Introduction: Community acquired pneumonia (CAP) is the most common infectious reason for admission to the Intensive Care Unit (ICU). The GenOSept study was designed to determine genetic influences on sepsis outcome. Phenotypic data was recorded using a robust clinical database allowing a contemporary analysis of the clinical characteristics, microbiology, outcomes and independent risk factors in patients with severe CAP admitted to ICUs across Europe. Methods: Kaplan-Meier analysis was used to determine mortality rates. A Cox Proportional Hazards (PH) model was used to identify variables independently associated with 28-day and six-month mortality. Results: Data from 1166 patients admitted to 102 centres across 17 countries was extracted. Median age was 64 years, 62% were male. Mortality rate at 28 days was 17%, rising to 27% at six months. Streptococcus pneumoniae was the commonest organism isolated (28% of cases) with no organism identified in 36%. Independent risk factors associated with an increased risk of death at six months included APACHE II score (hazard ratio, HR, 1.03; confidence interval, CI, 1.01-1.05), bilateral pulmonary infiltrates (HR1.44; CI 1.11-1.87) and ventilator support (HR 3.04; CI 1.64-5.62). Haematocrit, pH and urine volume on day one were all associated with a worse outcome. Conclusions: The mortality rate in patients with severe CAP admitted to European ICUs was 27% at six months. Streptococcus pneumoniae was the commonest organism isolated. In many cases the infecting organism was not identified. Ventilator support, the presence of diffuse pulmonary infiltrates, lower haematocrit, urine volume and pH on admission were independent predictors of a worse outcome.

BACKGROUND: Health care worker (HCW) safety is of pivotal importance during a pandemic such as coronavirus disease 2019 (COVID-19), and employee health and well-being ensure functionality of health care institutions. This is particularly true for an intensive care unit (ICU), where highly specialized staff cannot be readily replaced. In the light of lacking evidence for optimal staffing models in a pandemic, we hypothesized that staff shortage can be reduced when staff scheduling takes the epidemiology of a disease into account. METHODS: Various staffing models were constructed, and comprehensive statistical modeling was performed. A typical routine staffing model was defined that assumed full-time employment (40 h/wk) in a 40-bed ICU with a 2:1 patient-to-staff ratio. A pandemic model assumed that staff worked 12-hour shifts for 7 days every other week. Potential in-hospital staff infections were simulated for a total period of 120 days, with a probability of 10%, 25%, and 40% being infected per week when at work. Simulations included the probability of infection at work for a given week, of fatality after infection, and the quarantine time, if infected. RESULTS: Pandemic-adjusted staffing significantly reduced workforce shortage, and the effect progressively increased as the probability of infection increased. Maximum effects were observed at week 4 for each infection probability with a 17%, 32%, and 38% staffing reduction for an infection probability of 0.10, 0.25, and 0.40, respectively. CONCLUSIONS: Staffing along epidemiologic considerations may reduce HCW shortage by leveling the nadir of affected workforce. Although this requires considerable efforts and commitment of staff, it may be essential in an effort to best maintain staff health and operational functionality of health care facilities and systems.

The current COVID-19 pandemic is testing political leaders and healthcare systems worldwide, exposing deficits in crisis communication, leadership, preparedness and flexibility. Extraordinary situations abound, with global supply chains suddenly failing, media communicating contradictory information, and politics playing an increasingly bigger role in shaping each country's response to the crisis. The pandemic threatens not just our health but also our economy, liberty, and privacy. It challenges the speed at which we work, the quality of our research, and the effectiveness of communication within the scientific community. It can impose ethical dilemmas and emotional stress on healthcare workers. Nevertheless, the pandemic also provides an opportunity for healthcare organizations, leaders, and researchers to learn from their mistakes and to place their countries and institutions in a better position to face future challenges.

Introduction: Delays in adequate antimicrobial treatment contribute to high cost and mortality in sepsis. Polymerase chain reaction (PCR) assays are used alongside conventional cultures to accelerate the identification of microorganisms. We analyze the impact on medical outcomes and healthcare costs if improved adequacy of antimicrobial therapy is achieved by providing immediate coverage after positive PCR reports. Methods: A mathematical prediction model describes the impact of PCR-based rapid adjustment of antimicrobial treatment. The model is applied to predict cost and medical outcomes for 221 sepsis episodes of 189 post-surgical and intensive care unit (ICU) sepsis patients with available PCR data from a prospective, observational trial of a multiplex PCR assay in five hospitals. While this trial demonstrated reduction of inadequate treatment days, data on outcomes associated with reduced inadequate initial antimicrobial treatment had to be obtained from two other, bigger, studies which involved 1,147 (thereof 316 inadequately treated) medical or surgical ICU patients. Our results are reported with the (5% to 95%) percentile ranges from Monte Carlo simulation in which the input parameters were randomly and independently varied according to their statistical characterization in the three underlying studies. The model allows predictions also for different patient groups or PCR assays. Results: A total of 13.1% of PCR tests enabled earlier adequate treatment. We predict that cost for PCR testing (300 €/test) can be fully recovered for patients above 717 € (605 € to 1,710 €) daily treatment cost. A 2.6% (2.0 to 3.2%) absolute reduction of mortality is expected. Cost per incremental survivor calculates to 11,477 € (9,321 € to 14,977 €) and incremental cost-effectiveness ratio to 3,107 € (2,523 € to 4,055 €) per quality-adjusted life-year. Generally, for ICU patients with >25% incidence of inadequate empiric antimicrobial treatment, and at least 15% with a positive blood culture, PCR represents a cost-neutral adjunct method. Conclusions: Rapid PCR identification of microorganisms has the potential to become a cost-effective component for managing sepsis. The prediction model tested with data from three observational trials should be utilized as a framework to deepen insights when integrating more complementary data associated with utilization of molecular assays in the management of sepsis.

Chronic postsurgical pain (CPSP) is defined by pain intensity and pain-related functional interference. This study included measures of function in a composite score of patient-reported outcomes (PROs) to investigate the incidence of CPSP. Registry data were analyzed for PROs 1 day and 12 months postoperatively. Based on pain intensity and pain-related interference with function, patients were allocated to the groups “CPSPF” (at least moderate pain with interference), “mixed” (milder symptoms), and “no CPSPF”. The incidence of CPSPF was compared with CPSP rates referring to published data. Variables associated with the PRO-12 score (composite PROs at 12 months; numeric rating scale 0-10) were analyzed by linear regression analysis. Of 2319 patients, 8.6%, 32.5%, and 58.9% were allocated to the groups CPSPF, mixed, and no CPSPF, respectively. Exclusion of patients whose pain scores did not increase compared with the preoperative status, resulted in a 3.3% incidence. Of the patients without pre-existing pain, 4.1% had CPSPF. Previously published pain cutoffs of numeric rating scale >0, ≥3, or ≥4, used to define CPSP, produced rates of 37.5%, 9.7%, and 5.7%. Pre-existing chronic pain, preoperative opioid medication, and type of surgery were associated with the PRO-12 score (all P < 0.05). Opioid doses and PROs 24 hours postoperatively improved the fit of the regression model. A more comprehensive assessment of pain and interference resulted in lower CPSP rates than previously reported. Although inclusion of CPSP in the ICD-11 is a welcome step, evaluation of pain characteristics would be helpful in differentiation between CPSPF and continuation of pre-existing chronic pain.