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Background: Prognostication is an important component of medical decision-making. A patients' general prognosis can be difficult to measure. The Simple Prognostic Score (SPS) was designed to include patients' age, mobility, aggregated vital signs, and the treating physician's decision to admit to aid prognostication. Study Aim . Our study aim is to validate the SPS, compare it with the Emergency Severity Index (ESI) regarding its prognostic performance, and test the interrater reliability of the subjective variable of the decision to admit., Methods: Over a period of 9 weeks all patients presenting to the ED were included, routinely interviewed, final disposition registered, and followed up for one year. The C-statistics of discrimination was used to compare SPS and ESI predictions of 7-day, 30-day, and 1-year mortality. Youden J Statistics and Odds ratio, using logistical regression, were calculated for the Simple Prognostic Score. In a subset, a chart review was performed by senior physicians for a secondary assessment of the decision to admit. Interrater reliability was calculated using percentages and Cohens Kappa., Results: Out of 5648 patients, 3272 (57.9%) had a low SPS (i.e., ≤ 1); none of these patients died within 7 days, 2 (0.1%) died within 30 days after presentation and 19 (0.6%) died within a year. The area under the curve for 1-year mortality of the Simple Prognostic Score was 0.848. Secondary analysis of the interrater agreement for the decision to admit was 92%., Conclusion: In a prospective study of unselected ED patients, the Simple Prognostic Score was validated as a reliable predictor of short- and long-term mortality., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Jeannette-Marie Busch et al.)

Study Objective: We validate the Clinical Frailty Scale by examining its independent predictive validity for 30-day mortality, ICU admission, and hospitalization and by determining its reliability. We also determine frailty prevalence in our emergency department (ED) as measured with the Clinical Frailty Scale., Methods: This was a prospective observational study including consecutive ED patients aged 65 years or older, from a single tertiary care center during a 9-week period. To examine predictive validity, association with mortality was investigated through a Cox proportional hazards regression; hospitalization and ICU transfer were investigated through multivariable logistic regression. We assessed reliability by calculating Cohen's weighted κ for agreement of experts who independently assigned Clinical Frailty Scale levels, compared with trained study assistants. Frailty was defined as a Clinical Frailty Scale score of 5 and higher., Results: A total of 2,393 patients were analyzed in this study, of whom 128 died. Higher frailty levels were associated with higher hazards for death independent of age, sex, and condition (medical versus surgical). The area under the curve for 30-day mortality prediction was 0.81 (95% confidence interval [CI] 0.77 to 0.85), for hospitalization 0.72 (95% CI 0.70 to 0.74), and for ICU admission 0.69 (95% CI 0.66 to 0.73). Interrater reliability between the reference standard and the study team was good (weighted Cohen's κ was 0.74; 95% CI 0.64 to 0.85). Frailty prevalence was 36.8% (n=880)., Conclusion: The Clinical Frailty Scale appears to be a valid and reliable instrument to identify frailty in the ED. It might provide ED clinicians with useful information for decisionmaking in regard to triage, disposition, and treatment., (Copyright © 2020 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.)

Study Objective: To derive and validate a prognostic score to predict 1-year mortality using vital signs, mobility and other variables that are readily available at the bedside at no additional cost., Methods: Post hoc analysis of two independent prospective observational studies in two emergency departments, one in Denmark and the other in Switzerland., Participants: Alert and calm emergency department patients., Measurements: The prediction of mortality from presentation to 365 days by vital signs, mobility and other variables that are readily available at the bedside at no additional cost., Results: One thousand six hundred and eighteen alert and calm patients were in the Danish cohort and 1331 in the Swiss cohort. Logistic regression identified age >68 years, abnormal vital signs, impaired mobility and the decision to admit as significant predictors of 365-day mortality. A simple prognostic score awarded one point to each of these predictors. Less than two of these predictors were present in 45.6% of patients, and only 0.4% of these patients died within a year. If two or more of these predictors were present, 365-day mortality increased exponentially., Conclusion: Age >68 years, the decision for hospital admission, any vital sign abnormality at presentation and impaired mobility at presentation are equally powerful predictors of 1-year mortality in alert and calm emergency department patients. If validated by others these predictors could be used to discharge patients with confidence since nearly half of these patients had less than two predictors and none of them died within 30 days. However, when two or more predictors were present 365-day mortality increased exponentially., (© 2020 John Wiley & Sons Ltd.)

Objective: To determine the ability of a normal D-dimer level (<0.5 mg/l) to identify emergency department (ED) patients at low risk of 30-day all-cause mortality., Design: In this prospective observational study, D-dimer levels of adult medical patients were assessed at arrival to the ED. Data on 30-day survival status were extracted from the Danish Civil Registration System with complete follow-up., Setting: The Hospital of South West Jutland., Patients: All patients aged 18 years or older who required any blood sample on a clinical indication on arrival to the ED. Participants were required to give written informed consent before enrollment., Main Results: The study population of 1 518 patients with median age 66 years of which 49.4% were female. Of the 791 (52.1%) patients with normal D-dimer levels, 3 (0.4%) died within 30 days; one death resulted from an unrelated traumatic accident. Of the 727 (47.9%) patients with abnormal D-dimer levels (≥0.50 mg/l), 32 (4.4%) died within 30 days. Patients with normal D-dimer levels had a significantly lower 30-day mortality compared to patients with abnormal D-dimer levels (odds ratio 0.08, 95% CI 0.02-0.28): of the 35 patients who died within 30 days, 19 (54.3%) had normal or near normal vital signs when first assessed., Conclusion: Normal D-dimer levels identified patients at low risk of 30-day mortality. Since most patients who died within 30 days presented with normal or near normal vital signs, D-dimer levels appear to provide additional prognostic information., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Association of Physicians. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Nonspecific complaints (NSC) at the Emergency Department (ED) are not well researched yet., Objective: To investigate the number of patients who could be classified as having NSC early after arrival in the ED using an algorithm., Method: Retrospective cohort study was conducted among all hemodynamically stable non-trauma adult patients with MTS category orange/yellow visiting the ED. Patients who had no specific complaints/signs, predefined on a list, were categorized as NSC., Results: In total, 2419 patients, of whom 102 (4.2%) presented with NSC. Hospitalization was more prevalent (85.3% vs. 69.0%, p<0.001) and in-hospital mortality was higher in the NSC-group (11.8% vs. 3.5%, adjusted OR 2.0, 95% CI 1.0-3.9, p=0.04)., Conclusion: Using an algorithm it is possible to identify NSC patients who have (worse) outcomes than those classified as SC.

Aim: To investigate the combined use of NEWS and D-dimer levels to predict the 30-day and 365-day mortality rates of a cohort of Danish patients with complete follow-up., Methods: Post-hoc retrospective observational study of acutely admitted medical patients aged 18 years or older who had D-dimer measured within 6h after arrival to two medical admission units in Denmark., Results: The final study population consisted of 1201 patients with a median age of 65.0 years (range 18.0-107.0 years), and 44.7% were of male sex. Four patients (0.3%) died within 24h of admission, 69 (5.7%) within 30 days and 198 (16.5%) within 365 days. On admission, 576 (48%) patients had a NEWS≥3 - of these 441 had a D-dimer≥0.50mgL(-1): 55 (12.5%) of these patients died within 30 days, compared with 5 (3.7%) of the 135 patients with a D-dimer<0.50mgL(-1) (odds ratio 3.7, 95%CI 1.4-10.8). Nine of the 625 patients with a NEWS on admission <3 died within 30 days and all of these patients had a D-dimer≥0.50mgL(-1). None of the 218 patients with a D-dimer<0.50mgL(-1) died within 30 days of admission., Conclusion: The combination of NEWS score<3 and D-dimer levels below 0.50mgL(-1) appears to identify patients of low risk of mortality within 30 days and, therefore, may prove to be a powerful risk assessment tool for acutely ill medical patients., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

Background: Hospital readmissions are increasingly used as a quality indicator with a belief that they are a marker of poor care and have led to financial penalties in UK and USA. Risk scoring systems, such as LACE and HOSPITAL, have been proposed as tools for identifying patients at high risk of readmission but have not been validated in international populations., Aim: To perform an external independent validation of the HOSPITAL and LACE scores., Design: An unplanned secondary cohort study., Methods: Patients admitted to the medical admission unit at the Hospital of South West Jutland (10/2008-2/2009; 2/2010-5/2010) and the Odense University Hospital (6/2009-8/2011) were analysed. Validation of the scores using 30 day readmissions as the endpoint was performed., Results: A total of 19 277 patients fulfilled the inclusion criteria. Median age was 67 (range 18-107) years and 8977 (46.6%) were female. The LACE score had a discriminatory power of 0.648 with poor calibration and the HOSPITAL score had a discriminatory power of 0.661 with poor calibration. The HOSPITAL score was significantly better than the LACE score for identifying patients at risk of 30 day readmission (P < 0.001). The discriminatory power of both scores decreased with increasing age., Conclusion: Readmissions are a complex phenomenon with not only medical conditions contributing but also system, cultural and environmental factors exerting a significant influence. It is possible that the heterogeneity of the population and health care systems may prohibit the creation of a simple prediction tool that can be used internationally., (© The Author 2015. Published by Oxford University Press on behalf of the Association of Physicians. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Objectives: Patients presenting to the emergency department (ED) with nonspecific complaints are difficult to accurately triage, risk stratify, and diagnose. This can delay appropriate treatment. The extent to which key medical outcomes are at all predictable in these patients, and which (if any) predictors are useful, has previously been unclear. To investigate these questions, we tested an array of statistical and machine learning models in a large group of patients and estimated the predictability of mortality (which occurred in 6.6% of our sample of patients), acute morbidity (58%), and presence of acute infectious disease (28.2%)., Methods: To investigate whether the best available tools can predict the three key outcomes, we fed data from a sample of 1,278 ED patients with nonspecific complaints into 17 state-of-the-art statistical and machine learning models. The patient sample stems from a diagnostic multicenter study with prospective 30-day follow-up conducted in Switzerland. Predictability of the three key medical outcomes was quantified by computing the area under the receiver operating characteristic curve (AUC) for each model., Results: The models performed at different levels but, on average, the predictability of the target outcomes ranged between 0.71 and 0.82. The better models clearly outperformed physicians' intuitive judgments of how ill patients looked (AUC = 0.67 for mortality, 0.65 for morbidity, and 0.60 for infectious disease)., Conclusions: Modeling techniques can be used to derive formalized models that, on average, predict the outcomes of mortality, acute morbidity, and acute infectious disease in patients with nonspecific complaints with a level of accuracy far beyond chance. The models also predicted these outcomes more accurately than did physicians' intuitive judgments of how ill the patients look; however, the latter was among the small set of best predictors for mortality and acute morbidity. These results lay the groundwork for further refining triage and risk stratification tools for patients with nonspecific complaints. More research, informed by whether the goal of a model is high sensitivity or high specificity, is needed to develop readily applicable clinical decision support tools (e.g., decision trees) that could be supported by electronic health records., (© 2015 by the Society for Academic Emergency Medicine.)

Objectives: To the authors' knowledge, no prospectively validated, biomarker-based risk stratification tools exist for elderly patients presenting to the emergency department (ED) with nonspecific complaints (NSCs), such as generalized weakness, despite the fact that an acute serious disease often underlies nonspecific disease presentation. The primary purpose for this study was to validate the retrospectively derived model for outcome prediction using copeptin and peroxiredoxin 4 (Prx4), in a different group of patients, in a prospective fashion, in a multicenter setting. The secondary goals were to evaluate the potential contribution of the midregional portion of the precursor of adrenomedullin (MR-proADM) for outcome prediction and to investigate whether disposition decisions show promise for potential improvement by using biomarker levels in addition to a clinical assessment., Methods: The Basel Nonspecific Complaints (BANC) study is a delayed-type cross-sectional diagnostic study, carried out in three EDs in Switzerland, with a prospective 30-day follow-up. Patients presenting to the ED with NSCs, as defined previously, were included if their vital signs were within predefined limits. Measurement of biomarkers was performed in serum samples with sandwich immunoluminometric assays. To examine the disposition process, the final disposition was compared with a combination of the first clinical disposition decision and the risk assessment, which included the biomarker MR-proADM in a retrospective simulation. Patients were divided into three groups according to MR-proADM concentration, defining three risk classes with three disposition possibilities (admission to tertiary care, transfer to geriatric hospital, discharge)., Results: Thirty-three 30-day nonsurvivors were observed from among 504 study patients with NSCs. Biomarker levels were significantly greater in nonsurvivors than survivors (p < 0.0001 for all three biomarkers). Univariate Cox models reveal a C-index of 0.732 for MR-proADM, 0.719 for Prx4, and 0.723 for copeptin. The incremental added value for chi-square obtained via multivariate modeling showed that models inclusive of MR-proADM, copeptin, or Prx4 are superior to and independent of models limited to sex and age. The incrementally added chi-square for MR-proADM, beyond the chi-square of a base model consisting of age and sex, was 29.79 (p < 0.00001). In a multimarker approach, only Prx4 provided additional information to MR-proADM alone (C-index = 0.77). Applying an algorithm combining physicians' first clinical assessment plus biomarker information to derive a modified risk assessment, reassignment would lead to a potential decrease of 48 admissions to acute care, seven additional transfers to geriatric care, and 41 additional discharges (negative likelihood ratio [-LR] = 0.13). Analysis of 30-day mortality reveals that our algorithm is not inferior in terms of safety., Conclusions: In this study the authors confirm that these new stress biomarkers permit reliable prognostication of adverse outcomes in a heterogeneous group of patients with NSCs. A simulation showed that this prognostic information could be useful to enhance the appropriateness of disposition decisions of ED patients with NSC. The use of biomarkers for risk stratification in this patient group should be evaluated with prospective intervention studies., (© 2013 by the Society for Academic Emergency Medicine.)