How to interprete subclinical thyroid dysfunction in the prevention and management of heart failure events? Individual participant data analysis from six prospective cohorts

Background: Guidelines of the Diagnosis and Management of Heart Failure (HF) recommend investigating exacerbating conditions, such as thyroid dysfunction, but without specifying impact of different TSH levels. Limited prospective data exist regarding the association between subclinical thyroid dysfunction and HF events. Methods: We performed a pooled analysis of individual participant data using all available prospective cohorts with thyroid function tests and subsequent follow-up of HF events. Individual data on 25,390 participants with 216,247 person-years of follow-up were supplied from 6 prospective cohorts in the United States and Europe. Euthyroidism was defined as TSH 0.45-4.49 mIU/L, subclinical hypothyroidism as TSH 4.5-19.9 mIU/L and subclinical hyperthyroidism as TSH <0.45 mIU/L, both with normal free thyroxine levels. HF events were defined as acute HF events, hospitalization or death related to HF events. Results: Among 25,390 participants, 2068 had subclinical hypothyroidism (8.1%) and 648 subclinical hyperthyroidism (2.6%). In age- and gender-adjusted analyses, risks of HF events were increased with both higher and lower TSH levels (P for quadratic pattern<0.01): hazard ratio (HR) was 1.01 (95% confidence interval [CI] 0.81-1.26) for TSH 4.5-6.9 mIU/L, 1.65 (CI 0.84-3.23) for TSH 7.0-9.9 mIU/L, 1.86 (CI 1.27-2.72) for TSH 10.0-19.9 mIUL/L (P for trend <0.01), and was 1.31 (CI 0.88-1.95) for TSH 0.10-0.44 mIU/L and 1.94 (CI 1.01-3.72) for TSH <0.10 mIU/L (P for trend=0.047). Risks remained similar after adjustment for cardiovascular risk factors. Conclusion: Risks of HF events were increased with both higher and lower TSH levels, particularly for TSH ≥10 mIU/L and for TSH <0.10 mIU/L. Our findings might help to interpret TSH levels in the prevention and investigation of HF.

Cost-effectiveness analysis of cardiac resynchronization therapy in patients with NYHA I and NYHA II heart failure in Spain

Objectives: The aim of the study was to combine clinical results from the European Cohort of the REVERSE study and costs associated with the addition of cardiac resynchronization therapy (CRT) to optimal medical therapy (OMT) in patients with mild symptomatic (NYHA I-II) or asymptomatic left ventricular dysfunction and markers of cardiac dyssynchrony in Spain. Methods: A Markov model was developed with CRT + OMT (CRT-ON) versus OMT only (CRT-OFF) based on a retrospective cost-effectiveness analysis. Raw data was derived from literature and expert opinion, reflecting clinical and economic consequences of patient"s management in Spain. Time horizon was 10 years. Both costs (euro 2010) and effects were discounted at 3 percent per annum. Results: CRT-ON showed higher total costs than CRT-OFF; however, CRT reduced the length of hospitalization in ICU by 94 percent (0.006 versus 0.091 days) and general ward in by 34 percent (0.705 versus 1.076 days). Surviving CRT-ON patients (88.2 percent versus 77.5 percent) remained in better functional class longer, and they achieved an improvement of 0.9 life years (LYGs) and 0.77 years quality-adjusted life years (QALYs). CRT-ON proved to be cost-effective after 6 years, except for the 7th year due to battery depletion. At 10 years, the results were 18,431 per LYG and 21,500 per QALY gained. Probabilistic sensitivity analysis showed CRT-ON was cost-effective in 75.4 percent of the cases at 10 years. Conclusions: The use of CRT added to OMT represents an efficient use of resources in patients suffering from heart failure in NYHA functional classes I and II.

Impact of Aldosterone Antagonists on Sudden Cardiac Death Prevention in Heart Failure and Post-Myocardial Infarction Patients: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND AND OBJECTIVES: Sudden cardiac death (SCD) is a severe burden of modern medicine. Aldosterone antagonist is publicized as effective in reducing mortality in patients with heart failure (HF) or post myocardial infarction (MI). Our study aimed to assess the efficacy of AAs on mortality including SCD, hospitalization admission and several common adverse effects. METHODS: We searched Embase, PubMed, Web of Science, Cochrane library and clinicaltrial.gov for randomized controlled trials (RCTs) assigning AAs in patients with HF or post MI through May 2015. The comparator included standard medication or placebo, or both. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Event rates were compared using a random effects model. Prospective RCTs of AAs with durations of at least 8 weeks were selected if they included at least one of the following outcomes: SCD, all-cause/cardiovascular mortality, all-cause/cardiovascular hospitalization and common side effects (hyperkalemia, renal function degradation and gynecomastia). RESULTS: Data from 19,333 patients enrolled in 25 trials were included. In patients with HF, this treatment significantly reduced the risk of SCD by 19% (RR 0.81; 95% CI, 0.67-0.98; p = 0.03); all-cause mortality by 19% (RR 0.81; 95% CI, 0.74-0.88, p<0.00001) and cardiovascular death by 21% (RR 0.79; 95% CI, 0.70-0.89, p<0.00001). In patients with post-MI, the matching reduced risks were 20% (RR 0.80; 95% CI, 0.66-0.98; p = 0.03), 15% (RR 0.85; 95% CI, 0.76-0.95, p = 0.003) and 17% (RR 0.83; 95% CI, 0.74-0.94, p = 0.003), respectively. Concerning both subgroups, the relative risks respectively decreased by 19% (RR 0.81; 95% CI, 0.71-0.92; p = 0.002) for SCD, 18% (RR 0.82; 95% CI, 0.77-0.88, p < 0.0001) for all-cause mortality and 20% (RR 0.80; 95% CI, 0.74-0.87, p < 0.0001) for cardiovascular mortality in patients treated with AAs. As well, hospitalizations were significantly reduced, while common adverse effects were significantly increased. CONCLUSION: Aldosterone antagonists appear to be effective in reducing SCD and other mortality events, compared with placebo or standard medication in patients with HF and/or after a MI.

Failure Mode and Effect Analysis (FMEA) for confectionery manufacturing in developing countries: Turkish delight production as a case study

The Failure Mode and Effect Analysis (FMEA) was applied for risk assessment of confectionary manufacturing, in whichthe traditional methods and equipment were intensively used in the production. Potential failure modes and effects as well as their possible causes were identified in the process flow. Processing stages that involve intensive handling of food by workers had the highest risk priority numbers (RPN = 216 and 189), followed by chemical contamination risks in different stages of the process. The application of corrective actions substantially reduced the RPN (risk priority number) values. Therefore, the implementation of FMEA (The Failure Mode and Effect Analysis) model in confectionary manufacturing improved the safety and quality of the final products.

Analysis of the late correspondence between our administration and Great Britain & France, with an attempt to show what are the real causes of the failure of the negotiation.

Ten pieces originally published in the Columbian Centinel. A later edition with imprint New York, Printed for E. Sargeant, 1809, contains two additional pieces.

Bayesian Analysis for the Generalized Lognormal Distribution Applied to Failure Time Analysis

There are several versions of the lognormal distribution in the statistical literature, one is based in the exponential transformation of generalized normal distribution (GN). This paper presents the Bayesian analysis for the generalized lognormal distribution (logGN) considering independent non-informative Jeffreys distributions for the parameters as well as the procedure for implementing the Gibbs sampler to obtain the posterior distributions of parameters. The results are used to analyze failure time models with right-censored and uncensored data. The proposed method is illustrated using actual failure time data of computers.

Postmortem diagnosis of acute myocardial infarction in patients with acute respiratory failure - demographics, etiologic and pulmonary histologic analysis

OBJECTIVES: Acute respiratory failure is present in 5% of patients with acute myocardial infarction and is responsible for 20% to 30% of the fatal post-acute myocardial infarction. The role of inflammation associated with pulmonary edema as a cause of acute respiratory failure post-acute myocardial infarction remains to be determined. We aimed to describe the demographics, etiologic data and histological pulmonary findings obtained through autopsies of patients who died during the period from 1990 to 2008 due to acute respiratory failure with no diagnosis of acute myocardial infarction during life. METHODS: This study considers 4,223 autopsies of patients who died of acute respiratory failure that was not preceded by any particular diagnosis while they were alive. The diagnosis of acute myocardial infarction was given in 218 (4.63%) patients. The age, sex and major associated diseases were recorded for each patient. Pulmonary histopathology was categorized as follows: diffuse alveolar damage, pulmonary edema, alveolar hemorrhage and lymphoplasmacytic interstitial pneumonia. The odds ratio of acute myocardial infarction associated with specific histopathology was determined by logistic regression. RESULTS: In total, 147 men were included in the study. The mean age at the time of death was 64 years. Pulmonary histopathology revealed pulmonary edema as well as the presence of diffuse alveolar damage in 72.9% of patients. Bacterial bronchopneumonia was present in 11.9% of patients, systemic arterial hypertension in 10.1% and dilated cardiomyopathy in 6.9%. A multivariate analysis demonstrated a significant positive association between acute myocardial infarction with diffuse alveolar damage and pulmonary edema. CONCLUSIONS: For the first time, we demonstrated that in autopsies of patients with acute respiratory failure as the cause of death, 5% were diagnosed with acute myocardial infarction. Pulmonary histology revealed a significant inflammatory response, which has not previously been reported.

Survival Analysis of Patients with Heart Failure: Implications of Time-Varying Regression Effects in Modeling Mortality

Background: Several models have been designed to predict survival of patients with heart failure. These, while available and widely used for both stratifying and deciding upon different treatment options on the individual level, have several limitations. Specifically, some clinical variables that may influence prognosis may have an influence that change over time. Statistical models that include such characteristic may help in evaluating prognosis. The aim of the present study was to analyze and quantify the impact of modeling heart failure survival allowing for covariates with time-varying effects known to be independent predictors of overall mortality in this clinical setting. Methodology: Survival data from an inception cohort of five hundred patients diagnosed with heart failure functional class III and IV between 2002 and 2004 and followed-up to 2006 were analyzed by using the proportional hazards Cox model and variations of the Cox's model and also of the Aalen's additive model. Principal Findings: One-hundred and eighty eight (188) patients died during follow-up. For patients under study, age, serum sodium, hemoglobin, serum creatinine, and left ventricular ejection fraction were significantly associated with mortality. Evidence of time-varying effect was suggested for the last three. Both high hemoglobin and high LV ejection fraction were associated with a reduced risk of dying with a stronger initial effect. High creatinine, associated with an increased risk of dying, also presented an initial stronger effect. The impact of age and sodium were constant over time. Conclusions: The current study points to the importance of evaluating covariates with time-varying effects in heart failure models. The analysis performed suggests that variations of Cox and Aalen models constitute a valuable tool for identifying these variables. The implementation of covariates with time-varying effects into heart failure prognostication models may reduce bias and increase the specificity of such models.

Postmortem diagnosis of acute myocardial infarction in patients with acute respiratory failure: demographics, etiologic and pulmonary histologic analysis

OBJECTIVES: Acute respiratory failure is present in 5% of patients with acute myocardial infarction and is responsible for 20% to 30% of the fatal post-acute myocardial infarction. The role of inflammation associated with pulmonary edema as a cause of acute respiratory failure post-acute myocardial infarction remains to be determined. We aimed to describe the demographics, etiologic data and histological pulmonary findings obtained through autopsies of patients who died during the period from 1990 to 2008 due to acute respiratory failure with no diagnosis of acute myocardial infarction during life. METHODS: This study considers 4,223 autopsies of patients who died of acute respiratory failure that was not preceded by any particular diagnosis while they were alive. The diagnosis of acute myocardial infarction was given in 218 (4.63%) patients. The age, sex and major associated diseases were recorded for each patient. Pulmonary histopathology was categorized as follows: diffuse alveolar damage, pulmonary edema, alveolar hemorrhage and lymphoplasmacytic interstitial pneumonia. The odds ratio of acute myocardial infarction associated with specific histopathology was determined by logistic regression. RESULTS: In total, 147 men were included in the study. The mean age at the time of death was 64 years. Pulmonary histopathology revealed pulmonary edema as well as the presence of diffuse alveolar damage in 72.9% of patients. Bacterial bronchopneumonia was present in 11.9% of patients, systemic arterial hypertension in 10.1% and dilated cardiomyopathy in 6.9%. A multivariate analysis demonstrated a significant positive association between acute myocardial infarction with diffuse alveolar damage and pulmonary edema. CONCLUSIONS: For the first time, we demonstrated that in autopsies of patients with acute respiratory failure as the cause of death, 5% were diagnosed with acute myocardial infarction. Pulmonary histology revealed a significant inflammatory response, which has not previously been reported.

Treatment failure in pneumonia: Impact of antibiotic treatment and cost analysis

The aim of this study was to investigate treatment failure (TF) in hospitalised community-acquired pneumonia (CAP) patients with regard to initial antibiotic treatment and economic impact. CAP patients were included in two open, prospective multicentre studies assessing the direct costs for in-patient treatment. Patients received treatment either with moxifloxacin (MFX) or a nonstandardised antibiotic therapy. Any change in antibiotic therapy after >72 h of treatment to a broadened antibiotic spectrum was considered as TF. Overall, 1,236 patients (mean ± SD age 69.6 ± 16.8 yrs, 691 (55.9%) male) were included. TF occurred in 197 (15.9%) subjects and led to longer hospital stay (15.4 ± 7.3 days versus 9.8 ± 4.2 days; p < 0.001) and increased median treatment costs (€2,206 versus €1,284; p<0.001). 596 (48.2%) patients received MFX and witnessed less TF (10.9% versus 20.6%; p < 0.001). After controlling for confounders in multivariate analysis, adjusted risk of TF was clearly reduced in MFX as compared with β-lactam monotherapy (adjusted OR for MFX 0.43, 95% CI 0.27-0.68) and was more comparable with a β-lactam plus macrolide combination (BLM) (OR 0.68, 95% CI 0.38-1.21). In hospitalised CAP, TF is frequent and leads to prolonged hospital stay and increased treatment costs. Initial treatment with MFX or BLM is a possible strategy to prevent TF, and may thus reduce treatment costs.

Proposal on How To Conduct a Biopharmaceutical Process Failure Mode and Effect Analysis (FMEA) as a Risk Assessment Tool

With the publication of the quality guideline ICH Q9 "Quality Risk Management" by the International Conference on Harmonization, risk management has already become a standard requirement during the life cycle of a pharmaceutical product. Failure mode and effect analysis (FMEA) is a powerful risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to biopharmaceutical processes brings about some difficulties. The proposal presented here is intended to serve as a brief but nevertheless comprehensive and detailed guideline on how to conduct a biopharmaceutical process FMEA. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. The application for such a biopharmaceutical process FMEA is widespread. It can be useful whenever a biopharmaceutical manufacturing process is developed or scaled-up, or when it is transferred to a different manufacturing site. It may also be conducted during substantial optimization of an existing process or the development of a second-generation process. According to their resulting risk ratings, process parameters can be ranked for importance and important variables for process development, characterization, or validation can be identified. LAY ABSTRACT: Health authorities around the world ask pharmaceutical companies to manage risk during development and manufacturing of pharmaceuticals. The so-called failure mode and effect analysis (FMEA) is an established risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to pharmaceutical processes that use modern biotechnology (biopharmaceutical processes) brings about some difficulties, because those biopharmaceutical processes differ from processes in mechanical and electrical industries. The proposal presented here explains how a biopharmaceutical process FMEA can be conducted. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. With the help of this guideline, different details of the manufacturing process can be ranked according to their potential risks, and this can help pharmaceutical companies to identify aspects with high potential risks and to react accordingly to improve the safety of medicines.