visits (P=.01) and general practitioner visits (P=.02) both decreased for all intervention groups during the study period, whereas prescription claims (P<.001) increased. The frequency of other outpatient services (P=.001) and podiatrist visits (P=.04) decreased for the control group and least complex intervention group but increased for the 2 most complex intervention groups. No significant effects of utilization were observed to explain the clinically significant change in HbA1c. CONCLUSIONS: Claims data analyses identified patterns of utilization relevant to mHealth interventions. Findings may encourage patients and health providers to discuss the utilization of treatment-recommended services, lab tests, and prescribed medications. TRIAL REGISTRATION: ClinicalTrials.gov NCT01107015; https://clinicaltrials.gov/ct2/show/NCT01107015 (Archived by Webcite at http://www.webcitation.org/72XgTaxIj).

Mobile Diabetes Intervention Study of Patient Engagement and Impact on Blood Glucose: Mixed Methods Analysis.

BACKGROUND: Successful treatment of diabetes includes patient self-management behaviors to prevent or delay complications and comorbid diseases. On the basis of findings from large clinical trials and professional guidelines, diabetes education programs and health providers prescribe daily regimens of glucose monitoring, healthy eating, stress management, medication adherence, and physical activity. Consistent, long-term commitment to regimens is challenging. Mobile health is increasingly being used to assist patients with lifestyle changes and self-management behaviors between provider visits. The effectiveness of mobile health to improve diabetes outcomes depends on patient engagement with a technology, content, or interactions with providers. OBJECTIVES: In the current analysis, we aimed to identify patient engagement themes in diabetes messaging with diabetes providers and determine if differences in engagement in the Mobile Diabetes Intervention Study (MDIS) influenced changes in glycated hemoglobin A1c (HbA1c) over a 1-year treatment period (1.9% absolute decrease in the parent study). METHODS: In the primary MDIS study, 163 patients were enrolled into 1 of 3 mobile intervention groups or a usual care control group based on their physician cluster randomization assignment. The control group received care from their physicians as usual. Participants in each intervention group had access to a patient portal where they could record monitoring values for blood glucose, blood pressure, medication changes, or other self-management information while also assigned to varying levels of physician access to patient data. Intervention participants could choose to send and receive messages to assigned certified diabetes educators with questions or updates through the secure Web portal. For this secondary analysis, patient engagement was measured using qualitative methods to identify self-care themes in 4109 patient messages. Mixed methods were used to determine the impact of patient engagement on change in HbA1c over 1 year. RESULTS: Self-care behavior themes that received the highest engagement for participants were glucose monitoring (75/107, 70.1%), medication management (71/107, 66.4%), and reducing risks (71/107, 66.4%). The average number of messages sent per patient were highest for glucose monitoring (9.2, SD 14.0) and healthy eating (6.9, SD 13.2). Compared to sending no messages, sending any messages about glucose monitoring (P=.03) or medication (P=.01) led to a decrease in HbA1c of 0.62 and 0.72 percentage points, respectively. Sending any messages about healthy eating, glucose monitoring, or medication combined led to a decrease in HbA1c of 0.54 percentage points compared to not sending messages in these themes (P=.045). CONCLUSIONS: The findings from this study help validate the efficacy of the mobile diabetes intervention. The next step is to determine differences between patients who engage in mobile interventions and those who do not engage and identify methods to enhance patient engagement. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01107015; https://clinicaltrials.gov/ct2/show/NCT01107015 (Archived by WebCite at http://www.webcitation.org/6wh4ekP4R).

The Impact of a Mobile Diabetes Health Intervention on Diabetes Distress and Depression Among Adults: Secondary Analysis of a Cluster Randomized Controlled Trial.

BACKGROUND: Diabetes is a complex, demanding disease that requires the constant attention of patients. The burden of self-management, including different medication regimens, routine self-care activities, and provider visits, has an impact on patients' emotional well-being. Diabetes distress and depression are two important components of emotional well-being that may negatively affect diabetes outcomes. OBJECTIVE: The aim was to determine the impact of the 1-year Mobile Diabetes Intervention Study cluster randomized clinical trial on emotional well-being measured by diabetes distress and depression among adults with type 2 diabetes (T2D). METHODS: A total of 163 adults with not-well-managed T2D were enrolled from community primary care practices. Primary care practices were cluster randomized into either a usual care control group or intervention group. Intervention participants were given a mobile phone with coaching software including a Web portal to communicate with providers. A priori established secondary outcomes included distress measured by the Diabetes Distress Scale (DDS), with subscales measuring emotional burden, interpersonal distress, physician-related distress, and regimen-related distress, as well as depression measured by the Patient Health Questionnaire (PHQ-9). Linear mixed models were used to calculate the effect of the intervention on diabetes distress levels over time, both overall and separately by sex, and to determine if the intervention affected distress or depression. The impact of total DDS on changes in HbA1c was also studied. RESULTS: There were no significant treatment group effects for DDS total (baseline: P=.07; differences over time: P=.38) or for depression (P=.06 over time). Significant declines in total DDS were observed over the 12-month intervention period (P=.01). Regimen-related distress significantly decreased for all study participants (P<.001), but no significant change over time was observed for emotional burden (P=.83), interpersonal distress (P=.64), or physician-related distress (P=.73). Women in both the usual care and intervention groups were more likely to have higher overall DDS, emotional burden, physician-related distress, and regimen-related distress, but not interpersonal distress. Women also reported higher baseline depression compared to men (P=.006). Overall, depression decreased over the treatment period (P=.007), but remained unaffected by group assignment (P=.06) or by sex (P=.97). Diabetes distress had no effect on the change in HbA1c (P=.91) over the treatment period. CONCLUSIONS: Although we found no definitive overall or sex-specific effect of the intervention on diabetes distress or depression, this study makes an important contribution to the understanding of mobile health interventions and the impact on emotional health. Our study verified previous work that although diabetes distress and depression are highly correlated, these measures are not evaluating the same construct. Design of future mobile technology provides an opportunity to personalize, contextualize, and intervene in the emotional well-being of persons with diabetes. TRIAL REGISTRATION: Clinicaltrials.gov NCT01107015; https://clinicaltrials.gov/ct2/show/NCT01107015 (Archived by WebCite at http://www.webcitation.org/6vVgRCLAF).

Mobile Diabetes Intervention for Glycemic Control in 45- to 64-Year-Old Persons With Type 2 Diabetes.

The purpose of this study was to assess effects of a mobile coaching system on glycated hemoglobin (HbA1c) levels in younger versus older patients over 1 year. Participants (n = 118) included adult patients with Type 2 diabetes cared for by community physicians. Intervention patients received mobile phone coaching and individualized web portal. Control patients received usual care. Patients were stratified into two age groups: younger (<55 years) and older (≥ 55 years). The intervention resulted in greater 12-month declines in HbA1c, compared with usual care, for patients in both age groups (p < .0001). Among older patients, HbA1c changed by -1.8% (95% confidence interval [CI] = [-2.4, -1.1]) in the intervention group and -0.3% (95% CI = [-0.9, +0.3]) in the control group. Among younger patients, HbA1c changed by -2.0% (95% CI = [-2.5, -1.5]) in the intervention group and -1.0% (95% CI = [-1.6, -0.4]) in the control group. The mobile health intervention was as effective at managing Type 2 diabetes in older adults as younger persons.

Mobile Diabetes Intervention for Glycemic Control: Impact on Physician Prescribing.

Of adults with type 2 diabetes, 84% take antihyperglycemic medication. Successful treatment requires active monitoring and medication dose adjustment by health providers. The objective of this study was to determine how a mobile-phone-based coaching system for diabetes management influences physician prescribing behavior. This secondary data analysis is based on a cluster randomized clinical trial that reported patients provided with mobile self-management had reduction in glycated hemoglobin (HbA1c) of 1.9% over 1 year, compared to 0.7% in control patients (P < .001). Participants were primary care patients with type 2 diabetes randomized at physician practice level into a control group (n = 55) and intervention group (n = 62). Main study measures were patients' medication records (medication, dose, frequency, start and end date) abstracted at baseline and study end. Antihyperglycemic medications, including sulfonylureas or thiazolidinediones, and antihypertensive and antilipemic medications were analyzed. A higher percentage of patients in the intervention group had modification and intensification of incretin mimetics during the 1-year study period (9.7% vs 0.0% and 8.1% vs 0.0%, both P = .008). A higher percentage of patients in the intervention group had modification and intensification of metformin (24.2% vs 7.3%, P = .033). The overall difference in physician prescribing of oral antihyperglycemic medications was not statistically significant. Our results suggest mobile diabetes interventions can encourage physicians to modify and intensify antihyperglycemic medications in patients with type 2 diabetes. Differences in physician prescribing behavior were modest, and do not appear to be large enough to explain a 1.2% decrease in HbA1c.

Cluster-randomized trial of a mobile phone personalized behavioral intervention for blood glucose control.

OBJECTIVE: To test whether adding mobile application coaching and patient/provider web portals to community primary care compared with standard diabetes management would reduce glycated hemoglobin levels in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: A cluster-randomized clinical trial, the Mobile Diabetes Intervention Study, randomly assigned 26 primary care practices to one of three stepped treatment groups or a control group (usual care). A total of 163 patients were enrolled and included in analysis. The primary outcome was change in glycated hemoglobin levels over a 1-year treatment period. Secondary outcomes were changes in patient-reported diabetes symptoms, diabetes distress, depression, and other clinical (blood pressure) and laboratory (lipid) values. Maximal treatment was a mobile- and web-based self-management patient coaching system and provider decision support. Patients received automated, real-time educational and behavioral messaging in response to individually analyzed blood glucose values, diabetes medications, and lifestyle behaviors communicated by mobile phone. Providers received quarterly reports summarizing patient's glycemic control, diabetes medication management, lifestyle behaviors, and evidence-based treatment options. RESULTS: The mean declines in glycated hemoglobin were 1.9% in the maximal treatment group and 0.7% in the usual care group, a difference of 1.2% (P = 0.001) [corrected] over 12 months. Appreciable differences were not observed between groups for patient-reported diabetes distress, depression, diabetes symptoms, or blood pressure and lipid levels (all P > 0.05). CONCLUSIONS: The combination of behavioral mobile coaching with blood glucose data, lifestyle behaviors, and patient self-management data individually analyzed and presented with evidence-based guidelines to providers substantially reduced glycated hemoglobin levels over 1 year.