Do statins have a role in preventing or treating sepsis?

Statins have a variety of properties that are independent of their lipid lowering ability. These anti-inflammatory, antioxidant, immunomodulatory, and antiapoptotic features have been collectively referred to as pleiotropic effects. Severe sepsis is an intense infection-induced inflammatory syndrome that ultimately results in organ dysfunction. Because so many cascades are triggered during sepsis, merely blocking a single component may be insufficient to arrest the inflammatory process. A growing body of evidence suggests that statins may indeed have a protective effect against severe sepsis and reduce the rate of infection-related mortality. This novel primary prevention concept may have far-reaching implications for the future management of serious infections. Moreover, it was recently shown that statins potentially improve outcome after the onset of sepsis. The stage is now set for randomized clinical trials that will determine the precise role, if any, that statins may have in preventing and treating sepsis

Acid Suppression Therapy Does Not Predispose to Clostridium difficile Infection: The Case of the Potential Bias

Objective: An adverse effect of acid-suppression medications on the occurrence of Clostridium difficile infection (CDI) has been a common finding of many, but not all studies. We hypothesized that association between acid-suppression medications and CDI is due to the residual confounding in comparison between patients with infection to those without, predominantly from non-tested and less sick subjects. We aimed to evaluate the effect of acid suppression therapy on incidence of CDI by comparing patients with CDI to two control groups: not tested patients and patients suspected of having CDI, but with a negative test. Methods: We conducted a case-control study of adult patients hospitalized in internal medicine department of tertiary teaching hospital between 2005–2010 for at least three days. Controls from each of two groups (negative for CDI and non-tested) were individually matched (1∶1) to cases by primary diagnosis, Charlson comorbidity index, year of hospitalization and gender. Primary outcomes were diagnoses of International Classification of Diseases (ICD-9)–coded CDI occurring 72 hours or more after admission. Results: Patients with CDI were similar to controls with a negative test, while controls without CDI testing had lower clinical severity. In multivariable analysis, treatment by acid suppression medications was associated with CDI compared to those who were not tested (OR = 1.88, p-value = 0.032). Conversely, use of acid suppression medications in those who tested negative for the infection was not associated with CDI risk as compared to the cases (OR = 0.66; p = 0.059). Conclusions: These findings suggest that the reported epidemiologic associations between use of acid suppression medications and CDI risk may be spurious. The control group choice has an important impact on the results. Clinical differences between the patients with CDI and those not tested and not suspected of having the infection may explain the different conclusions regarding the acid suppression effect on CDI risk

The role of cardiac troponin I as a prognosticator in critically ill medical patients: a prospective observational cohort study

INTRODUCTION: Myocardial injury is frequently unrecognized in intensive care unit (ICU) patients. Cardiac troponin I (cTnI), a surrogate of myocardial injury, has been shown to correlate with outcome in selected groups of patients. We wanted to determine if cTnI level measured upon admission is an independent predictor of mortality in a heterogeneous group of critically ill medical patients. METHODS: We conducted a prospective observational cohort study; 128 consecutive patients admitted to a medical ICU at a tertiary university hospital were enrolled. cTnI levels were measured within 6 h of admission and were considered positive (>0.7 ng/ml) or negative. A variety of clinical and laboratory variables were recorded. RESULTS: Both cTnI positive and negative groups were similar in terms of age, sex and pre-admission co-morbidity. In a univariate analysis, positive cTnI was associated with increased mortality (OR 7.0, 95% CI 2.44–20.5, p < 0.001), higher Acute Physiology and Chronic Health Evaluation (APACHE) II scores and a higher rate of multi-organ failure and sepsis. This association between cTnI and mortality was more pronounced among elderly patients (>65 years of age). Multivariate analysis controlling for APACHE II score revealed that elevated cTnI levels are not independently associated with 28-day mortality. CONCLUSION: In critically ill medical patients, elevated cTnI level measured upon admission is associated with increased mortality rate. cTnI does not independently contribute to the prediction of 28-day mortality beyond that provided by APACHE II

The Esophageal Pressure-Guided Ventilation 2 (EPVent2) trial protocol: a multicentre, randomised clinical trial of mechanical ventilation guided by transpulmonary pressure

Introduction: Optimal ventilator management for patients with acute respiratory distress syndrome (ARDS) remains uncertain. Lower tidal volume ventilation appears to be beneficial, but optimal management of positive end-expiratory pressure (PEEP) remains unclear. The Esophageal Pressure-Guided Ventilation 2 Trial (EPVent2) aims to examine the impact of mechanical ventilation directed at maintaining a positive transpulmonary pressure (PTP) in patients with moderate-to-severe ARDS. Methods and analysis EPVent2 is a multicentre, prospective, randomised, phase II clinical trial testing the hypothesis that the use of a PTP-guided ventilation strategy will lead to improvement in composite outcomes of mortality and time off the ventilator at 28 days as compared with a high-PEEP control. This study will enrol 200 study participants from 11 hospitals across North America. The trial will utilise a primary composite end point that incorporates death and days off the ventilator at 28 days to test the primary hypothesis that adjusting ventilator pressure to achieve positive PTP values will result in improved mortality and ventilator-free days. Ethics and dissemination Safety oversight will be under the direction of an independent Data and Safety Monitoring Board (DSMB). Approval of the protocol was obtained from the DSMB prior to enrolling the first study participant. Approvals of the protocol as well as informed consent documents were also obtained from the Institutional Review Board of each participating institution prior to enrolling study participants at each respective site. The findings of this investigation, as well as associated ancillary studies, will be disseminated in the form of oral and abstract presentations at major national and international medical specialty meetings. The primary objective and other significant findings will also be presented in manuscript form. All final, published manuscripts resulting from this protocol will be submitted to PubMed Central in accordance with the National Institute of Health Public Access Policy. Trial registration number ClinicalTrials.gov under number NCT01681225

Hospital volume and mortality after transjugular intrahepatic portosystemic shunt creation in the United States

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141487/1/hep29354-sup-0001-suppinfo1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141487/2/hep29354_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141487/3/hep29354.pd

Attitudes toward risk among emergency physicians and advanced practice clinicians in Massachusetts

Objective Risk aversion is a personality trait influential to decision making in medicine. Little is known about how emergency department (ED) clinicians differ in their attitudes toward risk taking. Methods We conducted a cross-sectional survey of practicing ED clinicians (physicians and advanced practice clinicians [APCs]) in Massachusetts using the following 4 existing validated scales: the Risk-Taking Scale (RTS), Stress from Uncertainty Scale (SUS), the Fear of Malpractice Scale (FMS), and the Need for (Cognitive) Closure Scale (NCC). We used Cronbach\u27s α to assess the reliability of each scale and performed multivariable linear regressions to analyze the association between the score for each scale and clinician characteristics. Results Of 1458 ED clinicians recruited for participation, 1116 (76.5%) responded from 93% of acute care hospitals in Massachusetts. Each of the 4 scales demonstrated high internal consistency reliability with Cronbach\u27s αs ranging from 0.76 to 0.92. The 4 scales also were moderately correlated with one another (0.08 to 0.54; all P \u3c 0.05). The multivariable results demonstrated differences between physicians and APCs, with physicians showing a greater tolerance for risk or uncertainty (NCC difference, −3.58 [95% confidence interval, CI, −5.26 to −1.90]; SUS difference, −3.14 [95% CI: −4.99 to −1.29]) and a higher concern about malpractice (FMS difference, 1.14 [95% CI, 0.11–2.17]). Differences were also observed based on clinician age (a proxy for years of experience), with greater age associated with greater tolerance of risk or uncertainty (age older than 50 years compared with age 35 years and younger; NCC difference, −2.84 [95% CI, −4.69 to −1.00]; SUS difference, −4.71 [95% CI, −6,74 to −2.68]) and less concern about malpractice (FMS difference, −3.19 [95% CI, −4.31 to −2.06]). There were no appreciable differences based on sex, and there were no consistent associations between scale scores and the practice and payment characteristics assessed. Conclusion We found that risk attitudes of ED clinicians were associated with type of training (physician vs APC) and age (experience). These differences suggest one possible explanation for the observed differences in decision making

Estimation of hourly near surface air temperature across Israel using an ensemble model

Mapping of near-surface air temperature (Ta) at high spatio-temporal resolution is essential for unbiased assessment of human health exposure to temperature extremes, not least given the observed trend of urbanization and global climate change. Data constraints have led previous studies to focus merely on daily Ta metrics, rather than hourly ones, making them insufficient for intra-day assessment of health exposure. In this study, we present a three-stage machine learning-based ensemble model to estimate hourly Ta at a high spatial resolution of 1 × 1 km2, incorporating remotely sensed surface skin temperature (Ts) from geostationary satellites, reanalysis synoptic variables, and observations from weather stations, as well as auxiliary geospatial variables, which account for spatio-temporal variability of Ta. The Stage 1 model gap-fills hourly Ts at 4 × 4 km2 from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), which are subsequently fed into the Stage 2 model to estimate hourly Ta at the same spatio-temporal resolution. The Stage 3 model downscales the residuals between estimated and measured Ta to a grid of 1 × 1 km2, taking into account additionally the monthly diurnal pattern of Ts derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) data. In each stage, the ensemble model synergizes estimates from the constituent base learners—random forest (RF) and extreme gradient boosting (XGBoost)—by applying a geographically weighted generalized additive model (GAM), which allows the weights of results from individual models to vary over space and time. Demonstrated for Israel for the period 2004–2017, the proposed ensemble model outperformed each of the two base learners. It also attained excellent five-fold cross-validated performance, with overall root mean square error (RMSE) of 0.8 and 0.9 °C, mean absolute error (MAE) of 0.6 and 0.7 °C, and R2 of 0.95 and 0.98 in Stage 1 and Stage 2, respectively. The Stage 3 model for downscaling Ta residuals to 1 km MODIS grids achieved overall RMSE of 0.3 °C, MAE of 0.5 °C, and R2 of 0.63. The generated hourly 1 × 1 km2 Ta thus serves as a foundation for monitoring and assessing human health exposure to temperature extremes at a larger geographical scale, helping to further minimize exposure misclassification in epidemiological studies

Estimation of hourly near surface air temperature across Israel using an ensemble model

Mapping of near-surface air temperature (Ta) at high spatio-temporal resolution is essential for unbiased assessment of human health exposure to temperature extremes, not least given the observed trend of urbanization and global climate change. Data constraints have led previous studies to focus merely on daily Ta metrics, rather than hourly ones, making them insufficient for intra-day assessment of health exposure. In this study, we present a three-stage machine learning-based ensemble model to estimate hourly Ta at a high spatial resolution of 1 &times; 1 km2, incorporating remotely sensed surface skin temperature (Ts) from geostationary satellites, reanalysis synoptic variables, and observations from weather stations, as well as auxiliary geospatial variables, which account for spatio-temporal variability of Ta. The Stage 1 model gap-fills hourly Ts at 4 &times; 4 km2 from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), which are subsequently fed into the Stage 2 model to estimate hourly Ta at the same spatio-temporal resolution. The Stage 3 model downscales the residuals between estimated and measured Ta to a grid of 1 &times; 1 km2, taking into account additionally the monthly diurnal pattern of Ts derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) data. In each stage, the ensemble model synergizes estimates from the constituent base learners&mdash;random forest (RF) and extreme gradient boosting (XGBoost)&mdash;by applying a geographically weighted generalized additive model (GAM), which allows the weights of results from individual models to vary over space and time. Demonstrated for Israel for the period 2004&ndash;2017, the proposed ensemble model outperformed each of the two base learners. It also attained excellent five-fold cross-validated performance, with overall root mean square error (RMSE) of 0.8 and 0.9 &deg;C, mean absolute error (MAE) of 0.6 and 0.7 &deg;C, and R2 of 0.95 and 0.98 in Stage 1 and Stage 2, respectively. The Stage 3 model for downscaling Ta residuals to 1 km MODIS grids achieved overall RMSE of 0.3 &deg;C, MAE of 0.5 &deg;C, and R2 of 0.63. The generated hourly 1 &times; 1 km2 Ta thus serves as a foundation for monitoring and assessing human health exposure to temperature extremes at a larger geographical scale, helping to further minimize exposure misclassification in epidemiological studies

The Effect of Hospital Volume on Mortality in Patients Admitted with Severe Sepsis

Importance The association between hospital volume and inpatient mortality for severe sepsis is unclear. Objective: To assess the effect of severe sepsis case volume and inpatient mortality. Design Setting and Participants Retrospective cohort study from 646,988 patient discharges with severe sepsis from 3,487 hospitals in the Nationwide Inpatient Sample from 2002 to 2011. Exposures The exposure of interest was the mean yearly sepsis case volume per hospital divided into tertiles. Main Outcomes and Measures Inpatient mortality. Results: Compared with the highest tertile of severe sepsis volume (>60 cases per year), the odds ratio for inpatient mortality among persons admitted to hospitals in the lowest tertile (≤10 severe sepsis cases per year) was 1.188 (95% CI: 1.074–1.315), while the odds ratio was 1.090 (95% CI: 1.031–1.152) for patients admitted to hospitals in the middle tertile. Similarly, improved survival was seen across the tertiles with an adjusted inpatient mortality incidence of 35.81 (95% CI: 33.64–38.03) for hospitals with the lowest volume of severe sepsis cases and a drop to 32.07 (95% CI: 31.51–32.64) for hospitals with the highest volume. Conclusions and Relevance We demonstrate an association between a higher severe sepsis case volume and decreased mortality. The need for a systems-based approach for improved outcomes may require a high volume of severely septic patients

Trends in Severity of Illness on ICU Admission and Mortality among the Elderly

Background: There is an increase in admission rate for elderly patients to the ICU. Mortality rates are lower when more liberal ICU admission threshold are compared to more restrictive threshold. We sought to describe the temporal trends in elderly admissions and outcomes in a tertiary hospital before and after the addition of an 8-bed medical ICU. Methods: We conducted a retrospective analysis of a comprehensive longitudinal ICU database, from a large tertiary medical center, examining trends in patients’ characteristics, severity of illness, intensity of care and mortality rates over the years 2001–2008. The study population consisted of elderly patients and the primary endpoints were 28 day and one year mortality from ICU admission. Results: Between the years 2001 and 2008, 7,265 elderly patients had 8,916 admissions to ICU. The rate of admission to the ICU increased by 5.6% per year. After an eight bed MICU was added, the severity of disease on ICU admission dropped significantly and crude mortality rates decreased thereafter. Adjusting for severity of disease on presentation, there was a decreased mortality at 28- days but no improvement in one- year survival rates for elderly patient admitted to the ICU over the years of observation. Hospital mortality rates have been unchanged from 2001 through 2008. Conclusion: In a high capacity ICU bed hospital, there was a temporal decrease in severity of disease on ICU admission, more so after the addition of additional medical ICU beds. While crude mortality rates decreased over the study period, adjusted one-year survival in ICU survivors did not change with the addition of ICU beds. These findings suggest that outcome in critically ill elderly patients may not be influenced by ICU admission. Adding additional ICU beds to deal with the increasing age of the population may therefore not be effective