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Few personalised medicine investigations have been conducted for mental health. We aimed to generate and validate a risk tool that predicts adult attention-deficit/hyperactivity disorder (ADHD).
Using logistic regression models, we generated a risk tool in a representative population cohort (ALSPAC – UK, 5113 participants, followed from birth to age 17) using childhood clinical and sociodemographic data with internal validation. Predictors included sex, socioeconomic status, single-parent family, ADHD symptoms, comorbid disruptive disorders, childhood maltreatment, ADHD symptoms, depressive symptoms, mother's depression and intelligence quotient. The outcome was defined as a categorical diagnosis of ADHD in young adulthood without requiring age at onset criteria. We also tested Machine Learning approaches for developing the risk models: Random Forest, Stochastic Gradient Boosting and Artificial Neural Network. The risk tool was externally validated in the E-Risk cohort (UK, 2040 participants, birth to age 18), the 1993 Pelotas Birth Cohort (Brazil, 3911 participants, birth to age 18) and the MTA clinical sample (USA, 476 children with ADHD and 241 controls followed for 16 years from a minimum of 8 and a maximum of 26 years old).
The overall prevalence of adult ADHD ranged from 8.1 to 12% in the population-based samples, and was 28.6% in the clinical sample. The internal performance of the model in the generating sample was good, with an area under the curve (AUC) for predicting adult ADHD of 0.82 (95% confidence interval (CI) 0.79–0.83). Calibration plots showed good agreement between predicted and observed event frequencies from 0 to 60% probability. In the UK birth cohort test sample, the AUC was 0.75 (95% CI 0.71–0.78). In the Brazilian birth cohort test sample, the AUC was significantly lower –0.57 (95% CI 0.54–0.60). In the clinical trial test sample, the AUC was 0.76 (95% CI 0.73–0.80). The risk model did not predict adult anxiety or major depressive disorder. Machine Learning approaches did not outperform logistic regression models. An open-source and free risk calculator was generated for clinical use and is available online at https://ufrgs.br/prodah/adhd-calculator/.
The risk tool based on childhood characteristics specifically predicts adult ADHD in European and North-American population-based and clinical samples with comparable discrimination to commonly used clinical tools in internal medicine and higher than most previous attempts for mental and neurological disorders. However, its use in middle-income settings requires caution.
Introduction: We previously derived (N = 559) and validated (N = 1,100) the 10-item Ottawa Heart Failure Risk Scale (OHFRS), to assist with disposition decisions for patients with acute heart failure (AHF) in the emergency department (ED). In the current study we sought to use a larger dataset to develop a more concise and more accurate risk scale. Methods: We analyzed data from the prior two studies and from a new cohort. For all 3 groups we conducted prospective cohort studies that enrolled patients who required treatment for AHF at 8 tertiary care hospital EDs. Patients were followed for 30 days. The primary outcome was short-term serious outcome (SSO), defined as death within 30 days, intubation or non-invasive ventilation (NIV) after admission, myocardial infarction, or relapse resulting in hospital admission within 14 days. The fully pre-specified logistic regression model with 13 predictors (where age, pCO2, and SaO2 were modeled using spline functions) was fitted to 10 multiple imputation datasets. Harrell's fast stepdown procedure reduced the number of variables. We calculated the potential impact on sensitivity (95% CI) for SSO and hospital admissions, and estimated a sample size of 2,000 patients. Results: The 1,986 patients had mean age 77.3 years, male 54.1%, EMS arrival 41.2%, IV NTG 3.3%, ED NIV 5.4%, admission on initial visit 49.5%. Overall there were 236 (11.9%) SSOs including 61 deaths (3.1%), meaning that current admission practice sensitivity for SSO was only 59.7%. The final HEARTRISK6 scale is comprised of 6 variables (points) (C-statistic 0.68): Valvular heart disease (2) Antiarrhythmic medication (2) ED non-invasive ventilation (3) Creatinine 80–150 (1); ≥150 (3) Troponin ≥3x URL (2) Walk test failed (1). The probability of SSO ranged from 4.8% for a total score of 0 to 62.4% for a score of 10, showing good calibration. Choosing a HEARTRISK6 total point admission threshold of ≥3 would yield sensitivity of 70.8% (95%CI 64.5-76.5) for SSO with a slight decrease in admissions to 47.9%. Choosing a threshold of ≥2 would yield a sensitivity of 84.3% (95%CI 79.0-88.7) but require 66.6% admissions. Conclusion: Using a large prospectively collected dataset, we created a more concise and more sensitive risk scale to assist with admission decisions for patients with AHF in the ED. Implementation of the HEARTRISK6 scale should lead to safer and more efficient disposition decisions, with more high-risk patients being admitted and more low-risk patients being discharged.
Introduction: 9-1-1 telecommunicators receive minimal education on agonal breathing, often resulting in unrecognized out-of-hospital cardiac arrest (OHCA). We successfully piloted an educational intervention that significantly improved telecommunicators’ OHCA recognition and bystander CPR rates in Ottawa. We sought to better understand the operations of Canadian 9-1-1 communications centers (CC) in preparation for a multi-centre study of this intervention. Methods: We conducted a National survey of all Canadian CCs. Survey domains included information on organizational structure, dispatch system used, education curriculum, and performance monitoring. It was peer-reviewed, translated in French, pilot-tested, and distributed electronically using a modified Dillman method. We designated respondents in each CC before distribution and used targeted follow-up and small incentives to increase response rate. Respondents also described functioning of neighboring CCs if known. Results: We received information from 51/51 provincial and 1/25 territorial CCs, representing 99.7% of the Canadian population. CCs largely utilize the Medical Dispatch Priority System (MPDS) platform (93%), many are Province/Ministry regulated (50%) and most require a High School diploma as minimum entry level education (78%). Telecommunicators receive initial in-class training (median 1.3 months, IQR 0.3-1.9; range 0.1-2.2), often followed by a preceptorship (84.4%) (median 1.0 months, IQR 0.7-1.7; range 0.4-6.0). Educational curriculum includes information on agonal breathing in 41% of CC, without audio examples in 34%. Among responding CCs, over 39,000 suspected OHCA 9-1-1 calls are received annually. Few CCs maintain local performance statistics on OHCA recognition (25%), bystander CPR rates (25%) or survival rates (50%). Most (97%) expressed interest in future research collaborations. Conclusion: Most Canadian telecommunicators receive no or minimal education in recognizing agonal breathing. Further training and improved OHCA monitoring may assist recognition and enhance outcomes.
The Cambridge Handbook of the Psychology of Prejudice: Concise Student Edition aims to answer the questions: why is prejudice so persistent? How does it affect people exposed to it? And what can we do about it? With cutting-edge research from top scholars in the field, the chapters present an overview of psychological models of prejudice and investigate key domains such as racism, sexism, and the criminal justice system. This student edition of the award-winning Handbook includes new pedagogical features such as learning objectives, core terms and definitions, summary points, discussion questions, recommended reading, and an instructor's test bank. It also features a new conclusion chapter that analyzes eight hard problems currently faced by researchers and activists, thus engaging students in deep, forward-thinking discussion. Developed specifically for use in Psychology of Prejudice courses at the undergraduate and graduate levels, the Concise Student Edition is an essential teaching and learning resource.