Systematic Review and Individual Patient Data Meta-Analysis of Sex Differences in Depression and Prognosis in Persons With Myocardial Infarction: A MINDMAPS Study.

OBJECTIVE: Using combined individual patient data from prospective studies, we explored sex differences in depression and prognosis post-myocardial infarction (MI) and determined whether disease indices could account for found differences. METHODS: Individual patient data analysis of 10,175 MI patients who completed diagnostic interviews or depression questionnaires from 16 prospective studies from the MINDMAPS study was conducted. Multilevel logistic and Cox regression models were used to determine sex differences in prevalence of depression and sex-specific effects of depression on subsequent outcomes. RESULTS: Combined interview and questionnaire data from observational studies showed that 36% (635/1760) of women and 29% (1575/5526) of men reported elevated levels of depression (age-adjusted odds ratio = 0.68, 95% confidence interval [CI] = 0.60-0.77). The risk for all-cause mortality associated with depression was higher in men (hazard ratio = 1.38, 95% CI = 1.30-1.47) than in women (hazard ratio = 1.22, 95% CI = 1.14-1.31; sex by depression interaction: p < .001). Low left ventricular ejection fraction (LVEF) was associated with higher depression scores in men only (sex by LVEF interaction: B = 0.294, 95% CI = 0.090-0.498), which attenuated the sex difference in the association between depression and prognosis. CONCLUSIONS: The prevalence of depression post-MI was higher in women than in men, but the association between depression and cardiac prognosis was worse for men. LVEF was associated with depression in men only and accounted for the increased risk of all-cause mortality in depressed men versus women, suggesting that depression in men post-MI may, in part, reflect cardiovascular disease severity.

A finger photoplethysmography waveform during the valsalva maneuver detects changes in left heart filling pressure after hemodialysis.

BACKGROUND: A noninvasive system for determining left ventricular (LV) filling pressure may help to improve personalized fluid removal goals in hemodialysis patients. We previously showed that the change in photoplethysmography (PPG) pulse amplitude measured by finger PPG during a Valsalva maneuver correlates with invasively measured left ventricular end-diastolic pressure (LVEDP). This key PPG change, the ratio of finger PPG pulse amplitude at end-Valsalva to baseline, is known as the Pulse Amplitude Ratio, PAR. The objective of this study was to determine how PAR changes after fluid removal in hemodialysis. METHODS: We tested subjects with end-stage renal disease, before and after hemodialysis. Each subject performed a Valsalva maneuver with an effort of 20 mmHg for 10 s, guided by the device display. Finger PPG was recorded continuously before and during the maneuver. PAR was calculated automatically. RESULTS: Twenty-seven subjects (21 Males) ages 25-75 years were tested. Access sites were AV-fistulas of the arm predominantly. Weight decreased from 99.7 ± 36.9 kg to 97.0 ± 6.0 kg (p < 0.0003) with an average fluid removal of 3.07 ± 1.08 l. Correspondingly, PAR decreased from 0.74 ± 0.24 to 0.62 ± 0.23 (p = 0.003). The change in PAR was correlated with baseline PAR (r = 0.48, p = 0.01). CONCLUSION: An index of left heart filling pressure obtained noninvasively using finger photoplethysmography during the Valsalva maneuver is sensitive enough to detect reductions in filling pressure after fluid removal with hemodialysis. Further studies are warranted to determine if this method can be used to guide fluid removal during hemodialysis.

Sex dependent risk factors for mortality after myocardial infarction: individual patient data meta-analysis.

BACKGROUND: Although a number of risk factors are known to predict mortality within the first years after myocardial infarction, little is known about interactions between risk factors, whereas these could contribute to accurate differentiation of patients with higher and lower risk for mortality. This study explored the effect of interactions of risk factors on all-cause mortality in patients with myocardial infarction based on individual patient data meta-analysis. METHODS: Prospective data for 10,512 patients hospitalized for myocardial infarction were derived from 16 observational studies (MINDMAPS). Baseline measures included a broad set of risk factors for mortality such as age, sex, heart failure, diabetes, depression, and smoking. All two-way and three-way interactions of these risk factors were included in Lasso regression analyses to predict time-to-event related all-cause mortality. The effect of selected interactions was investigated with multilevel Cox regression models. RESULTS: Lasso regression selected five two-way interactions, of which four included sex. The addition of these interactions to multilevel Cox models suggested differential risk patterns for males and females. Younger women (age<50) had a higher risk for all-cause mortality than men in the same age group (HR 0.7 vs. 0.4), while men had a higher risk than women if they had depression (HR 1.4 vs. 1.1) or a low left ventricular ejection fraction (HR 1.7 vs. 1.3). Predictive accuracy of the Cox model was better for men than for women (area under the curves: 0.770 vs. 0.754). CONCLUSIONS: Interactions of well-known risk factors for all-cause mortality after myocardial infarction suggested important sex differences. This study gives rise to a further exploration of prediction models to improve risk assessment for men and women after myocardial infarction.

Grains of Sand to Clinical Pearls: Realizing the Potential of Wearable Data.

Despite the rapid growth of wearables as a consumer technology sector and a growing evidence base supporting their use, they have been slow to be adopted by the health system into clinical care. As regulatory, reimbursement, and technical barriers recede, a persistent challenge remains how to make wearable data actionable for clinicians-transforming disconnected grains of wearable data into meaningful clinical "pearls". In order to bridge this adoption gap, wearable data must become visible, interpretable, and actionable for the clinician. We showcase emerging trends and best practices that illustrate these 3 pillars, and offer some recommendations on how the ecosystem can move forward.

Data Science as a Core Competency in Undergraduate Medical Education in the Age of Artificial Intelligence in Health Care.

The increasingly sophisticated and rapidly evolving application of artificial intelligence in medicine is transforming how health care is delivered, highlighting a need for current and future physicians to develop basic competency in the data science that underlies this topic. Medical educators must consider how to incorporate central concepts in data science into their core curricula to train physicians of the future. Similar to how the advent of diagnostic imaging required the physician to understand, interpret, and explain the relevant results to patients, physicians of the future should be able to explain to patients the benefits and limitations of management plans guided by artificial intelligence. We outline major content domains and associated learning outcomes in data science applicable to medical student curricula, suggest ways to incorporate these themes into existing curricula, and note potential implementation barriers and solutions to optimize the integration of this content.

The variable natural history of idiopathic dilated cardiomyopathy.

BACKGROUND: Determining the prognosis of patients with heart failure is essential for patient management and clinical trial conduct. The relative value of traditional prognostic criteria remains unclear and the assessment of long-term prognosis for individual patients is problematic. OBJECTIVES: To determine the ability of clinical, hemodynamic and echocardiographic parameters to predict the long-term prognosis of patients with idiopathic dilated cardiomyopathy. METHODS: We investigated the ability of clinical, hemodynamic and echocardiographic parameters to predict the long-term prognosis of individual patients in a large, representative, contemporary cohort of idiopathic dilated cardiomyopathy (IDCM) patients referred to Johns Hopkins from 1997 to 2004 for evaluation of cardiomyopathy. In all patients a baseline history was taken, and physical examination, laboratory studies, echocardiogram, right heart catheterization and endomyocardial biopsy were performed. RESULTS: In 171 IDCM patients followed for a median 3.5 years, there were 50 long-term event-free survivors (LTS) (median survival 6.4 years) and 34 patients died or underwent ventricular assist device placement or transplantation within 5 years (NLTS; non-long-term survivors) (median time to event 1.83 years. Established risk factors (gender, race, presence of diabetes, serum creatinine, sodium) and the use of accepted heart failure medications (angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, beta blockers) were similar between the two groups. Although LTS had younger age, higher ejection fraction (EF) and lower New York Heart Association (NYHA) class at presentation, the positive predictive value of an EF < 25% was 64% (95% CI 41%-79%) and that of NYHA class > 2 was 53% (95% CI 36-69%). A logistic model incorporating these three variables incorrectly classified 29% of patients. CONCLUSIONS: IDCM exhibits a highly variable natural history and standard clinical predictors have limited ability to classify IDCM patients into broad prognostic categories. These findings suggest that there are important host-environmental factors still unappreciated in the biology of IDCM.

Recent Advances in Systems and Network Medicine: Meeting Report from the First International Conference in Systems and Network Medicine.

The First International Conference in Systems and Network Medicine gathered together 200 global thought leaders, scientists, clinicians, academicians, industry and government experts, medical and graduate students, postdoctoral scholars and policymakers. Held at Georgetown University Conference Center in Washington D.C. on September 11-13, 2019, the event featured a day of pre-conference lectures and hands-on bioinformatic computational workshops followed by two days of deep and diverse scientific talks, panel discussions with eminent thought leaders, and scientific poster presentations. Topics ranged from: Systems and Network Medicine in Clinical Practice; the role of -omics technologies in Health Care; the role of Education and Ethics in Clinical Practice, Systems Thinking, and Rare Diseases; and the role of Artificial Intelligence in Medicine. The conference served as a unique nexus for interdisciplinary discovery and dialogue and fostered formation of new insights and possibilities for health care systems advances.

A randomized controlled trial of online symptom searching to inform patient generated differential diagnoses.

Patient online health searching is now commonplace, however, the accuracy of patient generated differentials for new symptoms and potential for patient anxiety are concerns. We aimed primarily to determine the accuracy of patient generated differentials for new symptoms with and without online searching, and secondarily, to evaluate the impact of searching on anxiety levels. In the waiting room prior to seeing a clinician, 300 patients with new symptoms were randomly assigned 1:1:1 to Google searching with health related features including a symptom search tool vs Google searching with health related features disabled vs no searching. Participants were 18 years or older and presenting to the emergency department of an urban academic medical center with new low-acuity symptoms that were not due to exacerbation of a chronic condition. Search groups received access on a tablet/smartphone to Google searching with or without health related features. Both search groups could access any websites; health related features led the patient to common diagnoses and physician-validated information. The primary outcome was accuracy of the patient generated differential assessed by matching at least two of the top three diagnoses on the clinician's differential. A secondary outcome was anxiety by a visual analogue scale. Patients were a median of 33.1 (IQI 26.2-45.9) years old, 60% women, 63% black, 82% had a high school education or less, and 45.7% reported having performed an online search prior to presentation. Search group patients spent a median of 3.82 (2.53-5.72) minutes searching online. Similar proportions of patients in each group matched at least two of three clinician diagnoses: 27.0% and 28.3% for Google searching with and without health related features vs 23.8% in the no search group. Patients in the search groups had a similar odds of matching ≥2/3 diagnoses as the no search group [OR (95% CI): 1.23 (0.70-2.13), p = 0.47]. Anxiety was unchanged with online searching. In conclusion, brief online searching in the waiting room did not improve accuracy of patient generated differential diagnoses for new symptoms. The absence of an increase in patient anxiety provides reassurance for subsequent work to refine and investigate online symptom search tools.

Effect of depression on late (8 years) mortality after myocardial infarction.

Depression during hospitalization for myocardial infarction (MI) is associated with subsequent mortality, but whether this risk persisted long term is not well studied. This study was performed to determine whether depression during hospitalization for MI, which predicted mortality at 4 months, predicted mortality 8 years later. This was a prospective observational study of 284 hospitalized patients with MI. Major depression and dysthymia were assessed using structured interview for Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition, and depressive symptoms, using the Beck Depression Inventory. Mortality was determined using the Social Security Death Index. Mean age during MI hospitalization was 64.8 years, 43.0% of patients were women, 66.7% had hypertension, and 35.7% had diabetes mellitus. Any depression (major depression, dysthymia, and/or Beck Depression Inventory score > or =10) was present in 76 patients (26.8%). The 8-year mortality rate was 47.9% (136 deaths). Any depression at the time of MI was not associated with mortality at 8 years in unadjusted (hazard ratio 1.25, 95% confidence interval 0.87 to 1.81, p = 0.22) or multivariate models (hazard ratio 0.76, 95% confidence interval 0.47 to 1.24, p = 0.27). In conclusion, depression after MI was associated with increased short-term mortality, but its relation with mortality over time appeared to wane, at least in a group of older patients who had multiple co-morbidities.

Usefulness of persistent symptoms of depression to predict physical health status 12 months after an acute coronary syndrome.

Previous research has focused on the relation between depression after an acute coronary syndrome (ACS) and subsequent cardiac morbidity and mortality. However, the relation between depression and quality of life during recovery remains unclear. We investigated whether symptoms of depression during hospitalization for ACS or the course of depressive symptoms after ACS predict physical health status 12 months after ACS, controlling for physical health status at the time of the ACS. This was a prospective study of 425 patients with ACS assessed with the Beck Depression Inventory (BDI) and Short Form 12 (SF-12) Health Survey during hospitalization and 12 months later. Linear regression was used to assess the relation between in-hospital BDI scores and BDI symptom trajectory after ACS with physical health status 12 months later, controlling for baseline physical health status, age, gender, Killip class, history of acute myocardial infarction, and cardiac diagnosis. Baseline BDI scores predicted 12-month physical health (p <0.001). Compared with nondepressed patients, only patients with persistent symptoms of depression were at risk for poorer physical health. Patients with newly developed depressive symptoms after ACS were at slightly increased risk for worsened physical health (p = 0.060), whereas patients with transient depressive symptoms were not at increased risk. In conclusion, these results underscore the importance of assessing depression at the time of ACS and on an ongoing basis.

Probit structural equation regression model: general depressive symptoms predicted post-myocardial infarction mortality after controlling for somatic symptoms of depression.

OBJECTIVE: Reported links between depression and post-acute myocardial infarction (AMI) mortality may be due to confounding between somatic symptoms of depression and symptoms related to the AMI. The objective of this study was to assess the relationship between depressive symptoms and 12-month post-AMI mortality after removing potential bias from somatic symptoms of depression. STUDY DESIGN AND SETTING: Four hundred seventy-seven hospitalized AMI patients from 12 cardiac care units. The relationship of a General Depression factor with mortality was assessed using a probit structural equation regression model, controlling for an uncorrelated somatic symptom factor, age, Killip class, previous AMI, and other potential confounders. RESULTS: Mortality was significantly predicted by the General Depression factor (P=0.009), controlling for age (P=0.128), Killip class (P=0.210), history of AMI (P=0.001), and other predictors in a structural equation model that removed variance related to somatic factors, but unrelated to the General Depression factor. CONCLUSION: This study demonstrated that the use of structural equation modeling presents a viable mechanism to test links between symptoms of depression and health outcomes among patients with AMI after explicitly removing variance due to somatic symptoms that is unrelated to the General Depression factor.

Physical health status assessed during hospitalization for acute coronary syndrome predicts mortality 12 months later.

OBJECTIVE: Self-report measures of health status predict mortality in several groups of patients with cardiovascular disease, although overlap with symptoms of depression may reduce or eliminate this relationship. The association between self-reported health status and mortality has not been examined in patients hospitalized for acute coronary syndrome (ACS). The objective was to investigate whether the Physical Component Summary (PCS) and Mental Component Summary (MCS) scores of the SF-12 predicted 12-month all-cause mortality after controlling for cardiac risk factors and symptoms of depression. METHODS: The SF-12 and Beck Depression Inventory were administered 2-5 days after admission to 800 ACS patients from 12 coronary care units. Logistic regression was used to assess the relationship of the PCS and MCS with mortality 12 months later, controlling for age, sex, cardiac diagnosis (acute myocardial infarction vs. unstable angina), Killip class, history of myocardial infarction, and in-hospital depressive symptoms. RESULTS: Lower scores on the SF-12 PCS (worse health) were associated with a significantly higher risk of mortality [odds ratio (OR)=0.94, 95% confidence interval (CI)=0.92-0.97, P<.001]. MCS scores failed to reach significance (OR=0.98, CI=0.95-1.00, P=.053). The PCS significantly predicted mortality even after controlling for other cardiac risk factors and depressive symptoms (OR=0.96, CI=0.93-0.99, P=.008), equivalent to a 34% increase in risk per 10-point (1 SD) decrement in PCS scores. CONCLUSION: The brief SF-12 PCS presents an attractive option for improving risk stratification among hospitalized ACS patients.

Platelet function in patients with depression.

Depression accelerates the development and progression of cardiovascular disease and confers an increased risk of mortality. Platelets share biochemical similarity with the central nervous system, particularly in the uptake, storage, and metabolism of serotonin. Given this similarity, and considering the central role of platelets in the biology of cardiovascular disease, it is highly plausible that platelets play an important role in the increased cardiovascular risk of patients with depression. This article provides a comprehensive review of the evidence in this area and shows that the relationship between depression and platelet function is hardly straightforward. Whereas many studies have found that patients with depression have exaggerated platelet activation, quite a number of others show no such relationship or even lower levels of platelet activation in patients with depression. Larger, carefully designed, adequately powered studies with standardized methods of assessing platelet function are needed to address this issue.

Online Health Searches and Their Perceived Effects on Patients and Patient-Clinician Relationships: ASystematic Review.

Online health searches are common and may be impacting patients and their relationships with their clinicians in ways that are not fully understood. We searched PubMed, Embase, Cochrane Reviews, Cochrane Trials, Scopus, and CINAHL from January 1, 1990 to January 29, 2016 for studies in which patients searched online for any aspect of health care and then visited their clinician. We extracted data pertaining to either patients' or clinicians' perceptions of the effects of these online searches on patients and the patient-clinician relationship. Searches seemed to induce patient anxiety but more often led to patient reassurance, clinical understanding, and empowerment. Patients tended to perceive that online health searches had a positive effect on the patient-clinician relationship, although the nature of the effect could depend on the clinician's response to patient queries about the information. Clinicians generally perceived neutral effects on patients and the patient-clinician relationship and commonly raised concerns about the accuracy of online content. Significant methodologic heterogeneity prevented quantitative synthesis. Accuracy of online health search content was not assessed, and randomized controlled trials were notably lacking.

Individual depressive symptoms and all-cause mortality In 6673 patients with myocardial infarction: Heterogeneity across age and sex subgroups.

BACKGROUND: Depression predicts poor prognosis in patients with myocardial infarction (MI). However, individual depressive symptoms may have different prognostic value, and age and sex could be important effect modifiers. This study compared the prognostic value of individual depressive symptoms across age and sex subgroups in post-MI patients. METHODS: Individual patient-data were compiled for 6673 post-MI patients from seven studies. Depressive symptoms were measured with 10 items of the Beck Depression Inventory (BDI10). The endpoint was all-cause mortality (mean=3.8 years). Multilevel multivariable Cox regression analysis was used to estimate the mortality risk across age groups (≤55, 56-69 and ≥70 years) and sex for symptoms that potentially interacted with age and sex. RESULTS: At follow-up, 995 (15%) post-MI patients had died. BDI10 depression scores were associated with an increased mortality risk (HR:1.20;95%CI:1.11-1.28,p<.001). Negative self-image (HR:1.53;1.06-2.21;p=.022) and indecisiveness (HR:1.53;1.15-2.04;p=.003) were associated with increased mortality in men <55. Dissatisfaction was associated with increased mortality in men aged 56-69 (HR:1.35;1.07-1.71;p=. 011), and dissatisfaction (HR:1.34;1.10-1.63;p=.003) and fatigue (HR:1.45;1.20-1.74;p<.001) in men >70. Fatigue was associated with mortality in women aged 56-69 (HR:1.54;1.09-2.15;p=.012), and suicidal ideation in women aged >70 (HR:1.58;1.03-2.43;p=.037). Left-ventricular ejection fraction (LVEF) accounted for much of the associations in men ≤55 years and women ≥70 years. LIMITATIONS: Findings are sample-specific and need replication in future research; BDI10 items were derived from the original BDI assessment. CONCLUSIONS: There is large heterogeneity in the prognostic value of individual depressive symptoms in post-MI patients across sex and age subgroups. LVEF partially explained the depression-prognosis association in specific subgroups.

Using Innovative Methodologies From Technology and Manufacturing Companies to Reduce Heart Failure Readmissions.

Heart failure (HF) patients have high 30-day readmission rates with high costs and poor quality of life. This study investigated the impact of a framework blending Lean Sigma, design thinking, and Lean Startup on 30-day all-cause readmissions among HF patients. This was a prospective study in an academic hospital in Baltimore, Maryland. Thirty-day all-cause readmission was assessed using the hospital's electronic medical record. The baseline readmission rate for HF was 28.4% in 2010 with 690 discharges. The framework was developed and interventions implemented in the second half of 2011. The impact of the interventions was evaluated through 2012. The rate declined to 18.9% among 703 discharges (P < .01). There was no significant change for non-HF readmissions. This study concluded that methodologies from technology and manufacturing companies can reduce 30-day readmissions in HF, demonstrating the potential of this innovations framework to improve chronic disease care.

A bifactor model of the Beck Depression Inventory and its association with medical prognosis after myocardial infarction.

OBJECTIVES: Evidence suggests that depression is associated with adverse outcomes in patients with myocardial infarction (MI). Some of the symptoms of depression may also be symptoms of somatic illness and these may confound the association between depression and prognosis. We investigated whether depression following MI is associated with medical prognosis independent of these somatic symptoms. METHOD: The database of an individual patient data meta-analysis was used. Endpoints were all-cause mortality and cardiovascular events. Nine studies were included. Bifactor factor analysis included 13,100 participants and 7,595 participants were included in survival models. Dimensions were generated from the Beck Depression Inventory using factor analyses. The prognostic association was assessed using mixed-effects Cox regression analysis. RESULTS: A bifactor model, consisting of a general factor and 2 general depression-free subgroup factors (a somatic/affective and a cognitive/affective), provided the best fit. There was a significant association between the general depression factor and all-cause mortality (hazard ratio [HR] = 1.25; 95% confidence interval [CI] [1.17, 1.34], p < .001) and cardiovascular events (HR = 1.18; 95% CI [1.13, 1.23], p < .001). After adjustment for demographics, measures of cardiac disease severity, and health-related variables, the association between the general depression factor and all-cause mortality (HR = 1.14; 95% CI [1.04, 1.25], p = .003) and cardiovascular events (HR = 1.16; 95% CI [1.10, 1.23], p = .014) attenuated. Additionally, the general depression-free somatic/affective factor was significantly associated with the endpoints, while the general depression-free cognitive/affective was not. CONCLUSIONS: A general depression factor is associated with adverse medical prognosis following MI independent of somatic/affective symptoms that may be partly attributable to somatic illness. (PsycINFO Database Record

Constrictive pericarditis: etiology and cause-specific survival after pericardiectomy.

OBJECTIVES: We sought to determine the association of etiology of constrictive pericarditis (CP), pericardial calcification (CA), and other clinical variables with long-term survival after pericardiectomy. BACKGROUND: Constrictive pericarditis is the result of a spectrum of primary cardiac and noncardiac conditions. Few data exist on the cause-specific survival after pericardiectomy. The impact of CA on survival is unclear. METHODS: A total of 163 patients who underwent pericardiectomy for CP over a 24-year period at a single surgical center were studied. Constrictive pericarditis was confirmed by the surgical report. Vital status was obtained from the Social Security Death Index. RESULTS: Etiology of CP was idiopathic in 75 patients (46%), prior cardiac surgery in 60 patients (37%), radiation treatment in 15 patients (9%), and miscellaneous in 13 patients (8%). Median follow-up among survivors was 6.9 years (range 0.8 to 24.5 years), during which time there were 61 deaths. Perioperative mortality was 6%. Idiopathic CP had the best prognosis (7-year Kaplan-Meier survival: 88%, 95% confidence interval [CI] 76% to 94%) followed by postsurgical (66%, 95% CI 52% to 78%) and postradiation CP (27%, 95% CI 9% to 58%). In bootstrap-validated proportional hazards analyses, predictors of poor overall survival were prior radiation, worse renal function, higher pulmonary artery systolic pressure (PAP), abnormal left ventricular (LV) systolic function, lower serum sodium level, and older age. Pericardial calcification had no impact on survival. CONCLUSIONS: Long-term survival after pericardiectomy for CP is related to underlying etiology, LV systolic function, renal function, serum sodium, and PAP. The relatively good survival with idiopathic CP emphasizes the safety of pericardiectomy in this subgroup.