Unidimensional Models Do Not Fit Unidimensional Mixed Format Data Better than Multidimensional Models

This dissertation examines the scaling of large scale assessments containing both dichotomous and polytomous items, mixed format assessments. Because large scale assessments are generally built to measure one construct, e.g. eighth grade mathematics, unidimensional data was generated to simulate a mixed format assessment. The test length, number of polytomous to dichotomous items per assessment and the discrimination level between dichotomous and polytomous items were varied in this study. There were five item combinations and two level of discrimination defined. The goal of this dissertation was to compare the fit of the generated data to three different Item Response Theory models; one unidimensional and two multidimensional. The first model used to fit the data was the same model type used to generate the data; a 3PL IRT model in combination with the Generalized Partial Credit model. The second model was the Hierarchical MIRT Model. The final model was the bi-factor model. The research questions examined in this study were; (1) Which of the models achieves the best model fit across simulation conditions?, and (2) Do the variables of item combination or discrimination affect the model fit? The study showed that the bi-factor model fit unidimensional data, in mixed format, better than either the unidimensional or the hierarchical MIRT models. The criterion used to make this determination was the Bayesian convergence criterions; BIC, DIC and AIC. Overall, the bi-factor model fit the unidimensional mixed format data better than the generating model fit the data. The hierarchical MIRT model did not fit the data very well, and in a few cases, did not converge. The more polytomous item included on the assessment the better the bi-factor model improved overall fit over the unidimensional model. This result suggests that noise in the data from mixed format assessments can cause the unidimensional models to fail to fail to fit the data. This study illustrates the format alone can create the appearance of dimensionality. However since the data was generated as unidimensional, this format dimensionality affect was an attribute of the data alone, not of items or examinees interactions with the items. Mixed format assessments create an artifact in the data that causes the data to factor into dimensions that are not actually present. It appears there is noise in the data of mixed format assessment that needs to accounted for when scaling

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Epidemiological characteristics, practice of ventilation, and clinical outcome in patients at risk of acute respiratory distress syndrome in intensive care units from 16 countries (PRoVENT): an international, multicentre, prospective study

Background Scant information exists about the epidemiological characteristics and outcome of patients in the intensive care unit (ICU) at risk of acute respiratory distress syndrome (ARDS) and how ventilation is managed in these individuals. We aimed to establish the epidemiological characteristics of patients at risk of ARDS, describe ventilation management in this population, and assess outcomes compared with people at no risk of ARDS. Methods PRoVENT (PRactice of VENTilation in critically ill patients without ARDS at onset of ventilation) is an international, multicentre, prospective study undertaken at 119 ICUs in 16 countries worldwide. All patients aged 18 years or older who were receiving mechanical ventilation in participating ICUs during a 1-week period between January, 2014, and January, 2015, were enrolled into the study. The Lung Injury Prediction Score (LIPS) was used to stratify risk of ARDS, with a score of 4 or higher defining those at risk of ARDS. The primary outcome was the proportion of patients at risk of ARDS. Secondary outcomes included ventilatory management (including tidal volume [VT] expressed as mL/kg predicted bodyweight [PBW], and positive end-expiratory pressure [PEEP] expressed as cm H2O), development of pulmonary complications, and clinical outcomes. The PRoVENT study is registered at ClinicalTrials.gov, NCT01868321. The study has been completed. Findings Of 3023 patients screened for the study, 935 individuals fulfilled the inclusion criteria. Of these critically ill patients, 282 were at risk of ARDS (30%, 95% CI 27\u201333), representing 0\ub714 cases per ICU bed over a 1-week period. VT was similar for patients at risk and not at risk of ARDS (median 7\ub76 mL/kg PBW [IQR 6\ub77\u20139\ub71] vs 7\ub79 mL/kg PBW [6\ub78\u20139\ub71]; p=0\ub7346). PEEP was higher in patients at risk of ARDS compared with those not at risk (median 6\ub70 cm H2O [IQR 5\ub70\u20138\ub70] vs 5\ub70 cm H2O [5\ub70\u20137\ub70]; p<0\ub70001). The prevalence of ARDS in patients at risk of ARDS was higher than in individuals not at risk of ARDS (19/260 [7%] vs 17/556 [3%]; p=0\ub7004). Compared with individuals not at risk of ARDS, patients at risk of ARDS had higher in-hospital mortality (86/543 [16%] vs 74/232 [32%]; p<0\ub70001), ICU mortality (62/533 [12%] vs 66/227 [29%]; p<0\ub70001), and 90-day mortality (109/653 [17%] vs 88/282 [31%]; p<0\ub70001). VT did not differ between patients who did and did not develop ARDS (p=0\ub7471 for those at risk of ARDS; p=0\ub7323 for those not at risk). Interpretation Around a third of patients receiving mechanical ventilation in the ICU were at risk of ARDS. Pulmonary complications occur frequently in patients at risk of ARDS and their clinical outcome is worse compared with those not at risk of ARDS. There is potential for improvement in the management of patients without ARDS. Further refinements are needed for prediction of ARDS

Epidemiological characteristics, practice of ventilation, and clinical outcome in patients at risk of acute respiratory distress syndrome in intensive care units from 16 countries (PRoVENT): an international, multicentre, prospective study

Background Scant information exists about the epidemiological characteristics and outcome of patients in the intensive care unit (ICU) at risk of acute respiratory distress syndrome (ARDS) and how ventilation is managed in these individuals. We aimed to establish the epidemiological characteristics of patients at risk of ARDS, describe ventilation management in this population, and assess outcomes compared with people at no risk of ARDS. Methods PRoVENT (PRactice of VENTilation in critically ill patients without ARDS at onset of ventilation) is an international, multicentre, prospective study undertaken at 119 ICUs in 16 countries worldwide. All patients aged 18 years or older who were receiving mechanical ventilation in participating ICUs during a 1-week period between January, 2014, and January, 2015, were enrolled into the study. The Lung Injury Prediction Score (LIPS) was used to stratify risk of ARDS, with a score of 4 or higher defining those at risk of ARDS. The primary outcome was the proportion of patients at risk of ARDS. Secondary outcomes included ventilatory management (including tidal volume [VT] expressed as mL/kg predicted bodyweight [PBW], and positive end-expiratory pressure [PEEP] expressed as cm H2O), development of pulmonary complications, and clinical outcomes. The PRoVENT study is registered at ClinicalTrials.gov, NCT01868321. The study has been completed. Findings Of 3023 patients screened for the study, 935 individuals fulfilled the inclusion criteria. Of these critically ill patients, 282 were at risk of ARDS (30%, 95% CI 27–33), representing 0·14 cases per ICU bed over a 1-week period. VT was similar for patients at risk and not at risk of ARDS (median 7·6 mL/kg PBW [IQR 6·7–9·1] vs 7·9 mL/kg PBW [6·8–9·1]; p=0·346). PEEP was higher in patients at risk of ARDS compared with those not at risk (median 6·0 cm H2O [IQR 5·0–8·0] vs 5·0 cm H2O [5·0–7·0]; p<0·0001). The prevalence of ARDS in patients at risk of ARDS was higher than in individuals not at risk of ARDS (19/260 [7%] vs 17/556 [3%]; p=0·004). Compared with individuals not at risk of ARDS, patients at risk of ARDS had higher in-hospital mortality (86/543 [16%] vs 74/232 [32%]; p<0·0001), ICU mortality (62/533 [12%] vs 66/227 [29%]; p<0·0001), and 90-day mortality (109/653 [17%] vs 88/282 [31%]; p<0·0001). VT did not differ between patients who did and did not develop ARDS (p=0·471 for those at risk of ARDS; p=0·323 for those not at risk). Interpretation Around a third of patients receiving mechanical ventilation in the ICU were at risk of ARDS. Pulmonary complications occur frequently in patients at risk of ARDS and their clinical outcome is worse compared with those not at risk of ARDS. There is potential for improvement in the management of patients without ARDS. Further refinements are needed for prediction of ARDS

Geoeconomic variations in epidemiology, ventilation management, and outcomes in invasively ventilated intensive care unit patients without acute respiratory distress syndrome: a pooled analysis of four observational studies

Background: Geoeconomic variations in epidemiology, the practice of ventilation, and outcome in invasively ventilated intensive care unit (ICU) patients without acute respiratory distress syndrome (ARDS) remain unexplored. In this analysis we aim to address these gaps using individual patient data of four large observational studies. Methods: In this pooled analysis we harmonised individual patient data from the ERICC, LUNG SAFE, PRoVENT, and PRoVENT-iMiC prospective observational studies, which were conducted from June, 2011, to December, 2018, in 534 ICUs in 54 countries. We used the 2016 World Bank classification to define two geoeconomic regions: middle-income countries (MICs) and high-income countries (HICs). ARDS was defined according to the Berlin criteria. Descriptive statistics were used to compare patients in MICs versus HICs. The primary outcome was the use of low tidal volume ventilation (LTVV) for the first 3 days of mechanical ventilation. Secondary outcomes were key ventilation parameters (tidal volume size, positive end-expiratory pressure, fraction of inspired oxygen, peak pressure, plateau pressure, driving pressure, and respiratory rate), patient characteristics, the risk for and actual development of acute respiratory distress syndrome after the first day of ventilation, duration of ventilation, ICU length of stay, and ICU mortality. Findings: Of the 7608 patients included in the original studies, this analysis included 3852 patients without ARDS, of whom 2345 were from MICs and 1507 were from HICs. Patients in MICs were younger, shorter and with a slightly lower body-mass index, more often had diabetes and active cancer, but less often chronic obstructive pulmonary disease and heart failure than patients from HICs. Sequential organ failure assessment scores were similar in MICs and HICs. Use of LTVV in MICs and HICs was comparable (42·4% vs 44·2%; absolute difference -1·69 [-9·58 to 6·11] p=0·67; data available in 3174 [82%] of 3852 patients). The median applied positive end expiratory pressure was lower in MICs than in HICs (5 [IQR 5-8] vs 6 [5-8] cm H2O; p=0·0011). ICU mortality was higher in MICs than in HICs (30·5% vs 19·9%; p=0·0004; adjusted effect 16·41% [95% CI 9·52-23·52]; p<0·0001) and was inversely associated with gross domestic product (adjusted odds ratio for a US$10 000 increase per capita 0·80 [95% CI 0·75-0·86]; p<0·0001). Interpretation: Despite similar disease severity and ventilation management, ICU mortality in patients without ARDS is higher in MICs than in HICs, with a strong association with country-level economic status