Development and validation of a nomogram prediction model for ADHD in children based on individual, family, and social factors.

OBJECTIVES: A reliable, user-friendly, and multidimensional prediction tool can help to identify children at high risk for ADHD and facilitate early recognition and family management of ADHD. We aimed to develop and validate a risk nomogram for ADHD in children aged 3-17 years in the United States based on clinical manifestations and complex environments. METHODS: A total of 141,356 cases were collected for the prediction model. Another 54,444 cases from a new data set were utilized for performing independent external validation. The LASSO regression was used to control possible variables. A final risk nomogram for ADHD was established based on logistic regression, and the discrimination and calibration of the established nomogram were evaluated by bootstrapping with 1000 resamples. RESULTS: A final risk nomogram for ADHD was established based on 13 independent predictors, including behavioral problems, learning disabilities, age, intellectual disabilities, anxiety symptoms, gender, premature birth, maternal age at childbirth, parent-child interaction patterns, etc. The C-index of this model was 0.887 in the training set, and 0.862 in the validation set. Internal and external validation proved that the model was reliable. CONCLUSIONS: A nomogram, a statistical prediction tool that assesses individualized ADHD risk for children is helpful for the early identification of children at high risk for ADHD and the construction of a conceptual model of society-family-school collaborative diagnosis, treatment, and management of ADHD.

Comparación entre las calculadoras de riesgo del European Randomized Study for Screening of Prostate Cancer (ERSPC) y Prostate Biopsy Collaborative Group (PBCG): predicción del riesgo de cáncer de próstata clínicamente significativo en una cohorte de pacientes de Argentina / Comparison between the European Randomized Study for Screening of Prostate Cancer (ERSPC) and Prostate Biopsy Collaborative Group (PBCG) risk calculators: Prediction of clinically significant prostate cancer risk in a cohort of patients from Argentina

Objetivo Comparar el desempeño de las calculadoras de riesgo del European Randomised Study for Screening of Prostate Cancer (ERSPC-RC) y el Prostate Biopsy Collaborative Group (PBCG-RC) en predecir el riesgo de presentar cáncer de próstata clínicamente significativo. Material y métodos Retrospectivamente, se identificó a los pacientes que fueron sometidos a biopsia prostática en el Sanatorio Allende Cerro, Ciudad de Córdoba, Argentina, desde enero de 2018 a diciembre de 2021. Se calculó la probabilidad de tener cáncer de próstata con las dos calculadoras por separado y luego se compararon los resultados para establecer cuál de las dos tuvo mejor desempeño. Para esto, se analizaron áreas bajo la curva (ABC). Resultados Se incluyeron 250 pacientes, 140 (56%) presentaron cáncer de próstata, de los cuales 92 (36,8%) tuvieron cáncer de próstata clínicamente significativo (Score de Gleason ≥7). Los pacientes que presentaron cáncer tenían mayor edad, mayor valor de antígeno prostático específico (PSA) y menor tamaño prostático. El ABC para predecir la probabilidad de tener cáncer de próstata clínicamente significativo fue de 0,79 y 0,73 para PBCG-RC y ERSPC-RC, respectivamente (p=0,0084). Conclusión En esta cohorte de pacientes, ambas calculadoras de riesgo de cáncer de próstata mostraron un buen desempeño para predecir el riesgo de cáncer de próstata clínicamente significativo, si bien el PBCG-RC mostró mejor exactitud. (AU)

Objective To compare the performance of the risk calculators of the European Randomized Study for Screening of Prostate Cancer (ERSPC) and the Prostate Biopsy Collaborative Group (PBCG) in predicting the risk of presenting clinically significant prostate cancer. Material and methods Retrospectively, patients who underwent prostate biopsy at Sanatorio Allende Cerro, Ciudad de Córdoba, Argentina, were identified from January 2018 to December 2021. The probability of having prostate cancer was calculated with the two calculators separately and then the results were compared to establish which of the two performed better. For this, areas under the curve (AUC) were analyzed. Results 250 patients were included, 140 (56%) presented prostate cancer, of which 92 (65.71%) had clinically significant prostate cancer (Gleason score ≥7). The patients who presented cancer were older, had a higher prostate-specific antigen (PSA) value, and had a smaller prostate size. The AUC to predict the probability of having clinically significant prostate cancer was 0.79 and 0.73 for PBCG-RC and ERSPC-RC respectively (p=0.0084). Conclusion In this cohort of patients, both prostate cancer risk calculators performed well in predicting clinically significant prostate cancer risk, although the PBCG-RC showed better accuracy. (AU)

Peripheral perfusion index stratifies risk in patients with intraoperative anemia: A multicentre cohort study.

STUDY OBJECTIVE: Evidence for red blood cell (RBC) transfusion thresholds in the intraoperative setting is limited, and current perioperative recommendations may not correspond with individual intraoperative physiological demands. Hemodynamics relevant for the decision to transfuse may include peripheral perfusion index (PPI). The objective of this prospective study was to assess the associations of PPI and hemoglobin levels with the risk of postoperative morbidity and mortality. DESIGN: Multicenter cohort study. SETTING: Bispebjerg and Hvidovre University Hospitals, Copenhagen, Denmark. PATIENTS: We included 741 patients who underwent acute high risk abdominal surgery or hip fracture surgery. INTERVENTIONS: No interventions were carried out. MEASUREMENTS: Principal values collected included measurements of peripheral perfusion index and hemoglobin values. METHODS: The study was conducted using prospectively obtained data on adults who underwent emergency high-risk surgery. Subjects were categorized into high vs. low subgroups stratified by pre-defined PPI levels (PPI: > 1.5 vs. < 1.5) and Hb levels (Hb: > 9.7 g/dL vs. < 9.7 g/dL). The study assessed mortality and severe postoperative complications within 90 days. MAIN RESULTS: We included 741 patients. 90-day mortality was 21% (n = 154), frequency of severe postoperative complications was 31% (n = 231). Patients with both low PPI and low Hb had the highest adjusted odds ratio for both 90-day severe postoperative complications (2.95, [1.62-5.45]) and 90-day mortality (3.13, [1.45-7.11]). A comparison of patients with low PPI and low Hb to those with high PPI and low Hb detected significantly higher 90-day mortality risk in the low PPI and low Hb group (OR 8.6, [1.57-162.10]). CONCLUSION: High PPI in acute surgical patients who also presents with anemia was associated with a significantly better outcome when compared with patients with both low PPI and anemia. PPI should therefore be further investigated as a potential parameter to guide intraoperative RBC transfusion therapy.

Computed tomography-based radiomics to predict early recurrence of hepatocellular carcinoma post-hepatectomy in patients background on cirrhosis.

BACKGROUND: The prognosis for hepatocellular carcinoma (HCC) in the presence of cirrhosis is unfavourable, primarily attributable to the high incidence of recurrence. AIM: To develop a machine learning model for predicting early recurrence (ER) of post-hepatectomy HCC in patients with cirrhosis and to stratify patients' overall survival (OS) based on the predicted risk of recurrence. METHODS: In this retrospective study, 214 HCC patients with cirrhosis who underwent curative hepatectomy were examined. Radiomics feature selection was conducted using the least absolute shrinkage and selection operator and recursive feature elimination methods. Clinical-radiologic features were selected through univariate and multivariate logistic regression analyses. Five machine learning methods were used for model comparison, aiming to identify the optimal model. The model's performance was evaluated using the receiver operating characteristic curve [area under the curve (AUC)], calibration, and decision curve analysis. Additionally, the Kaplan-Meier (K-M) curve was used to evaluate the stratification effect of the model on patient OS. RESULTS: Within this study, the most effective predictive performance for ER of post-hepatectomy HCC in the background of cirrhosis was demonstrated by a model that integrated radiomics features and clinical-radiologic features. In the training cohort, this model attained an AUC of 0.844, while in the validation cohort, it achieved a value of 0.790. The K-M curves illustrated that the combined model not only facilitated risk stratification but also exhibited significant discriminatory ability concerning patients' OS. CONCLUSION: The combined model, integrating both radiomics and clinical-radiologic characteristics, exhibited excellent performance in HCC with cirrhosis. The K-M curves assessing OS revealed statistically significant differences.

Comparison of performances of SIREN or MFSRS in stroke risk prediction in an African environment.

BACKGROUND: The Modified Framingham Stroke Risk Score (MFSRS) is a widely utilized stroke risk assessment algorithm usually applied in international comparison. The Stroke Investigative Research and Educational Network (SIREN) is the only known African-specific stroke risk assessment algorithm. AIMS AND OBJECTIVES: To compare stroke risk estimates from the SIREN and the MFSRS in an African community. METHODS: This was a population-based cross-sectional survey involving consecutively recruited 310 consenting adult residents (mean age = 37.21 ± 15.84 years) of a Nigerian community. Risk factors of stroke were assessed among the participants and were utilized in calculating stroke risk estimates on the MFSRS and the SIREN. The obtained data were analyzed using descriptive statistics and the Spearman-rank order correlation test at an alpha level of 0.05. RESULTS: The percentage stroke risk scores estimated by the SIREN and the MFSRS were 34.5% and 6.79% respectively. The most prevalent risk factors among the participants were hypertriglyceridemia (100.0%), raised waist-hip ratio (50.6%), hypercholesterolemia (45.5), physical inactivity (43.2%), psychological stress (41.3%), and hypertension (37.7%). Only two (hypertriglyceridemia and high blood pressure) out of the six factors considered in the MFSRS were rated among the first 10 most impactful risks by the SIREN. There was a weak correlation between the total scores on the MFSRS and the SIREN (rho = 0.39; p < 0.01) suggesting that the two ratings were discordant. CONCLUSION: There were disagreements between the risk estimates on the SIREN and MFSRS with SIREN having a higher estimate that corresponded with the literature; this may be suggesting a poorer estimation of stroke risks by the MFSRS in an African environment. There is a need for large African-based quality control studies to determine and address these lapses.

Perceived balance and self-reported falls: A retrospective cross-sectional study using the National Health and Aging Trend Study.

AIMS: To examine how perceived balance problems are associated with self-reported falls in the past month after controlling for known correlates of falls among older adults. BACKGROUND: Approximately 30% of adults age 65 and older fall each year. Most accidental falls are preventable, and older adults' engagement in fall prevention is imperative. Limited research suggest that older adults do not use the term 'fall risk' to describe their risk for falls. Instead, they commonly use the term 'balance problems'. Yet, commonly used fall risk assessment tools in both primary and acute care do not assess older adults' perceived balance. DESIGN AND METHOD: The Health Belief Model and the concept of perceived susceptibility served as the theoretical framework. A retrospective, cross-sectional secondary analysis using data from the National Health and Aging Trends Study from year 2015 was conducted. The outcome variable was self-reported falls in the last month. RESULTS: A subsample of independently living participants (N = 7499) was selected, and 10.3% of the sample reported a fall. Multiple logistic regression analysis revealed that the odds of reporting a fall in the past month was 3.4 times (p < .001) greater for participants who self-reported having a balance problem compared to those who did not. In contrast, fear of falling and perceived memory problems were not uniquely associated with falls. Using a mobility device, reporting pain, poor self-rated health status, depression and anxiety scores were also associated with falling. CONCLUSION AND IMPLICATIONS: Older adults' perceived balance problem is strongly associated with their fall risk. Perceived balance may be important to discuss with older adults to increase identification of fall risk. Older adults' perceived balance should be included in nursing fall risk assessments and fall prevention interventions. A focus on balance may increase older adults' engagement in fall prevention.

Effects of the Million Hearts Model on Myocardial Infarctions, Strokes, and Medicare Spending: A Randomized Clinical Trial.

Importance: The Million Hearts Model paid health care organizations to assess and reduce cardiovascular disease (CVD) risk. Model effects on long-term outcomes are unknown. Objective: To estimate model effects on first-time myocardial infarctions (MIs) and strokes and Medicare spending over a period up to 5 years. Design, Setting, and Participants: This pragmatic cluster-randomized trial ran from 2017 to 2021, with organizations assigned to a model intervention group or standard care control group. Randomized organizations included 516 US-based primary care and specialty practices, health centers, and hospital-based outpatient clinics participating voluntarily. Of these organizations, 342 entered patients into the study population, which included Medicare fee-for-service beneficiaries aged 40 to 79 years with no previous MI or stroke and with high or medium CVD risk (a 10-year predicted probability of MI or stroke [ie, CVD risk score] ≥15%) in 2017-2018. Intervention: Organizations agreed to perform guideline-concordant care, including routine CVD risk assessment and cardiovascular care management for high-risk patients. The Centers for Medicare & Medicaid Services paid organizations to calculate CVD risk scores for Medicare fee-for-service beneficiaries. CMS further rewarded organizations for reducing risk among high-risk beneficiaries (CVD risk score ≥30%). Main Outcomes and Measures: Outcomes included first-time CVD events (MIs, strokes, and transient ischemic attacks) identified in Medicare claims, combined first-time CVD events from claims and CVD deaths (coronary heart disease or cerebrovascular disease deaths) identified using the National Death Index, and Medicare Parts A and B spending for CVD events and overall. Outcomes were measured through 2021. Results: High- and medium-risk model intervention beneficiaries (n = 130 578) and standard care control beneficiaries (n = 88 286) were similar in age (median age, 72-73 y), sex (58%-59% men), race (7%-8% Black), and baseline CVD risk score (median, 24%). The probability of a first-time CVD event within 5 years was 0.3 percentage points lower for intervention beneficiaries than control beneficiaries (3.3% relative effect; adjusted hazard ratio [HR], 0.97 [90% CI, 0.93-1.00]; P = .09). The 5-year probability of combined first-time CVD events and CVD deaths was 0.4 percentage points lower in the intervention group (4.2% relative effect; HR, 0.96 [90% CI, 0.93-0.99]; P = .02). Medicare spending for CVD events was similar between the groups (effect estimate, -$1.83 per beneficiary per month [90% CI, -$3.97 to -$0.30]; P = .16), as was overall Medicare spending including model payments (effect estimate, $2.11 per beneficiary per month [90% CI, -$16.66 to $20.89]; P = .85). Conclusions and Relevance: The Million Hearts Model, which encouraged and paid for CVD risk assessment and reduction, reduced first-time MIs and strokes. Results support guidelines to use risk scores for CVD primary prevention. Trial Registration: ClinicalTrials.gov Identifier: NCT04047147.

Potencia estadística en investigación médica. ¿Qué postura tomar cuando los resultados de la investigación son significativos? / Statistical power in medical research. What stance should be taken when the research results are significant?

Cuando el investigador pide subvención y autorización a entidades financieras para llevar a cabo su proyecto, entre las primeras cuestiones que le plantean está: ¿qué potencia estadística tiene este estudio que usted propone? Si el investigador responde, por ejemplo, el 90%, y el evaluador se da por satisfecho, es seguro que no conoce realmente el tema. La potencia de un estudio no es única. Depende de determinados parámetros y ocurre que, en la mayoría de los casos, variando ligeramente los valores de esos parámetros, la potencia toma un valor aceptable. Si no es así, y a pesar de ello se lleva a cabo el estudio, y sus resultados son muy significativos, no ha lugar a cuestionar el éxito encontrado argumentando que el estudio tenía poca potencia. Tan sólo es momento de celebrarlo. (AU)

When researchers request funding and authorisation from financial institutions to carry out their project, one of the first questions they are asked is: what is the statistical power of the study you are proposing? If the researcher answers, for example, 90%, and the evaluator is satisfied, it is certain that he/she is not really familiar with the subject. The power of a study is not unique. It depends on certain parameters and what happens is that, in most cases, by introducing a slight variation in the values of these parameters, the power takes on an acceptable value. If this is not the case and the study is carried out anyway, and its results are very significant, there is no room to question its success by arguing that the power of the study was very low. It is just the time to celebrate. (AU)

Divulgados os resultados da avaliação de riscos e perigos do aspartame

A Agência Internacional para Pesquisa em Câncer (IARC) e o Comitê Conjunto FAO/OMS de Especialistas em Aditivos Alimentares (JECFA) da Organização Mundial da Saúde (OMS) e da Organização das Nações Unidas para Agricultura e Alimentação (FAO) publicam, nesta sexta-feira (14/07), suas avaliações sobre os efeitos do aspartame, um adoçante sem açúcar, na saúde.

Evaluation of the Risk Identification for Suicide and Enhanced Care Model in a Native American Community.

Importance: There are many prognostic models of suicide risk, but few have been prospectively evaluated, and none has been developed specifically for Native American populations. Objective: To prospectively validate a statistical risk model implemented in a community setting and evaluate whether use of this model was associated with improved reach of evidence-based care and reduced subsequent suicide-related behavior among high-risk individuals. Design, Setting, and Participants: This prognostic study, done in partnership with the White Mountain Apache Tribe, used data collected by the Apache Celebrating Life program for adults aged 25 years or older identified as at risk for suicide and/or self-harm from January 1, 2017, through August 31, 2022. Data were divided into 2 cohorts: (1) individuals and suicide-related events from the period prior to suicide risk alerts being active (February 29, 2020) and (2) individuals and events from the time after alerts were activated. Main Outcomes and Measures: Aim 1 focused on a prospective validation of the risk model in cohort 1. Aim 2 compared the odds of repeated suicide-related events and the reach of brief contact interventions among high-risk cases between cohort 2 and cohort 1. Results: Across both cohorts, a total of 400 individuals identified as at risk for suicide and/or self-harm (mean [SD] age, 36.5 [10.3] years; 210 females [52.5%]) had 781 suicide-related events. Cohort 1 included 256 individuals with index events prior to active notifications. Most index events (134 [52.5%]) were for binge substance use, followed by 101 (39.6%) for suicidal ideation, 28 (11.0%) for a suicide attempt, and 10 (3.9%) for self-injury. Among these individuals, 102 (39.5%) had subsequent suicidal behaviors. In cohort 1, the majority (220 [86.3%]) were classified as low risk, and 35 individuals (13.3%) were classified as high risk for suicidal attempt or death in the 12 months after their index event. Cohort 2 included 144 individuals with index events after notifications were activated. For aim 1, those classified as high risk had a greater odds of subsequent suicide-related events compared with those classified as low risk (odds ratio [OR], 3.47; 95% CI, 1.53-7.86; P = .003; area under the receiver operating characteristic curve, 0.65). For aim 2, which included 57 individuals classified as high risk across both cohorts, during the time when alerts were inactive, high-risk individuals were more likely to have subsequent suicidal behaviors compared with when alerts were active (OR, 9.14; 95% CI, 1.85-45.29; P = .007). Before the active alerts, only 1 of 35 (2.9%) individuals classified as high risk received a wellness check; after the alerts were activated, 11 of 22 (50.0%) individuals classified as high risk received 1 or more wellness checks. Conclusions and Relevance: This study showed that a statistical model and associated care system developed in partnership with the White Mountain Apache Tribe enhanced identification of individuals at high risk for suicide and was associated with a reduced risk for subsequent suicidal behaviors and increased reach of care.

Black Patients May See Shorter Wait Times for Kidney Transplants.

A race-based formula underestimating disease progress has been discarded.

Association of Life's Simple 7 and ideal cardiovascular health in American Indians/Alaska Natives.

OBJECTIVE: American Indians and Alaska Natives (AI/ANs) are an understudied population at high risk for cardiovascular diseases (CVDs); little is known about contextual factors contributing to CVDs in AI/ANs. This study examined the association of Life's Simple 7 (LS7) factors and social determinants of health (SDH) with CVD outcomes in a nationally representative sample of AI/ANs. METHODS: We conducted a cross-sectional study of 8497 AI/ANs using 2017 Behavioural Risk Factor Surveillance Survey data. Individual LS7 factors were summarised as ideal and poor levels. Coronary heart disease, myocardial infarction and stroke were defined as CVD outcomes. Healthcare access measures represented SDH. Logistic regression analyses examined associations of LS7 factors and SDH with CVD outcomes. Population attributable fractions (PAFs) quantified individual contributions of LS7 factors to CVD outcomes. RESULTS: N=1,297 (15%) participants with CVD outcomes were identified. Smoking, physical inactivity, diabetes, hypertension and hyperlipidaemia were LS7 factors associated with CVD outcomes. Hypertension was the largest contributor to CVD (aPAF 42%; 95% CI 37% to 51%), followed by hyperlipidaemia (aPAF 27%; 95% CI 17% to 36%) and diabetes (aPAF 18%; 95% CI 7% to 23%). Compared with individuals with poor LS7 levels, participants with ideal levels showed 80% lower odds of CVD outcomes (aOR 0.20; 95% CI 0.16 to 0.25). Access to health insurance (aOR 1.43, 95% CI 1.08 to 1.89) and a regular care provider (aOR 1.47, 95% CI 1.24 to 1.76) were associated with CVD outcomes. CONCLUSIONS: Effective interventions are needed to address SDH and attain ideal LS7 factors to improve cardiovascular health among AI/ANs.

Statistical learning methods and cross-cultural fairness: Trade-offs and implications for risk assessment instruments.

The use of statistical learning methods has recently increased within the risk assessment literature. They have primarily been used to increase accuracy and the area under the curve (AUC, i.e., discrimination). Processing approaches applied to statistical learning methods have also emerged to increase cross-cultural fairness. However, these approaches are rarely trialed in the forensic psychology discipline nor have they been trialed as an approach to increase fairness in Australia. The study included 380 Aboriginal and Torres Strait Islander and non-Aboriginal and Torres Strait Islander males assessed with the Level of Service/Risk Needs Responsivity (LS/RNR). Discrimination was assessed through the AUC, and fairness was assessed through the cross area under the curve (xAUC), error rate balance, calibration, predictive parity, and statistical parity. Logistic regression, penalized logistic regression, random forest, stochastic gradient boosting, and support vector machine algorithms using the LS/RNR risk factors were used to compare performance against the LS/RNR total risk score. The algorithms were then subjected to pre- and postprocessing approaches to see if fairness could be improved. Statistical learning methods were found to produce comparable or marginally improved AUC values. Processing approaches increased several fairness definitions (namely xAUC, error rate balance, and statistical parity) between Aboriginal and Torres Strait Islanders and non-Aboriginal and Torres Strait Islanders. The findings demonstrate that statistical learning methods may be a useful approach to increasing the discrimination and cross-cultural fairness of risk assessment instruments. However, both fairness and the use of statistical learning methods encompass significant trade-offs that need to be considered. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Cost-effectiveness evaluation of risk-based breast cancer screening in Urban Hebei Province.

To evaluate the implementations of Cancer Screening Program in Urban Hebei and to model the cost-effectiveness of a risk-based breast Cancer Screening Program. Women aged 40-74 years were invited to participate the Cancer Screening Program in Urban Hebei form 2016 to 2020 by completing questionnaires to collect information about breast cancer exposure. Clinical screening including ultrasound and mammography examination were performed. We developed a Markov model to estimate the lifetime costs and benefits, in terms of quality-adjusted life years (QALY), of a high-risk breast Cancer Screening Program. Nine screening strategies and no screening were included in the study. The age-specific incidence, transition probability data and lifetime treatment costs were derived and adopted from other researches. Average cost-effectiveness ratios (ACERs) were estimated as the ratios of the additional costs of the screening strategies to the QLYG compared to no screening. Incremental cost-effectiveness ratios (ICERs) were calculated based on the comparison of a lower cost strategies to the next more expensive and effective strategies after excluding dominated strategies and extendedly dominated strategies. ICERs were used to compare with a willingness-to-pay (WTP) threshold. Sensitivity analysis was explored the influence factors. A total of 84,029 women completed a risk assessment questionnaire, from which 20,655 high-risk breast cancer females were evaluated, with a high-risk rate of 24.58%. There were 13,392 high-risk females completed the screening program, with participation rate was 64.84%. Undergoing ultrasound, mammography and combined screening, the suspicious positive detection rates were 15.00%, 9.20% and 19.30%, and the positive detection rates were 2.11%, 2.76% and 3.83%, respectively. According to the results by Markov model, at the end of 45 cycle, the early diagnosis rates were 55.53%, 60.68% and 62.47% underwent the annual screening by ultrasound, mammography and combined, the proportion of advanced cancer were 17.20%, 15.85% and 15.36%, respectively. Different screening method and interval yield varied. In the exploration of various scenarios, annual ultrasound screening is the most cost-effective strategy with the ICER of ¥116,176.15/QALY. Sensitivity analyses demonstrated that the results are robust. Although it was not cost effective, combined ultrasound and mammography screening was an effective strategy for higher positive detection rate of breast cancer. High-risk population-based breast cancer screening by ultrasound annually was the most cost-effective strategy in Urban Hebei Province.

Análisis de un algoritmo de riesgo de errores de medicación: una experiencia portuguesa / Analysis of a medication error risk algorithm: a portuguese experience

Los errores de medicación son cada vez más comunes lo cual pone en peligro la salud de los pacientes, de ahí la importancia de prevenirlos y controlarlos. El concepto de crear una herramienta de decisión clínica que permita gestionar mejor estos eventos no es nuevo. Utilizando una experiencia danesa, decidimos aplicar el algoritmo de MERIS (Medication Risk Score) en un servicio de accidente cerebrovascular de un hospital portugués con el fin de probar su aplicabilidad, determinar volumen de pacientes de riesgo y comprobar cual variable del algoritmo se correlaciona más con paciente de riesgo. Con una muestra de 65 pacientes con sus respectivos reportes MERIS se determinó que durante dos meses más de la mitad de los pacientes admitidos eran de alto riesgo para errores en su medicación. Se seleccionó la prueba de correlación de Spearman para determinar cuál de todas las variables de MERIS estaba más relacionada a un puntaje alto. Encontramos correlaciones positivas fuertes y estadísticamente significativas entre el puntaje de Meris y: función renal reducida, número de fármacos con bajo riesgo de daño, número de fármacos con alto riesgo de daño, número de fármacos, número de fármacos con riesgo medio de daño y número de fármacos con riesgo de interacción bajo a medio, siendo estos últimos tres los más significativos. No hubo una correlación estadísticamente significativa entre el puntaje MERIS y el número de fármacos con alto riesgo de interacción. Finalmente, modificamos la lista de medicamentos propuesta por los autores anteriores adaptada a nuestro hospital. (AU)

Medication errors are gradually more common, risking patients health, hence the importance of preventing and controlling them. The concept of creating a clinical decision tool to better manage these events is not new. Using a Danish experience, we applied the MERIS (Medication Risk Score) algorithm in a stroke unit of a Portuguese hospital in order to test its applicability, determine the volume of patients at risk and check which variable of the algorithm correlates more with patient risk. Using a sample of 65 patients with their respective MERIS reports, we determined that for two months more than half of the admitted patients were at high risk of errors in their medication. The Spearman correlation test was selected to determine which MERIS variable was most related to a high score. We found strong and statistically significant positive correlations between the Meris score and: reduced kidney function, number of drugs with low risk of damage, number of drugs with high risk of damage, number of drugs, number of drugs with medium risk of damage and number of drugs with low to medium risk of interaction, the latter three being the most significant. There was no statistically significant correlation between the MERIS score and the number of drugs with a high risk of interaction. Finally, we modify the list of medications proposed by the previous authors adapted to our hospital. (AU)

The Faroe Islands COVID-19 Recreational Football Study: Player-to-Player Distance, Body-to-Body Contact, Body-to-Ball Contact and Exercise Intensity during Various Types of Football Training for Both Genders and Various Age Groups.

We determined player-to-player distance, body-to-ball contact, and exercise intensity during three training modalities in various football populations. 213 participants were recruited, ranging from 9-year-old boys to young men and 11-year-old girls to middle-aged women. All groups were analysed with video-filming and GPS-based Polar Pro monitors during three types of football training for 20 min, i.e., COVID-19-modified training (CMT) with >2-metre player-to-player distance, small-sided games (SSG), and simulated match-play with normal rules (SMP), in randomised order. Time spent in a danger zone (1.5 m) per-percent-infected-player (DZ PPIP) ranged from 0.015 to 0.279% of playing time. DZ PPIP for SSG was higher (P < 0.05) than CMT and SMP. The average number of contacts (within 1.5 m) with a potentially infected player ranged from 12 to 73 contacts/hour. SSG had more (P < 0.05) contacts than CMT and SMP, with SMP having a higher (P < 0.05) number of contacts than CMT. Time/contact ranged from 0.87 to 3.00 seconds for the groups. No player-to-player and body-to-ball touches were registered for CMT. Total player-to-player contacts were 264% higher (P < 0.05) in SSG than SMP, ranging from 80 to 170 and 25 to 56 touches, respectively. In all groups, a greater total distance was covered during SMP compared to CMT (38-114%; P < 0.05). All groups performed more high-intensity running (33-54%; P < 0.05) and had higher heart rates during SMP compared to CMT. Different types of football training all appear to exert a minor COVID-19 infection risk; however, COVID-19-modified training may be safer than small-sided game training, but also match-play. In contrast, exercise intensity is lower during COVID-19-modified training than match-play.

Lipidomic risk scores are independent of polygenic risk scores and can predict incidence of diabetes and cardiovascular disease in a large population cohort.

Type 2 diabetes (T2D) and cardiovascular disease (CVD) represent significant disease burdens for most societies and susceptibility to these diseases is strongly influenced by diet and lifestyle. Physiological changes associated with T2D or CVD, such has high blood pressure and cholesterol and glucose levels in the blood, are often apparent prior to disease incidence. Here we integrated genetics, lipidomics, and standard clinical diagnostics to assess future T2D and CVD risk for 4,067 participants from a large prospective population-based cohort, the Malmö Diet and Cancer-Cardiovascular Cohort. By training Ridge regression-based machine learning models on the measurements obtained at baseline when the individuals were healthy, we computed several risk scores for T2D and CVD incidence during up to 23 years of follow-up. We used these scores to stratify the participants into risk groups and found that a lipidomics risk score based on the quantification of 184 plasma lipid concentrations resulted in a 168% and 84% increase of the incidence rate in the highest risk group and a 77% and 53% decrease of the incidence rate in lowest risk group for T2D and CVD, respectively, compared to the average case rates of 13.8% and 22.0%. Notably, lipidomic risk correlated only marginally with polygenic risk, indicating that the lipidome and genetic variants may constitute largely independent risk factors for T2D and CVD. Risk stratification was further improved by adding standard clinical variables to the model, resulting in a case rate of 51.0% and 53.3% in the highest risk group for T2D and CVD, respectively. The participants in the highest risk group showed significantly altered lipidome compositions affecting 167 and 157 lipid species for T2D and CVD, respectively. Our results demonstrated that a subset of individuals at high risk for developing T2D or CVD can be identified years before disease incidence. The lipidomic risk, which is derived from only one single mass spectrometric measurement that is cheap and fast, is informative and could extend traditional risk assessment based on clinical assays.

Half of germline pathogenic and likely pathogenic variants found on panel tests do not fulfil NHS testing criteria.

Genetic testing for cancer predisposition has been curtailed by the cost of sequencing, and testing has been restricted by eligibility criteria. As the cost of sequencing decreases, the question of expanding multi-gene cancer panels to a broader population arises. We evaluated how many additional actionable genetic variants are returned by unrestricted panel testing in the private sector compared to those which would be returned by adhering to current NHS eligibility criteria. We reviewed 152 patients referred for multi-gene cancer panels in the private sector between 2014 and 2016. Genetic counselling and disclosure of all results was standard of care provided by the Consultant. Every panel conducted was compared to current eligibility criteria. A germline pathogenic / likely pathogenic variant (P/LP), in a gene relevant to the personal or family history of cancer, was detected in 15 patients (detection rate of 10%). 46.7% of those found to have the P/LP variants (7 of 15), or 4.6% of the entire set (7 of 152), did not fulfil NHS eligibility criteria. 46.7% of P/LP variants in this study would have been missed by national testing guidelines, all of which were actionable. However, patients who do not fulfil eligibility criteria have a higher Variant of Uncertain Significance (VUS) burden. We demonstrated that the current England NHS threshold for genetic testing is missing pathogenic variants which would alter management in 4.6%, nearly 1 in 20 individuals. However, the clinical service burden that would ensue is a detection of VUS of 34%.

Predictive Ability of Visit-to-Visit Variability of HbA1c Measurements for the Development of Diabetic Kidney Disease: A Retrospective Longitudinal Observational Study.

AIMS: This study is aimed at clarifying the relationship between visit-to-visit variability of glycated hemoglobin (HbA1c) and the risk of diabetic kidney disease (DKD) and to identifying the most useful index of visit-to-visit variability of HbA1c. METHODS: This clinic-based retrospective longitudinal study included 699 Japanese type 2 diabetes mellitus patients. Visit-to-visit variability of HbA1c was calculated as the internal standard deviation of HbA1c (HbA1c-SD), the coefficient of variation of HbA1c (HbA1c-CV), the HbA1c change score (HbA1c-HVS), and the area under the HbA1c curve (HbA1c-AUC) with 3-year serial HbA1c measurement data, and the associations between these indices and the development/progression of DKD were examined. RESULTS: Cox proportional hazards models showed that the HbA1c-SD and HbA1c-AUC were associated with the incidence of microalbuminuria, independently of the HbA1c level. These results were verified and replicated in propensity score (PS) matching and bootstrap analyses. Moreover, the HbA1c-SD and HbA1c-AUC were also associated with oxidized human serum albumin (HSA), an oxidative stress marker. CONCLUSIONS: Visit-to-visit variability of HbA1c was an independent risk factor of microalbuminuria in association with oxidative stress among type 2 diabetes mellitus patients. HbA1c-AUC, a novel index of HbA1c variability, may be a potent prognostic indicator in predicting the risk of microalbuminuria.

Dihydroceramide- and ceramide-profiling provides insights into human cardiometabolic disease etiology.

Metabolic alterations precede cardiometabolic disease onset. Here we present ceramide- and dihydroceramide-profiling data from a nested case-cohort (type 2 diabetes [T2D, n = 775]; cardiovascular disease [CVD, n = 551]; random subcohort [n = 1137]) in the prospective EPIC-Potsdam study. We apply the novel NetCoupler-algorithm to link a data-driven (dihydro)ceramide network to T2D and CVD risk. Controlling for confounding by other (dihydro)ceramides, ceramides C18:0 and C22:0 and dihydroceramides C20:0 and C22:2 are associated with higher and ceramide C20:0 and dihydroceramide C26:1 with lower T2D risk. Ceramide C16:0 and dihydroceramide C22:2 are associated with higher CVD risk. Genome-wide association studies and Mendelian randomization analyses support a role of ceramide C22:0 in T2D etiology. Our results also suggest that (dh)ceramides partly mediate the putative adverse effect of high red meat consumption and benefits of coffee consumption on T2D risk. Thus, (dihydro)ceramides may play a critical role in linking genetic predisposition and dietary habits to cardiometabolic disease risk.