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This study investigated the effects of two temporal response properties of the auditory nerve (i.e., neural adaptation and recovery from neural adaptation) on speech perception performance in postlingually deafened adult cochlear implant (CI) users.Study participants included 18 postlingually deafened adults who were Cochlear Nucleus device users with a full electrode array insertion in the test ear(s). Neural adaptation and adaptation recovery of the auditory nerve (AN) were evaluated using electrophysiological measures of the electrically evoked compound action potential (eCAP). The amount of neural adaptation was quantified by the adaptation index within three time windows: 0 to 8.89 (window 1), 44.44 to 50.00 (window 2), and 94.44 to 100.00 ms (window 3). The speed of neural adaptation was estimated using a two-parameter power law function. To evaluate adaptation recovery of the AN, eCAPs to the last pulse of the 100-ms pulse train were recorded at masker-probe-intervals ranging from 1.054 to 256 ms in logarithmic steps. The amount of adaptation recovery was quantified by the adaptation recovery ratio. The time-constant of adaptation recovery was estimated using an exponential function with up to three components. Speech perception performance was evaluated by measuring consonant-nucleus-consonant (CNC) word scores presented in quiet and in speech-shaped noise at a signal-to-noise ratio (SNR) of +10 dB. One-tailed Pearson Product Moment correlation tests were used (1) to assess the associations among parameters of neural adaptation and adaptation recovery and (2) to evaluate the strength of association between these parameters and CNC word scores measured in quiet and in noise. The contributions of different parameters quantifying neural adaptation and adaptation recovery on speech perception scores were evaluated using multivariable linear regression analyses.The Pearson Product Moment correlation coefficient demonstrated a moderate, negative correlation between the speed of adaptation recovery and CNC word scores measured in quiet and in noise. The speed of adaptation recovery accounted for 14.1% of variability in CNC word scores measured in quiet and 16.7% of variability in CNC word scores measured in noise. The correlation strengths between CNC word scores and the adaptation index, the adaptation recovery ratio and the speed of neural adaptation ranged from negligible to weak.The speed of adaptation recovery plays a more important role than other features of neural adaptation and adaptation recovery of the AN in speech perception in postlingually deafened adult CI users. Patients with prolonged adaptation recovery tend to show poorer speech perception performance.

Purpose To estimate the prevalence of current and past COVID-19 in Ohio adults. Methods We used stratified, probability-proportionate-to-size cluster sampling. During July 2020, we enrolled 727 randomly-sampled adult English- and Spanish-speaking participants through a household survey. Participants provided nasopharyngeal swabs and blood samples to detect current and past COVID-19. We used Bayesian latent class models with multilevel regression and poststratification to calculate the adjusted prevalence of current and past COVID-19. We accounted for the potential effects of non-ignorable non-response bias. Results The estimated statewide prevalence of current COVID-19 was 0.9% (95% credible interval: 0.1%-2.0%), corresponding to ∼85,000 prevalent infections (95% credible interval: 6,300-177,000) in Ohio adults during the study period. The estimated statewide prevalence of past COVID-19 was 1.3% (95% credible interval: 0.2%-2.7%), corresponding to ∼118,000 Ohio adults (95% credible interval: 22,000-240,000). Estimates did not change meaningfully due to non-response bias. Conclusions Total COVID-19 cases in Ohio in July 2020 were approximately 3.5 times as high as diagnosed cases. The lack of broad COVID-19 screening in the United States early in the pandemic resulted in a paucity of population-representative prevalence data, limiting the ability to measure the effects of statewide control efforts.

Background Previous epidemiological studies have found positive associations between maternal infections and childhood leukaemia; however, evidence from prospective cohort studies is scarce. We aimed to examine the associations using large-scale prospective data. Methods Data were pooled from six population-based birth cohorts in Australia, Denmark, Israel, Norway, the UK and the USA (recruitment 1950s-2000s). Primary outcomes were any childhood leukaemia and acute lymphoblastic leukaemia (ALL); secondary outcomes were acute myeloid leukaemia (AML) and any childhood cancer. Exposures included maternal self-reported infections [influenza-like illness, common cold, any respiratory tract infection, vaginal thrush, vaginal infections and urinary tract infection (including cystitis)] and infection-associated symptoms (fever and diarrhoea) during pregnancy. Covariate-adjusted hazard ratio (HR) and 95% confidence interval (CI) were estimated using multilevel Cox models. Results Among 312 879 children with a median follow-up of 13.6 years, 167 leukaemias, including 129 ALL and 33 AML, were identified. Maternal urinary tract infection was associated with increased risk of any leukaemia [HR (95% CI) 1.68 (1.10–2.58)] and subtypes ALL [1.49 (0.87–2.56)] and AML [2.70 ([0.93–7.86)], but not with any cancer [1.13 (0.85–1.51)]. Respiratory tract infection was associated with increased risk of any leukaemia [1.57 (1.06–2.34)], ALL [1.43 (0.94–2.19)], AML [2.37 (1.10–5.12)] and any cancer [1.33 (1.09–1.63)]; influenza-like illness showed a similar pattern but with less precise estimates. There was no evidence of a link between other infections and any outcomes. Conclusions Urinary tract and respiratory tract infections during pregnancy may be associated with childhood leukaemia, but the absolute risk is small given the rarity of the outcome.

Objective The objective of this study was to create three point-of-care predictive models for very preterm birth using variables available at three different time points: prior to pregnancy, at the end of the first trimester, and mid-pregnancy. Study Design This is a retrospective cohort study of 359,396 Ohio Medicaid mothers from 2008 to 2015. The last baby for each mother was included in the final dataset. Births prior to 22 weeks were excluded. Multivariable logistic regression was used to create three models. These models were validated on a cohort that was set aside and not part of the model development. The main outcome measure was birth prior to 32 weeks. Results The final dataset contained 359,396 live births with 6,516 (1.81%) very preterm births. All models had excellent calibration. Goodness-of-fit tests suggested strong agreement between the probabilities estimated by the model and the actual outcome experience in the data. The mid-pregnancy model had acceptable discrimination with an area under the receiver operator characteristic curve of approximately 0.75 in both the developmental and validation datasets. Conclusion Using data from a large Ohio Medicaid cohort we developed point-of-care predictive models that could be used before pregnancy, after the first trimester, and in mid-pregnancy to estimate the probability of very preterm birth. Future work is needed to determine how the calculator could be used to target interventions to prevent very preterm birth. Key Points

Evaluating the goodness of fit of logistic regression models is crucial to ensure the accuracy of the estimated probabilities. Unfortunately, such evaluation is problematic in large samples. Because the power of traditional goodness of fit tests increases with the sample size, practically irrelevant discrepancies between estimated and true probabilities are increasingly likely to cause the rejection of the hypothesis of perfect fit in larger and larger samples. This phenomenon has been widely documented for popular goodness of fit tests, such as the Hosmer-Lemeshow test. To address this limitation, we propose a modification of the Hosmer-Lemeshow approach. By standardizing the noncentrality parameter that characterizes the alternative distribution of the Hosmer-Lemeshow statistic, we introduce a parameter that measures the goodness of fit of a model but does not depend on the sample size. We provide the methodology to estimate this parameter and construct confidence intervals for it. Finally, we propose a formal statistical test to rigorously assess whether the fit of a model, albeit not perfect, is acceptable for practical purposes. The proposed method is compared in a simulation study with a competing modification of the Hosmer-Lemeshow test, based on repeated subsampling. We provide a step-by-step illustration of our method using a model for postneonatal mortality developed in a large cohort of more than 300 000 observations.

Comparing outcomes across different levels of trauma centers is vital in evaluating regionalized trauma care. With observational data, it is critical to adjust for patient characteristics to render...

The global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in more than 129 million confirm cases. Many health authorities around the world have implemented wastewater-based epidemiology as a rapid and complementary tool for the COVID-19 surveillance system and more recently for variants of concern emergence tracking. In this study, three SARS-CoV-2 target genes (N1 and N2 gene regions, and E gene) were quantified from wastewater influent samples (n = 250) obtained from the capital city and 7 other cities in various size in central Ohio from July 2020 to January 2021. To determine human-specific fecal strength in wastewater samples more accurately, two human fecal viruses (PMMoV and crAssphage) were quantified to normalize the SARS-CoV-2 gene concentrations in wastewater. To estimate the trend of new case numbers from SARS-CoV-2 gene levels, different statistical models were built and evaluated. From the longitudinal data, SARS-CoV-2 gene concentrations in wastewater strongly correlated with daily new confirmed COVID-19 cases (average Spearman's r = 0.70, p, Graphical abstract Unlabelled Image

The global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in more than 129 million confirm cases. Many health authorities around the world have implemented wastewater-based epidemiology as a rapid and complementary tool for the COVID-19 surveillance system and more recently for variants of concern emergence tracking. In this study, three SARS-CoV-2 target genes (N1, N2, and E) were quantified from wastewater influent samples (n = 250) obtained from the capital city and 7 other cities in various size in central Ohio from July 2020 to January 2021. To determine human-specific fecal strength in wastewater samples more accurately, two human fecal viruses (PMMoV and crAssphage) were quantified to normalize the SARS-CoV-2 gene concentrations in wastewater. To estimate the trend of new case numbers from SARS-CoV-2 gene levels, different statistical models were built and evaluated. From the longitudinal data, SARS-CoV-2 gene concentrations in wastewater strongly correlated with daily new confirmed COVID-19 cases (average Spearman’s r = 0.70, p < 0.05), with the N2 gene being the best predictor of the trend of confirmed cases. Moreover, average daily case numbers can help reduce the noise and variation from the clinical data. Among the models tested, the quadratic polynomial model performed best in correlating and predicting COVID-19 cases from the wastewater surveillance data, which can be used to track the effectiveness of vaccination in the later stage of the pandemic. Interestingly, neither of the normalization methods using PMMoV or crAssphage significantly enhanced the correlation with new case numbers, nor improved the estimation models. Whole-genome sequencing result showed that those detected SARS-CoV-2 variants of concern from the wastewater matched with the clinical isolates from the communities. The findings from this study suggest that wastewater surveillance is effective in COVID-19 trend tracking and variant emergence and transmission within a community.

Rationale: In 2013, the New York State Department of Health (NYSDOH) began a mandatory state-wide initiative to improve early recognition and treatment of severe sepsis and septic shock. Objectives: This study examines protocol initiation, 3-hour and 6-hour sepsis bundle completion, and risk-adjusted hospital mortality among adult patients with severe sepsis and septic shock. Methods: Cohort analysis included all patients from all 185 hospitals in New York State reported to the NYSDOH from April 1, 2014, to June 30, 2016. A total of 113,380 cases were submitted to NYSDOH, of which 91,357 hospitalizations from 183 hospitals met study inclusion criteria. NYSDOH required all hospitals to submit and follow evidence-informed protocols (including elements of 3-h and 6-h sepsis bundles: lactate measurement, early blood cultures and antibiotic administration, fluids, and vasopressors) for early identification and treatment of severe sepsis or septic shock. Measurements and Main Results: Compliance with elements of the sepsis bundles and risk-adjusted mortality were studied. Of 91,357 patients, 74,293 (81.3%) had the sepsis protocol initiated. Among these individuals, 3-hour bundle compliance increased from 53.4% to 64.7% during the study period (P

ObjectiveThe Community Awareness Resources and Education (CARE) project: Reducing Cervical Cancer in Appalachia is part of the NIH Centers for Population Health and Health Disparities initiative. It aims to increase screening rates for cervical cancer, to assist in tobacco cessation, and to determine the role of human papillomavirus (HPV) in contributing to the increased risk of cervical cancer.MethodsEligible subjects were recruited from 14 clinics in Appalachian Ohio. CARE’s cross sectional survey (CS) (571 participants) characterized social, behavioral, and environmental factors of Pap smear screening and smoking. The intervention projects tested programs to increase Pap smear screening (280 participants) or aid in smoking cessation (300 participants). A case control study (1360 participants) assessed social, behavioral, and biologic predictors of abnormal Pap tests.ResultsThe CS participants tended to be younger, more educated, and were more likely to be employed than the general population of Appalachian women 18 and over. They were similar to the other samples in terms of race, marital status, income level and smoking status.ConclusionsCARE will provide valuable information about the multi-level barriers to obtaining regular Pap smears and quitting smoking, as well as help to identify important biological and social risk factors related to abnormal Pap smears.

The "delayed infection hypothesis" states that a paucity of infections in early childhood may lead to higher risks of childhood leukemia (CL), especially acute lymphoblastic leukemia (ALL). Using prospectively collected data from six population-based birth cohorts we studied the association between birth order (a proxy for pathogen exposure) and CL. We explored whether other birth or parental characteristics modify this association. With 2.2 × 106 person-years of follow-up, 185 CL and 136 ALL cases were ascertained. In Cox proportional hazards models, increasing birth order (continuous) was inversely associated with CL and ALL; hazard ratios (HR) = 0.88, 95% confidence interval (CI): (0.77-0.99) and 0.85: (0.73-0.99), respectively. Being later-born was associated with similarly reduced hazards of CL and ALL compared to being first-born; HRs = 0.78: 95% CI: 0.58-1.05 and 0.73: 0.52-1.03, respectively. Successive birth orders were associated with decreased CL and ALL risks (P for trend 0.047 and 0.055, respectively). Multivariable adjustment somewhat attenuated the associations. We found statistically significant and borderline interactions between birth weight (p = 0.024) and paternal age (p = 0.067), respectively, in associations between being later-born and CL, with the lowest risk observed for children born at

Objectives In accordance with Rory's Regulations, hospitals across New York State developed and implemented protocols for sepsis recognition and treatment to reduce variations in evidence informed care and preventable mortality. The New York Department of Health sought to develop a risk assessment model for accurate and standardized hospital mortality comparisons of adult septic patients across institutions using case-mix adjustment. Design Retrospective evaluation of prospectively collected data. Patients Data from 43,204 severe sepsis and septic shock patients from 179 hospitals across New York State were evaluated. Settings Prospective data were submitted to a database from January 1, 2015, to December 31, 2015. Interventions None. Measurement and main results Maximum likelihood logistic regression was used to estimate model coefficients used in the New York State risk model. The mortality probability was estimated using a logistic regression model. Variables to be included in the model were determined as part of the model-building process. Interactions between variables were included if they made clinical sense and if their p values were less than 0.05. Model development used a random sample of 90% of available patients and was validated using the remaining 10%. Hosmer-Lemeshow goodness of fit p values were considerably greater than 0.05, suggesting good calibration. Areas under the receiver operator curve in the developmental and validation subsets were 0.770 (95% CI, 0.765-0.775) and 0.773 (95% CI, 0.758-0.787), respectively, indicating good discrimination. Development and validation datasets had similar distributions of estimated mortality probabilities. Mortality increased with rising age, comorbidities, and lactate. Conclusions The New York Sepsis Severity Score accurately estimated the probability of hospital mortality in severe sepsis and septic shock patients. It performed well with respect to calibration and discrimination. This sepsis-specific model provides an accurate, comprehensive method for standardized mortality comparison of adult patients with severe sepsis and septic shock.

The calibration belt is a graphical approach designed to evaluate the goodness of fit of binary outcome models such as logistic regression models. The calibration belt examines the relationship between estimated probabilities and observed outcome rates. Significant deviations from the perfect calibration can be spotted on the graph. The graphical approach is paired to a statistical test, synthesizing the calibration assessment in a standard hypothesis testing framework. In this article, we present the calibrationbelt command, which implements the calibration belt and its associated test in Stata.

Background: When the treatment effect on the outcome of interest is influenced by a baseline/demographic factor, investigators say that an interaction is present. In randomized clinical trials (RCTs), this type of analysis is typically referred to as subgroup analysis. Although interaction (or subgroup) analyses are usually stated as a secondary study objective, it is not uncommon that these results lead to changes in treatment protocols or even modify public health policies. Nonetheless, recent reviews have indicated that their proper assessment, interpretation and reporting remain challenging. Results: Therefore, this article provides an overview of these challenges, to help investigators find the best strategy for application of interaction analyses on binary outcomes in RCTs. Specifically, we discuss the key points of formal interaction testing, including the estimation of both additive and multiplicative interaction effects. We also provide recommendations that, if adhered to, could increase the clarity and the completeness of reports of RCTs. Conclusion: Altogether, this article provides a brief non-statistical guide for clinical investigators on how to perform, interpret and report interaction (subgroup) analyses in RCTs.

Background: Historically, cutoff points for childhood and adolescent overweight and obesity have been based on population-specific percentiles derived from cross-sectional data. To obtain cutoff points that might better predict overweight and obesity in young adulthood, we examined the association between childhood body-mass index (BMI) and young adulthood BMI status in a longitudinal cohort. Methods: In this study, we used data from the International Childhood Cardiovascular Cohort (i3C) Consortium (which included seven childhood cohorts from the USA, Australia, and Finland) to establish childhood overweight and obesity cutoff points that best predict BMI status at the age of 18 years. We included 3779 children who were followed up from 1970 onwards, and had at least one childhood BMI measurement between ages 6 years and 17 years and a BMI measurement specifically at age 18 years. We used logistic regression to assess the association between BMI in childhood and young adulthood obesity. We used the area under the receiver operating characteristic curve (AUROC) to assess the ability of fitted models to discriminate between different BMI status groups in young adulthood. The cutoff points were then compared with those defined by the International Obesity Task Force (IOTF), which used cross-sectional data, and tested for sensitivity and specificity in a separate, independent, longitudinal sample (from the Special Turku Coronary Risk Factor Intervention Project [STRIP] study) with BMI measurements available from both childhood and adulthood. Findings: The cutoff points derived from the longitudinal i3C Consortium data were lower than the IOTF cutoff points. Consequently, a larger proportion of participants in the STRIP study was classified as overweight or obese when using the i3C cutoff points than when using the IOTF cutoff points. Especially for obesity, i3C cutoff points were significantly better at identifying those who would become obese later in life. In the independent sample, the AUROC values for overweight ranged from 0·75 (95% CI 0·70–0·80) to 0·88 (0·84–0·93) for the i3C cutoff points, and the corresponding values for the IOTF cutoff points ranged from 0·69 (0·62–0·75) to 0·87 (0·82–0·92). For obesity, the AUROC values ranged from 0·84 (0·75–0·93) to 0·90 (0·82–0·98) for the i3C cutoff points and 0·57 (0·49–0·66) to 0·76 (0·65–0·88) for IOTF cutoff points. Interpretation: The childhood BMI cutoff points obtained from the i3C Consortium longitudinal data can better predict risk of overweight and obesity in young adulthood than can standards that are currently used based on cross-sectional data. Such cutoff points should help to more accurately identify children at risk of adult overweight or obesity.

Objective To summarize the published evidence regarding the association between maternal infection during pregnancy and childhood leukemia. Study design In this systematic review and meta-analysis (PROSPERO number, CRD42018087289), we searched PubMed and Embase to identify relevant studies. We included human studies that reported associations of at least one measure of maternal infection during pregnancy with acute lymphoblastic leukemia (ALL) or all childhood leukemias in the offspring. One reviewer extracted the data first using a standardized form, and the second reviewer independently checked the data for accuracy. Two reviewers used the Newcastle-Ottawa Scale to assess the quality of included studies. We conducted random effects meta-analyses to pool the ORs of specific type of infection on ALL and childhood leukemia. Results This review included 20 studies (ALL, n = 15; childhood leukemia, n = 14) reported in 32 articles. Most (>65%) included studies reported a positive association between infection variables and ALL or childhood leukemia. Among specific types of infection, we found that influenza during pregnancy was associated with higher risk of ALL (pooled OR, 3.64; 95% CI, 1.34-9.90) and childhood leukemia (pooled OR, 1.77; 95% CI, 1.01-3.11). Varicella (pooled OR, 10.19; 95% CI, 1.98-52.39) and rubella (pooled OR, 2.79; 95% CI, 1.16-6.71) infections were also associated with higher childhood leukemia risk. Conclusions Our findings suggest that maternal infection during pregnancy may be associated with a higher risk of childhood leukemia.

Parental occupational exposures to pesticides, animals and organic dust have been associated with an increased risk of childhood cancer based mostly on case–control studies. We prospectively evaluated parental occupational exposures and risk of childhood leukemia and central nervous system (CNS) tumors in the International Childhood Cancer Cohort Consortium. We pooled data on 329,658 participants from birth cohorts in five countries (Australia, Denmark, Israel, Norway and United Kingdom). Parental occupational exposures during pregnancy were estimated by linking International Standard Classification of Occupations-1988 job codes to the ALOHA+ job exposure matrix. Risk of childhood (

Background: Historically, cut-points for childhood and adolescent overweight and obesity have been based on population-specific percentiles derived from cross-sectional data. To obtain cut-points that might better predict overweight and obesity in adulthood, we examined the association between childhood body mass index (BMI) and adult BMI status in a longitudinal cohort. Methods: Using data from the International Childhood Cardiovascular Cohort (i3C) Consortium pooled cohort we determined childhood overweight and obesity cut-points that best predict BMI status at the age of 18. Logistic regression analysis was used to assess the association between BMI in childhood and adult obesity. Area under the Receiver Operating Characteristic curve was used to assess the ability of fitted models to discriminate different BMI status groups in adulthood. The cut-points were then compared to those defined by the International Obesity Task Force (IOTF) using cross-sectional data, and tested for sensitivity and specificity in a separate, independent longitudinal sample with BMI measurements available from both childhood and adulthood. Findings: The cut-points derived from the longitudinal i3C Consortium data were lower than the IOTF cut-points. Consequently, a larger percentage of the sample was classified as overweight or obese when using the i3C cut-points in the independent sample. The i3C cut-points were better than the previously used IOTF cut-points at discriminating those who would later become overweight or obese in early adulthood from those whose BMI was normal when tested in the independent sample. Interpretation: The childhood BMI cut-points based on the i3C Consortium longitudinal data provide better predictors of future risk of adult overweight and obesity than estimates based on cross-sectional data. The result is more specific identification of the childhood population at risk of adult overweight or obesity than the currently used IOTF standards. Funding: Authors Kartiosuo, Ramakrishnan, Lemeshow, Juonala, Daniels, Sabin, Hu, Prineas and Dwyer declare no support from funding organisations for their work. Authors Woo, Jacobs, Steinberger, Urbina, Bazzano and Sinaiko declare their work was supported by the National Institutes of Health (NHLBI) grant no. i3C R01 HL121230. Dr Burns declares the acquisition and management of historic Muscatine Study data was supported by a Specialized Center of Research (SCOR) in Atherosclerosis, Lipids and Thrombosis grant from the National Heart, Lung and Blood Institute (NHLBI) HL-14230; M01-FR59 and RR-00059 from the General Clinical Research Centers Program, NCRR, NIH; and the Lipid Research Clinics Program (NIH-NHLBI-N01-HV-2-2913-L). Dr Raitakari declares The Young Finns Study has been financially supported by the Academy of Finland: grants 286284, 134309 (Eye), 126925, 121584, 124282, 129378 (Salve), 117787 (Gendi), and 41071 (Skidi); the Social Insurance Institution of Finland; Competitive State Research Financing of the Expert Responsibility area of Kuopio, Tampere and Turku University Hospitals (grant X51001); Juho Vainio Foundation; Paavo Nurmi Foundation; Finnish Foundation for Cardiovascular Research ; Finnish Cultural Foundation; The Sigrid Juselius Foundation; Tampere Tuberculosis Foundation; Emil Aaltonen Foundation; Yrjo Jahnsson Foundation; Signe and Ane Gyllenberg Foundation; Diabetes Research Foundation of Finnish Diabetes Association; EU Horizon 2020 (grant 755320 for TAXINOMISIS); European Research Council (grant 742927 for MULTIEPIGEN project); and Tampere University Hospital Supporting Foundation. Dr Venn declares the CDAH follow-up study received grant support from the National Health and Medical Research Council (APP211316). Dr. Bazzano is also supported in part by the following grants from the National Institutes of Health: R01AG041200, R21057983, R01062309, K12HD043451, and P20GM109036. Declaration of Interest: All authors have declared no conflict of interest. Ethical Approval: The following studies used in the work were covered by ethical approval detailed as follows: The protocols for all relevant Muscatine Study data acquisition were approved by the University of Iowa Institutional Review Board. Informed consent was obtained from all parents and adult participants; assent was obtained from participants while they were children/adolescents. The Princeton and NGHS studies were approved by the IRB at Cincinnati Children’s Hospital Medical Center. The NGHS cohort all study participants or their legal guardian if

Background Childhood cancer is a rare but leading cause of morbidity and mortality. Established risk factors, accounting for Methods Eligibility criteria, follow‐up methods and identification of paediatric cancer cases are described for cohorts currently participating or planning future participation. Also described are exposure assessments, harmonisation methods, biological samples potentially available for I4C research, the role of the I4C data and biospecimen coordinating centres and statistical approaches used in the pooled analyses. Results Currently, six cohorts recruited over six decades (1950s‐2000s) contribute data on 388 120 mother‐child pairs. Nine new cohorts from seven countries are anticipated to contribute data on 627 500 additional projected mother‐child pairs within 5 years. Harmonised data currently includes over 20 “core” variables, with notable variability in mother/child characteristics within and across cohorts, reflecting in part, secular changes in pregnancy and birth characteristics over the decades. Conclusions The I4C is the first cohort consortium to have published findings on paediatric cancer using harmonised variables across six pregnancy/birth cohorts. Projected increases in sample size, expanding sources of exposure data (eg, linkages to environmental and administrative databases), incorporation of biological measures to clarify exposures and underlying molecular mechanisms and forthcoming joint efforts to complement case‐control studies offer the potential for breakthroughs in paediatric cancer aetiologic research.

Our paper aims to describe firearm-related behavior among American households and to quantify the influence of household characteristics on the probability of firearms possession and storage practices. Applying logistic regression techniques to data from the 2004 Behavioral Risk Factor Surveillance Survey (BRFSS), we use separate models to estimate the effect of an array of respondent demographic characteristics factors on the likelihood that households will have a gun at home and, if so, whether they will keep it at either of two levels of risk. We find that rates of firearm ownership vary widely by household characteristics, including the state in which they reside. Simultaneously controlling for all of these factors scarcely diminishes variation in odds for ownership. Differences in the likelihood that owners will store guns unsafely are narrower and significant for fewer factors. Having children in the home scarcely affects the propensity to possess firearms but greatly reduces the chances a domestic firearm will be stored loaded and unsecured. Our findings support a consensus on the demographics of ownership but show more and stronger predictors of storage behavior than previous work. Differing dynamics of ownership and storage reveal the existence of two regional gun cultures. From these findings, we conclude that to mitigate mortality risks associated with guns in the home, encouraging safer storage by owners may be as effective as controlling sales. States and localities should test a range of promising but largely unproven interventions.

The adverse effects of multicollinearity and unusual observations are seen in logistic regression and attention had been given in the literature to each of these problems separately. However, multicollinearity and unusual observations can arise simultaneously in logistic regression. The objective of this paper is to propose the statistics for detecting the unusual observations in an ill-conditioned data set under the ridge logistic estimator. A numerical example and two Monte Carlo simulation studies are used to illustrate the methodology. The present investigation shows that ridge logistic estimation copes with unusual observations by downweighting their influence. © 2017, Springer-Verlag GmbH Germany.

BackgroundIn 2013, New York began requiring hospitals to follow protocols for the early identification and treatment of sepsis. However, there is controversy about whether more rapid treatment of sepsis improves outcomes in patients. MethodsWe studied data from patients with sepsis and septic shock that were reported to the New York State Department of Health from April 1, 2014, to June 30, 2016. Patients had a sepsis protocol initiated within 6 hours after arrival in the emergency department and had all items in a 3-hour bundle of care for patients with sepsis (i.e., blood cultures, broad-spectrum antibiotic agents, and lactate measurement) completed within 12 hours. Multilevel models were used to assess the associations between the time until completion of the 3-hour bundle and risk-adjusted mortality. We also examined the times to the administration of antibiotics and to the completion of an initial bolus of intravenous fluid. ResultsAmong 49,331 patients at 149 hospitals, 40,696 (82.5%) had the 3-hour...

BACKGROUND The association between cognitive scores in young adulthood and long-term cardiometabolic risks remains unclear. METHODS Using population-based registries, we followed 6502 military conscripts from their 22nd birthday until death, emigration, or 55 years of age. We calculated risks and hazard ratios (HRs) associating quartiles of cognitive scores (very high, high, moderate, and low) with type 2 diabetes, hypertension, myocardial infarction, stroke, venous thromboembolism, and death before age 55 years. RESULTS The 33-year risk of the combined outcome was inversely associated with cognitive scores (26% for low and 16% for very high scores). Compared with very high scores, the HR for the combined outcome was 1.20 (95% confidence interval = 1.02, 1.41) for high, 1.43 (1.22, 1.68) for moderate, and 1.67 (1.43, 1.95) for low scores. Similar HRs were observed for individual outcomes. CONCLUSION Low cognitive score in young adulthood was a strong predictor for type 2 diabetes, cardiovascular morbidity, and death before 55 years of age.

Background: Surgical site infection (SSI) is a major complication following total joint arthroplasty. Host susceptibility to infection has emerged as an important predictor of SSI. The purpose of this study was to develop and validate a preoperative SSI risk-assessment tool for primary or revision knee and hip arthroplasty. Methods: Data for 6,789 patients who underwent total joint arthroplasty (from the years 2000 to 2011) were obtained from a single hospital system. SSI was defined as a superficial infection within 30 days or deep infection within 1 year. Logistic regression modeling was utilized to create a risk scoring system for a derivation sample (n = 5,789; 199 SSIs), with validation performed on a hold-out sample (a subset of observations chosen randomly from the initial sample to form a testing set; n = 1,000; 41 SSIs). Results: On the basis of logistic regression modeling, we created a scoring system to assess SSI risk (range, 0 to 35 points) that is the point sum of the following: primary hip arthroplasty (0 points); primary knee (1); revision hip (3); revision knee (3); non-insulin-dependent diabetes (1); insulin-dependent diabetes (1.5); chronic obstructive pulmonary disease (COPD) (1); inflammatory arthropathy (1.5); tobacco use (1.5); lower-extremity osteomyelitis or pyogenic arthritis (2); pelvis, thigh, or leg traumatic fracture (2); lower-extremity pathologic fracture (2.5); morbid obesity (2.5); primary bone cancer (4); reaction to prosthesis in the last 3 years (4); and history of staphylococcal septicemia (4.5). The risk score had good discriminatory capability (area under the ROC [receiver operating characteristic] curve = 0.77) and calibration (Hosmer-Lemeshow chi-square test, p = 0.34) and was validated using the independent sample (area under the ROC curve = 0.72). A small subset of patients (5.9%) had a >10% estimated infection risk. Conclusions: The patient comorbidities composing the risk score heavily influenced SSI risk for primary or revision knee and hip arthroplasty. We believe that infection risk can be objectively determined in a preoperative setting with the proposed SSI risk score.

MoBa and the International Childhood Cancer Cohort Consortium (I4C) Terence Dwyer, Gabriella Tikellis, Akram Ghantous, Stanley Lemeshow, Siri E. Haberg, Jorn Olsen, Ora Paltiel, Jean Golding, Martha S. Linet, Zdenko Herceg, Monica C. Munthe-Kaas and Camilla Stoltenberg 1) The George Institute for Global Health, Nuffield Department of Population Health, University of Oxford, Oxford, UK 2) The International Agency for Research on Cancer, Lyon, France 3) Murdoch Children’s Research Institute, Royal Children’s Hospital, University of Melbourne, Melbourne, Australia 4) The Ohio State University College of Public Health, Columbus, Ohio 5) Norwegian Institute of Public Health, Oslo, Norway 6) Department of Epidemiology, University of California, Los Angeles, CA, USA 7) School of Public Health and Department of Hematology, Hadassah-Hebrew University, Jerusalem, Israel 8) Centre for Child & Adolescent Health, School of Social & Community Medicine, University of Bristol, Bristol, UK 9) Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA 10) Department of Pediatrics, Oslo University Hospital, Oslo, Norway

The Surviving Sepsis Campaign (SSC) developed guidelines and treatment bundles for the administration of steroids in adult septic shock. However, it is not clear how this has affected clinical practice or patient outcome.The SSC has developed an extensive database to assess the overall effect of its guidelines on clinical practice and patient outcome. This analysis focuses on one particular element of the SSC's management bundle, namely, the administration of low-dose steroids in adult septic shock. This analysis was conducted on data submitted from January 2005 through March 2010 including 27,836 subjects at 218 sites.A total of 17,847 (of the total 27,836) patients in the database required vasopressor therapy despite fluid resuscitation and therefore met the eligibility criteria for receiving low-dose steroids. A total of 8,992 patients (50.4 %) received low-dose steroids for their septic shock. Patients in Europe (59.4 %) and South America (51.9 %) were more likely to be prescribed low-dose steroids compared to their counterparts in North America (46.2 %, p0.001). The adjusted hospital mortality was significantly higher (OR 1.18, 95 % CI 1.09-1.23, p0.001) in patients who received low-dose steroids compared to those who did not. There was still an association with increased adjusted hospital mortality with low-dose steroids even if they were prescribed within 8 h (OR 1.23, 95 % CI 1.13-1.34, p0.001).Steroids were commonly administered in the treatment of septic shock in this subset analysis of the Surviving Sepsis Campaign database. However, this was associated with an increase in adjusted hospital mortality.

To determine the association between excess weight and processes of care and outcomes for critically ill adults.Prospective cohort study.Three medical intensive care units at two hospitals.Five hundred eighty mechanically ventilated adult patients admitted between February 1, 2006 and January 31, 2008.None.After adjusting weight based on the recorded fluid balance before enrollment, 21.9% of subjects were categorized into different body mass index categories than without this adjustment. We used a competing risk analysis with events of interest considered death during hospitalization and successful liberation from mechanical ventilation. We found no statistically significant difference between body mass index categories (25 kg/m² vs. 25 to30 kg/m² vs. ≥30 kg/m²) in the competing risks analyses when the results were unadjusted or adjusted for severity of illness and comorbidities. When the analyses were adjusted for the use of continuous infusions of opioids and/or sedatives and ventilator parameters (tidal volume per ideal body weight, positive end-expiratory pressure, and airway pressure), subjects with an overweight fluid-balance-adjusted body mass index had significantly lower hazard ratios for dying while hospitalized (adjusted hazard ratio 0.68 [95% confidence interval 0.47-0.99], p=.044), and those with an obese fluid-adjusted body mass index had significantly higher hazard ratios for successful extubation (adjusted hazard ratio 1.53 [95% confidence interval 1.14-2.06], p=.005). An analysis of longer-term mortality found lower adjusted hazard ratios for subjects with overweight (adjusted hazard ratio 0.74 [95% confidence interval 0.56-0.96]) and obese (adjusted hazard ratio 0.74 [95% confidence interval 0.59-0.94]) fluid-balance-adjusted body mass indices.Processes of provided care may affect the observed association between excess weight and outcomes for critically ill adults and should be considered when making inferences about observed results. It is unknown if disparities in processes of care are due to clinically justified reasons for variation, bias against heavier patients, or other reasons.

The Surviving Sepsis Campaign developed guidelines for the administration of recombinant human activated protein C in adult severe sepsis. However, it is not clear how these impacted clinical practice or patient outcome.The Surviving Sepsis Campaign has developed an extensive database to assess the efficacy of the overall effect of its guidelines on clinical practice and patient outcome. From data submitted to the Surviving Sepsis Campaign database from January 2005 through March 2008, we evaluated data regarding the administration of recombinant human activated protein C in adult severe sepsis.Data from 15,022 subjects at 165 sites were analyzed.Of patients with severe sepsis in the database, 1,009 of 15,022 (8%) received recombinant human activated protein C. Recombinant human activated protein C was administered within 24 hrs of the onset of sepsis in 76% (771 of 1009) of patients. Patients in North America (7.1%) and Europe (6.8%) were more likely to receive recombinant human activated protein C than patients in South America (4.2%, p.001). After adjusting for covariates, the group that received recombinant human activated protein C had a significantly reduced associated hospital mortality (odds ratio 0.76, 95% confidence interval 0.66-0.86, p.001). Comparing all the patients who received recombinant human activated protein C to those who did not receive recombinant human activated protein C, the reduction in the adjusted hospital mortality was only statistically significant in patients who had multiorgan dysfunction (odds ratio 0.82, 95% confidence interval 0.69-0.98, p=.027) vs. those who only had single organ dysfunction (odds ratio 0.78, 95% confidence interval 0.59-1.02, p=.072). However, in patients who received recombinant human activated protein C before 24 hrs there was a reduction in adjusted hospital mortality in patients with only one organ dysfunction (odds ratio 0.70, 95% confidence interval 0.51-0.9, p=.03) as well as patients with multiorgan dysfunction (odds ratio 0.78, 95% confidence interval 0.64-0.94 p=.012). There was a statistically significant increase over time in the percentage compliance with the institution of a recombinant human activated protein C administration policy from the first, second, and eighth quarters (47.4%, 46.2%, and 60.7%, respectively) (p.001). There was also a statistically significant increase in the actual administration rates of recombinant human activated protein C over the same timeline (p.001), with administration rates of recombinant human activated protein C reaching 9.2% in the last quarter.Recombinant human activated protein C use was associated with a significant improvement in hospital mortality in patients who participated in the Surviving Sepsis Campaign.