PRECEPT: an evidence assessment framework for infectious disease epidemiology, prevention and control.

Decisions in public health should be based on the best available evidence, reviewed and appraised using a rigorous and transparent methodology. The Project on a Framework for Rating Evidence in Public Health (PRECEPT) defined a methodology for evaluating and grading evidence in infectious disease epidemiology, prevention and control that takes different domains and question types into consideration. The methodology rates evidence in four domains: disease burden, risk factors, diagnostics and intervention. The framework guiding it has four steps going from overarching questions to an evidence statement. In step 1, approaches for identifying relevant key areas and developing specific questions to guide systematic evidence searches are described. In step 2, methodological guidance for conducting systematic reviews is provided; 15 study quality appraisal tools are proposed and an algorithm is given for matching a given study design with a tool. In step 3, a standardised evidence-grading scheme using the Grading of Recommendations Assessment, Development and Evaluation Working Group (GRADE) methodology is provided, whereby findings are documented in evidence profiles. Step 4 consists of preparing a narrative evidence summary. Users of this framework should be able to evaluate and grade scientific evidence from the four domains in a transparent and reproducible way.

Evidence-based decision-making in infectious diseases epidemiology, prevention and control: matching research questions to study designs and quality appraisal tools.

BACKGROUND: The Project on a Framework for Rating Evidence in Public Health (PRECEPT) was initiated and is being funded by the European Centre for Disease Prevention and Control (ECDC) to define a methodology for evaluating and grading evidence and strength of recommendations in the field of public health, with emphasis on infectious disease epidemiology, prevention and control. One of the first steps was to review existing quality appraisal tools (QATs) for individual research studies of various designs relevant to this area, using a question-based approach. METHODS: Through team discussions and expert consultations, we identified 20 relevant types of public health questions, which were grouped into six domains, i.e. characteristics of the pathogen, burden of disease, diagnosis, risk factors, intervention, and implementation of intervention. Previously published systematic reviews were used and supplemented by expert consultation to identify suitable QATs. Finally, a matrix was constructed for matching questions to study designs suitable to address them and respective QATs. Key features of each of the included QATs were then analyzed, in particular in respect to its intended use, types of questions and answers, presence/absence of a quality score, and if a validation was performed. RESULTS: In total we identified 21 QATs and 26 study designs, and matched them. Four QATs were suitable for experimental quantitative study designs, eleven for observational quantitative studies, two for qualitative studies, three for economic studies, one for diagnostic test accuracy studies, and one for animal studies. Included QATs consisted of six to 28 items. Six of the QATs had a summary quality score. Fourteen QATs had undergone at least one validation procedure. CONCLUSIONS: The results of this methodological study can be used as an inventory of potentially relevant questions, appropriate study designs and QATs for researchers and authorities engaged with evidence-based decision-making in infectious disease epidemiology, prevention and control.

Proactive Identification of Patients with Diabetes at Risk of Uncontrolled Outcomes during a Diabetes Management Program: Conceptualization and Development Study Using Machine Learning.

BACKGROUND: The growth in the capabilities of telehealth have made it possible to identify individuals with a higher risk of uncontrolled diabetes and provide them with targeted support and resources to help them manage their condition. Thus, predictive modeling has emerged as a valuable tool for the advancement of diabetes management. OBJECTIVE: This study aimed to conceptualize and develop a novel machine learning (ML) approach to proactively identify participants enrolled in a remote diabetes monitoring program (RDMP) who were at risk of uncontrolled diabetes at 12 months in the program. METHODS: Registry data from the Livongo for Diabetes RDMP were used to design separate dynamic predictive ML models to predict participant outcomes at each monthly checkpoint of the participants' program journey (month-n models) from the first day of onboarding (month-0 model) up to the 11th month (month-11 model). A participant's program journey began upon onboarding into the RDMP and monitoring their own blood glucose (BG) levels through the RDMP-provided BG meter. Each participant passed through 12 predicative models through their first year enrolled in the RDMP. Four categories of participant attributes (ie, survey data, BG data, medication fills, and health signals) were used for feature construction. The models were trained using the light gradient boosting machine and underwent hyperparameter tuning. The performance of the models was evaluated using standard metrics, including precision, recall, specificity, the area under the curve, the F1-score, and accuracy. RESULTS: The ML models exhibited strong performance, accurately identifying observable at-risk participants, with recall ranging from 70% to 94% and precision from 40% to 88% across the 12-month program journey. Unobservable at-risk participants also showed promising performance, with recall ranging from 61% to 82% and precision from 42% to 61%. Overall, model performance improved as participants progressed through their program journey, demonstrating the importance of engagement data in predicting long-term clinical outcomes. CONCLUSIONS: This study explored the Livongo for Diabetes RDMP participants' temporal and static attributes, identification of diabetes management patterns and characteristics, and their relationship to predict diabetes management outcomes. Proactive targeting ML models accurately identified participants at risk of uncontrolled diabetes with a high level of precision that was generalizable through future years within the RDMP. The ability to identify participants who are at risk at various time points throughout the program journey allows for personalized interventions to improve outcomes. This approach offers significant advancements in the feasibility of large-scale implementation in remote monitoring programs and can help prevent uncontrolled glycemic levels and diabetes-related complications. Future research should include the impact of significant changes that can affect a participant's diabetes management.

The Effect of a Digital Mental Health Program on Anxiety and Depression Symptoms: Retrospective Analysis of Clinical Severity.

BACKGROUND: Evidence-based digital health programs have shown efficacy in being primary tools to improve emotional and mental health, as well as offering supplementary support to individuals undergoing psychotherapy for anxiety, depression, and other mental health disorders. However, information is lacking about the dose response to digital mental health interventions. OBJECTIVE: The objective of the study was to examine the effect of time in program and program usage on symptom change among individuals enrolled in a real-world comprehensive digital mental health program (myStrength) who are experiencing severe anxiety or depression. METHODS: Eligible participants (N=18,626) were adults aged 18 years and older who were enrolled in myStrength for at least four weeks as part of their employee wellness benefit program, who completed baseline, the 2-week, 2-month, and 6-month surveys querying symptoms of anxiety (Generalized Anxiety Disorder-7 [GAD-7]) and depression (Patient Health Questionnaire-9 [PHQ-9]). Linear growth curve models were used to analyze the effect of average weekly program usage on subsequent GAD-7 and PHQ-9 scores for participants with scores indicating severe anxiety (GAD-7≥15) or depression (PHQ-9≥15). All models were adjusted for baseline score and demographics. RESULTS: Participants in the study (N=1519) were 77.4% female (1176/1519), had a mean age of 45 years (SD 14 years), and had an average enrollment time of 3 months. At baseline, participants reported an average of 9.39 (SD 6.04) on the GAD-7 and 11.0 (SD 6.6) on the PHQ-9. Those who reported 6-month results had an average of 8.18 (SD 6.15) on the GAD-7 and 9.18 (SD 6.79) on the PHQ-9. Participants with severe scores (n=506) experienced a significant improvement of 2.97 (SE 0.35) and 3.97 (SE 0.46) at each time point for anxiety and depression, respectively (t=-8.53 and t=-8.69, respectively; Ps<.001). Those with severe baseline scores also saw a reduction of 0.27 (SE 0.08) and 0.25 (SE 0.09) points in anxiety and depression, respectively, for each additional program activity per week (t=-3.47 and t=-2.66, respectively; Ps<.05). CONCLUSIONS: For participants with severe baseline scores, the study found a clinically significant reduction of approximately 9 points for anxiety and 12 points for depression after 6 months of enrollment, suggesting that interventions targeting mental health must maintain active, ongoing engagement when symptoms are present and be available as a continuous resource to maximize clinical impact, specifically in those experiencing severe anxiety or depression. Moreover, a dosing effect was shown, indicating improvement in outcomes among participants who engaged with the program every other day for both anxiety and depression. This suggests that digital mental health programs that provide both interesting and evidence-based activities could be more successful in further improving mental health outcomes.

Association of physical activity on blood glucose in individuals with type 2 diabetes.

Regular physical activity (PA) has been shown to improve glycemic control in persons with type 2 diabetes. This study aimed to investigate the impact of PA on blood glucose after controlling for medication use, demographics, and week of activation using a real-world population of individuals with type 2 diabetes. A longitudinal, retrospective study was performed evaluating weekly PA of Livongo members (N = 9,509), which analyzed fasting blood glucose (FBG), step counts, and daily active minutes. Linear mixed-effect modeling technique was used to investigate within member and between member effects of input variables on average weekly FBG. Of members enrolled, 6,336 (32%) had self-reported body mass index, qualified week with diabetes medications, and FBG measures. Members' baseline average age was 49.4 (SD 10.1) years old, 43% female, and 45,496 member weeks with an average of 7.2 qualified weeks (PA observable in ≥4 days) per member. Average weekly FBG was 140.5 mg/dL (SD 39.8), and average daily step counts were 4,833 (SD 3,266). Moving from sedentary (<5,000 steps per day) to active (≥5,000 steps per day) resulted in mean weekly FBG reduction of 13 mg/dL (95% CI: -22.6 to -3.14). One additional day of ≥8,000 steps reduced mean weekly FBG by 0.47 mg/dL (95% CI: -0.77 to -0.16). Members who completed 30 min of moderate to vigorous PA above the population average reduced mean weekly FBG by 7.7 mg/dL (95% CI: -13.4 to -2.0). PA is associated with a mean weekly FBG reduction of 13 mg/dL when changing from a sedentary to active lifestyle while participating in a remote diabetes monitoring program.

Risk factors, resource use, and cost of postoperative low cardiac output syndrome.

OBJECTIVE: Low cardiac output syndrome complicates recovery after cardiac surgery. We examined the incidence and risk factors for low cardiac output syndrome and its association with postoperative mortality, morbidity, resource use, and cost. METHODS: This cross-sectional retrospective observational study examined patients having cardiac surgery captured in the Premier Healthcare Database. Low cardiac output syndrome was defined as the requirement for postoperative mechanical circulatory support and/or hemodynamic instability requiring prolonged inotropic support. Incidence, risk factors, and association of low cardiac output syndrome with postoperative outcomes, including mortality, hospital and intensive care unit length of stay, hospital readmission, and cost at 30 days, 90 days, and 6 months, were examined. RESULTS: Among 59,810 patients from 164 hospitals having cardiac surgery between July 1, 2012, and June 30, 2014, low cardiac output syndrome developed in 6067 (10.1%) patients. Patients presenting in cardiogenic shock or systolic (± diastolic) heart failure were at greatest risk. Risk-adjusted in-hospital mortality was 12-fold greater with low cardiac output syndrome (odds ratio, 12.0; 95% confidence interval, 10.6-13.5). Risk-adjusted hospital costs (2019$; median [Q1, Q3]) were $64,041 [21,439] in patients who developed low cardiac output syndrome versus $48,086 [16,098] without; P < .001. Increased costs were driven by longer risk-adjusted hospital stay (10.1 [4.5] vs 8.5 [3.8] days); P < .001, intensive care unit (5.5 [2.5] vs 3.3 [1.5] days; P < .001) stay, and all-cause 30-day adjusted hospital readmission rates (mean [SD] 16.6 [8.2]% vs 13.9 [7.2]%; P < .001). CONCLUSIONS: Cardiac surgical patients who develop postoperative low cardiac output syndrome suffer greater mortality and have greater resource use, health care costs, and all-cause readmission, which informs perioperative decision making, and impacts hospital performance metrics and federal priority to reduce health care costs.

Impact of a diabetes remote monitoring program on medication adherence.

BACKGROUND: Medication nonadherence in diabetes is well documented to be associated with inadequate glycemic control. Through remote blood glucose (BG) monitoring, unlimited test strip and lancet supplies, personal coaching, and online access to clinical information and educational resources, diabetes remote monitoring (DRM) programs may provide a solution. OBJECTIVE: To examine the relationship between patient participation in a DRM solution and adherence to oral antidiabetic drugs (OAD). METHODS: A retrospective, propensity score-matched cohort study was conducted using deidentified administrative claims data from a large pharmacy benefit manager. Commercially insured patients aged 18 years or older and having 2 or more 30-day adjusted OAD claims comprised the target sample. Patients enrolled in insurance plans that implemented DRM, who had at least 1 BG check (ever engaged) between April 1, 2015, and March 31, 2018 (exposure) were matched to patients enrolled in insurance plans that did not implement DRM (nonexposure). After a 1:2 matching on baseline demographics, disease burden proxy, total pharmacy out-of-pocket costs, previous adherence and insulin use, nonexposure group participants were assigned the same first BG check date as their matched DRM participants. Medication adherence measured as proportion of days covered (PDC) in the 365 days following first BG check was examined as a continuous and binary outcome measure (PDC > 80% or adherent vs < 80% or nonadherent). Multivariable linear and logistic regression were conducted to examine differential magnitude in adherence and likelihood of being adherent, respectively. RESULTS: The final sample consisted of 6,002 exposure and 12,004 nonexposure group patients. DRM participants who were ever engaged had a 4.5% higher adherence rate (P < 0.001) and 42% higher odds of being adherent (P < 0.001) in the period after engagement compared with non-DRM participants. Sensitivity analyses showed that patients engaged continuously (> 1 BG check per week) for 3, 6, and 12 months had 5.1%, 5.2%, and 6.4% higher adherence rates, respectively (P < 0.001), and 52%, 64%, and 98% higher odds of being adherent, respectively (P < 0.001), compared with non-DRM participants. CONCLUSIONS: The study findings offer evidence that DRM engagement is associated with higher odds of medication adherence. DRM solutions that provide access to glucose test results, personalized coaching, educational resources, and lower testing supply cost can also influence adherence. Our findings have important implications for payers and patients related to improved health outcomes due to higher medication adherence. DISCLOSURES: Funding for this study was provided by Express Scripts. Munshi, Amelung, Carter, and Henderson are employed by Express Scripts. James and Shah are employed by Livongo, which provided the DRM solution.

Pressure ulcer prevention in long-term-care facilities: a pilot study implementing standardized nurse aide documentation and feedback reports.

OBJECTIVE: To design and facilitate implementation of practice-based evidence changes associated with decreases in pressure ulcer (PrU) development in long-term-care (LTC) facilities and promote these practices as part of routine care. DESIGN: Pre/post observational study. SETTINGS AND PARTICIPANTS: Frail older adult residents in 11 US LTC facilities. INTERVENTION: Project facilitators assisted frontline multidisciplinary teams (certified nurse aides [CNAs], nurses, and dietitians/dietary aides) to develop streamlined standardized CNA documentation and weekly reports to identify high-risk residents and to integrate clinical reports into day-to-day practice and clinical decision making. The program was called "Real-Time Optimal Care Plans for Nursing Home QI" (Real-Time). MAIN OUTCOME MEASURES: Prevalence of PrUs using Centers for Medicare & Medicaid Services (CMS) quality measures (QMs), number of in-house-acquired PrUs, and number and completeness of CNA documentation forms. MAIN RESULTS: Seven study LTC facilities that reported data to CMS experienced a combined 33% (SD, 36.1%) reduction in the CMS high-risk PrU QM in 18 months and reduction in newly occurring PrUs (number of ulcers in the fourth quarter of 2003: range, 2-19; and in the third quarter of 2005: range, 1-6). Five of these LTC facilities that fully implemented Real-Time experienced a combined 48.1% (SD, 23.4%) reduction in the CMS high-risk PrU QM. Ten facilities reduced by an average of 2 to 5 their number of CNA documentation forms; CNA weekly documentation completeness reached a consistent level of 90% to 95%, and 8 facilities integrated the use of 2 to 4 weekly project reports in routine clinical decision making. CONCLUSIONS: Quality improvement efforts that provide access to focused and timely clinical information, facilitate change, and promote staff working together in multidisciplinary teams impacted clinical outcomes. Prevention of PrUs showed a trend of improvement in facilities that fully integrated tools to identify high-risk residents into day-to-day practice. CNA documentation facilitated better information for clinical decision making. More than 70 additional LTC facilities across the United States are implementing this QI program.

Practice-based evidence for clinical practice improvement: an alternative study design for evidence-based medicine.

This chapter gives an educational overview of * The limitations of evidence-based practice. * Strengths and weaknesses of RCT and observational studies. * The general PBE-CPI study design. * Benefits of PBE-CPI studies and how they can enhance our ability to discover and establish standards for best practice. * The relationship between CIS and PBE-CPI studies.

Relationship Between Diabetes, Stress, and Self-Management to Inform Chronic Disease Product Development: Retrospective Cross-Sectional Study.

BACKGROUND: Technology is rapidly advancing our understanding of how people with diabetes mellitus experience stress. OBJECTIVE: The aim of this study was to explore the relationship between stress and sequelae of diabetes mellitus within a unique data set composed of adults enrolled in a digital diabetes management program, Livongo, in order to inform intervention and product development. METHODS: Participants included 3263 adults under age 65 who were diagnosed with diabetes mellitus and had access to Livongo through their employer between June 2015 and August 2018. Data were collected at time of enrollment and 12 months thereafter, which included demographic information, glycemic control, presence of stress, diabetes distress, diabetes empowerment, behavioral health diagnosis, and utilization of behavioral health-related medication and services. Analysis of variance and chi-square tests compared variables across groups that were based on presence of stress and behavioral health diagnosis or utilization. RESULTS: Fifty-five percent of participants (1808/3263) reported stress at the time of at least 1 blood glucose reading. Fifty-two percent of participants (940/1808) also received at least 1 behavioral health diagnosis or intervention. Compared to their peers, participants with stress reported greater diabetes distress, lower diabetes empowerment, greater insulin use, and poorer glycemic control. Participants with stress and a behavioral health diagnosis/utilization additionally had higher body mass index and duration of illness. CONCLUSIONS: Stress among people with diabetes mellitus is associated with reduced emotional and physical health. Digital products that focus on the whole person by offering both diabetes mellitus self-management tools and behavioral health skills and support can help improve disease-specific and psychosocial outcomes.

Drivers of weight loss in a CDC-recognized digital diabetes prevention program.

INTRODUCTION: To investigate the impact of the digital Livongo Diabetes Prevention Program (DPP) on weight at 12 months, understand participants' self-monitoring behaviors associated with greater weight loss, and evaluate the impact of coaching interactions on more frequent self-monitoring behaviors. RESEARCH DESIGN AND METHODS: A retrospective analysis was performed using data from 2037 participants enrolled in the Livongo DPP who completed lesson 1 and recorded a starting weight during 2016-2017. Self-monitoring behaviors, including weigh-ins, food logging, activity, and coach-participant interactions, were analyzed at 6 and 12 months. Subgroup analysis was conducted based on those who were highly engaged versus those minimally engaged. Multiple regression analysis was performed using demographic, self-monitoring, and lesson attendance data to determine predictors of weight loss at 12 months and coaching impact on self-monitoring. RESULTS: Participants had a mean age of 50 years (SD ±12), with a starting weight of 94 kg (SD ±21), were college-educated (78%), and were female (74%). Overall, participants lost on average 5.1% of their starting weight. Highly engaged participants lost 6.6% of starting body weight, with 25% losing ≥10% at 12 months. Logistic regression analysis showed each submitted food log was associated with 0.23 kg (p<0.05) weight loss, each lesson completed was associated with 0.14 kg (p<0.05) weight loss, and a week of 150 active minutes was associated with 0.1 kg (p<0.01) weight loss. One additional coach-participant message each week was associated with 1.4 more food logs per week, 1.6% increase in weeks with four or more weigh-ins, and a 2.7% increase in weeks with 150 min of activity. CONCLUSIONS: Food logging had the largest impact on weight loss, followed by lesson engagement and physical activity. Future studies should examine further opportunities to deliver nutrition-based content to increase and sustain weight loss for DPP.

Characterizing rehabilitation services for patients with knee and hip replacement in skilled nursing facilities and inpatient rehabilitation facilities.

OBJECTIVE: To characterize rehabilitation services for patients with knee and hip replacement in 3 types of postacute facilities in the U.S. DESIGN: Multi-site prospective observational cohort study. SETTING: Eight freestanding skilled nursing facilities (SNFs), 1 hospital-based SNF, and 11 inpatient rehabilitation facilities (IRFs). PARTICIPANTS: Patients (N=2158) with knee or hip replacement. INTERVENTIONS: No new interventions. MAIN OUTCOME MEASURES: Length of stay (LOS), amount and intensity of physical therapy (PT) and occupational therapy (OT), types of therapy activities. RESULTS: Average LOS was about 15 days for freestanding SNF patients, and 9 to 10 days for hospital-based SNF and IRF patients. Freestanding SNFs and IRFs provide about the same number of hours of PT and OT; the hospital-based SNF provided 27% fewer hours. Freestanding SNFs and the hospital-based SNF provided fewer hours a day than did IRFs. Joint replacement patients across all 3 types of facilities spent, on average, 70% to 75% of their PT time in just 2 activities--exercise and gait and spent 56% to 66% of their OT time in 3 activities--exercise, functional mobility, and dressing lower body. CONCLUSIONS: Both freestanding SNFs and IRFs provided similar amounts of PT with a similar emphasis on exercise and gait activities. IRFs, however, provided more OT than freestanding SNFs. IRFs had shorter LOSs and more intensive therapy services than freestanding SNFs. Study freestanding SNFs exhibited greater variation in LOS and intensity of therapy than IRFs.

Clostridial collagenase ointment and medicinal honey utilization for pressure ulcers in US hospitals.

AIMS: To describe the utilization of clostridial collagenase ointment (CCO) and medicinal honey debridement methods in real-world inpatient and outpatient hospital settings among pressure ulcer (PU) patients and compare the frequency of healthcare re-encounters between CCO- and medicinal honey-treated patients. MATERIALS AND METHODS: De-identified hospital discharge records for patients receiving CCO or medicinal honey methods of debridement and having an ICD-9 code for PU were extracted from the US Premier Healthcare Database. Multivariable analysis was used to compare the frequency of inpatient and outpatient revisits up to 6 months after an index encounter for CCO- vs medicinal honey-treated PUs. RESULTS: The study identified 48,267 inpatients and 2,599 outpatients with PUs treated with CCO or medicinal honeys. Among study inpatients, n = 44,725 (93%) were treated with CCO, and n = 3,542 (7%) with medicinal honeys. CCO and medicinal honeys accounted for 1,826 (70%) and 773 (30%), respectively, of study outpatients. In adjusted models, those treated with CCO had lower odds for inpatient readmissions (OR = 0.86, 95% CI = 0.80-0.94) after inpatient index visits, and outpatient re-encounters both after inpatient (OR = 0.73, 95% CI = 0.67-0.79) and outpatient (OR = 0.78, 95% CI = 0.64-0.95) index visits in 6 months of follow-up. LIMITATIONS: The study was observational in nature, and did not adjust for reasons why patients were hospitalized initially, or why they returned to the facility. Although the study adjusted for differences in a variety of demographic, clinical, and hospital characteristics between the treatments, we are not able to rule out selection bias. CONCLUSION: Patients with CCO-treated PUs returned to inpatient and outpatient hospital settings less often compared with medicinal honey-treated PUs. These results from real-world administrative data help to gain a better understanding of the clinical characteristics of patients with PUs treated with these two debridement methods and the economic implications of debridement choice in the acute care setting.

Occupational therapy activities and intervention techniques for clients with stroke in six rehabilitation hospitals.

OBJECTIVE: To prospectively monitor occupational therapy activities and intervention techniques used during inpatient stroke rehabilitation in order to provide a description of current clinical practice. METHODS: Data were collected prospectively from 954 clients with stroke receiving occupational therapy from six U.S. rehabilitation hospitals. Descriptive statistics summarized frequency, intensity, and duration of occupational therapy sessions; proportion of time spent in 16 therapeutic activities; and proportion of those activities that included any of 31 interventions. RESULTS: Clients received on average 11.8 days (SD = 7.2) of occupational therapy, with each session lasting on average 39.4 min (SD = 16.9). Upper-extremity control (22.9% of treatment time) and dressing (14.2% of treatment time) were the most frequently provided activities. Interventions provided most frequently during upper-extremity control activities were strengthening, motor learning, and postural awareness. CONCLUSION: Occupational therapy provided reflected an integration of treatment approaches. Upper-extremity control and basic activities of daily living were the most frequent activities. A small proportion of sessions addressed community integration.

K-ras proto-oncogene exhibits tumor suppressor activity as its absence promotes tumorigenesis in murine teratomas.

Ras proteins transduce signals from membrane-bound receptors via multiple downstream effector pathways and thereby affect fundamental cellular processes, including proliferation, apoptosis, and differentiation. K-ras activating mutations play a key role in neoplastic progression and are particularly prevalent in colorectal, pancreatic, and lung cancers. The present study addressed whether the K-ras proto-oncogene displays a tumor suppressor function by comparative analysis of mouse teratomas derived from wild-type embryonic stem (ES) cells, K-ras null (K-ras(-/-)) ES cells, and K-ras(-/-) ES cells that stably reexpress either wild-type K-ras(gly12) or oncogenic K-ras(val12). K-ras(-/-) and K-ras(val12) teratomas were significantly larger than teratomas that expressed wild-type K-ras, contained significantly higher proportions of undifferentiated embryonal carcinoma-like cells, and showed significantly increased mitotic activity. However, K-ras(val12) but not K-ras(-/-) teratomas exhibited significantly higher levels of apoptosis than wild-type teratomas. K-ras(-/-) and K-ras(val12) ES cells showed a higher capacity for stem cell self-renewal in vitro compared with wild-type ES cells, and reexpression of K-ras(gly12) in K-ras(-/-) ES cells restored the K-ras(-/-) phenotype to wild-type values. Thus, in view of evidence that tumors can derive from tissue stem cells and that tumors harbor "cancer stem cells," aberrant K-ras expression could promote neoplastic progression by increasing their capacity for self-renewal.

Developing a checklist for guideline implementation planning: review and synthesis of guideline development and implementation advice.

BACKGROUND: Developers, users and others have requested or advocated for guidance on how to plan for, and implement guidelines concurrent to their development given that existing resources are lacking such information. The purpose of this research was to develop a guideline implementation planning checklist. METHODS: Documents that described or evaluated the processes of planning or undertaking implementation were identified in several publications that had systematically identified such resources, and by searching medical literature databases (MEDLINE, EMBASE). Data that described implementation planning; how to develop guideline versions or tools that would support user implementation; and options and mechanisms for disseminating or implementing guidelines were independently extracted from eligible documents by the principal investigator and a trained research assistant. Data were integrated to create a unique list of guideline implementation planning processes and considerations. RESULTS: Thirty-five documents were eligible. Of these, 16 (45.7%) provided sparse information on implementation planning, 25 (71.4%) mentioned different versions or tools for implementation, and 30 (85.7%) listed options for dissemination or implementation. None provided instructions for operationalizing implementation strategies. Data were integrated into a multi-item Guideline Implementation Planning Checklist including considerations for implementation planning (12), development of implementation tools (8), types of implementation tools (12), and options for dissemination (11) and implementation (12). CONCLUSIONS: Developers or users can apply the Guideline Implementation Planning Checklist to prepare for and/or undertake guideline implementation. Further development of the checklist is warranted to elaborate on all components. In ongoing research, we will consult with the international guideline community to do so. At the same time, guideline implementation is complex, so developers and users would benefit from training, and by including knowledge translation experts and brokers on implementation planning committees.

Towards a framework for evaluating and grading evidence in public health.

The Project on a Framework for Rating Evidence in Public Health (PRECEPT) is an international collaboration of public health institutes and universities which has been funded by the European Centre for Disease Prevention and Control (ECDC) since 2012. Main objective is to define a framework for evaluating and grading evidence in the field of public health, with particular focus on infectious disease prevention and control. As part of the peer review process, an international expert meeting was held on 13-14 June 2013 in Berlin. Participants were members of the PRECEPT team and selected experts from national public health institutes, World Health Organization (WHO), and academic institutions. The aim of the meeting was to discuss the draft framework and its application to two examples from infectious disease prevention and control. This article introduces the draft PRECEPT framework and reports on the meeting, its structure, most relevant discussions and major conclusions.

Functional Smoothened is required for expression of GLI3 in colorectal carcinoma cells.

We investigated a role for Hedgehog signalling in colon cancer by studying transcription of members of the pathway in human colorectal carcinoma cell lines. We determined the methylation status and screened the gene encoding the Hedgehog receptor-associated protein Smoothened (SMO) for putative mutations. In three cell lines lacking SMO expression the SMO promoter was fully methylated and the transcription factor GLI3 was not expressed. Two additional cell lines both having one methylated SMO allele and expressing mutant SMO did not express GLI3. Our results suggest that expression of wild-type SMO is required for expression of GLI3 by a mechanism that is independent of conventional Hedgehog signalling.

Comparison of the Effects of Different Negative Pressure Wound Therapy Modes-Continuous, Noncontinuous, and With Instillation-on Porcine Excisional Wounds.

OBJECTIVE: Negative pressure wound therapy (NPWT) can be delivered in continuous or noncontinuous modes, while NPWT with instillation (NPWTi) couples NPWT with automated delivery and removal of topical wound treatment solutions and suspensions. This porcine study compared granulation response of NPWTi (instillation foam dressing with saline) to NPWT (standard foam dressing) in continuous and noncontinuous modes. METHODS: Full-thickness dorsal excisional wounds in pigs were treated with continuous NPWT, intermittent NPWT, dynamic (controlled variable) NPWT, and NPWTi with saline (n = 10 per group). Wound dimensions were determined from 3D images collected on days 0, 2, 5, and 7. On day 7, animals were euthanized and specimens were harvested for histopathological review. RESULTS: Average granulation thickness was not statistically different among continuous (3.29 ± 0.33 mm), intermittent (3.03 ± 0.47 mm), and dynamic (3.40 ± 0.34 mm) NPWT wounds at day 7. Average granulation thickness of NPWTi wounds (4.75 ± 0.54 mm), however, was statistically greater (P < .05) by 44%, 57%, and 40%, respectively, than that of wounds treated with continuous, intermittent, and dynamic NPWT. Analysis of 3D images revealed a greater reduction in wound area and perimeter in NPWTi wounds compared to all NPWT wounds (P < .05). In addition, the average wound fill rate for NPWTi wounds was faster than that for continuous (40%; P < .05), intermittent (25%; P > .05), and dynamic (65%; P < .05) NPWT wounds. CONCLUSIONS: Although not confirmed in humans, these porcine data suggest that NPWTi with saline may stimulate a faster rate of wound granulation than NPWT in continuous and noncontinuous modes.