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  • The Greatest Gift: How a Patient’s Death Taught Me to Be a Physician

    Abstract Full Text
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    JAMA. 2017; 318(18):1761-1762. doi: 10.1001/jama.2017.15158
  • JAMA June 21, 2016

    Figure 3: Benefits, Harms, and Burden of Colorectal Screening Strategies Over a Lifetime

    Outcomes are from Cancer Intervention and Surveillance Modeling Network (CISNET) models, which include the Simulation Model of Colorectal Cancer (SimCRC), the Microsimulation Screening Analysis (MISCAN) for Colorectal Cancer, and the Colorectal Cancer Simulated Population model for Incidence and Natural History (CRC-SPIN). Screening occurs between the ages of 50 and 75 years, with follow-up continuing throughout an individual’s remaining life span. FIT indicates fecal immunochemical test; FIT-DNA, multitargeted stool DNA test; HSgFOBT, high-sensitivity guaiac-based fecal occult blood test. aThese strategies yield comparable life-years gained (ie, the life-years gained with the noncolonoscopy strategies were within 90% of those gained with the colonoscopy strategy) and an efficient balance of benefits and harms (ie, no other strategy or combination of strategies within the class of screening tests provides more life-years with the same [or fewer] number of colonoscopies, which represents the primary source of harms from screening).bComputed tomographic (CT) colonography can also be considered efficient, but if cathartic bowel preparation is considered to be a proxy measure for the burden of screening (instead of number of lifetime colonoscopies), its efficiency ratio (ie, the incremental number of colonoscopies required to achieve an additional year of life gained [∆COL/∆LYG]) exceeds that of colonoscopy.cGastrointestinal events include perforations, bleeding, transfusions, paralytic ileus, nausea and vomiting, dehydration, and abdominal pain. Cardiovascular events include myocardial infarction, angina, arrhythmia, congestive heart failure, cardiac or respiratory arrest, syncope, hypotension, and shock.
  • Sodium Excretion and the Risk of Cardiovascular Disease in Patients With Chronic Kidney Disease

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    JAMA. 2016; 315(20):2200-2210. doi: 10.1001/jama.2016.4447

    This cohort study investigates the association between urinary sodium excretion and heart failure, myocardial infarction, and stroke in patients with chronic kidney disease.

  • Gene Transfer Improves Heart Function in Patients With Heart Failure

    Abstract Full Text
    JAMA. 2016; 315(20):2159-2159. doi: 10.1001/jama.2016.5372
  • JAMA April 26, 2016

    Figure 2: Elements of Clinical Prediction Score and Distribution of Score Among Randomized DAPT Study Patients (Derivation Cohort, 11 648 Patients)

    CHF indicates congestive heart failure; LVEF, left ventricular ejection fraction; MI, myocardial infarction; PCI, percutaneous coronary intervention. Variables reflect characteristics at the time of the index procedure. Cigarette smoking was defined as smoking within 1 year prior to index procedure.
  • JAMA January 26, 2016

    Figure: Flow of Participants From a Longitudinal Cohort and a Community-Based Cohort in a Trial of Nicotine Patch vs Varenicline vs C-NRT for Smoking Cessation

    C-NRT indicates combination nicotine replacement therapy. Cohort 1 comprises participants recruited from an ongoing longitudinal study of smokers, the Wisconsin Smokers Health Study, while cohort 2 participants were recruited for this study from the community via media and community outreach.aExclusion due to diagnosis of or treatment for schizophrenia, a psychotic disorder, or bipolar disorder in the last 10 years.bExclusion due to hospitalization for stroke, myocardial infarction, congestive heart failure, or diabetes in the last year.cExclusion reasons: carotid stenosis (60% visual or peak systolic velocity 130 cm/s), n = 50; cardiac ischemia, n = 16; cardiac arrhythmia, n = 15; long QT interval, n = 12; other, n = 31.dData on withdrawals were collected through 52 weeks.
  • JAMA April 14, 2015

    Figure 1: Cohort Creation

    IQR indicates interquartile range.aCHADS2 score components include congestive heart failure (1 point), hypertension (1 point), age 75 years or older (1 point), diabetes mellitus (1 point), prior stroke (2 points), CHA2DS2VASc score components include congestive heart failure (1 point), hypertension (1 point), age 75 years or older (2 points), diabetes mellitus (1 point), prior stroke (2 points), vascular disease (1 point), age 65 to 74 years (1 point), female sex (1 point).bHigh-performing sites were defined as having achieved an adherence rate at or above the median proportion of adherence in this cohort (74%); low-performing sites were defined as an adherence rate of less than the median proportion the adherence in this cohort.
  • JAMA April 14, 2015

    Figure 3: Forest Plot Showing Association Between Various Monitoring Strategies and Patient Adherence to Dabigatran

    Adherence to dabigatran was defined as the proportion of days covered as being at least 80%. The dotted line represents no effect. All observations to the right of the vertical line signify a positive association with dabigatran adherence. The error bars represent 95% CIs. Variables included in the model were age, sex, race (white), congestive heart failure, hypertension, diabetes, stroke or transient ischemic attack, chronic kidney disease, bleeding, myocardial infarction, liver disease, depression, alcohol, drug abuse, region, patients per hospital, median income in hospital’s county, proportion of urban to rural patients at hospital, education, selection, and follow-up.
  • JAMA March 10, 2015

    Figure: Total and Potentially Preventable 90-Day Readmissions Among Survivors of Severe Sepsis and Matched Hospitalizations for Acute Medical Conditions

    Potentially preventable readmission diagnoses include pneumonia, hypertension, dehydration, asthma, urinary tract infection, chronic obstructive pulmonary disease exacerbation, perforated appendix, diabetes, angina, congestive heart failure, sepsis, acute renal failure, skin or soft tissue infection, and aspiration pneumonitis. The shaded areas indicate 95% confidence intervals.
  • Association Between Physician Time-Unlimited vs Time-Limited Internal Medicine Board Certification and Ambulatory Patient Care Quality

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    JAMA. 2014; 312(22):2358-2363. doi: 10.1001/jama.2014.13992

    This retrospective analysis reports that there were no significant differences between physicians with time-limited vs time-unlimited board certification on 10 primary care performance measures.

  • JAMA December 3, 2014

    Figure: Example of Relationship of Risk Factors With Lifetime Benefit of Colorectal Cancer Screening With Colonoscopy

    CRC indicates colorectal cancer; RR, relative risk.aIndividuals are classified as having moderate comorbidity if diagnosed with an ulcer, rheumatologic disease, peripheral vascular disease, diabetes, paralysis, or cerebrovascular disease and in case of a history of acute myocardial infarction; as having severe comorbidity if diagnosed with chronic obstructive pulmonary disease, congestive heart failure, moderate or severe liver disease, chronic renal failure, dementia, cirrhosis and chronic hepatitis, or AIDS; and as having no comorbidity if none of these conditions is present.bThe range of the background risk for CRC is based on the National Cancer Institute’s Colorectal Cancer Risk Assessment Tool. In white women, the minimum background risk for CRC is 0.5, the maximum background risk in the absence of a family history of CRC is 1.8, and the maximum risk in the presence of a family history of CRC is 3.5.
  • Recognizing Worsening Chronic Heart Failure as an Entity and an End Point in Clinical Trials

    Abstract Full Text
    JAMA. 2014; 312(8):789-790. doi: 10.1001/jama.2014.6643
  • JAMA March 12, 2014

    Figure: Odds of Dying at Home With Home Palliative Care Compared With Usual Care

    Source: Data have been adapted with permission from Wiley. Odds ratio calculated using the Mantel-Haenszel random-effect method. The size of the data markers is proportional to the weight assigned in the meta-analysis. Data from Jordhøy were adjusted using the 0.02 estimate of intracorrelation coefficient; this reduced the sample size in meta-analysis both for number of events (ie, death at home) and total in each of the groups. The association with death at home was evaluated in 1222 patients included in 7 of 20 trials (those with data on home death). Diagnoses: Ahlner-Elmqvist, Bakitas, Axelsson, and Jordhøy: all cancer patients; Brumley: cancer (n = 138), congestive heart failure (n = 97), chronic obstructive pulmonary disease (n = 62); Grande: cancer (n = 198), noncancer (n = 31); Zimmer: those classified as terminal were “largely cancer” patients.
  • JAMA February 26, 2014

    Figure 2: Distribution of Hospital Risk-Standardized Rates of Transfusion

    Variations in frequency of receipt of transfusion by hospital (N=1431) after adjustment for patient risk factors such as age, sex, body mass index, acute coronary syndromes presentation, percutaneous coronary intervention (PCI) status, cardiogenic shock, New York Heart Association class IV congestive heart failure (CHF), history of CHF, peripheral vascular disease, chronic lung disease, diabetes, dialysis, previous PCI, coronary lesion ≥50%, and glomerular filtration rate.
  • JAMA February 5, 2014

    Figure 3: Relationship of Atrial Fibrillation Recurrence With Percent Fibrosis

    Adjusted for age, sex, hypertension, congestive heart failure, mitral valve disease, diabetes, atrial fibrillation type (paroxysmal or persistent), left atrial volume, left ventricular ejection fraction, and participating center (model 5) based on a cubic spline analysis with follow-up censored at day 325 after the blanking period. The strength of the association was greater at lower levels of fibrosis than at higher levels (P = .03 for test of nonlinearity). Blue dashed lines indicate 95% CI.
  • From JAMA ’s Daily News Site

    Abstract Full Text
    JAMA. 2013; 309(20):2086-2086. doi: 10.1001/jama.2013.6020
  • Mortality Rates for Medicare Beneficiaries Admitted to Critical Access and Non–Critical Access Hospitals, 2002-2010

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    JAMA. 2013; 309(13):1379-1387. doi: 10.1001/jama.2013.2366
    To evaluate trends in mortality for patients receiving care at critical access hospitals compared with non–critical access hospitals, Joynt and coauthors conducted a retrospective observational study using data from Medicare beneficiaries admitted to acute care hospitals between 2002 and 2010. Ioannidis provides comment in the related Editorial.
  • Reengineering US Health Care

    Abstract Full Text
    JAMA. 2013; 309(7):661-662. doi: 10.1001/jama.2012.214571
  • Association of Online Patient Access to Clinicians and Medical Records With Use of Clinical Services

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    JAMA. 2012; 308(19):2012-2019. doi: 10.1001/jama.2012.14126
    Palen and coauthors investigated health care utilization before and after initiation of a patient online access system using a matched analysis based on 44 321 users and 44 321 nonusers of online access. In an Editorial, Bates and Wells discuss the importance of organizations knowing what to expect after the adoption of electronic health portals.