https://caltcm.memberclicks.net/assets/documents/acc_aha_chf_2013_guidelines.pdf

2013 ACCF/AHA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines

XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

Standards of Medical Care in Diabetes

WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Blaha, MD, MPH Stephanie E. Chiuve, ScD Mary Cushman, MD, MSc, FAHA Sandeep R. Das, MD, MPH, FAHA Rajat Deo, MD, MTR Sarah D. de Ferranti, MD, MPH James Floyd, MD, MS Myriam Fornage, PhD, FAHA Cathleen Gillespie, MS Carmen R. Isasi, MD, PhD, FAHA Monik C. Jiménez, ScD, SM Lori Chaffin Jordan, MD, PhD Suzanne E. Judd, PhD Daniel Lackland, DrPH, FAHA Judith H. Lichtman, PhD, MPH, FAHA Lynda Lisabeth, PhD, MPH, FAHA Simin Liu, MD, ScD, FAHA Chris T. Longenecker, MD Rachel H. Mackey, PhD, MPH, FAHA Kunihiro Matsushita, MD, PhD, FAHA Dariush Mozaffarian, MD, DrPH, FAHA Michael E. Mussolino, PhD, FAHA Khurram Nasir, MD, MPH, FAHA Robert W. Neumar, MD, PhD, FAHA Latha Palaniappan, MD, MS, FAHA Dilip K. Pandey, MBBS, MS, PhD, FAHA Ravi R. Thiagarajan, MD, MPH Mathew J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Rodriguez, MD, MPH, FAHA Gregory A. Roth, MD, MPH Wayne D. Rosamond, PhD, FAHA Comilla Sasson, MD, PhD, FAHA Amytis Towfighi, MD Connie W. Tsao, MD, MPH Melanie B. Turner, MPH Salim S. Virani, MD, PhD, FAHA Jenifer H. Voeks, PhD Joshua Z. Willey, MD, MS John T. Wilkins, MD Jason HY. Wu, MSc, PhD, FAHA Heather M. Alger, PhD Sally S. Wong, PhD, RD, CDN, FAHA Paul Muntner, PhD, MHSc On behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee Heart Disease and Stroke Statistics—2017 Update

Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association

Author(s): Writing Group Members; Mozaffarian, Dariush; Benjamin, Emelia J; Go, Alan S; Arnett, Donna K; Blaha, Michael J; Cushman, Mary; Das, Sandeep R; de Ferranti, Sarah; Despres, Jean-Pierre; Fullerton, Heather J; Howard, Virginia J; Huffman, Mark D; Isasi, Carmen R; Jimenez, Monik C; Judd, Suzanne E; Kissela, Brett M; Lichtman, Judith H; Lisabeth, Lynda D; Liu, Simin; Mackey, Rachel H; Magid, David J; McGuire, Darren K; Mohler, Emile R; Moy, Claudia S; Muntner, Paul; Mussolino, Michael E; Nasir, Khurram; Neumar, Robert W; Nichol, Graham; Palaniappan, Latha; Pandey, Dilip K; Reeves, Mathew J; Rodriguez, Carlos J; Rosamond, Wayne; Sorlie, Paul D; Stein, Joel; Towfighi, Amytis; Turan, Tanya N; Virani, Salim S; Woo, Daniel; Yeh, Robert W; Turner, Melanie B; American Heart Association Statistics Committee; Stroke Statistics Subcommittee

Heart Disease and Stroke Statistics—2016 Update: A Report From the American Heart Association

March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Benjamin, MD, ScM, FAHA, Chair Paul Muntner, PhD, MHS, FAHA, Vice Chair Alvaro Alonso, MD, PhD, FAHA Marcio S. Bittencourt, MD, PhD, MPH Clifton W. Callaway, MD, FAHA April P. Carson, PhD, MSPH, FAHA Alanna M. Chamberlain, PhD Alexander R. Chang, MD, MS Susan Cheng, MD, MMSc, MPH, FAHA Sandeep R. Das, MD, MPH, MBA, FAHA Francesca N. Delling, MD, MPH Luc Djousse, MD, ScD, MPH Mitchell S.V. Elkind, MD, MS, FAHA Jane F. Ferguson, PhD, FAHA Myriam Fornage, PhD, FAHA Lori Chaffin Jordan, MD, PhD, FAHA Sadiya S. Khan, MD, MSc Brett M. Kissela, MD, MS Kristen L. Knutson, PhD Tak W. Kwan, MD, FAHA Daniel T. Lackland, DrPH, FAHA Tené T. Lewis, PhD Judith H. Lichtman, PhD, MPH, FAHA Chris T. Longenecker, MD Matthew Shane Loop, PhD Pamela L. Lutsey, PhD, MPH, FAHA Seth S. Martin, MD, MHS, FAHA Kunihiro Matsushita, MD, PhD, FAHA Andrew E. Moran, MD, MPH, FAHA Michael E. Mussolino, PhD, FAHA Martin O’Flaherty, MD, MSc, PhD Ambarish Pandey, MD, MSCS Amanda M. Perak, MD, MS Wayne D. Rosamond, PhD, MS, FAHA Gregory A. Roth, MD, MPH, FAHA Uchechukwu K.A. Sampson, MD, MBA, MPH, FAHA Gary M. Satou, MD, FAHA Emily B. Schroeder, MD, PhD, FAHA Svati H. Shah, MD, MHS, FAHA Nicole L. Spartano, PhD Andrew Stokes, PhD David L. Tirschwell, MD, MS, MSc, FAHA Connie W. Tsao, MD, MPH, Vice Chair Elect Mintu P. Turakhia, MD, MAS, FAHA Lisa B. VanWagner, MD, MSc, FAST John T. Wilkins, MD, MS, FAHA Sally S. Wong, PhD, RD, CDN, FAHA Salim S. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee

Heart Disease and Stroke Statistics—2019 Update: A Report From the American Heart Association

We performed a systematic search of publications using MEDLINE (1966-2009), EMBASE (from 1980), the Cochrane Library, and manual searches without language restrictions. Studies were included if they were prospective, follow-up .3 years, had duration of sleep at baseline, and incident cases of CHD, stroke, or CVD. Relative risks (RR) and 95% confidence interval (CI) were pooled using a random-effect model. Overall, 15 studies (24 cohort samples) included 474 684 male and female participants (follow-up 6.9-25 years), and 16 067 events (4169 for CHD, 3478 for stroke, and 8420 for total CVD). Sleep duration was assessed by questionnaire and incident cases through certifica- tion and event registers. Short duration of sleep was associated with a greater risk of developing or dying of CHD (RR 1.48, 95% CI 1.22-1.80, P , 0.0001), stroke (1.15, 1.00-1.31, P ¼ 0.047), but not total CVD (1.03, 0.93-1.15, P ¼ 0.52) with no evidence of publication bias (P ¼ 0.95, P ¼ 0.30, and P ¼ 0.46, respectively). Long duration of sleep was also associated with a greater risk of CHD (1.38, 1.15-1.66, P ¼ 0.0005), stroke (1.65, 1.45-1.87, P , 0.0001), and total CVD (1.41, 1.19-1.68, P , 0.0001) with no evidence of publication bias (P ¼ 0.92, P ¼ 0.96, and P ¼ 0.79, respectively).

/pdf/sleep-duration-predicts-cardiovascular-outcomes-a-systematic-qhwdsamqru.pdf

Sleep duration predicts cardiovascular outcomes: a systematic review and meta-analysis of prospective studies

Background: Increasing evidence suggests an association between both short and long duration of habitual sleep with adverse health outcomes.
 
Objectives: To assess whether the population longitudinal evidence supports the presence of a relationship between duration of sleep and all-cause mortality, to investigate both short and long sleep duration and to obtain an estimate of the risk.
 
Methods: We performed a systematic search of publications using MEDLINE (1966-2009), EMBASE (from 1980), the Cochrane Library, and manual searches without language restrictions. We included studies if they were prospective, had follow-up >3 years, had duration of sleep at baseline, and all-cause mortality prospectively. We extracted relative risks (RR) and 95% confidence intervals (CI) and pooled them using a random effect model. We carried out sensitivity analyses and assessed heterogeneity and publication bias.
 
Results: Overall, the 16 studies analyzed provided 27 independent cohort samples. They included 1,382,999 male and female participants (follow-up range 4 to 25 years), and 112,566 deaths. Sleep duration was assessed by questionnaire and outcome through death certification. In the pooled analysis, short duration of sleep was associated with a greater risk of death (RR: 1.12; 95% CI 1.06 to 1.18; P <0.01) with no evidence of publication bias (P = 0.74) but heterogeneity between studies (P = 0.02). Long duration of sleep was also associated with a greater risk of death (1.30; [1.22 to 1.38]; P < 0.0001) with no evidence of publication bias (P = 0.18) but significant heterogeneity between studies (P < 0.0001).
 
Conclusion: Both short and long duration of sleep are significant predictors of death in prospective population studies.

/pdf/sleep-duration-and-all-cause-mortality-a-systematic-review-3n9cfnbxft.pdf

Sleep Duration and All-Cause Mortality: A Systematic Review and Meta-Analysis of Prospective Studies

OBJECTIVE - To assess the relationship between habitual sleep disturbances and the incidence of type 2 diabetes and to obtain an estimate of the risk.
 
RESEARCH DESIGN AND METHODS - We conducted a systematic search of publications using MEDLINE (1955-April 2009), EMBASE, and the Cochrane Library and manual searches Without language restrictions. We included studies if they were prospective with follow-up >3 years and had an assessment of sleep disturbances at baseline and incidence of type 2 diabetes. We recorded several characteristics for each study. We extracted quantity and quality of sleep, how they were assessed, and incident cases defined with different validated methods. We extracted relative risks (RRs) and 95% Cl and pooled them using random-effects models. We performed sensitivity analysis and assessed heterogeneity and publication bias.
 
RESULTS - we included 10 Studies (13 independent cohort Samples; 107,756 male and female participants, follow-up range 4.2-32 years, and 3,586 incident cases Of type 2 diabetes). In pooled analyses, quantity and quality of sleep predicted the risk of development Of type 2 diabetes. For short duration of sleep (: 8-9 h/night), the RR was 1.48 (1.13-1.96, P = 0.005); for difficulty in initiating sleep, the RR was 1.57 (1.25-1.97, P < 0.0001); and for difficulty in maintaining sleep, the RR was 1.84 (1.39-2.43, P < 0.0001).
 
CONCLUSIONS - Quantity and quality of sleep consistently and significantly predict the risk Of the development Of type 2 diabetes. The mechanisms Underlying this relation may differ between short and long sleepers.

/pdf/quantity-and-quality-of-sleep-and-incidence-of-type-2-3arwq3xnbk.pdf

Quantity and Quality of Sleep and Incidence of Type 2 Diabetes A systematic review and meta-analysis

Objective To assess the relation between the level of habitual salt intake and stroke or total cardiovascular disease outcome. Design Systematic review and meta-analysis of prospective studies published 1966-2008. Data sources Medline (1966-2008), Embase (from 1988), AMED (from 1985), CINAHL (from 1982), Psychinfo (from 1985), and the Cochrane Library. Review methods For each study, relative risks and 95% confidence intervals were extracted and pooled with a random effect model, weighting for the inverse of the variance. Heterogeneity, publication bias, subgroup, and meta-regression analyses were performed. Criteria for inclusion were prospective adult population study, assessment of salt intake as baseline exposure, assessment of either stroke or total cardiovascular disease as outcome, follow-up of at least three years, indication of number of participants exposed and number of events across different salt intake categories. Results There were 19 independent cohort samples from 13 studies, with 177 025 participants (follow-up 3.5-19 years) and over 11 000 vascular events. Higher salt intake was associated with greater risk of stroke (pooled relative risk 1.23, 95% confidence interval 1.06 to 1.43; P=0.007) and cardiovascular disease (1.14, 0.99 to 1.32; P=0.07), with no significant evidence of publication bias. For cardiovascular disease, sensitivity analysis showed that the exclusion of a single study led to a pooled estimate of 1.17 (1.02 to 1.34; P=0.02). The associations observed were greater the larger the difference in sodium intake and the longer the follow-up. Conclusions High salt intake is associated with significantly increased risk of stroke and total cardiovascular disease. Because of imprecision in measurement of salt intake, these effect sizes are likely to be underestimated. These results support the role of a substantial population reduction in salt intake for the prevention of cardiovascular disease.

https://www.bmj.com/content/bmj/339/bmj.b4567.full.pdf

Potassium intake, stroke, and cardiovascular disease: a meta-analysis of prospective studies

Background and Purpose— A systematic review of the prospective studies addressing the relationship of overweight and obesity to major stroke subtypes is lacking. We evaluated the occurrence of a graded association between overweight, obesity, and incidence of ischemic and hemorrhagic stroke by a meta-analysis of cohort studies. Methods— A search of online databases and relevant reviews was performed. Inclusion criteria were original article in English, prospective study design, follow-up ≥4 years, indication of number of subjects exposed, and number of events across body mass index categories. Crude unadjusted relative risk (RR) and 95% CI were calculated for each study for overweight or obese compared with normal-weight categories. Log-transformed values and SE were used to calculate the pooled RR with random effects models; publication bias was checked. Additional analyses were performed using the multivariate estimates of risk reported in the individual studies. Results— Twenty-five studies were includ...

Lanfranco D'Elia

Papers

Sleep duration predicts cardiovascular outcomes: a systematic review and meta-analysis of prospective studies

Sleep Duration and All-Cause Mortality: A Systematic Review and Meta-Analysis of Prospective Studies

Quantity and Quality of Sleep and Incidence of Type 2 Diabetes A systematic review and meta-analysis

Potassium intake, stroke, and cardiovascular disease: a meta-analysis of prospective studies

Excess Body Weight and Incidence of Stroke Meta-Analysis of Prospective Studies With 2 Million Participants