Search

Background and Objective: Despite the proven effectiveness of organized PSA-based screening in reducing prostate cancer-related mortality, there is currently no program in Germany covered by statutory health insurance. In accordance with the EU Council Decision (2022/0290(NLE)), the German Society of Urology (DGU) has developed a concept for risk-adapted prostate cancer early detection., Materials and Methods: Based on a literature review of current screening studies, an algorithm for PSA-based prostate cancer early detection was developed., Results: Risk-adapted prostate cancer screening involves PSA testing in the age group of 45-70 years, followed by PSA-based individual risk stratification and stepwise expansion of diagnostics through magnetic resonance imaging (MRI) to biopsy. While initially up to 2.6 million men will undergo PSA testing, a reduction in these initial examinations to fewer than 200,000 men per year will occur from year four onwards., Conclusions: The presented algorithm provides clear recommendations for risk-adapted PSA-based early detection for prostate cancer for urologists and patients. The goal is to improve diagnosis of clinically significant prostate cancer, while reducing overdiagnosis and overtreatment., (© 2024. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

Background: The risk factors for acute skin failure (ASF), a serious complication of the skin, are not fully understood., Purpose: This study was designed to explore the risk factors for ASF in critically ill patients and construct a clinical prediction model., Methods: Intensive care unit patients were prospectively observed and assigned into two groups: with and without ASF. A logistic regression model was constructed, and its predictive power and clinical utility were evaluated., Results: Of the 204 eligible patients enrolled as participants, 58 (28.43%) developed ASF. Sepsis, vasoactive drugs, and age were shown to be risk factors for ASF, whereas peripheral perfusion index ratio and albumin level were shown to be protective factors. The area under the receiver operating characteristic curve was 0.83. The maximum Youden index of the model was 0.39 (specificity: 0.87, sensitivity: 0.77). The Hosmer-Lemeshow test (p = .20) and calibration curve showed good fitness and predictive utility with respect to the model., Conclusions: The developed model effectively predicts ASF risk, allowing for the early identification of high-risk patients. Identifying risk factors such as sepsis, vasoactive drugs, and age and considering protective factors such as peripheral perfusion index and albumin levels may help optimize care plans. Clinical staff should pay special attention to these factors and their impact on skin health in critically ill patients., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc.)

Background: The Braden scale, one of the most widely used risk assessment tools is often criticized when used in the Intensive Care Unit. Most patients in the Intensive Care Unit are at risk of pressure ulcer development meaning that the Braden score will usually indicate high risk for these patients. This study set out to determine the correlation between Sub-Epidermal Moisture measurements and Braden scores among Intensive Care Unit patients., Methods: This study employed an observational research design. Braden score was assessed on all study days (1-5), in addition to visual skin assessment and Sub-Epidermal Moisture measurements at the sacrum and heels. Sub-Epidermal Moisture measurements were categorised as low (<0.5), borderline abnormal (≥0.5), and high (≥0.8). Correlation was assessed between Sub-Epidermal Moisture levels and Braden scores., Results: A total of 53 participants were recruited. The median (interquartile range) baseline Braden score was 9 (9-10) and 81 % (n = 43) of participants were at very high/high risk of pressure ulcer development. Braden scores remained relatively constant over time with little fluctuation in scores. 19 % (n = 10) of patients had normal (<0.5) Sub-Epidermal Moisture delta measurements on enrolment, and all developed abnormal measurements by day 2. There were no significant correlations between Braden scores and Sub-Epidermal Moisture measurements., Conclusion: Although this was not its original intention, a missing link with the Braden scale is that it does not provide information on how patients are responding to the adverse effects of pressure and shear forces. Furthermore, in patients who are critically unwell, most patients are classified as being "at risk" of pressure ulcer development. Therefore, an objective measure of how patients are responding to pressure and shear forces at different anatomical areas is needed., Implications to Clinical Practice: Sub-Epidermal Moisture measurements can offer more information, not only on identifying those who are at risk, but also how those patients are tolerating this risk at different anatomical sites., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: The School of Nursing & Midwifery at the Royal College of Surgeons in Ireland have a research collaboration with Bruin Biometrics. The SEM scanner used in this study was provided by Bruin Biometrics., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Patients with cancer are susceptible to pressure injuries, which accelerate deterioration and death. In patients with post-acute cancer, the risk of pressure injury is ignored in home or community settings., Objective: To develop and validate a community-acquired pressure injury risk prediction model for cancer patients., Methods: All research data were extracted from the hospital's electronic medical record system. The identification of optimal predictors is based on least absolute shrinkage and selection operator regression analysis combined with clinical judgment. The performance of the model was evaluated by drawing a receiver operating characteristic curve and calculating the area under the curve (AUC), calibration analysis and decision curve analysis. The model was used for internal and external validation, and was presented as a nomogram., Results: In total, 6257 participants were recruited for this study. Age, malnutrition, chronic respiratory failure, body mass index, and activities of daily living scores were identified as the final predictors. The AUC of the model in the training and validation set was 0.87 (95 % confidence interval [CI], 0.85-0.89), 0.88 (95 % CI, 0.85-0.91), respectively. The model demonstrated acceptable calibration and clinical benefits., Conclusions: Comorbidities in patients with cancer are closely related to the etiology of pressure injury, and can be used to predict the risk of pressure injury., Implications for Practice: This study provides a tool to predict the risk of pressure injury for cancer patients. This suggests that improving the respiratory function and nutritional status of cancer patients may reduce the risk of community-acquired pressure injury., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Tissue Viability Society / Society of Tissue Viability. Published by Elsevier Ltd. All rights reserved.)

Research participants are often deceived for methodological reasons. However, assessing the ethical acceptability of an individual study that uses deception is not straightforward. The academic literature is scattered on the subject and several aspects of the acceptability assessment are only scarcely addressed, which parallels reports of inconsistent ethics review. Therefore, we aimed to investigate where normative guidance documents agree and disagree about this assessment. A PRISMA-Ethics-guided systematic review of normative guidance documents that discuss deception of research participants was conducted. Our search strategy resulted in 55 documents that were subsequently analyzed through abductive thematic analysis. While guidance documents mention little about specific risks and opportunities of deception, our analysis describes a rich picture of the thresholds for acceptability of the risks and benefits of deception and their integration, the comparison with the risk-benefit analysis of alternative non-deceptive methods, and the bodies of people who are positioned to do the review. Our review reveals an agreement on the general process of assessing the acceptability of studies that use deception, although significant variability remains in the details and several topics are largely or completely unaddressed in guidance documents.

Objectives: To assess the interrater reliability of the COMHON (level of COnciousness, Mobility, Haemodynamics, Oxygenation, Nutrition) Index pressure injury risk assessment tool., Design: Interrater reliability was tested. Twenty-five intensive care patients were each assessed by five different nurse-raters from a pool of intensive care nurses who were available on the days of assessment. In total, 25 nurses participated., Setting: Two general and one cardiovascular surgery intensive care units in Istanbul, Turkey., Main Outcome Measures: Interrater reliability was analysed using intraclass correlations, and standard errors of measurement (SEM) were calculated for sum scores, risk level and item scores. Minimally detectable change (MDC) was also calculated for sum score. Consistency between paired raters was analysed using Pearson's Product Moment Correlation (r) for sum score and Spearman's rho (r s ) for ordinal variables., Results: All assessments were completed in ≤5 min. Interrater reliability was very high [ICC (1,1) = 0.998 (95 % CI 0.996 - 0.999)] with a SEM of 0.14 and MDC of 0.39. Consistency between paired raters was strong for sum and item scores and risk levels (coefficients >0.6). All scale items showed correlations of >.3 with the sum score., Conclusion: The results demonstrate near-perfect interrater reliability. Further research into the psychometric properties of the COMHON Index and its impact on preventative intervention use is warranted., Implications for Clinical Practice: Pressure injury risk assessment within intensive care should be setting-specific due to the unique risk factors inherent to the patient population, which are not considered by general pressure injury risk assessment tools. An intensive care-specific pressure injury risk assessment tool was tested and demonstrated high reliability between intensive care nurses. Further research is needed to understand how its use in practice affects preventative intervention implementation and, in turn, how it impacts pressure injury outcomes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Objective: To analyse the psychometric properties of the Braden scale to assess pressure injury risk in adults in intensive care., Design: A systematic review was conducted, with literature searches undertaken in five electronic databases. No date limits were applied. Selection, data extraction and risk of bias assessment were completed by two reviewers independently. A customised data extraction template was used, with risk of bias conducted using the COSMIN Risk of Bias checklist. Data were analysed using narrative synthesis., Results: Thirty-four studies met inclusion criteria. Two studies reported internal consistency with Cronbach's alpha ranging from poor (0.43) to good (0.85). For interrater reliability, only four studies reported intraclass correlation, ranging from 0.66 to 0.96 for Braden sum score. Three studies reported convergent validity, with strong associations found between the COMHON Index (r = 0.70), Cubbin-Jackson scale (r = 0.80), and Norton scale (r = 0.77), but contrasting associations with the Waterlow score (r = 0.22 to 0.72). A large majority of studies reported predictive validity (n = 29), with wide variability. Several studies investigated optimal cut-off scores, with the majority indicating this was in the range of 12-14., Conclusions: This review demonstrates inconsistency in the psychometric properties of the Braden scale in ICU settings. Further research is needed to determine suitability of the Braden scale for ICU before it can be recommended as standard for clinical practice, including comparison with other ICU-specific risk assessment tools., Implications for Clinical Practice: When used in ICU, the reliability, validity and reported cut-off scores of the Braden scale are variable. As a predictive tool, the scale should be used cautiously. In ICU, the value of the Braden scale resides in its ability to identify patients that are most at risk of developing a pressure injury and to implement preventative measures to mitigate identified risk factors., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Introduction: The reason for this study was void of a data-driven imminent risk assessment instrument for aggression in psychiatry clinics in Estonia. The predictive accuracy of the observer-rated Dynamic Assessment of Situational Aggression (DASA) has been repeatedly demonstrated. However, the research gap remains regarding a deeper conceptual understanding of the underlying latent structure of the DASA., Aim: Comprehensively evaluate the psychometric properties of the Estonian DASA version for cross-cultural clinical use., Method: We used a prospective repeated measure design and collected 6097 risk evaluations from 381 adult inpatients, 151 of whom committed 1013 aggressive incidents during the study., Results: The Estonian DASA version has acceptable inter-rater reliability (Kendall's τ = 0.74) and is a useful instrument with excellent predictive validity (AUC = 0.86) for identifying potentially aggressive inpatients. In our sample, the DASA has a bi-factorial structure which explains 83% of the total variance., Discussion: The adapted DASA has acceptable validity and reliability indices for measuring imminent aggression risk in adult inpatient units., Implications for Practice: Evidence-based risk assessment of aggression in psychiatric clinics enhances recognition of the signs of potentially aggressive behaviour in order to apply preventive actions and reduce aggression, thereby improving the quality of the care provided., (© 2024 John Wiley & Sons Ltd.)

Background: Binary classification models are frequently used to predict clinical deterioration, however they ignore information on the timing of events. An alternative is to apply time-to-event models, augmenting clinical workflows by ranking patients by predicted risks. This study examines how and why time-to-event modelling of vital signs data can help prioritise deterioration assessments using lift curves, and develops a prediction model to stratify acute care inpatients by risk of clinical deterioration., Methods: We developed and validated a Cox regression for time to in-hospital mortality. The model used time-varying covariates to estimate the risk of clinical deterioration. Adult inpatient medical records from 5 Australian hospitals between 1 January 2019 and 31 December 2020 were used for model development and validation. Model discrimination and calibration were assessed using internal-external cross validation. A discrete-time logistic regression model predicting death within 24 h with the same covariates was used as a comparator to the Cox regression model to estimate differences in predictive performance between the binary and time-to-event outcome modelling approaches., Results: Our data contained 150,342 admissions and 1016 deaths. Model discrimination was higher for Cox regression than for discrete-time logistic regression, with cross-validated AUCs of 0.96 and 0.93, respectively, for mortality predictions within 24 h, declining to 0.93 and 0.88, respectively, for mortality predictions within 1 week. Calibration plots showed that calibration varied by hospital, but this can be mitigated by ranking patients by predicted risks., Conclusion: Time-varying covariate Cox models can be powerful tools for triaging patients, which may lead to more efficient and effective care in time-poor environments when the times between observations are highly variable., (© 2024. The Author(s).)

Objective: This study aimed to develop and validate a quantitative index system for evaluating the data quality of Electronic Medical Records (EMR) in disease risk prediction using Machine Learning (ML)., Materials and Methods: The index system was developed in four steps: (1) a preliminary index system was outlined based on literature review; (2) we utilized the Delphi method to structure the indicators at all levels; (3) the weights of these indicators were determined using the Analytic Hierarchy Process (AHP) method; and (4) the developed index system was empirically validated using real-world EMR data in a ML-based disease risk prediction task., Results: The synthesis of review findings and the expert consultations led to the formulation of a three-level index system with four first-level, 11 second-level, and 33 third-level indicators. The weights of these indicators were obtained through the AHP method. Results from the empirical analysis illustrated a positive relationship between the scores assigned by the proposed index system and the predictive performances of the datasets., Discussion: The proposed index system for evaluating EMR data quality is grounded in extensive literature analysis and expert consultation. Moreover, the system's high reliability and suitability has been affirmed through empirical validation., Conclusion: The novel index system offers a robust framework for assessing the quality and suitability of EMR data in ML-based disease risk predictions. It can serve as a guide in building EMR databases, improving EMR data quality control, and generating reliable real-world evidence., (© 2024. The Author(s).)

Background and Purpose: The Munro Pressure Injury Risk Assessment Scale for Perioperative Patients (Munro Scale) is the first three-phase risk instrument designed specifically for perioperative patients. The purpose of this study was to establish validity and reliability evidence for the Munro Scale. This study also had a goal to reduce the data into more manageable constructs with fewer items. Methods: Exploratory and confirmatory factor analyses were used to test the hypothesized model for risk assessment using the Munro Scale to identify latent variables. A retrospective review of charts from 630 risk assessments was analyzed from two community acute care hospital settings. Results: The model explained 95% of the variance in the cumulative final risk level, R 2 = .95, F (20, 588) = 501.88, p < .001. Six latent variables emerged in the model with a cumulative contribution rate of 56% of the variance. Similar results were obtained in studies with Chinese and Turkish translations of the Munro Scale. Conclusions: The validity and reliability evidence obtained in this study supports the implementation of the Munro Scale for clinical practice in the perioperative setting., (© Copyright 2024 Springer Publishing Company, LLC.)

Background: Following a national multicentre study, two emergency department (ED) screening tools were developed to determine risk of medication-related problems; one for use at ED presentation and another at ED discharge to the community. This study aimed to determine the inter-rater reliability amongst ED health professionals when applying these screening tools to a series of case scenarios., Methods: A prospective, cross-sectional study was undertaken in the ED of a major metropolitan hospital. Twelve case scenarios were developed following ED observation of a range of patients, which were incorporated into a questionnaire and distributed to 50 health professionals. Inter-rater reliabilities of each explanatory variable of the screening tools and overall assessment were calculated using Fleiss' multi-rater kappa., Results: The questionnaire was completed by 15 doctors, 19 nurses and 16 pharmacists. Fleiss' kappa showed an overall inter-rater reliability for the ED presentation tool of 0.83 (95% CI 0.83-0.84), indicating near perfect agreement. Fleiss' kappa for the ED discharge tool was 0.83 (95% CI 0.83-0.85), which also showed near perfect agreement., Conclusions: The screening tools produced favourable inter-rater reliability amongst ED health professionals. These results have important implications for ensuring consistency of ED decision-making in screening patients at risk of developing medication-related problems., Competing Interests: Declaration of Competing Interest All authors wish to confirm there are no known actual or potential conflicts of interest in relation to this paper or the research conducted in relation to this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: An accurate perception of death risk is a prerequisite for advanced cancer patients to make informed end-of-life care decisions. However, there is to date no suitable scale to measure death risk perception. This study was to develop and psychometrically test the death risk perception scale (DRPS) for advanced cancer patients., Methods: Process of instrument development and psychometric evaluation were used. First, qualitative research, a literature review, brainstorming, a Delphi study, and cognitive interviews were conducted to construct a pretest scale of death risk perception. Second, a scale-based survey was administered to 479 advanced cancer patients. Item, exploratory factor, and confirmatory factor analyses were employed to optimize the scale. The Cronbach's alpha was calculated as a reliability analysis. The validity analysis included construct, convergent, discriminant, and content validity values., Results: A three-dimension, 12-item scale was developed, including deliberative, affective, and experiential risk perception. The confirmatory factor analysis supported the three-factor model with satisfactory convergent and discriminant validity levels. The Cronbach's alpha coefficient for internal consistency was 0.807 and scale-level content validity index was 0.98., Conclusions: The 12-item DRPS is a reliable and valid instrument for assessing the level of death risk perception in advanced cancer patients. More studies are needed to examine its structure and robustness prior to use., (© 2024. The Author(s).)

Aims: To determine the prevalence, risk, and determinants of pressure ulcer risk in a large cohort of hospitalized patients., Design: A prospective cross-sectional study with data collection in January 2023., Methods: Registered nurses collected data from 798 patients admitted to 27 health care units of an Italian hospital. The pressure ulcer risk was assessed using the Braden scale. The presence of comorbidities was collected from clinical reports. Obesity was assessed according to international indicators (Body Mass Index). The receiver operating characteristic (ROC) curve was used to estimate the sensitivity and specificity of different Braden scores for identifying participants with pressure ulcers., Results: The prevalence of pressure ulcers was 9.5%, and 57.4% of the sample were at risk of developing pressure ulcers. The area under the ROC curve was 0.88. The best sensitivity and specificity were found for a Braden cutoff score of 15.5 (sensibility = 0.76; specificity = 0.85). The determinants of lower Braden scores were older age (p < 0.001), comorbidities (p < 0.001), wounds of other nature (p = 0.001), urinary incontinence (p < 0.001), fecal incontinence (p < 0.001), and urinary catheterization (p < 0.001)., Conclusion: Several demographic factors and specific clinical indicators have been identified as determinants of the risk of developing pressure ulcers, which are easily ascertainable by healthcare providers; thus, they may routinely complement the Braden Scale in the assessment of pressure ulcer risk in order to reinforce and accelerate clinical judgment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Aim: This study was carried out to determine the prevalence of pressure injury and risk factors in patients hospitalized in a university hospital's level 3 intensive care unit., Design: It is a descriptive, prospective, observational type study., Method: The sample of the study consisted of 176 patients aged 18 and over who were admitted to the intensive care units of a University Hospital for at least 24 h. Patient Information Form and Braden Risk Assessment Scale, Glasgow Coma Scale were used to collect data. IBM SPSS Statistics 20 program was used to analyze the data., Results: Presence of chronic disease in the development of pressure injury (22.7%), high-risk patients according to the Glasgow Coma Scale (21%), high-risk patients according to the Braden Risk Assessment Scale (84.2%), low hemoglobin (31%), low albumin levels (32.4%) and duration of stay in the intensive care unit until the day of evaluation were found to be independent risk factors (p < 0.05). The prevalence of pressure injury was determined to be 32.4%, and the rate of pressure injury due to medical devices was 7.4%., Conclusion: Pressure injuries are still common in adult intensive care patients. In terms of patient safety, it is important to give more space to care standards and awareness-raising research and training to prevent pressure injuries., (Copyright © 2024 Tissue Viability Society / Society of Tissue Viability. Published by Elsevier Ltd. All rights reserved.)

Background: Physical rehabilitation of critically ill patients is implemented to improve physical outcomes from an intensive care stay. However, before rehabilitation is implemented, a risk assessment is essential, based on robust safety data. To develop this information, a uniform definition of relevant adverse events is required. The assessment of cardiovascular stability is particularly relevant before physical activity as there is uncertainty over when it is safe to start rehabilitation with patients receiving vasoactive drugs., Methods: A three-stage Delphi study was carried out to (a) define adverse events for a general ICU cohort, and (b) to define which risks should be assessed before physical rehabilitation of patients receiving vasoactive drugs. An international group of intensive care clinicians and clinician researchers took part. Former ICU patients and their family members/carers were involved in generating consensus for the definition of adverse events. Round one was an open round where participants gave their suggestions of what to include. In round two, participants rated their agreements with these suggestions using a five-point Likert scale; a 70% consensus agreement threshold was used. Round three was used to re-rate suggestions that had not reached consensus, whilst viewing anonymous feedback of participant ratings from round two., Results: Twenty-four multi-professional ICU clinicians and clinician researchers from 10 countries across five continents were recruited. Average duration of ICU experience was 18 years (standard deviation 8) and 61% had publications related to ICU rehabilitation. For the adverse event definition, five former ICU patients and one patient relative were recruited. The Delphi process had a 97% response rate. Firstly, 54 adverse events reached consensus; an adverse event tool was created and informed by these events. Secondly, 50 risk factors requiring assessment before physical rehabilitation of patients receiving vasoactive drugs reached consensus. A second tool was created, informed by these suggestions., Conclusions: The adverse event tool can be used in studies of physical rehabilitation to ensure uniform measurement of safety. The risk assessment tool can be used to inform clinical practise when risk assessing when to start rehabilitation with patients receiving vasoactive drugs. Trial registration This study protocol was retrospectively registered on https://www.researchregistry.com/ (researchregistry2991)., (© 2024. The Author(s).)

Importance: An estimated 1.2 million persons in the US currently have HIV, and more than 760 000 persons have died of complications related to HIV since the first cases were reported in 1981. Although treatable, HIV is not curable and has significant health consequences. Therefore, effective strategies to prevent HIV are an important public health and clinical priority., Objective: The US Preventive Services Task Force (USPSTF) commissioned a systematic review to evaluate the benefits and harms of preexposure prophylaxis with antiretroviral therapy for the prevention of HIV acquisition, and the diagnostic accuracy of risk assessment tools to identify persons at increased risk of HIV acquisition., Population: Adolescents and adults who do not have HIV and are at increased risk of HIV., Evidence Assessment: The USPSTF concludes with high certainty that there is a substantial net benefit from the use of effective antiretroviral therapy to reduce the risk of acquisition of HIV in persons at increased risk of acquiring HIV., Recommendation: The USPSTF recommends that clinicians prescribe preexposure prophylaxis using effective antiretroviral therapy to persons at increased risk of HIV acquisition to decrease the risk of acquiring HIV. (A recommendation).

Objective: To evaluate the effectiveness of a risk-adapted colorectal cancer screening strategy constructed utilizing genetic and environmental risk score (ERS). Methods: A polygenic risk score (PRS) was constructed based on 20 previously published single nucleotide polymorphisms for colorectal cancer in East Asian populations, using 2 160 samples with MassARRAY test results from a multicenter randomized controlled trial of colorectal cancer screening in China. The ERS was calculated using the Asia-Pacific Colorectal Screening Score system. Logistic regression was used to analyze the association between PRS alone and PRS combined with ERS and colorectal neoplasms risk, respectively. We also designed a risk-adapted screening strategy based on PRS and ERS (high-risk participants undergo a single colonoscopy, low-risk participants undergo an annual fecal immunochemical test, and those with positive results undergo further diagnostic colonoscopy) and compared its effectiveness with the all-acceptance colonoscopy strategy. Results: The high PRS group had a 26% increased risk of colorectal neoplasms compared with the low PRS group ( OR =1.26, 95% CI : 1.03-1.54, P =0.026). Participants with the highest PRS and ERS were 3.03 times more likely to develop advanced colorectal neoplasms than those with the lowest score (95% CI : 1.87-4.90, P <0.001). As the risk-adapted screening simulation reached the third round, the detection rate of the PRS combined with ERS strategy was not statistically different from the all-acceptance colonoscopy strategy (8.79% vs. 10.46%, P =0.075) and had a higher positive predictive value (14.11% vs. 10.46%, P <0.001) and lower number of colonoscopies per advanced neoplasms detected (7.1 vs. 9.6, P <0.001). Conclusion: The risk-adapted screening strategy combining PRS and ERS helps achieve population risk stratification and better effectiveness than the traditional colonoscopy-based screening strategy.

Importance: Stroke is the fifth-highest cause of death in the US and a leading cause of serious long-term disability with particularly high risk in Black individuals. Quality risk prediction algorithms, free of bias, are key for comprehensive prevention strategies., Objective: To compare the performance of stroke-specific algorithms with pooled cohort equations developed for atherosclerotic cardiovascular disease for the prediction of new-onset stroke across different subgroups (race, sex, and age) and to determine the added value of novel machine learning techniques., Design, Setting, and Participants: Retrospective cohort study on combined and harmonized data from Black and White participants of the Framingham Offspring, Atherosclerosis Risk in Communities (ARIC), Multi-Ethnic Study for Atherosclerosis (MESA), and Reasons for Geographical and Racial Differences in Stroke (REGARDS) studies (1983-2019) conducted in the US. The 62 482 participants included at baseline were at least 45 years of age and free of stroke or transient ischemic attack., Exposures: Published stroke-specific algorithms from Framingham and REGARDS (based on self-reported risk factors) as well as pooled cohort equations for atherosclerotic cardiovascular disease plus 2 newly developed machine learning algorithms., Main Outcomes and Measures: Models were designed to estimate the 10-year risk of new-onset stroke (ischemic or hemorrhagic). Discrimination concordance index (C index) and calibration ratios of expected vs observed event rates were assessed at 10 years. Analyses were conducted by race, sex, and age groups., Results: The combined study sample included 62 482 participants (median age, 61 years, 54% women, and 29% Black individuals). Discrimination C indexes were not significantly different for the 2 stroke-specific models (Framingham stroke, 0.72; 95% CI, 0.72-073; REGARDS self-report, 0.73; 95% CI, 0.72-0.74) vs the pooled cohort equations (0.72; 95% CI, 0.71-0.73): differences 0.01 or less (P values >.05) in the combined sample. Significant differences in discrimination were observed by race: the C indexes were 0.76 for all 3 models in White vs 0.69 in Black women (all P values <.001) and between 0.71 and 0.72 in White men and between 0.64 and 0.66 in Black men (all P values ≤.001). When stratified by age, model discrimination was better for younger (<60 years) vs older (≥60 years) adults for both Black and White individuals. The ratios of observed to expected 10-year stroke rates were closest to 1 for the REGARDS self-report model (1.05; 95% CI, 1.00-1.09) and indicated risk overestimation for Framingham stroke (0.86; 95% CI, 0.82-0.89) and pooled cohort equations (0.74; 95% CI, 0.71-0.77). Performance did not significantly improve when novel machine learning algorithms were applied., Conclusions and Relevance: In this analysis of Black and White individuals without stroke or transient ischemic attack among 4 US cohorts, existing stroke-specific risk prediction models and novel machine learning techniques did not significantly improve discriminative accuracy for new-onset stroke compared with the pooled cohort equations, and the REGARDS self-report model had the best calibration. All algorithms exhibited worse discrimination in Black individuals than in White individuals, indicating the need to expand the pool of risk factors and improve modeling techniques to address observed racial disparities and improve model performance.

The American Institute of CPAs issued 10 new standards for external auditors. The standards address both documentation requirements for the audit and terminology used in professional mandates. Eight of the standards are collectively known as the Risk Assessment Standards; they focus on assessing the various risks in the audit engagement and on the procedures used by the auditor to address those risks. The forensic accountant should gain a thorough understanding of the requirements of these new external audit standards. The work completed by the external auditor will be substantially enhanced under these mandates and thus, will yield more information useful to forensic accountants. [ABSTRACT FROM AUTHOR]

The objective of this retrospective cohort study was to decrease the frequency of laboratory draws and the number of neonates receiving empiric antibiotics who are born to mothers with chorioamnionitis from 100% to 50% 6 months following implementation of the sepsis risk calculator (SRC) at a level 1 community nursery. Data were compared pre- and post-implementation of the SRC using the Fischer's exact test. The rate of intravenous (IV) antibiotic use decreased from 93% to 7% ( P < .0001). The rate of blood culture collection decreased from 100% to 46% ( P < .0001). With implementation of the SRC, administration of IV antibiotics, laboratory draws, and IV placement significantly decreased without increasing rates of early-onset sepsis in our patient population. Our study demonstrated that the SRC can be effectively and safely implemented at a level 1 community-based newborn nursery, resulting in a decrease in unnecessary medical treatment without negative patient outcomes.

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%., (© 2022. The Author(s).)

Background & Aims: Guidelines recommend hepatocellular carcinoma (HCC) surveillance in patients with chronic HBV infection. Several HCC risk prediction models are available to guide surveillance decisions, but their comparative performance remains unclear., Methods: Using a retrospective cohort of patients with HBV treated with nucleos(t)ide analogues at 130 Veterans Administration facilities between 9/1/2008 and 12/31/2018, we calculated risk scores from 10 HCC risk prediction models (REACH-B, PAGE-B, m-PAGE-B, CU-HCC, HCC-RESCUE, CAMD, APA-B, REAL-B, AASL-HCC, RWS-HCC). We estimated the models' discrimination and calibration. We calculated HCC incidence in risk categories defined by the reported cut-offs for all models., Results: Of 3,101 patients with HBV (32.2% with cirrhosis), 47.0% were treated with entecavir, 40.6% tenofovir, and 12.4% received both. During a median follow-up of 4.5 years, 113 patients developed HCC at an incidence of 0.75/100 person-years. AUC values for 3-year HCC risk were the highest for RWS-HCC, APA-B, REAL-B, and AASL-HCC (all >0.80). Of these, 3 (APA-B, RWS-HCC, REAL-B) incorporated alpha-fetoprotein. AUC values for the other models ranged from 0.73 for PAGE-B to 0.79 for CAMD and HCC-RESCUE. Of the 7 models with AUC >0.75, only APA-B was poorly calibrated. In total, 10-20% of the cohort was deemed low-risk based on the published cut-offs. None of the patients in the low-risk groups defined by PAGE-B, m-PAGE-B, AASL-HCC, and REAL-B developed HCC during the study timeframe., Conclusion: In this national cohort of US-based patients with HBV on antiviral treatment, most models performed well in predicting HCC risk. A low-risk group, in which no cases of HCC occurred within a 3-year timeframe, was identified by several models (PAGE-B, m-PAGE-B, CAMD, AASL-HCC, REAL-B). Further studies are warranted to examine whether these patients could be excluded from HCC surveillance., Lay Summary: Risk prediction models for hepatocellular carcinoma (HCC) in patients infected with hepatitis B virus (HBV) could guide HCC surveillance decisions. In this large cohort of US-based patients receiving treatment for HBV, most published models discriminated between those who did or did not develop HCC, although the RWS-HCC, REAL-B, and AASL-HCC performed the best. If confirmed in future studies, these models could help identify a low-risk subset of patients on antiviral treatment who could be excluded from HCC surveillance., Competing Interests: Conflict of interest The authors declare no conflicts of interest that pertain to this work. Please refer to the accompanying ICMJE disclosure forms for further details., (Copyright © 2021. Published by Elsevier B.V.)

Background: Due to the low cancer-detection rate in patients with PIRADS category 3 lesions, we created machine learning (ML) models to facilitate decision-making about whether to perform prostate biopsies or monitor clinical information without biopsy results., Methods: In our retrospective, single-center study, 101 eligible patients with at least one PIRADS category 3 lesion but no higher PIRADS lesions underwent MRI/US fusion biopsies between September 2017 and June 2020. Thirty additional patients were included as the validation cohort from the next chronological period from June 2020 to October 2020. Our ML research was a supervised classification problem, with a binary output based on pathological reports of cancerous or benign tissue. The clinical inputs were age, prostate-specific antigen (PSA), prostate volume, prostate-specific antigen density (PSAD), and the number of previous biopsies. The radiology-report inputs were the number of lesions, maximum lesion diameter, lesion location, and lesion zone. We subsequently removed the inputs with low importance. Logistic Regression, Support Vector Machine, Naive Bayes, Decision Tree, Random Forest, and eXtreme Gradient Boosting Tree (XGBoost) were employed. From receiver operating characteristic (ROC) curves, we determined Area Under the ROC Curve (AUC), the cut-off point, and sensitivity score (recall score) to evaluate the ML-model performance., Results: Twenty-four adenocarcinoma patients had a mean age of 70 ± 5.79 years, a mean PSA of 12.42 ± 6.67 ng/ml, a mean prostate volume of 46.49 ± 23.13 ml, and a mean PSAD of 0.31 ± 0.22 ng/ml 2 . Seventy-seven patients with benign tissue reports had a mean age of 66.39 ± 6.66 years, a mean PSA of 11.31 ± 7.50 ng/ml, a mean prostate volume of 65.25 ± 35.88 ml, and a mean PSAD of 0.19 ± 0.13 ng/ml 2 . On the validation cohort, XGBoost had the best AUC of 0.76, which considered 80% sensitivity and 72% specificity at a probability cutoff of 57%. The remaining possible ML models performed worse with lesser AUC. The worst was Naïve Bayes, with AUC of 0.50., Conclusions: ML models facilitate PIRADS 3 patient selection for MRI/US fusion biopsies. ML could optimize how we use previously known clinical risk factors to their full potential., (© 2021 Wiley Periodicals LLC.)

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., Competing Interests: The authors declare that they have no conflict of interest., (Copyright © 2022 Yunyi Yan et al.)

Purpose: Neuroendocrine cervical carcinoma (NECC) is an uncommon malignancy of the female reproductive system. This study aimed to evaluate cancer-specific mortality and to construct prognostic nomograms for predicting the survival of patients with NECC., Methods: we assembled the patients with NECC diagnosed between 2004 to 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Meanwhile, we identified other patients with NECC from the Wenling Maternal and Child Health Care Hospital between 2002 to 2017. Fine and Gray's test and Kaplan-Meier methods were used to evaluate cancer-specific mortality and overall survival (OS) rates, respectively. Nomograms were constructed for predicting cancer-specific survival (CSS) and OS for patients with NECC. The developed nomograms were validated both internally and externally., Results: a total of 894 patients with NECC were extracted from the SEER database, then classified into the training cohort (n = 628) and the internal validation cohort (n = 266). Besides, 106 patients from the Wenling Maternal and Child Health Care Hospital served as an external validation cohort. Nomograms for predicting CSS and OS were constructed on clinical predictors. The validation of nomograms was calculated by calibration curves and concordance indexes (C-indexes). Furthermore, the developed nomograms presented higher areas under the receiver operating characteristic (ROC) curves when compared to the FIGO staging system., Conclusions: we established the first competing risk nomograms to predict the survival of patients with NECC. Such a model with high predictive accuracy could be a practical tool for clinicians., (© 2021. The Author(s).)

Objective: To assess the validity of the Caprini risk assessment model (RAM) in risk stratification for deep vein thrombosis (DVT) and to investigate the diagnostic value of Caprini score combined with D-dimer in predicting DVT., Methods: This study involved 429 patients with thoracolumbar fractures caused by high-energy injuries between October 2016 and November 2019. All patients were treated surgically and had a mean age of 45.3 ± 11.4 years. Patients were risk-stratified using the 2013 Caprini RAM. Mechanical and chemical prophylaxis were used for DVT. Duplex ultrasound of both lower extremities was performed before surgery., Results: Of the 429 patients, 62 (14.45%) developed DVT. The incidence of preoperative DVT was correlated with Caprini score according to risk stratification(χ 2  = 117.4, P < 0.001). Based on the original Caprini RAM, all the patients scored in the highest risk category (score ≥5). Further substratification showed that the majority (277 of 429, 64.57%) of the patients were in the Caprini score range 7-8 and the risk of preoperative DVT was significantly higher among patients with Caprini score >10. The area under the receiver operating characteristic curve of Caprini score and D-dimer was 0.816 and 0.769 when Caprini score >8 or D-dimer >1.81mg/L was considered the criterion of predicting the risk of DVT. When combining the 2 variables, the area under the ROC curve can increase to 0.846., Conclusions: The Caprini RAM is an effective and reliable DVT risk stratification tool in patients with thoracolumbar fractures caused by high-energy injuries. Caprini score >8 or D-dimer >1.81 mg/L may predict the occurrence of preoperative DVT and the Caprini score combined with D-dimer exhibit better diagnostic performance., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background & Aims: Childhood obesity is a global public health threat, with an alarming rise in incidence. Obesity at young age has short-term and long-term morbidity. It is, therefore, important to accurately assess body composition throughout infancy and childhood to identify excess adiposity. However, reference values for age 2-5 years, needed to interpret measurements and identify young children at risk, are lacking. Our primary objective was to fill the current gap in reference values by constructing sex-specific body composition reference values and charts for fat mass (FM), fat mass percentage (FM%), fat mass index (FMI), lean body mass (LBM), lean body mass index (LBMI) and total body less head bone mineral density (BMD TBLH ) for children aged 2-5 years using Dual-Energy X-ray Absorptiometry (DXA)., Methods: We performed 599 accurate DXA-measurements in 340 term-born children aged 2-5 years, using Lunar Prodigy with Encore software (V14.1). Using GAMLSS, sex-specific reference values and charts were created for FM, FM%, FMI, LBM, LBMI and BMD TBLH ., Results: Sex-specific body composition reference values and charts for age 2-5 years were constructed. In boys and girls, FM and LBM increased from age 2-5 years (all p ≤ 0.001), but body size-corrected FM% and FMI decreased (all p ≤ 0.023). LBMI remained similar between 2 and 5 years of age. Girls had higher FM, FM% and FMI and lower LBM and LBMI compared to boys. BMC and BMD TBLH increased with age between 2 and 5 years of age (all p < 0.001) and were similar for boys and girls., Conclusions: We present sex-specific reference values and charts for body composition and total body bone mineral density measured by DXA, based on a large cohort of healthy children aged 2-5 years. These longitudinal references can be used for clinical practice and research purposes to monitor body composition and bone mineral density development and identify children at risk for excess adiposity., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background and Purpose: The net benefit of carotid endarterectomy (CEA) is determined partly by the risk of procedural stroke or death. Current guidelines recommend CEA if 30-day risks are <6% for symptomatic stenosis and <3% for asymptomatic stenosis. We aimed to identify prediction models for procedural stroke or death after CEA and to externally validate these models in a large registry of patients from the United States., Methods: We conducted a systematic search in MEDLINE and EMBASE for prediction models of procedural outcomes after CEA. We validated these models with data from patients who underwent CEA in the American College of Surgeons National Surgical Quality Improvement Program (2011-2017). We assessed discrimination using C statistics and calibration graphically. We determined the number of patients with predicted risks that exceeded recommended thresholds of procedural risks to perform CEA., Results: After screening 788 reports, 15 studies describing 17 prediction models were included. Nine were developed in populations including both asymptomatic and symptomatic patients, 2 in symptomatic and 5 in asymptomatic populations. In the external validation cohort of 26 293 patients who underwent CEA, 702 (2.7%) developed a stroke or died within 30-days. C statistics varied between 0.52 and 0.64 using all patients, between 0.51 and 0.59 using symptomatic patients, and between 0.49 to 0.58 using asymptomatic patients. The Ontario Carotid Endarterectomy Registry model that included symptomatic status, diabetes, heart failure, and contralateral occlusion as predictors, had C statistic of 0.64 and the best concordance between predicted and observed risks. This model identified 4.5% of symptomatic and 2.1% of asymptomatic patients with procedural risks that exceeded recommended thresholds., Conclusions: Of the 17 externally validated prediction models, the Ontario Carotid Endarterectomy Registry risk model had most reliable predictions of procedural stroke or death after CEA and can inform patients about procedural hazards and help focus CEA toward patients who would benefit most from it.

Objective: To evaluate the impact of a first-trimester combined screening program for pre-eclampsia, based on the Fetal Medicine Foundation (FMF) algorithm, on the rate of small-for-gestational age (SGA) at birth and adverse pregnancy outcome., Methods: This was a retrospective cohort study of data obtained from a London tertiary hospital between January 2017 and March 2019. The data were derived from a secondary analysis of the cohort evaluated in a clinical-effectiveness study on the implementation of a first-trimester screening program for pre-eclampsia. The cohort included 7720 women screened according to the UK National Institute for Health and Care Excellence (NICE) risk-based approach and 4841 women screened by the FMF multimodal approach, which combines maternal risk factors, blood pressure, pregnancy-associated plasma protein-A and uterine artery Doppler indices. The care package for the FMF-screened group included 150-mg aspirin prophylaxis, ultrasound scans at 28 and 36 weeks' gestation and scheduled delivery at 40 weeks. Outcome measures included the rates of SGA neonates at birth, admission to the neonatal unit, intrauterine demise, neonatal death and hypoxic-ischemic encephalopathy assessed by interrupted time series analysis (ITSA)., Results: There was no significant difference in the rates of intrauterine demise, neonatal death and hypoxic-ischemic encephalopathy between the FMF-screened and NICE-screened cohorts. ITSA showed a significant reduction in the rate of term SGA birth < 10 th percentile at 21 months following implementation of the FMF screening program, with a relative effect reduction of 45.1% (P = 0.004). However, there was no significant relative effect reduction in term SGA birth < 5 th or < 3 rd percentile., Conclusions: First-trimester combined screening for pre-eclampsia based on the FMF algorithm accompanied by a care package including serial ultrasound scans for growth evaluation and elective birth from 40 weeks' gestation resulted in a significant 45% relative effect reduction in term SGA birth < 10 th percentile but did not affect term SGA birth < 5 th or < 3 rd percentile. Further screening strategies to detect and improve the outcome of cases with SGA birth < 5 th percentile need to be considered. © 2021 International Society of Ultrasound in Obstetrics and Gynecology., (© 2021 International Society of Ultrasound in Obstetrics and Gynecology.)

Background/aim: The use of multi-gene panels for germline testing in breast cancer enables the estimation of cancer risk and guides risk-reducing management options. The aim of this study was to present data that demonstrate the different levels of actionability for multi-gene panels used in genetic testing of breast cancer patients and their family members., Materials and Methods: We performed an analysis in our clinical database to identify breast cancer patients undergoing genetic testing. We reviewed positive results in respect of risk estimation and management, cascade family testing, secondary findings and information for treatment decision-making., Results: A total of 415 positive test reports were identified with 57.1%, 18.1%, 10.8% and 13.5% of individuals having pathogenic/likely pathogenic variants in high, moderate, low and with insufficient evidence for breast cancer risk genes, respectively. Six point seven percent of individuals were double heterozygotes., Conclusion: Germline findings in 92% of individuals are linked to evidence-based treatment information and risk estimates for predisposition to breast and/or other cancer types. The use of germline findings for treatment decision making expands the indication of genetic testing to include individuals that could benefit from targeted treatments., (Copyright © 2022, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Background: There are few large studies examining and predicting the diversified cardiovascular/noncardiovascular comorbidity relationships with stroke. We investigated stroke risks in a very large prospective cohort of patients with multimorbidity, using two common clinical rules, a clinical multimorbid index and a machine-learning (ML) approach, accounting for the complex relationships among variables, including the dynamic nature of changing risk factors., Methods: We studied a prospective U.S. cohort of 3,435,224 patients from medical databases in a 2-year investigation. Stroke outcomes were examined in relationship to diverse multimorbid conditions, demographic variables, and other inputs, with ML accounting for the dynamic nature of changing multimorbidity risk factors, two clinical risk scores, and a clinical multimorbid index., Results: Common clinical risk scores had moderate and comparable c indices with stroke outcomes in the training and external validation samples (validation-CHADS 2 : c index 0.812, 95% confidence interval [CI] 0.808-0.815; CHA 2 DS 2 -VASc: c index 0.809, 95% CI 0.805-0.812). A clinical multimorbid index had higher discriminant validity values for both the training/external validation samples (validation: c index 0.850, 95% CI 0.847-0.853). The ML-based algorithms yielded the highest discriminant validity values for the gradient boosting/neural network logistic regression formulations with no significant differences among the ML approaches (validation for logistic regression: c index 0.866, 95% CI 0.856-0.876). Calibration of the ML-based formulation was satisfactory across a wide range of predicted probabilities. Decision curve analysis demonstrated that clinical utility for the ML-based formulation was better than that for the two current clinical rules and the newly developed multimorbid tool. Also, ML models and clinical stroke risk scores were more clinically useful than the "treat all" strategy., Conclusion: Complex relationships of various comorbidities uncovered using a ML approach for diverse (and dynamic) multimorbidity changes have major consequences for stroke risk prediction. This approach may facilitate automated approaches for dynamic risk stratification in the significant presence of multimorbidity, helping in the decision-making process for risk assessment and integrated/holistic management., Competing Interests: None declared., (Thieme. All rights reserved.)

Background: Aspiration pneumonia after endoscopic submucosal dissection (ESD) is rare, but can be fatal. We aimed to investigate risk factors and develop a simple risk scoring system for aspiration pneumonia., Methods: We retrospectively reviewed medical records of 7833 patients who underwent gastric ESD for gastric neoplasm under anesthesiologist-directed sedation. Candidate risk factors were screened and assessed for significance using a least absolute shrinkage and selection operator (LASSO)-based method. Top significant factors were incorporated into a multivariable logistic regression model, whose prediction performance was compared with those of other machine learning models. The final risk scoring system was created based on the estimated odds ratios of the logistic regression model., Results: The incidence of aspiration pneumonia was 1.5%. The logistic regression model showed comparable performance to the best predictive model, extreme gradient boost (area under receiver operating characteristic curve [AUROC], 0.731 vs 0.740). The estimated odds ratios were subsequently used for the development of the clinical scoring system. The final scoring system exhibited an AUROC of 0.730 in the test dataset with risk factors: age (≥70 years, 4 points), male sex (8 points), body mass index (≥27 kg/m2, 4 points), procedure time (≥80 minutes, 5 points), lesion in the lower third of the stomach (5 points), tumor size (≥10 mm, 3 points), recovery time (≥35 minutes, 4 points), and desaturation during ESD (9 points). For patients with total scores ranging between 0 and 33 points, aspiration pneumonia probabilities spanned between 0.1% and 17.9%. External validation using an additional cohort of 827 patients yielded AUROCs of 0.698 for the logistic regression model and 0.680 for the scoring system., Conclusions: Our simple risk scoring system has 8 predictors incorporating patient-, procedure-, and sedation-related factors. This system may help clinicians to stratify patients at risk of aspiration pneumonia after ESD., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2021 International Anesthesia Research Society.)

Some fragrance ingredients may have the potential to induce skin sensitization in humans but can still be safely formulated into consumer products. Quantitative Risk Assessment (QRA) for dermal sensitization is required to determine safe levels at which potential skin sensitizers can be incorporated into consumer products. The no expected sensitization induction level or NESIL is the point of departure for the dermal QRA. Sensitization assessment factors are applied to the NESIL to determine acceptable exposure levels at which no skin sensitization induction would be expected in the general population. This paper details the key steps involved in deriving a weight of evidence (WoE) NESIL for a given fragrance ingredient using all existing data, including in vivo, in vitro, and in silico. Read-across can be used to derive a NESIL for a group of structurally similar materials when data are insufficient. When sufficient target and read-across data are lacking, exposure waiving threshold (the DST) may be used. We outline the process as it currently stands at the Research Institute for Fragrance Materials Inc. (RIFM) and provide examples, but it is dynamic and is bound to change with evolving science as new approach methodologies (NAMs) are actively incorporated., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Introduction: Recurrent venous thromboembolism (VTE) despite curative anticoagulation is frequent in patients with cancer. Identifying patients with a high risk of recurrence could have therapeutic implications. A prospective study was designed to validate the Ottawa risk score of recurrent VTE in cancer patients., Methods: In a prospective multicenter observational cohort, adult cancer patients with a recent diagnosis of symptomatic or incidental lower limb deep vein thrombosis or pulmonary embolism (PE) were treated with tinzaparin for 6 months. The primary endpoint was the recurrence of symptomatic or asymptomatic VTE within the first 6 months of treatment. All clinical events were centrally reviewed and adjudicated. Time-to-event outcomes were estimated by the Kalbfleisch and Prentice method to take into account the competing risk of death. A C-statistic value of > 0.70 was needed to validate the Ottawa score., Results: A total of 409 patients were included and analyzed on an intention-to-treat basis. Median age was 68 years, 60.4% of patients had PE, and VTE was symptomatic in 271 patients (66.3%). The main primary sites were lung (31.3%), lower digestive tract (14.4%), and breast (13.9%) cancers. The Ottawa score was high (≥ 1) in 58% of patients. The 6-month cumulative incidence of recurrent VTE was 7.3% (95% confidence interval [CI]: 4.9-11.1) overall, and 5.0% (95% CI: 2.3-10.8) versus 9.1% (95%CI: 6.1-13.6) in the Ottawa low versus high risk groups, respectively. The C-statistic value was 0.60 (95% CI: 0.55-0.65)., Conclusion: In this prospective cohort of patients with cancer receiving tinzaparin for VTE, the Ottawa score failed to accurately predict recurrent VTE., Competing Interests: All participants have received fees from LEO Pharma for this research, either personally and/or to support the local organization of the research. Anne Lamblin is an employee of LEO Pharma., (Thieme. All rights reserved.)

Abstract: The aim of this study was to construct a nomogram for predicting prostate cancer (PCa) in patients with PSA ≤ 20 ng/mL at initial biopsy.The patients with PSA ≤ 20 ng/mL who underwent prostate biopsy were retrospectively included in this study. The nomogram was developed based on predictors for PCa, which were assessed by multivariable logistic regression analysis. The receiver operating characteristic curve, calibration plots and decision curve analysis (DCA) were used to evaluate the performance of the nomogram.This retrospective study included 691 patients, who were divided into training set (505 patients) and validation set (186 patients). The nomogram was developed based on the multivariable logistic regression model, including age, total PSA, free PSA, and prostate volume. It had a high area under the curve of 0.857, and was well verified in validation set. Calibration plots and DCA further validated its discrimination and potential clinical benefits. Applying the cut-off value of 15%, our nomogram would avoid 42.5% of unnecessary biopsies while miss only 4.4% of PCa patients.The nomogram provided high predictive accuracy for PCa in patients with PSA ≤ 20 ng/mL at initial biopsy, which could be used to avoid the unnecessary biopsies in clinical practice., Competing Interests: The authors of this article have no conflicts of interest., (Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Idiopathic pulmonary fibrosis (IPF) is characterized by a poor prognosis, with a progressive decline in lung function and considerable variability in the disease's natural history. Besides lung transplantation (LTx), the only available treatments are anti-fibrosing drugs, which have shown to slow down the disease course. Therefore, predicting the prognosis is of pivotal importance to avoid treatment delays, which may be fatal for patients with a high risk of progression. Previous studies showed that a multi-dimensional approach is practical and effective in the development of a reliable prognostic score for IPF. In the RIsk Stratification scorE (RISE), physiological parameters, an objective measure of patient-reported dyspnea and exercise capacity are combined to capture different domains of the complex pathophysiology of IPF., Methods: This is an observational, multi-centre, prospective cohort study, designed to reflect common clinical practice in IPF. A development cohort and a validation cohort will be included. Patients newly diagnosed with IPF based on the ATS/ERS criteria and multi-disciplinary discussion will be included in the study. A panel of chest radiologists and lung pathologists will further assess eligibility. At the first visit (time of diagnosis), and every 4-months, MRC dyspnea score, pulmonary function tests (FEV 1 , FVC and DLCO), and 6-min walking distance will be recorded. Patients will be prospectively followed for 3 years. Comorbidities will be considered. The radiographic extent of fibrosis on HRCT will be recalculated at a 2-year interval. RISE, Gender-Age-Physiology, CPI and Mortality Risk Scoring System will be calculated at 4-month intervals. Longitudinal changes of each variable considered will be assessed. The primary endpoint is 3-year LTx-free survival from the time of diagnosis. Secondary endpoints include several, clinically-relevant information to ensure reproducibility of results across a wide range of disease severity and in concomitance of associated pulmonary hypertension or emphysema., Discussion: The objective of this study is to validate RISE as a simple, straightforward, inexpensive and reproducible tool to guide clinical decision making in IPF, and potentially as an endpoint for future clinical trials., Trial Registration: U.S National Library of Medicine Clinicaltrials.gov, trial n. NCT02632123 "Validation of the risk stratification score in idiopathic pulmonary fibrosis". Date of registration: December 16th, 2015., (© 2021. The Author(s).)

Objectives: To assess risk factors and non-thyroid specific postoperative complications for thyroid lobectomy compared to total thyroidectomy., Methods: A retrospective, cross-sectional study of adults undergoing a lobectomy or total thyroidectomy using the National Surgical Quality Improvement Program database between 2005 and 2017. Patients not treated by otolaryngologists or general surgeons and with unknown demographic variables were excluded., Results: A total of 106 915 patients were analyzed, 64 763 total thyroidectomies and 42 152 lobectomies. Multivariable analysis demonstrated that total thyroidectomy patients were half as likely to return to the operating room (OR = 0.491 (95%CI 0.445-0.542), P  < .001). Within this cohort, patients at greater risk for reoperation had a history of hypertension (OR = 1.225 (95%CI 1.090-1.376), P  < .001), a malignant pathology (OR = 1.921 (95%CI 1.734-2.128), P  < .001), and smoked (OR = 1.237 (95%CI 1.087-1.407), P  = .001). Conversely, diabetes and body mass index did not impact the rate of reoperation when assessing total thyroidectomy and lobectomy. The most frequent non-thyroid specific complications in total thyroidectomy were unplanned intubation (0.5%), urinary tract infection (0.3%), and superficial surgical site infection (0.3%). In thyroid lobectomy, the most common complications were superficial surgical site infection (0.3%) and urinary tract infection (0.2%)., Conclusions: Our multi-institutional study indicates specific risk factors for returning to the operating room that may warrant closer follow up after surgery for total thyroidectomy or thyroid lobectomy. We also identified the most common post-operative complications. During pre-operative planning, these findings should be considered by thyroid surgeons to help mitigate risk to patients.

Background & Aims: Management of long-term immunosuppression following liver transplantation (LT) remains empirical. Surveillance liver biopsies in combination with transcriptional profiling could overcome this challenge by identifying recipients with active alloimmune-mediated liver damage despite normal liver tests, but this approach lacks applicability. Our aim was to investigate the utility of non-invasive tools for the stratification of stable long-term survivors of LT, according to their immunological risk and need for immunosuppression., Methods: We conducted a cross-sectional multicentre study of 190 adult LT recipients assessed to determine their eligibility to participate in an immunosuppression withdrawal trial. Patients had stable liver allograft function and had been transplanted for non-autoimmune non-replicative viral liver disease >3 years before inclusion. We performed histological, immunogenetic and serological studies and measured the intrahepatic transcript levels of an 11-gene classifier highly specific for T cell-mediated rejection (TCMR)., Results: In this cohort, 35.8% of patients harboured clinically silent fibro-inflammatory liver lesions (13.7% had mild damage and 22.1% had moderate-to-severe damage). The severity of liver allograft damage was positively associated with TCMR-related transcripts, class II donor-specific antibodies (DSAs), ALT, AST, and liver stiffness measurement (LSM), and negatively correlated with serum creatinine and tacrolimus trough levels. Liver biopsies were stratified according to their TCMR transcript levels using a cut-off derived from biopsies with clinically significant TCMR. Two multivariable prediction models, integrating ALT+LSM or ALT+class II DSAs, had a high discriminative capacity for classifying patients with or without alloimmune damage. The latter model performed well in an independent cohort of 156 liver biopsies obtained from paediatric liver recipients with similar inclusion/exclusion criteria., Conclusion: ALT, class II DSAs and LSM are valuable tools to non-invasively identify stable LT recipients without significant underlying alloimmunity who could benefit from minimisation of immunosuppression., Lay Summary: A large proportion of liver transplant patients with normal liver tests have inflammatory liver lesions, which in 17% of cases are molecularly indistinguishable from those seen at the time of rejection. ALT, class II donor-specific antibodies and liver stiffness are useful in identifying patients with this form of subclinical rejection. We propose these markers as a useful tool to help clinicians determine if the immunosuppression administered is adequate., Competing Interests: Conflict of interest The authors have no conflicts of interest to declare. Please refer to the accompanying ICMJE disclosure forms for further details., (Copyright © 2021. Published by Elsevier B.V.)

Background: The performance of existing predictive models of readmissions, such as the LACE, LACE+, and Epic models, is not established in urban safety-net populations. We assessed previously validated predictive models of readmission performance in a socially complex, urban safety-net population, and if augmentation with additional variables such as the Area Deprivation Index, mental health diagnoses, and housing access improves prediction. Through the addition of new variables, we introduce the LACE-social determinants of health (SDH) model., Methods: This retrospective cohort study included adult admissions from July 1, 2016, to June 30, 2018, at a single urban safety-net health system, assessing the performance of the LACE, LACE+, and Epic models in predicting 30-day, unplanned rehospitalization. The LACE-SDH development is presented through logistic regression. Predictive model performance was compared using C-statistics., Results: A total of 16,540 patients met the inclusion criteria. Within the validation cohort (n=8314), the Epic model performed the best (C-statistic=0.71, P<0.05), compared with LACE-SDH (0.67), LACE (0.65), and LACE+ (0.61). The variables most associated with readmissions were (odds ratio, 95% confidence interval) against medical advice discharge (3.19, 2.28-4.45), mental health diagnosis (2.06, 1.72-2.47), and health care utilization (1.94, 1.47-2.55)., Conclusions: The Epic model performed the best in our sample but requires the use of the Epic Electronic Health Record. The LACE-SDH performed significantly better than the LACE and LACE+ models when applied to a safety-net population, demonstrating the importance of accounting for socioeconomic stressors, mental health, and health care utilization in assessing readmission risk in urban safety-net patients., Competing Interests: The authors declare no conflict of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: The goal of this study was to develop an approach that can be used where baseline risk estimates that are directly applicable to prioritized patient-important outcomes are not available from published studies., Study Design: The McMaster University GRADE Centre and the ASH guideline panel for the prevention of VTE in surgical patients developed a modeling approach based on explicit assumptions about the distribution of symptoms, anatomical location, and severity of VTE events., Results: We applied the approach to derive modeled estimates of baseline risk. These estimates were used to calculated absolute measures of anticipated effects that informed the discussion of the evidence and the formulation of 30 guideline recommendations., Conclusion: Our approach can assist guideline developers facing a lack of information about baseline risk estimates that directly apply to outcomes of interest. The use of modeled estimates increases transparency in the process and makes the baseline risk used by guideline experts explicit during their decision-making., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Introduction: The ACS NSQIP Surgical Risk Calculator (SRC) assesses risk to support goal-concordant care. While it accurately predicts US outcomes, its performance internationally is unknown. This study evaluates SRC accuracy in predicting mortality following low anterior resection (LAR) and pancreaticoduodenectomy (PD) in NSQIP patients and accuracy retention when applied to native Japanese patients (National Clinical Database, NCD)., Methods: NSQIP (41,260 LAR; 15,114 PD) and NCD cases (61,220 LAR; 27,901 PD) from 2015 to 2017 were processed through the SRC mortality model. Country-specific calibration and discrimination were assessed with and without an intercept correction applied to the Japanese data., Results: The SRC exhibited acceptable calibration for LAR and PD when applied to NSQIP data but miscalibration for NCD data. A simple correction to the model intercept, motivated by lower mortality rates in the Japanese data, successfully remediated the miscalibration., Conclusions: The SRC may inaccurately predict surgical risk when applied to the native Japanese population. An intercept correction method is suggested when miscalibration is encountered; it is simple to implement and may permit effective international use of the SRC., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Objectives: Studies on the association of estimated glomerular filtration rate (eGFR) levels with hospital discharge disposition after stroke are limited with inconsistent results. This study investigated the odds of home discharge with eGFR levels at admission for patients with stroke using the Taiwan Stroke Registry (TSR) data., Methods: From the TSR database, a total of 51,338 stroke patients from 2006 to 2015 were categorized into five groups based on eGFR levels at admission. The proportion of home discharge by the eGFR levels was calculated and logistic regression analysis was used to estimate the related odds ratio (OR) and 95% confidence interval., Results: Near 85% of stroke patients were discharged to home. The proportion of home discharges decreased as the eGFR level declined. Compared to patients with eGFR ≥90 mL/min/1.73 m 2 , the adjusted ORs of home discharge were 0.91, 0.85, 0.63, 0.56 for patients with eGFR 60-89, eGFR 30-59, eGFR 15-29, and eGFR < 15 mL/min/1.73 m 2 or on dialysis, respectively, in a graded relationship. The trends were consistent in the ischemic stroke and hemorrhagic stroke patients. The areas under the receiver operating characteristic curve for all stroke patients, ischemic stroke patients, and hemorrhagic stroke patients were 0.801, 0799, 0.815, respectively., Conclusion: The odds of home discharge for stroke patients decreased with a significant independent graded association with declining eGFR levels. Renal function could predict home discharge after stroke.

Purpose: The clinician treating patients with neurogenic lower urinary tract dysfunction (NLUTD) needs to balance a variety of factors when making treatment decisions. In addition to the patient's urologic symptoms and urodynamic findings, other issues that may influence management options of the lower urinary tract include cognition, hand function, type of neurologic disease, mobility, bowel function/management, and social and caregiver support. This Guideline allows the clinician to understand the options available to treat patients, understand the findings that can be seen in NLUTD, and appreciate which options are best for each individual patient. This allows for decisions to be made with the patient, in a shared decision-making manner, such that the patient's quality of life can be optimized with respect to their bladder management., Materials and Methods: A comprehensive search for studies assessing patients undergoing evaluation, surveillance, management, or follow-up for NLUTD was conducted from January 2001 through October 2017 and was rerun in February 2021 to capture newer literature. The primary search returned 20,496 unique citations. Following a title and abstract screen, full texts were obtained for 3,036 studies. During full-text review, studies were primarily excluded for not meeting the PICO criteria. One hundred eight-four primary literature studies met the inclusion criteria and were included in the evidence base., Results: This guideline was developed to inform clinicians on the proper evaluation, diagnosis, and risk stratification of adult patients with NLUTD and the non-surgical and surgical treatment options available. Additional statements on urinary tract infection and autonomic dysreflexia were developed to guide the clinician., Conclusions: NLUTD patients may undergo non-surgical and surgical treatment options depending on their level of risk, symptoms, and urodynamic findings. Appropriate follow-up, primarily based on their risk stratification, must be maintained after treatment.

Aim: This study aimed to develop and validate a nomogram to recognize in-hospital cardiac arrest (CA) in patients with acute coronary syndrome (ACS)., Methods: This multicenter case-control study reviewed 164 ACS patients who had in-hospital CA and randomly selected 521 ACS patients with no CA experience. We randomly assigned 80% of the participants to a development cohort, 20% of those to an independent validation cohort. The least absolute shrinkage and selection operator (LASSO) regression model was used for data dimension reduction, and multivariable logistic regression analysis was used to develop the CA prediction nomogram. Nomogram performance was assessed with respect to discrimination, calibration, and clinical usefulness., Results: Seven parameters, including chest pain, Killip class, potassium, BNP, arrhythmia, platelet count, and NEWS, were used to create individualized CA prediction nomograms. The CA prediction nomogram showed good discrimination (C-index of 0.896, 95%CI, 0.865-0.927) and calibration. Application of the CA prediction nomogram in assessments of the validation cohort improved discrimination (C-index of 0.914, 95%CI, 0.873-0.967) and calibration. The results of decision curve analysis demonstrated that the CA prediction nomogram was clinically useful., Conclusion: Our study generated a friendly risk score to recognize in-hospital CA with good discrimination and calibration. Further studies need to establish a pathway to guide the application of the risk score in clinical practice., Competing Interests: Declaration of competing interest None., (Copyright © 2021. Published by Elsevier Inc.)