Light-to-moderate alcohol consumption and mortality in the physicians’ health study enrollment cohort

AbstractOBJECTIVESThis study examined the relationship between light-to-moderate alcohol consumption and cause-specific mortality.BACKGROUNDPrevious studies suggest a J-shaped relation between alcohol and total mortality in men. A decrease in cardiovascular disease (CVD) mortality without a significant increase in other causes of mortality may explain the overall risk reduction at light-to-moderate levels.METHODSWe conducted a prospective cohort study of 89,299 U.S. men from the Physicians’ Health Study enrollment cohort who were 40 to 84 years old in 1982 and free of known myocardial infarction, stroke, cancer or liver disease at baseline. Usual alcohol consumption was estimated by a limited food frequency questionnaire.RESULTSThere were 3,216 deaths over 5.5 years of follow-up. We observed a U-shaped relationship between alcohol consumption and total mortality. Compared with rarely/never drinkers, consumers of 1, 2 to 4 and 5 to 6 drinks per week and 1 drink per day had significant reductions in risk of death (multivariate relative risks [RRs] of 0.74, 0.77, 0.78 and 0.82, respectively) with no overall benefit or harm detected at the ≥2 drinks per day level (RR = 0.95; 95% confidence interval (CI), 0.79 to 1.14). The relationship with CVD mortality was inverse or L-shaped with apparent risk reductions even in the highest category of ≥2 drinks per day (RR = 0.76; 95% CI, 0.57 to 1.01). We found no clear harm or benefit for total or common site-specific cancers. For remaining other cancers, there was a nonsignificant 28% increased risk for those consuming ≥2 drinks per day.CONCLUSIONSThese data support a U-shaped relation between alcohol and total mortality among light-to-moderate drinking men. The U-shaped curve may reflect an inverse association for CVD mortality, no association for common site-specific cancers and a possible positive association for less common cancers

Immunomodulatory agents as potential therapeutic or preventive strategies for COVID-19

Currently, the COVID-19 pandemic, caused by the novel SARS-CoV-2 coronavirus, represents the greatest global health threat. Most people infected by the virus present mild to moderate respiratory symptoms and recover with supportive treatments. However, certain susceptible hosts develop an acute respiratory distress syndrome (ARDS), associated with an inflammatory “cytokine storm”, leading to lung damage. Despite the current availability of different COVID-19 vaccines, the new emerging SARS-CoV-2 genetic variants represent a major concern worldwide, due to their increased transmissibility and rapid spread. Indeed, it seems that some mutations or combinations of mutations might confer selective advantages to the virus, such as the ability to evade the host immune responses elicited by COVID-19 vaccines. Several therapeutic approaches have been investigated but, to date, a unique and fully effective therapeutic protocol has not yet been achieved. In addition, steroid-based therapies, aimed to reduce inflammation in patients with severe COVID-19 disease, may increase the risk of opportunistic infections, increasing the hospitalization time and mortality rate of these patients. Hence, there is an unmet need to develop more effective therapeutic options. Here, we discuss the potential use of natural immunomodulators such as Thymosin α1 (Tα1), all-trans retinoic acid (ATRA), and lactoferrin (LF), as adjunctive or preventive treatment of severe COVID-19 disease. These agents are considered to be multifunctional molecules because of their ability to enhance antiviral host immunity and restore the immune balance, depending on the host immune status. Furthermore, they are able to exert a broad-spectrum antimicrobial activity by means of direct interactions with cellular or molecular targets of pathogens or indirectly by increasing the host immune response. Thus, due to the aforementioned properties, these agents might have a great potential in a clinical setting, not only to counteract SARS-CoV-2 infection, but also to prevent opportunistic infections in critically ill COVID-19 patients

Multimorbidity, control and treatment of noncommunicable diseases among primary healthcare attenders in the Western Cape, South Africa

Background. South Africa (SA) is facing a heavy burden of non-communicable diseases (NCDs). Few studies address multimorbidity, control and treatment of NCDs in patients attending primary healthcare (PHC) clinics. Objectives. To describe multimorbidity, related risk factors, disease severity and treatment status of patients with four important NCDs attending public sector PHC clinics in two districts in SA. Methods. A cross-sectional sample of patients completed baseline data collection for a randomised controlled trial of a health systems intervention. The study population comprised adults attending PHC clinics in the Eden and Overberg districts of the Western Cape in 2011. Four subgroups of patients were identified: hypertension, diabetes, chronic respiratory disease and depression. A total of 4 393 participants enrolled from 38 clinics completed a baseline structured questionnaire and had measurements taken. Prescription data were recorded. Results. Of participants with hypertension, diabetes, respiratory disease and depression, 80%, 92%, 88% and 80%, respectively, had at least one of the other three conditions. There were low levels of control and treatment: 59% of participants with hypertension had a blood pressure ≥140/90 mmHg, the mean haemoglobin A1c (HbA1c) value in participants with diabetes was 9%, 12% of participants in the depression group were prescribed an antidepressant at a therapeutic dose, and 48% of respiratory participants were prescribed a b2-agonist and 34% an inhaled corticosteroid. Conclusion. Considerable multimorbidity and unmet treatment needs exist among patients with NCDs attending public sector PHC clinics. Improved strategies are required for diagnosing and managing NCDs in this sector

Cost-effectiveness analysis of sacubitril/valsartan vs enalapril in patients with heart failure and reduced ejection fraction

Importance  The angiotensin receptor neprilysin inhibitor sacubitril/valsartan was associated with a reduction in cardiovascular mortality, all-cause mortality, and hospitalizations compared with enalapril. Sacubitril/valsartan has been approved for use in heart failure (HF) with reduced ejection fraction in the United States and cost has been suggested as 1 factor that will influence the use of this agent. Objective  To estimate the cost-effectiveness of sacubitril/valsartan vs enalapril in the United States. Design, Setting, and Participants  Data from US adults (mean [SD] age, 63.8 [11.5] years) with HF with reduced ejection fraction and characteristics similar to those in the PARADIGM-HF trial were used as inputs for a 2-state Markov model simulated HF. Risks of all-cause mortality and hospitalization from HF or other reasons were estimated with a 30-year time horizon. Quality of life was based on trial EQ-5D scores. Hospital costs combined Medicare and private insurance reimbursement rates; medication costs included the wholesale acquisition cost for sacubitril/valsartan and enalapril. A discount rate of 3% was used. Sensitivity analyses were performed on key inputs including: hospital costs, mortality benefit, hazard ratio for hospitalization reduction, drug costs, and quality-of-life estimates. Main Outcomes and Measures  Hospitalizations, quality-adjusted life-years (QALYs), costs, and incremental costs per QALY gained. Results  The 2-state Markov model of US adult patients (mean age, 63.8 years) calculated that there would be 220 fewer hospital admissions per 1000 patients with HF treated with sacubitril/valsartan vs enalapril over 30 years. The incremental costs and QALYs gained with sacubitril/valsartan treatment were estimated at $35 512 and 0.78, respectively, compared with enalapril, equating to an incremental cost-effectiveness ratio (ICER) of$45 017 per QALY for the base-case. Sensitivity analyses demonstrated ICERs ranging from $35 357 to$75 301 per QALY. Conclusions and Relevance  For eligible patients with HF with reduced ejection fraction, the Markov model calculated that sacubitril/valsartan would increase life expectancy at an ICER consistent with other high-value accepted cardiovascular interventions. Sensitivity analyses demonstrated sacubitril/valsartan would remain cost-effective vs enalapril

Microbiology and Clinical Outcome of Hospital-Acquired Respiratory Infections in an Italian Teaching Hospital: A Retrospective Study

The burden, microbial etiology and clinical impact of hospital-acquired respiratory infections (HARIs) were determined at an Italian teaching hospital over a 12-month period. For this purpose, overall ordinary hospitalizations >= 2 days of subjects over 18 years old with discharge from 1 January 2018 to 31 December 2018 were examined by cross-referencing demographic and clinical data from hospital discharge forms with microbiological data from the computer system of the Microbiology Unit. We identified 329 individuals with HARIs (96 females and 233 males; median age 70 years, range 18-93), who represented 1/4 of the total hospital-acquired infections (HAIs) in the period. The inpatient setting was medical and surgical in similar proportions (169 vs. 160, respectively) and the mean hospital stay was 38.9 +/- 33.6 days. One hundred and forty patients (42.6% of the total sample) were suffering from one or more chronic diseases. A total of 581 microorganisms (82 antibiotic-resistant and 499 non-resistant) were detected in HARI patients. The most common isolated species were Staphylococcus aureus (16.7%), Klebsiella pneumoniae (13.3%), Pseudomonas spp. (12.6%) and Acinetobacter baumannii (10.5%), followed by Enterobacter spp. (5.3%), Escherichia coli (5.2%) and Enterococcus spp. (4.8%). One hundred and sixty-seven individuals (49.0% of the total) had polymicrobial infections. One hundred thirty-one patients (39.8% of the total) underwent endotracheal intubation and mechanical ventilation and 62.6% of them died, compared to 17.7% of the non-intubated patients. Multivariable analysis confirmed a positive correlation between death and increased age (p = 0.05), surgical MDC (p = 0.007), number of microorganisms over the sample mean (p = 0.001), the presence of chronic diseases (p = 0.046), and intubation and mechanical ventilation (p < 0.0001). A positive correlation between intubation and antibiotic-resistant organisms (p = 0.003) was also found. HARIs are still a major public health problem and require constant surveillance due to their severe clinical outcome

An application of conditional logistic regression and multifactor dimensionality reduction for detecting gene-gene Interactions on risk of myocardial infarction: The importance of model validation

BACKGROUND: To examine interactions among the angiotensin converting enzyme (ACE) insertion/deletion, plasminogen activator inhibitor-1 (PAI-1) 4G/5G, and tissue plasminogen activator (t-PA) insertion/deletion gene polymorphisms on risk of myocardial infarction using data from 343 matched case-control pairs from the Physicians Health Study. We examined the data using both conditional logistic regression and the multifactor dimensionality reduction (MDR) method. One advantage of the MDR method is that it provides an internal prediction error for validation. We summarize our use of this internal prediction error for model validation. RESULTS: The overall results for the two methods were consistent, with both suggesting an interaction between the ACE I/D and PAI-1 4G/5G polymorphisms. However, using ten-fold cross validation, the 46% prediction error for the final MDR model was not significantly lower than that expected by chance. CONCLUSIONS: The significant interaction initially observed does not validate and may represent a type I error. As data-driven analytic methods continue to be developed and used to examine complex genetic interactions, it will become increasingly important to stress model validation in order to ensure that significant effects represent true relationships rather than chance findings

Validation of a Blood-Based Protein Biomarker Panel for a Risk Assessment of Lethal Lung Cancer in the Physicians\u27 Health Study

This study aimed to assess a four-marker protein panel (4MP)\u27s performance, including the precursor form of surfactant protein B, cancer antigen 125, carcinoembryonic antigen, and cytokeratin-19, for predicting lung cancer in a cohort enriched with never- and ever-smokers. Blinded pre-diagnostic plasma samples collected within 2 years prior to a lung cancer diagnosis from 25 cases and 100 sex-, age-, and smoking-matched controls were obtained from the Physicians\u27 Health Study (PHS). The 4MP yielded AUC performance estimates of 0.76 (95% CI: 0.61-0.92) and 0.69 (95% CI: 0.56-0.82) for predicting lung cancer within one year and within two years of diagnosis, respectively. When stratifying into ever-smokers and never-smokers, the 4MP had respective AUCs of 0.77 (95% CI: 0.63-0.92) and 0.72 (95% CI: 0.17-1.00) for a 1-year risk of lung cancer. The AUCs of the 4MP for predicting metastatic lung cancer within one year and two years of the blood draw were 0.95 (95% CI: 0.87-1.00) and 0.78 (95% CI: 0.62-0.94), respectively. Our findings indicate that a blood-based biomarker panel may be useful in identifying ever- and never-smokers at high risk of a diagnosis of lung cancer within one-to-two years

Genome-wide association studies and cross-population meta-analyses investigating short and long sleep duration

Sleep duration has been linked to a wide range of negative health outcomes and to reduced life expectancy. We present genome-wide association studies of short ( ≤ 5 h) and long ( ≥ 10 h) sleep duration in adults of European (N = 445,966), African (N = 27,785), East Asian (N = 3141), and admixed-American (N = 16,250) ancestry from UK Biobank and the Million Veteran Programme. In a cross-population meta-analysis, we identify 84 independent loci for short sleep and 1 for long sleep. We estimate SNP-based heritability for both sleep traits in each ancestry based on population derived linkage disequilibrium (LD) scores using cov-LDSC. We identify positive genetic correlation between short and long sleep traits (rg = 0.16 ± 0.04; p = 0.0002), as well as similar patterns of genetic correlation with other psychiatric and cardiometabolic phenotypes. Mendelian randomisation reveals a directional causal relationship between short sleep and depression, and a bidirectional causal relationship between long sleep and depression