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Background: A prediction model that estimates mortality at admission to the intensive care unit (ICU) is of potential benefit to both patients and society. Logistic regression models like Simplified Acute Physiology Score 3 (SAPS 3) and APACHE are the traditional ICU mortality prediction models. With the emergence of machine learning (machine learning) and artificial intelligence, new possibilities arise to create prediction models that have the potential to sharpen predictive accuracy and reduce the likelihood of misclassification in the prediction of 30‐day mortality. Methods: We used the Swedish Intensive Care Registry (SIR) to identify and include all patients ≥18 years of age admitted to general ICUs in Sweden from 2008 to 2022 with SAPS 3 score registered. Only data collected within 1 h of ICU admission was used. We had 153 candidate predictors including baseline characteristics, previous medical conditions, blood works, physiological parameters, cause of admission, and initial treatment. We stratified the data randomly on the outcome variable 30‐day mortality and created a training set (80% of data) and a test set (20% of data). We evaluated several hundred prediction models using multiple ML frameworks including random forest, gradient boosting, neural networks, and logistic regression models. Model performance was evaluated by comparing the receiver operator characteristic area under the curve (AUC‐ROC). The best performing model was fine‐tuned by optimizing hyperparameters. The model's calibration was evaluated by a calibration belt. Ultimately, we simplified the best performing model with the top 1–20 predictors. Results: We included 296,344 first‐time ICU admissions. We found age, Glasgow Coma Scale, creatinine, systolic blood pressure, and pH being the most important predictors. The AUC‐ROC was 0.884 in test data using all predictors, specificity 95.2%, sensitivity 47.0%, negative predictive value of 87.9% and positive predictive value of 70.7%. The final model showed excellent calibration. The ICU risk evaluation for 30‐day mortality (ICURE) prediction model performed equally well to the SAPS 3 score with only eight variables and improved further with the addition of more variables. Conclusion: The ICURE prediction model predicts 30‐day mortality rate at first‐time ICU admission superiorly compared to the established SAPS 3 score. [ABSTRACT FROM AUTHOR]

Background: Wrist fracture is one of most common fractures frequently requiring surgical anaesthesia. There is limited information related to the anaesthetic practice and quality including 30‐day mortality associated with wrist fracture in Sweden in recent years. Aim: The aim of the present register‐based study was to investigate the anaesthesia techniques used and quality indices including 30‐day mortality associated with wrist fracture surgery in Sweden during the period 2018–2021. Materials and Methods: All fracture repositions, and surgical interventions related to wrist fracture requiring anaesthesia in patients aged >18 years registered in the Swedish Perioperative Register (SPOR) between 2018 and 2021 were included in the analysis. Information on age, ASA class, anaesthesia technique, severe operative events, most reported side‐effects during recovery room stay and all‐cause 30‐day mortality was collected. Results: The data set included 25,147 procedures split into 14,796 females and 10,252 males (missing information n = 99) with a mean age of 52.9 ± 18.7 years and a significant age difference between females and males, 60.3 ± 15.4 and 42.2 ± 17.7 years, respectively. Mean age and ASA class increased during the study period (2018–2021), from 52.8 ± 18.6 to 54.0 ± 18.4 and ASA class 3–5 from 8.1% to 9.4% (p <.001 and p <.041, respectively). General anaesthesia (GA), GA combined with regional anaesthesia (RA), RA with or without sedation and sedation only was used in 41%, 13%, 40% and 6% of procedures, respectively, with minor changes over the study period. Pain at arrival in the recovery room (RR), (3.4%), severe pain during RR stay (2.1%), hypothermia (1.4%), postoperative nausea and vomiting (PONV) (1.2%) and urinary retention (0.5%) were the most reported side‐effects during the RR stay. (RA) was associated with significantly lower occurrence of pain and PONV, and shorter RR stay, compared with GA (p <.001). The all‐cause 30‐day mortality was low (19 of 25,147 (0.08%)) with no differences over the period studied or anaesthetic technique. Conclusion: General anaesthesia or general anaesthesia combined with regional anaesthesia are the most used anaesthetic techniques for wrist fracture procedures in Sweden. Recovery room pain, PONV, hypothermia and urinary retention is reported in overall low frequencies, with no change over the period studied, but in lower frequencies for regional anaesthesia. All‐cause 30‐day mortality was low; 0.08% with no change over time or between anaesthetic techniques. Thus, the present quality review based on SPOR data supports high quality of perioperative anaesthesia care. [ABSTRACT FROM AUTHOR]

Background and purpose: Autoantibodies have been found to contribute to pathology and are used in the diagnosis of some neurological diseases. We examined the prevalence of autoantibodies in patients with various neurological diseases and whether patients who had autoantibodies differed in age, sex, or disability from those who did not. Methods: We examined the prevalence of neural surface and onconeural autoantibodies in cerebrospinal fluid (CSF) and serum from patients with multiple sclerosis (n = 64), Parkinson disease plus atypical parkinsonism (n = 150), amyotrophic lateral sclerosis (n = 43), or autoimmune encephalitis (positive control; n = 7) and a healthy control group (n = 37). A total of 12 onconeural autoantibodies and six neural surface autoantibodies were tested in all participants. Results: Autoantibodies were present in all cohorts. The prevalence of autoantibodies was high (>80%) in the autoimmune encephalitis cohort but low (<20%) in all other cohorts. When comparing patients within cohorts who were positive for autoantibodies to patients who were not, there was no difference in age, sex, and disability. This was apart from the multiple sclerosis and Parkinson disease plus atypical parkinsonism cohorts, where those with positivity for autoantibodies in the CSF were significantly older. Conclusions: The presence of the autoantibodies examined does not appear to have a substantial clinical impact within the diseases examined in this study. The presence of autoantibodies in all cohorts presents a risk for misdiagnosis when the method is used incorrectly on patients with atypical clinical presentation. [ABSTRACT FROM AUTHOR]

Background: Synaptic dysfunction and degeneration are central contributors to the pathogenesis and progression of parkinsonian disorders. Therefore, identification and validation of biomarkers reflecting pathological synaptic alterations are greatly needed and could be used in prognostic assessment and to monitor treatment effects. Objective: To explore candidate biomarkers of synaptic dysfunction in Parkinson's disease (PD) and related disorders. Methods: Mass spectrometry was used to quantify 15 synaptic proteins in two clinical cerebrospinal fluid (CSF) cohorts, including PD (n1 = 51, n2 = 101), corticobasal degeneration (CBD) (n1 = 11, n2 = 3), progressive supranuclear palsy (PSP) (n1 = 22, n2 = 21), multiple system atrophy (MSA) (n1 = 31, n2 = 26), and healthy control (HC) (n1 = 48, n2 = 30) participants, as well as Alzheimer's disease (AD) (n2 = 23) patients in the second cohort. Results: Across both cohorts, lower levels of the neuronal pentraxins (NPTX; 1, 2, and receptor) were found in PD, MSA, and PSP, compared with HC. In MSA and PSP, lower neurogranin, AP2B1, and complexin‐2 levels compared with HC were observed. In AD, levels of 14‐3‐3 zeta/delta, beta‐ and gamma‐synuclein were higher compared with the parkinsonian disorders. Lower pentraxin levels in PD correlated with Mini‐Mental State Exam scores and specific cognitive deficits (NPTX2; rho = 0.25–0.32, P < 0.05) and reduced dopaminergic pre‐synaptic integrity as measured by DaTSCAN (NPTX2; rho = 0.29, P = 0.023). Additionally, lower levels were associated with the progression of postural imbalance and gait difficulty symptoms (All NPTX; β‐estimate = −0.025 to −0.038, P < 0.05) and cognitive decline (NPTX2; β‐estimate = 0.32, P = 0.021). Conclusions: These novel findings show different alterations of synaptic proteins in parkinsonian disorders compared with AD and HC. The neuronal pentraxins may serve as prognostic CSF biomarkers for both cognitive and motor symptom progression in PD. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Background: Frail older adults experience higher rates of adverse health outcomes. Therefore, assessing pre-hospital frailty early in the course of care is essential to identify the most vulnerable patients and determine their risk of deterioration. The Clinical Frailty Scale (CFS) is a frailty assessment tool that evaluates pre-hospital mobility, energy, physical activity, and function to generate a score that ranges from very fit to terminally ill. Purpose: To synthesize the evidence of the association between the CFS degree and all-cause mortality, all-cause readmission, length of hospital stay, adverse discharge destination, and functional decline in patients > 65 years in acute clinical settings. Design: Systematic review with narrative synthesis. Methods: Electronic databases (PubMed, EMBASE, CINAHL, Scopus) were searched for prospective or retrospective studies reporting a relationship between pre-hospital frailty according to the CFS and the outcomes of interest from database inception to April 2020. Results: Our search yielded 756 articles, of which 29 studies were included in this review (15 were at moderate risk and 14 at low risk of bias). The included studies represented 26 cohorts from 25 countries (N = 44166) published between 2011 and 2020. All included studies showed that pre-hospital frailty according to the CFS is an independent predictor of all adverse health outcomes included in the review. Conclusion: A primary purpose of the CFS is to grade clinically increased risk (i.e. risk stratification). Our results report the accumulated knowledge on the risk-predictive performance of the CFS and highlight the importance of routinely including frailty assessments, such as the CFS, to estimate biological age, improve risk assessments, and assist clinical decision-making in older adults in acute care. Further research into the potential of the CFS and whether implementing the CFS in routine practice will improve care and patients' quality of life is warranted. [ABSTRACT FROM AUTHOR]