Weight loss in a digital app-based diabetes prevention program powered by artificial intelligence.

Objective: The National Diabetes Prevention Program (DPP) reduces diabetes incidence and associated medical costs but is typically staffing-intensive, limiting scalability. We evaluated an alternative delivery method with 3933 members of a program powered by conversational Artificial Intelligence (AI) called Lark DPP that has full recognition from the Centers for Disease Control and Prevention (CDC). Methods: We compared weight loss maintenance at 12 months between two groups: 1) CDC qualifiers who completed ≥4 educational lessons over 9 months (n = 191) and 2) non-qualifiers who did not complete the required CDC lessons but provided weigh-ins at 12 months (n = 223). For a secondary aim, we removed the requirement for a 12-month weight and used logistic regression to investigate predictors of weight nadir in 3148 members. Results: CDC qualifiers maintained greater weight loss at 12 months than non-qualifiers (M = 5.3%, SE = .8 vs. M = 3.3%, SE = .8; p = .015), with 40% achieving ≥5%. The weight nadir of 3148 members was 4.2% (SE = .1), with 35% achieving ≥5%. Male sex (ß = .11; P = .009), weeks with ≥2 weigh-ins (ß = .68; P < .0001), and days with an AI-powered coaching exchange (ß = .43; P < .0001) were associated with a greater likelihood of achieving ≥5% weight loss. Conclusions: An AI-powered DPP facilitated weight loss and maintenance commensurate with outcomes of other digital and in-person programs not powered by AI. Beyond CDC lesson completion, engaging with AI coaching and frequent weighing increased the likelihood of achieving ≥5% weight loss. An AI-powered program is an effective method to deliver the DPP in a scalable, resource-efficient manner to keep pace with the prediabetes epidemic.

Reach of a Fully Digital Diabetes Prevention Program in Health Professional Shortage Areas.

The National Diabetes Prevention Program (NDPP) offers lifestyle change education to adults at risk for diabetes across the United States, but its reach is curbed due, in part, to limitations of traditional in-person programs. Diabetes Prevention Programs (DPPs) that are fully digital may increase reach by overcoming these barriers. The aim of this research was to examine the reach of Lark's DPP, a fully digital artificial-intelligence-powered DPP. This study assessed geographic features and demographic characteristics of a sample of Lark DPP commercial health plan members with complete data (N = 16,327) and compared several demographic features with a large composite sample of members from DPPs across the nation (NDPP; N = 143,489) and a National Health Interview Survey (NHIS) sample of prediabetic adults in the United States (NHIS; N = 2118). Examination of the Lark DPP sample revealed that 24.4% of members lived in rural areas, 30.8% lived in whole county health professional shortage areas, and only 7.6% of members lived in a zip code with an in-person DPP. When comparing the Lark sample with the NDPP and NHIS samples, Lark DPP enrollees tended to be younger and have a higher body mass index (BMI) (p's < 0.001). Lark provides convenient access to a DPP for individuals living in hard-to-reach areas who may face barriers to participating in in-person or telephonic DPPs or who prefer a digital program. Compared with the NDPP sample, Lark is also reaching younger and higher BMI users, who are traditionally difficult to enroll and have a high need for intervention.

Risk factors for surgical site infections following spinal fusion procedures: a case-control study.

BACKGROUND: Spinal fusion procedures are associated with a significant rate of surgical site infection (SSI) (1%-12%). The goal of this study was to identify modifiable risk factors for spinal fusion SSIs at a large tertiary care center. METHODS: A retrospective, case-control (1:3 ratio) analysis of SSIs following posterior spine fusion procedures was performed over a 1-year period. Clinical and surgical data were collected through electronic database and chart review. Variables were evaluated by univariate analysis and multivariable logistic regression. RESULTS: In total, 57 deep SSIs were identified out of 1587 procedures (3.6%). Infections were diagnosed a mean of 13.5 ± 8 days postprocedure. Staphylococcus aureus was the predominant pathogen (63%); 1/3 of these isolates were methicillin resistant. Significant patient risk factors for infection by univariate analysis included ASA score >2 and male gender. Among surgical variables, infected cases had significantly higher proportions of staged procedures and thoracic level surgeries and had a greater number of vertebrae fused. Notably, infected fusion procedures had a longer duration of closed suction drains than controls (5.1 ± 2 days vs 3.4 ± 1 day, respectively; P < .001). Drain duration (unit odds ratio [OR], 1.6 per day drain present; 95% confidence interval [CI], 1.3-1.9), body mass index (OR, 1.1; 95% CI, 1.0-1.1), and male gender (OR, 2.7; 95% CI, 1.4-5.6) were significant risk factors in the multivariate analysis. CONCLUSIONS: Prolonged duration of closed suction drains is a strong independent risk factor for SSI following instrumented spinal fusion procedures. Therefore, removing drains as early as possible may lower infection rates.

Older Adults Engage With Personalized Digital Coaching Programs at Rates That Exceed Those of Younger Adults.

Background: The US population is aging and has an expanding set of healthcare needs for the prevention and management of chronic conditions. Older adults contribute disproportionately to US healthcare costs, accounting for 34% of total healthcare expenditures in 2014 but only 15% of the population. Fully automated, digital health programs offer a scalable and cost-effective option to help manage chronic conditions. However, the literature on technology use suggests that older adults face barriers to the use of digital technologies that could limit their engagement with digital health programs. The objective of this study was to characterize the engagement of adults 65 years and older with a fully automated digital health platform called Lark Health and compare their engagement to that of adults aged 35-64 years. Methods: We analyzed data from 2,169 Lark platform users across four different coaching programs (diabetes prevention, diabetes care, hypertension care, and prevention) over a 12-month period. We characterized user engagement as participation in digital coaching conversations, meals logged, and device measurements. We compared engagement metrics between older and younger adults using nonparametric bivariate analyses. Main Results: Aggregate engagement across all users during the 12-month period included 1,623,178 coaching conversations, 588,436 meals logged, and 203,693 device measurements. We found that older adults were significantly more engaged with the digital platform than younger adults, evidenced by older adults participating in a larger median number of coaching conversations (514 vs. 428) and logging more meals (174 vs. 89) and device measurements (39 vs. 28) all p ≤ 0.01. Conclusions: Older adult users of a commercially available, fully digital health platform exhibited greater engagement than younger adults. These findings suggest that despite potential barriers, older adults readily adopted digital health technologies. Fully digital health programs may present a widely scalable and cost-effective alternative to traditional telehealth models that still require costly touchpoints with human care providers.

The postprandial increase in blood triglycerides has no direct effect on the brain BOLD response.

A previous study showed that ingestion of a liquid meal high in polyunsaturated lipids decreased the blood-oxygenation-level-dependent (BOLD) response measured by functional magnetic resonance imaging (fMRI) during a finger-tapping motor task, and suggested that this effect was due to a direct effect of blood lipids on the cerebral vasculature. This study compared the time course and magnitude of the BOLD response in fixed anatomic locations before and 3 h after ingestion of high versus low lipid content liquid meals (235 ml Ensure Plus [Abbot Labs] with or without 50 ml added canola oil). Blood triglyceride content peaked 3 h after the high lipid meal and was elevated by 33% compared with the low lipid meal. There was no significant effect of meal composition on the time course or magnitude of the BOLD response in fixed-location clusters of voxels which were activated during either a motor (finger-tapping), a visual (flashing checkerboard), or an integrative/cognitive (number addition) block-design task paradigm. The results indicate that increased blood total triglyceride content after a meal with relatively high polyunsaturated fat does not directly alter the hemodynamic BOLD response to neural activity. However, the postprandial effect on BOLD response of other meals with varying fat types and amounts, as well as other nutrients and phytochemicals, remains to be determined.

Negative regulation of NF-kappaB signaling by PIAS1.

The NF-kappaB family of transcription factors is activated by a wide variety of signals to regulate a spectrum of cellular processes. The proper regulation of NF-kappaB activity is critical, since abnormal NF-kappaB signaling is associated with a number of human illnesses, such as chronic inflammatory diseases and cancer. We report here that PIAS1 (protein inhibitor of activated STAT1) is an important negative regulator of NF-kappaB. Upon cytokine stimulation, the p65 subunit of NF-kappaB translocates into the nucleus, where it interacts with PIAS1. The binding of PIAS1 to p65 inhibits cytokine-induced NF-kappaB-dependent gene activation. PIAS1 blocks the DNA binding activity of p65 both in vitro and in vivo. Consistently, chromatin immunoprecipitation assays indicate that the binding of p65 to the promoters of NF-kappaB-regulated genes is significantly enhanced in Pias1-/- cells. Microarray analysis indicates that the removal of PIAS1 results in an increased expression of a subset of NF-kappaB-mediated genes in response to tumor necrosis factor alpha and lipopolysaccharide. Consistently, Pias1 null mice showed elevated proinflammatory cytokines. Our results identify PIAS1 as a novel negative regulator of NF-kappaB.

Design of a randomized controlled trial comparing a mobile phone-based hypertension health coaching application to home blood pressure monitoring alone: The Smart Hypertension Control Study.

BACKGROUND: Hypertension is a major cause of morbidity and mortality but frequently remains uncontrolled. A smartphone application that provides coaching regarding home blood pressure monitoring and other aspects of hypertension self-care and related behavior change may be a scalable way to help manage hypertension. METHODS/DESIGN: The Smart Hypertension Control Study is a prospective, randomized controlled trial to assess the effects of a hypertension personal control program (HPCP), which consists of an automated artificial intelligence smartphone application that provides individualized support and coaching to promote home monitoring and healthy behavior changes related to hypertension self-management. Enrolled adults with uncontrolled hypertension will be randomized in a 1:1 fashion to the HPCP with home blood pressure monitoring or to home monitoring alone. We plan to enroll 350 participants, with a target of 300 participants with complete six-month follow-up data. The primary study outcome will be systolic blood pressure at six months. Additional outcomes include measures of antihypertensive medication adherence, home blood pressure monitoring practices, self-management practices, weight, and self-reported health behaviors. CONCLUSION: The Smart Hypertension Control Study will evaluate blood pressure and hypertension self-management behavior outcomes in participants with uncontrolled hypertension exposed to a smartphone-based hypertension health coaching application in addition to home blood pressure monitoring compared to those exposed to home blood pressure monitoring alone.

A Fully Automated Conversational Artificial Intelligence for Weight Loss: Longitudinal Observational Study Among Overweight and Obese Adults.

BACKGROUND: Type 2 diabetes is the most expensive chronic disease in the United States. Two-thirds of US adults have prediabetes or are overweight and at risk for type 2 diabetes. Intensive in-person behavioral counseling can help patients lose weight and make healthy behavior changes to improve their health outcomes. However, with the shortage of health care providers and associated costs, such programs do not adequately service all patients who could benefit. The health care system needs effective and cost-effective interventions that can lead to positive health outcomes as scale. This study investigated the ability of conversational artificial intelligence (AI), in the form of a standalone, fully automated text-based mobile coaching service, to promote weight loss and other health behaviors related to diabetes prevention. This study also measured user acceptability of AI coaches as alternatives to live health care professionals. OBJECTIVE: The objective of this study was to evaluate weight loss, changes in meal quality, and app acceptability among users of the Lark Weight Loss Health Coach AI (HCAI), with the overarching goal of increasing access to compassionate health care via mobile health. Lessons learned in this study can be applied when planning future clinical trials to evaluate HCAI and when designing AI to promote weight loss, healthy behavior change, and prevention and self-management of chronic diseases. METHODS: This was a longitudinal observational study among overweight and obese (body mass index ≥25) participants who used HCAI, which encourages weight loss and healthy diet choices through elements of cognitive behavioral therapy. Weight loss, meal quality, physical activity, and sleep data were collected through user input and, for sleep and physical activity, partly through automatic detection by the user's mobile phone. User engagement was assessed by duration and amount of app use. A 4-question in-app user trust survey assessed app usability and acceptability. RESULTS: Data were analyzed for participants (N=70) who met engagement standards set forth by the Centers for Disease Control and Prevention criteria for Diabetes Prevention Program, a clinically proven weight loss program focused on preventing diabetes. Weight loss (standard error of the mean) was 2.38% (0.69%) of baseline weight. The average duration of app use was 15 (SD 1.0) weeks, and users averaged 103 sessions each. Predictors of weight loss included duration of AI use, number of counseling sessions, and number of meals logged. Percentage of healthy meals increased by 31%. The in-app user trust survey had a 100% response rate and positive results, with a satisfaction score of 87 out of 100 and net promoter score of 47. CONCLUSIONS: This study showed that use of an AI health coach is associated with weight loss comparable to in-person lifestyle interventions. It can also encourage behavior changes and have high user acceptability. Research into AI and its application in telemedicine should be pursued, with clinical trials investigating effects on weight, health behaviors, and user engagement and acceptability.

Impact of race and socioeconomic status on presentation and management of ventral hernias.

OBJECTIVE: To assess for disparity in presentation and management of ventral hernias. DESIGN: Retrospective review. SETTING: Academic center. PATIENTS: Three hundred twenty-one patients who underwent ventral hernia repair from 2005 to 2008. MAIN OUTCOME MEASURES: Disparity in ventral hernia presentation, management, and outcome. Univariate analysis was conducted by unpaired t test and chi(2) test. RESULTS: Black individuals were more likely than white individuals to present with acute hernia complications requiring emergent surgery (11% vs 4%; P < .01). This finding persisted after controlling for socioeconomic status (SES). Assessment by SES demonstrated patients with Medicaid were more likely to present with incarcerated or strangulated hernias (39% vs 25%; P < .001) and had longer hospital stays (4.7 vs 3 days; P < .05) as compared with patients with private insurance. Patients classified as low income had increased 30-day readmission rates as compared with average- or high-income patients (32% vs 9% vs 7%, respectively; P < .01). No difference in use of minimally invasive technique, performance of primary vs mesh repair, or postoperative morbidity or mortality was demonstrated. Twelve-month follow-up demonstrated no difference in recurrence rate by race or SES. CONCLUSIONS: Our study demonstrates the existence of disparity in patient presentation with complicated ventral hernia. Despite clear disparity by race and SES, at our institution, disparate presentation did not equate to disparate treatment or postoperative complications. No difference was demonstrated by use of operative technique, perioperative outcome, or 12-month recurrence rate. This study illustrates the need for long-term measures directed at reevaluation of organizational and institutional factors that perpetuate inequality.

PIAS1 selectively inhibits interferon-inducible genes and is important in innate immunity.

Interferon (IFN) activates the signal transducer and activator of transcription (STAT) pathway to regulate immune responses. The protein inhibitor of activated STAT (PIAS) family has been suggested to negatively regulate STAT signaling. To understand the physiological function of PIAS1, we generated Pias1(-/-) mice. Using PIAS1-deficient cells, we show that PIAS1 selectively regulates a subset of IFN-gamma- or IFN-beta-inducible genes by interfering with the recruitment of STAT1 to the gene promoter. The antiviral activity of IFN-gamma or IFN-beta was consistently enhanced by Pias1 disruption. Pias1(-/-) mice showed increased protection against pathogenic infection. Our data indicate that PIAS1 is a physiologically important negative regulator of STAT1 and suggest that PIAS1 is critical for the IFN-gamma- or IFN-beta-mediated innate immune responses.