Open data from the third observing run of LIGO, Virgo, KAGRA and GEO

The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in April of 2019 and lasting six months, O3b starting in November of 2019 and lasting five months, and O3GK starting in April of 2020 and lasting 2 weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main dataset, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages.Comment: 27 pages, 3 figure

Validation of a claims-based algorithm identifying eligible study subjects in the ADAPTABLE pragmatic clinical trial

Objective: Validate an algorithm that uses administrative claims data to identify eligible study subjects for the ADAPTABLE (Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness) pragmatic clinical trial (PCT). Materials and methods: This study used medical records from a random sample of patients identified as eligible for the ADAPTABLE trial. The inclusion criteria for ADAPTABLE were a history of acute myocardial infarction (AMI) or percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG), or other coronary artery disease (CAD), plus at least one of several risk-enrichment factors. Exclusion criteria included a history of bleeding disorders or aspirin allergy. Using a claims-based algorithm, based on International Classification of Diseases, 9th Edition, Clinical Modification (ICD-9-CM) and 10th Edition (ICD-10) codes and Current Procedural Terminology (CPT) codes, we identified patients eligible for the PCT. The primary outcome was the positive predictive value (PPV) of the identification algorithm: the proportion of sampled patients whose medical records confirmed their ADAPTABLE study eligibility. Exact 95% confidence limits for binomial random variables were calculated for the PPV estimates. Results: Of the 185 patients whose medical records were reviewed, 168 (90.8%; 95% Confidence Interval: 85.7%, 94.6%) were confirmed study eligible. This proportion did not differ between patients identified with codes for AMI and patients identified with codes for PCI or CABG. Conclusion: The estimated PPV was similar to those in claims-based identification of drug safety surveillance events, indicating that administrative claims data can accurately identify study-eligible subjects for pragmatic clinical trials. Keywords: Cardiovascular disease, Aspirin, Real-world evidence, Acute myocardial infarction, Computable phenotyp

Psychometric assessment of the Persian translation of the Interpersonal Mindfulness Scale with undergraduate students

Interpersonal mindfulness is a construct that significantly contributes to social interaction. To date, no validated measure assessing interpersonal mindfulness has been developed in Iran. Therefore, the aim of this study was to translate and validate the Interpersonal Mindfulness Scale (IMS) among Iranian undergraduate students. Participants in the study (370 undergraduate students; 220 females) from the Azad University completed the translated IMS, the Five Facet Mindfulness Questionnaire, and the Inventory of Interpersonal Problems Scale. The translated measure demonstrated acceptable face validity. All items had acceptable content validity and were deemed essential to the scale. The results of a Confirmatory Factor Analysis (CFA) confirmed a scale with four subscales (presence, awareness of self and others, non-judgmental acceptance, and non-reactivity), with acceptable internal consistency. The findings support the psychometric properties of the Persian translated Interpersonal Mindfulness Scale, which could be used to measure interpersonal mindfulness among undergraduate students in Iran

Post-Authorization Safety Studies of Acute Liver Injury and Severe Complications of Urinary Tract Infection in Patients with Type 2 Diabetes Exposed to Dapagliflozin in a Real-World Setting

INTRODUCTION: At the time of dapagliflozin\u27s approval in Europe (2012) to treat patients with type 2 diabetes mellitus, concerns regarding acute liver injury and severe complications of urinary tract infection (sUTI) led to two post-authorization safety (PAS) studies of these outcomes to monitor the safety of dapagliflozin in real-world use. OBJECTIVE: To investigate the incidence of hospitalization for acute liver injury (hALI) or sUTI (pyelonephritis or urosepsis) among patients initiating dapagliflozin compared with other glucose-lowering drugs (GLDs). METHODS: These two noninterventional cohort studies identified initiators of dapagliflozin and comparator GLDs in November 2012-February 2019 using data from three longitudinal, population-based data sources: Clinical Practice Research Datalink (UK), the HealthCore Integrated Research Database (USA), and the Medicare database (USA). Outcomes (hALI and sUTI) were identified with electronic algorithms. Incidence rates were estimated by exposure group. Incidence rate ratios (IRRs) were calculated comparing dapagliflozin to comparator GLDs, using propensity score trimming and stratification to address confounding. The sUTI analyses were conducted separately by sex. RESULTS: In all data sources, hALI and sUTI incidence rates were generally lower in dapagliflozin initiators than comparator GLD initiators. The adjusted IRR (95% confidence interval) pooled across data sources for hALI was 0.85 (0.59-1.24) and for sUTI was 0.76 (0.60-0.96) in females and 0.74 (0.56-1.00) in males. Findings from sensitivity analyses were largely consistent with the primary analyses. CONCLUSIONS: These real-world studies do not suggest increased risks of hALI or sUTI, and they suggest a potential decreased risk of sUTI with dapagliflozin exposure compared with other GLDs

Post-Authorization Safety Study of Hospitalization for Acute Kidney Injury in Patients with Type 2 Diabetes Exposed to Dapagliflozin in a Real-World Setting

INTRODUCTION: Dapagliflozin is a sodium-glucose cotransporter 2 inhibitor approved to treat type 2 diabetes mellitus (T2DM), among other conditions. When dapagliflozin was approved in Europe for treating T2DM (2012), potential safety concerns regarding its effect on kidney function resulted in this post-authorization safety study to assess hospitalization for acute kidney injury (hAKI) among dapagliflozin initiators in a real-world setting. OBJECTIVE: The aim of this study was to evaluate the incidence of hAKI in adults with T2DM initiating dapagliflozin compared with other glucose-lowering drugs (GLDs). METHODS: This noninterventional cohort study identified new users of dapagliflozin and comparator GLDs from November 2012 to February 2019 from three longitudinal, population-based data sources: Clinical Practice Research Datalink (CPRD; United Kingdom), the HealthCore Integrated Research Database (HIRD; United States [US]), and Medicare (US). Electronic algorithms identified occurrences of hAKI, from which a sample underwent validation. Incidence rates for hAKI were calculated, and incidence rate ratios (IRRs) compared hAKI in dapagliflozin with comparator GLDs. Propensity score trimming and stratification were conducted for confounding adjustment. RESULTS: In all data sources, dapagliflozin initiators had a lower hAKI incidence rate than comparator GLD initiators (adjusted IRRs: CPRD, 0.44 [95% confidence interval (CI), 0.22-0.86]; HIRD, 0.76 [95% CI, 0.62-0.93]; Medicare, 0.69 [95% CI, 0.59-0.79]). The adjusted IRR pooled across the data sources was 0.70 (95% CI, 0.62-0.78). Results from sensitivity and stratified analyses were consistent with the primary analysis. CONCLUSIONS: This study, with \u3e 34,000 person-years of real-world dapagliflozin exposure, suggests a decreased risk of hAKI in patients with T2DM exposed to dapagliflozin, aligning with results from dapagliflozin clinical trials. STUDY REGISTRATION: European Union Post-Authorisation Studies Register, EUPAS 11684; ClinicalTrials.gov, NCT02695082

The comparative genomics and complex population history of Papio baboons

Recent studies suggest that closely related species can accumulate substantial genetic and phenotypic differences despite ongoing gene flow, thus challenging traditional ideas regarding the genetics of speciation. Baboons (genus Papio) are Old World monkeys consisting of six readily distinguishable species. Baboon species hybridize in the wild, and prior data imply a complex history of differentiation and introgression. We produced a reference genome assembly for the olive baboon (Papio anubis) and whole-genome sequence data for all six extant species. We document multiple episodes of admixture and introgression during the radiation of Papio baboons, thus demonstrating their value as a model of complex evolutionary divergence, hybridization, and reticulation. These results help inform our understanding of similar cases, including modern humans, Neanderthals, Denisovans, and other ancient hominins

Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome Associated with COVID-19: An Emulated Target Trial Analysis

International audienc

Characteristics, management, and prognosis of elderly patients with COVID-19 admitted in the ICU during the first wave: insights from the COVID-ICU study

International audienceBackground: The COVID-19 pandemic is a heavy burden in terms of health care resources. Future decision-making policies require consistent data on the management and prognosis of the older patients (> 70 years old) with COVID-19 admitted in the intensive care unit (ICU). Methods: Characteristics, management, and prognosis of critically ill old patients (> 70 years) were extracted from the international prospective COVID-ICU database. A propensity score weighted-comparison evaluated the impact of intubation upon admission on Day-90 mortality. Results: The analysis included 1199 (28% of the COVID-ICU cohort) patients (median [interquartile] age 74 [72–78] years). Fifty-three percent, 31%, and 16% were 70–74, 75–79, and over 80 years old, respectively. The most frequent comorbidities were chronic hypertension (62%), diabetes (30%), and chronic respiratory disease (25%). Median Clinical Frailty Scale was 3 (2–3). Upon admission, the PaO2/FiO2 ratio was 154 (105–222). 740 (62%) patients were intubated on Day-1 and eventually 938 (78%) during their ICU stay. Overall Day-90 mortality was 46% and reached 67% among the 193 patients over 80 years old. Mortality was higher in older patients, diabetics, and those with a lower PaO2/FiO2 ratio upon admission, cardiovascular dysfunction, and a shorter time between first symptoms and ICU admission. In propensity analysis, early intubation at ICU admission was associated with a significantly higher Day-90 mortality (42% vs 28%; hazard ratio 1.68; 95% CI 1.24–2.27; p < 0·001). Conclusion: Patients over 70 years old represented more than a quarter of the COVID-19 population admitted in the participating ICUs during the first wave. Day-90 mortality was 46%, with dismal outcomes reported for patients older than 80 years or those intubated upon ICU admission

Predicting 90-day survival of patients with COVID-19: Survival of Severely Ill COVID (SOSIC) scores

International audienceBackground Predicting outcomes of critically ill intensive care unit (ICU) patients with coronavirus-19 disease (COVID-19) is a major challenge to avoid futile, and prolonged ICU stays. Methods The objective was to develop predictive survival models for patients with COVID-19 after 1-to-2 weeks in ICU. Based on the COVID–ICU cohort, which prospectively collected characteristics, management, and outcomes of critically ill patients with COVID-19. Machine learning was used to develop dynamic, clinically useful models able to predict 90-day mortality using ICU data collected on day (D) 1, D7 or D14. Results Survival of Severely Ill COVID (SOSIC)-1, SOSIC-7, and SOSIC-14 scores were constructed with 4244, 2877, and 1349 patients, respectively, randomly assigned to development or test datasets. The three models selected 15 ICU-entry variables recorded on D1, D7, or D14. Cardiovascular, renal, and pulmonary functions on prediction D7 or D14 were among the most heavily weighted inputs for both models. For the test dataset, SOSIC-7’s area under the ROC curve was slightly higher (0.80 [0.74–0.86]) than those for SOSIC-1 (0.76 [0.71–0.81]) and SOSIC-14 (0.76 [0.68–0.83]). Similarly, SOSIC-1 and SOSIC-7 had excellent calibration curves, with similar Brier scores for the three models. Conclusion The SOSIC scores showed that entering 15 to 27 baseline and dynamic clinical parameters into an automatable XGBoost algorithm can potentially accurately predict the likely 90-day mortality post-ICU admission (sosic.shinyapps.io/shiny). Although external SOSIC-score validation is still needed, it is an additional tool to strengthen decisions about life-sustaining treatments and informing family members of likely prognosis

Characteristics and prognosis of bloodstream infection in patients with COVID-19 admitted in the ICU: an ancillary study of the COVID-ICU study

International audienceBackground Patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-COV 2) and requiring intensive care unit (ICU) have a high incidence of hospital-acquired infections; however, data regarding hospital acquired bloodstream infections (BSI) are scarce. We aimed to investigate risk factors and outcome of BSI in critically ill coronavirus infectious disease-19 (COVID-19) patients. Patients and methods We performed an ancillary analysis of a multicenter prospective international cohort study (COVID-ICU study) that included 4010 COVID-19 ICU patients. For the present analysis, only those with data regarding primary outcome (death within 90 days from admission) or BSI status were included. Risk factors for BSI were analyzed using Fine and Gray competing risk model. Then, for outcome comparison, 537 BSI-patients were matched with 537 controls using propensity score matching. Results Among 4010 included patients, 780 (19.5%) acquired a total of 1066 BSI (10.3 BSI per 1000 patients days at risk) of whom 92% were acquired in the ICU. Higher SAPS II, male gender, longer time from hospital to ICU admission and antiviral drug before admission were independently associated with an increased risk of BSI, and interestingly, this risk decreased over time. BSI was independently associated with a shorter time to death in the overall population (adjusted hazard ratio (aHR) 1.28, 95% CI 1.05–1.56) and, in the propensity score matched data set, patients with BSI had a higher mortality rate (39% vs 33% p = 0.036). BSI accounted for 3.6% of the death of the overall population. Conclusion COVID-19 ICU patients have a high risk of BSI, especially early after ICU admission, risk that increases with severity but not with corticosteroids use. BSI is associated with an increased mortality rate