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Allergic diseases such as asthma, atopic dermatitis, and food allergies are a burgeoning health challenge in the Asia-Pacific region. Compounding this, the region has become increasingly susceptible to the impacts of climate change. The region has weathered extreme precipitation, intense heat waves, and dust storms over the recent decades. While the effects of environmental and genetic factors on allergic diseases are well understood, prevailing gaps in understanding the complex interactions between climate change and these factors remain. We aim to provide insights into the various pathways by which climate change influences allergic diseases in the Asia-Pacific population. We outline practical steps that allergists can take to reduce the carbon footprint of their practice on both a systemic and patient-specific level. We recommend that allergists optimize disease control to reduce the resources required for each patient's care, which contributes to reducing greenhouse gas emissions. We encourage the responsible prescription of metered dose inhalers by promoting the switch to dry powder inhalers for certain patients, at each clinician's discretion. We also recommend the utilization of virtual consultations to reduce patient travel while ensuring that evidence-based guidelines for rational allergy management are closely adhered to. Finally, eliminating unnecessary testing and medications will also reduce greenhouse gas emissions in many areas of medical care., (© 2024 The Author(s). Pediatric Allergy and Immunology published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.)

Postoperative colorectal imaging studies play an important role in the detection of surgical complications and disease recurrence. In this pictorial essay, we briefly describe methods of surgery, imaging findings of their early and late complications, and postsurgical recurrence of cancer and inflammatory bowel disease., Competing Interests: Conflicts of Interest: The authors have no potential conflicts of interest to disclose., (Copyrights © 2024 The Korean Society of Radiology.)

Background: Although much attention has been paid to admission and transfer patterns for cardiogenic shock, contemporary data are lacking on decompensated heart failure (HF) admissions and transfers and the impact of advanced therapy centers (ATCs) on outcomes., Methods: HF hospitalizations were obtained from the Nationwide Readmissions Database 2016 to 2019. Centers performing at least 1 heart transplant or left ventricular assist device were classified as ATCs. Patient characteristics, outcomes, and procedural volume were compared among 3 cohorts: admissions to non-ATCs, admissions to ATCs, and transfers to ATCs. A secondary analysis evaluated outcomes for severe HF hospitalizations (cardiogenic shock, cardiac arrest, and mechanical ventilation). Multivariable logistic regression was performed to adjust for the presence of HF decompensations and significant clinical variables during univariate analysis., Results: A total of 2 331 690 hospitalizations (81.2%) were admissions to non-ATCs (94.5% of centers), 525 037 (18.3%) were admissions to ATCs (5.5% of centers), and 15 541 (0.5%) were transferred to ATCs. Patients treated at ATCs (especially those transferred) had higher rates of HF decompensations, procedural frequency, lengths of stay, and costs. Unadjusted mortality was 2.6% at non-ATCs and was higher at ATCs, both for directly admitted (2.9%, P <0.001) and transferred (11.2%, P <0.001) patients. However, multivariable-adjusted mortality was significantly lower at ATCs, both for directly admitted (odds ratio, 0.82 [95% CI, 0.78-0.87]; P <0.001) and transferred (odds ratio, 0.66 [95% CI, 0.57-0.78]; P <0.001) patients. For severe HF admissions, unadjusted mortality was 37.2% at non-ATCs and was lower at ATCs, both for directly admitted (25.3%, P <0.001) and transferred (25.2%, P <0.001) patients, with similarly lower multivariable-adjusted mortality., Conclusions: Patients with HF treated at ATCs were sicker but associated with higher procedural volume and lower adjusted mortality., Competing Interests: Dr Cheung has received consulting fees from Abbott, Boston Scientific, and Biotronik, fellowship grant support from Abbott, Biotronik, Boston Scientific, and Medtronic, and research support from Boston Scientific. R.M. Minutello is on the advisory board for Medtronic. Dr Goyal is supported by the American Heart Association grant 18IPA34170185 and is a recipient of a National Institute on Aging Loan Repayment Plan. Dr Horn has received consulting income from Biotronik. Dr Uriel is on the advisory board of Livemetric, Revamp, and Leviticus and has received grant support from Abbott and Abiomed. Dr Kim has received consulting fees from Axon Therapies and fellowship grant support from Medtronic and Abbott. All other authors have reported no conflict of interest relevant to the publication of this article.

Background: Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is increasingly used for patients with cardiogenic shock. Although Impella or intra-aortic balloon pump (IABP) is frequently used for left ventricular unloading (LVU) during VA-ECMO treatment, there are limited data on comparative outcomes. We compared outcomes of Impella and IABP for LVU during VA-ECMO., Methods and Results: Using the Nationwide Readmissions Database between 2016 and 2020, we analyzed outcomes in 3 groups of patients with cardiogenic shock requiring VA-ECMO based on LVU strategies: extracorporeal membrane oxygenation (ECMO) only, ECMO with IABP, and ECMO with Impella. Of 15 980 patients on VA-ECMO, IABP and Impella were used in 19.4% and 16.4%, respectively. The proportion of patients receiving Impella significantly increased from 2016 to 2020 (6.5% versus 25.8%; P -trend<0.001). In-hospital mortality was higher with ECMO with Impella (54.8%) compared with ECMO only (50.4%) and ECMO with IABP (48.4%). After adjustment, ECMO with IABP versus ECMO only was associated with lower in-hospital mortality (adjusted odds ratio [aOR], 0.83; P =0.02). ECMO with Impella versus ECMO only had similar in-hospital mortality (aOR, 1.09; P =0.695) but was associated with more bleeding (aOR, 1.21; P =0.007) and more acute kidney injury requiring hemodialysis (aOR, 1.42; P <0.001). ECMO with Impella versus ECMO with IABP was associated with greater risk of acute kidney injury requiring hemodialysis (aOR, 1.49; P =0.002), higher in-hospital mortality (aOR, 1.32; P =0.001), and higher 40-day mortality (hazard ratio, 1.25; P <0.001)., Conclusions: In patients with cardiogenic shock on VA-ECMO, LVU with Impella, particularly with 2.5/CP, was not associated with improved survival at 40 days but was associated with increased adverse events compared with IABP. More data are needed to assess Impella platform-specific comparative outcomes of LVU.

This paper provides a comprehensive overview of the security vulnerability known as rowhammer in Dynamic Random-Access Memory (DRAM). While DRAM offers many desirable advantages, including low latency, high density, and cost-effectiveness, rowhammer vulnerability, first identified in 2014, poses a significant threat to computing systems. Rowhammer attacks involve repetitive access to specific DRAM rows, which can cause bit flips in neighboring rows, potentially compromising system credentials, integrity, and availability. The paper discusses the various stages of rowhammer attacks, explores existing attack techniques, and examines defense strategies. It also emphasizes the importance of understanding DRAM organization and the associated security challenges.

Background and Objectives: This study aimed to analyze patients with rhabdomyolysis who presented to emergency departments and identify their distribution of related disease and prognostic factors. Materials and Methods: A retrospective cohort study was conducted on patients with rhabdomyolysis who presented to emergency departments over a 10-year period. Patient data, including patients' demographic variables (sex and age), mode of arrival, final diagnosis, statin use, rhabdomyolysis trigger factors, and levels of serum creatine phosphokinase (CPK), myoglobin, creatinine, sodium, potassium, phosphate, calcium, and lactate, were analyzed. Univariate and multivariate logistic regression analyses were conducted to identify the predictive factors of acute kidney injury (AKI). Results: Among the patients, 268 (65.6%) were found to have trigger factors without underlying diseases. Furthermore, 115 (28.2%) patients developed AKI. This comprehensive study sheds light on the diverse factors influencing the occurrence of AKI in rhabdomyolysis and provides insights into AKI predictive markers. Furthermore, we analyzed the cases by dividing them into six groups: occurrence of AKI, occurrence of infection, and simple or complex rhabdomyolysis. CPK time course was found to be important in clinical prognosis, such as AKI occurrence, dialysis or not, and mortality. Conclusions: Age, statin use, elevated creatinine and lactate levels, and initial serum CPK level emerged as significant predictors of AKI. CPK time course was also found to be an important factor in predicting the clinical outcomes of patients with rhabdomyolysis.

Periprosthetic joint infection (PJI) following revision total knee arthroplasty (TKA) for aseptic failure is associated with poor outcomes, patient morbidity, and high health care expenditures. The aim of this study was to develop novel machine learning algorithms for the prediction of PJI following revision TKA for patients with aseptic indications for revision surgery. A single-institution database consisting of 1,432 consecutive revision TKA patients with aseptic etiologies was retrospectively identified. The patient cohort included 208 patients (14.5%) who underwent re-revision surgery for PJI. Three machine learning algorithms (artificial neural networks, support vector machines, k-nearest neighbors) were developed to predict this outcome and these models were assessed by discrimination, calibration, and decision curve analysis. This is a retrospective study. Among the three machine learning models, the neural network model achieved the best performance across discrimination (area under the receiver operating characteristic curve = 0.78), calibration, and decision curve analysis. The strongest predictors for PJI following revision TKA for aseptic reasons were prior open procedure prior to revision surgery, drug abuse, obesity, and diabetes. This study utilized machine learning as a tool for the prediction of PJI following revision TKA for aseptic failure with excellent performance. The validated machine learning models can aid surgeons in patient-specific risk stratifying to assist in preoperative counseling and clinical decision making for patients undergoing aseptic revision TKA., Competing Interests: None declared., (Thieme. All rights reserved.)

Background: Previous studies have shown that women have worse outcomes for cardiogenic shock (CS) than men. Patients who receive care in CS "hubs" have also been shown to have improved outcomes when compared to those treated at "spokes." This study aimed to examine the presence of sex disparities in the outcomes of CS in relation to hospital type., Methods: Hospitalizations of adults with a diagnosis of CS were identified using data from the 2016-2019 Nationwide Readmissions Database. CS "hubs" were defined as any centers receiving at least 1 interhospital transfer with CS, while those without such transfers were classified as "spokes." Data were combined across years and multivariable logistic regression modeling was used to evaluate the association of sex with in-hospital mortality, invasive procedures, and transfer to hubs., Results: There were a total of 618,411 CS hospitalizations (62.2% men) with CS related to acute myocardial infarction comprising 15.3 to 17.3% of women hospitalizations and 17.8 to 20.3% of men hospitalizations. In-hospital mortality was lower at hubs (34.5% for direct admissions, 31.6% for transfers) than at spokes (40.3%, all P < .01). Women underwent fewer invasive procedures (right heart catheterization, percutaneous coronary intervention, mechanical circulatory support) and had higher mortality than men. Female sex was independently associated with decreased transfers to hubs (odds ratio, 0.93; 95% CI, 0.89-0.96) and increased mortality (odds ratio, 1.09; 95% CI, 1.05-1.12)., Conclusions: Women with CS were less likely to be treated at a hub or transferred to a hub, had higher in-hospital mortality, and had a lower likelihood of receiving CS-related procedures than men. Further research is needed to understand sex-specific gaps in CS outcomes., (© 2023 The Author(s).)

The vertebrate organizer is a specified embryonic tissue that regulates dorsoventral patterning and axis formation. Although numerous cellular signaling pathways have been identified as regulators of the organizer's dynamic functions, the process remains incompletely understood, and as-yet unknown pathways remain to be explored for sophisticated mechanistic understanding of the vertebrate organizer. To identify new potential key factors of the organizer, we performed complementary DNA (cDNA) microarray screening using organizer-mimicking Xenopus laevis tissue. This analysis yielded a list of prospective organizer genes, and we determined the role of six-transmembrane domain containing transmembrane protein 150b (Tmem150b) in organizer function. Tmem150b was expressed in the organizer region and induced by Activin/Nodal signaling. In X. laevis, Tmem150b knockdown resulted in head defects and a shortened body axis. Moreover, Tmem150b negatively regulated bone morphogenetic protein (BMP) signaling, likely via physical interaction with activin receptor-like kinase 2 (ALK2). These findings demonstrated that Tmem150b functions as a novel membrane regulatory factor of BMP signaling with antagonistic effects, contributing to the understanding of regulatory molecular mechanisms of organizer axis function. Investigation of additional candidate genes identified in the cDNA microarray analysis could further delineate the genetic networks of the organizer during vertebrate embryogenesis., (© 2023 Wiley Periodicals LLC.)

Background: There are limited data on the feasibility of Impella-assisted percutaneous coronary intervention (PCI) in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR)., Methods: To assess the feasibility of the Impella-assisted PCI in patients with severe symptomatic AS, we retrospectively reviewed the medical records to identify patients who were electively admitted for Impella-assisted PCI with a subsequent TAVR at Weill Cornell Medical Center from 2016 to 2021., Results: During the study period, 15 patients were identified to be eligible for the study, but the Impella failed to cross the aortic valve in 1 patient despite a concomitant balloon aortic valvuloplasty requiring a switch to an intra-aortic balloon pump to assist PCI. A total of 14 patients underwent successful PCI with the Impella CP and were included in the analysis. The median age was 89 years, and women accounted for 43% of the cohort. The median aortic valve area and mean gradient were 0.85 cm 2 and 40 mm Hg, respectively, with a median left ventricular ejection fraction of 51%. The median SYNTAX score was 13. The left main stent was placed in 6 patients (43%), with a rotational atherectomy performed in 10 patients (71%). The balloon aortic valvuloplasty was performed in 2 patients before Impella placement. The TAVR was performed in all 14 patients on a median post-Impella-assisted PCI day of 25. No procedural complications were noted post-TAVR with no in-hospital or 30-day death., Conclusions: In this single-center study of patients with severe AS, the elective Impella-assisted high-risk PCI was feasible and safe before TAVR in selected patients., (© 2023 The Author(s).)

Introduction: Revision total hip arthroplasty (THA) represents a technically demanding surgical procedure which is associated with significant morbidity and mortality. Understanding risk factors for failure of revision THA is of clinical importance to identify at-risk patients. This study aimed to develop and validate novel machine learning algorithms for the prediction of re-revision surgery for patients following revision total hip arthroplasty., Methods: A total of 2588 consecutive patients that underwent revision THA was evaluated, including 408 patients (15.7%) with confirmed re-revision THA. Electronic patient records were manually reviewed to identify patient demographics, implant characteristics and surgical variables that may be associated with re-revision THA. Machine learning algorithms were developed to predict re-revision THA and these models were assessed by discrimination, calibration and decision curve analysis., Results: The strongest predictors for re-revision THA as predicted by the four validated machine learning models were the American Society of Anaesthesiology score, obesity (> 35 kg/m 2 ) and indication for revision THA. The four machine learning models all achieved excellent performance across discrimination (AUC > 0.80), calibration and decision curve analysis. Higher net benefits for all machine learning models were demonstrated, when compared to the default strategies of changing management for all patients or no patients., Conclusion: This study developed four machine learning models for the prediction of re-revision surgery for patients following revision total hip arthroplasty. The study findings show excellent model performance, highlighting the potential of these computational models to assist in preoperative patient optimization and counselling to improve revision THA patient outcomes., Level of Evidence: Level III, case-control retrospective analysis., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Prolonged surgical operative time is associated with postoperative adverse outcomes following total knee arthroplasty (TKA). Increasing operating room efficiency necessitates the accurate prediction of surgical operative time for each patient. One potential way to increase the accuracy of predictions is to use advanced predictive analytics, such as machine learning. The aim of this study is to use machine learning to develop an accurate predictive model for surgical operative time for patients undergoing primary total knee arthroplasty., Methods: A retrospective chart review of electronic medical records was conducted to identify patients who underwent primary total knee arthroplasty at a tertiary referral center. Three machine learning algorithms were developed to predict surgical operative time and were assessed by discrimination, calibration and decision curve analysis. Specifically, we used: (1) Artificial Neural Networks (ANNs), (2) Random Forest (RF), and (3) K-Nearest Neighbor (KNN)., Results: We analyzed the surgical operative time for 10,021 consecutive patients who underwent primary total knee arthroplasty. The neural network model achieved the best performance across discrimination (AUC = 0.82), calibration and decision curve analysis for predicting surgical operative time. Based on this algorithm, younger age (< 45 years), tranexamic acid non-usage, and a high BMI (> 40 kg/m 2 ) were the strongest predictors associated with surgical operative time., Conclusions: This study shows excellent performance of machine learning models for predicting surgical operative time in primary total knee arthroplasty. The accurate estimation of surgical duration is important in enhancing OR efficiency and identifying patients at risk for prolonged surgical operative time., Level of Evidence: Level III, case control retrospective analysis., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Cardiac implantable electronic device (CIED)-associated infections are associated with substantial morbidity, mortality, and costs. Guidelines have cited endocarditis as a Class I indication for transvenous lead removal/extraction (TLE) among patients with CIEDs., Objectives: The authors sought to study utilization of TLE among hospital admissions with infective endocarditis using a nationally representative database., Methods: Using the Nationwide Readmissions Database (NRD), 25,303 admissions for patients with CIEDs and endocarditis between 2016 and 2019 were evaluated on the basis of International Classification of Diseases-10th Revision, Clinical-Modification (ICD-10-CM) codes., Results: Among admissions for patients with CIEDs and endocarditis, 11.5% were managed with TLE. The proportion undergoing TLE increased significantly from 2016 to 2019 (7.6% vs 14.9%; P trend < 0.001). Procedural complications were identified in 2.7%. Index mortality was significantly lower among patients managed with TLE (6.0% vs 9.5%; P < 0.001). Presence of Staphylococcus aureus infection, implantable cardioverter-defibrillator, and large hospital size were independently associated with TLE management. TLE management was less likely with older age, female sex, dementia, and kidney disease. After adjustment for comorbidities, TLE was independently associated with significantly lower odds of mortality (adjusted OR: 0.47; 95% CI: 0.37-0.60 by multivariable logistic regression, and adjusted OR: 0.51; 95% CI: 0.40-0.66 by propensity score matching)., Conclusions: Utilization of lead extraction among patients with CIEDs and endocarditis is low, even in the presence of low rates of procedural complications. Lead extraction management is associated with significantly lower mortality, and its use has trended upward between 2016 and 2019. Barriers to TLE for patients with CIEDs and endocarditis require investigation., Competing Interests: Funding Support and Author Disclosures This work was supported by grants from the Michael Wolk Heart Foundation, the New York Cardiac Center, Inc, and the New York Weill Cornell Medical Center Alumni Council. Dr Cheung has received consulting fees from Abbott, Biotronik, and Boston Scientific; has received research grant support from Boston Scientific; and has received fellowship grant support from Abbott, Biosense Webster, Biotronik, Boston Scientific, and Medtronic. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

This is a retrospective study. Surgical site infection (SSI) is associated with adverse postoperative outcomes following total knee arthroplasty (TKA). However, accurately predicting SSI remains a clinical challenge due to the multitude of patient and surgical factors associated with SSI. This study aimed to develop and validate machine learning models for the prediction of SSI following primary TKA. This is a retrospective study for patients who underwent primary TKA. Chart review was performed to identify patients with superficial or deep SSIs, defined in concordance with the criteria of the Musculoskeletal Infection Society. All patients had a minimum follow-up of 2 years (range: 2.1-4.7 years). Five machine learning algorithms were developed to predict this outcome, and model assessment was performed by discrimination, calibration, and decision curve analysis. A total of 10,021 consecutive primary TKA patients was included in this study. At an average follow-up of 2.8 ± 1.1 years, SSIs were reported in 404 (4.0%) TKA patients, including 223 superficial SSIs and 181 deep SSIs. The neural network model achieved the best performance across discrimination (area under the receiver operating characteristic curve = 0.84), calibration, and decision curve analysis. The strongest predictors of the occurrence of SSI following primary TKA, in order, were Charlson comorbidity index, obesity (BMI >30 kg/m 2 ), and smoking. The neural network model presented in this study represents an accurate method to predict patient-specific superficial and deep SSIs following primary TKA, which may be employed to assist in clinical decision-making to optimize outcomes in at-risk patients., Competing Interests: None declared., (Thieme. All rights reserved.)

Background: Patient-reported outcome measures (PROMs) are increasingly used as quality benchmark in total hip and knee arthroplasty (THA; TKA) due to bundled payment systems that aim to provide a patient-centered, value-based treatment approach. However, there is a paucity of predictive tools for postoperative PROMs. Therefore, this study aimed to develop and validate machine learning models for the prediction of numerous patient-reported outcome measures following primary hip and knee total joint arthroplasty., Methods: A total of 4526 consecutive patients (2137 THA; 2389 TKA) who underwent primary hip and knee total joint arthroplasty and completed both pre- and postoperative PROM scores was evaluated in this study. The following PROM scores were included for analysis: HOOS-PS, KOOS-PS, Physical Function SF10A, PROMIS SF Physical and PROMIS SF Mental. Patient charts were manually reviewed to identify patient demographics and surgical variables associated with postoperative PROM scores. Four machine learning algorithms were developed to predict postoperative PROMs following hip and knee total joint arthroplasty. Model assessment was performed through discrimination, calibration and decision curve analysis., Results: The factors most significantly associated with the prediction of postoperative PROMs include preoperative PROM scores, Charlson Comorbidity Index, American Society of Anaesthesiology score, insurance status, age, length of hospital stay, body mass index and ethnicity. The four machine learning models all achieved excellent performance across discrimination (AUC > 0.83), calibration and decision curve analysis., Conclusion: This study developed machine learning models for the prediction of patient-reported outcome measures at 1-year following primary hip and knee total joint arthroplasty. The study findings show excellent performance on discrimination, calibration and decision curve analysis for all four machine learning models, highlighting the potential of these models in clinical practice to inform patients prior to surgery regarding their expectations of postoperative functional outcomes following primary hip and knee total joint arthroplasty., Level of Evidence: Level III, case control retrospective analysis., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Objective: The proportion of ST-segment elevation myocardial infarction (STEMI) patients without standard modifiable risk factors (SMuRFs: hypertension, diabetes, hypercholesterolemia and smoking) has increased over time. The absence of SMuRFs is known to be associated with worse outcomes, but its association with age and sex is uncertain. We sought to evaluate the association between age and sex with the outcomes of post-STEMI patients without SMuRFs among patients without preexisting coronary artery disease., Methods: Patients who underwent primary PCI for STEMI were identified from the Nationwide Readmission Database of the United States. Clinical characteristics, in-hospital, and 30-day outcomes in patients with or without SMuRFs were compared in men versus women and stratified into five age groups., Results: Between January 2010 and November 2014, of 474,234 patients who underwent primary PCI for STEMI, 52,242 (11.0%) patients did not have SMuRFs. Patients without SMuRFs had higher in-hospital mortality rates than those with SMuRFs. Among those without SMuRFs, the in-hospital mortality rate was significantly higher in women than men (10.6% vs 7.3%, p<0.001), particularly in older age groups. The absence of SMuRFs was associated with higher 30-day readmission-related mortality rates (0.5% vs 0.3% with SMuRFs, p<0.001). Among patients without SMuRFs, women had a higher 30-day readmission-related mortality rates than men (0.6% vs 0.4%, p<0.001). After multivariable adjustment, the increased rates of in-hospital (odds ratio 1.89 (95% CI 1.72 to 2.07) and 30-day readmission-related mortality (hazard ratio 1.30 (95% CI 1.01 to 1.67)) in patients without SMuRFs remained significant., Conclusions: STEMI patients without SMuRFs have a significantly higher risk of in-hospital and 30-day mortality than those with SMuRFs. Women and older patients without SMuRFs experienced significantly higher in-hospital and 30-day readmission-related mortality., Competing Interests: None declared, (Published by Elsevier B.V.)

Background: Clostridioides difficile (formerly known as Clostridium difficile ) infection (CDI) is one of the most prevalent healthcare-associated infections in the United States (US). In the early 2000s, CDI emerged as a great threat with increasing prevalence, mortality, and severity, especially in advanced age. We investigated the US national trends in in-hospital CDI prevalence, mortality, severity, and age composition from 2003 to 2014., Methods: We identified the patients with CDI using the national inpatient sample data from 2003 to 2014. We performed Poisson regression model and Kendall's tau-b correlation test for our analyses., Results: Adjusted overall CDI prevalence did not significantly change during 2003-2014. In-hospital mortality of overall CDI did not significantly change during 2003-2008, then significantly decreased during 2008-2014. Severity of overall CDI significantly increased during 2003-2008, then decreased during 2008-2014. The proportions of patients with age ≥ 65 years decreased in CDI prevalence, mortality, and severity during 2003-2014., Conclusions: Compared to the earlier years 2003-2008, overall CDI outcome improved in the later years 2008-2014. Younger patients increasingly contributed to CDI prevalence, mortality, and severity during 2003-2014. More studies to understand underlying driving forces of changes in CDI trends are warranted to mitigate CDI.

Background There are limited data on the sex-based differences in the outcome of readmission after cardiac arrest. Methods and Results Using the Nationwide Readmissions Database, we analyzed patients hospitalized with cardiac arrest between 2010 and 2015. Based on International Classification of Diseases, Ninth Revision, Clinical Modification ( ICD-9-CM ) codes, we identified comorbidities, therapeutic interventions, and outcomes. Multivariable logistic regression was performed to assess the independent association between sex and outcomes. Of 835 894 patients, 44.4% (n=371 455) were women, of whom 80.7% presented with pulseless electrical activity (PEA)/asystole. Women primarily presented with PEA/asystole (80.7% versus 72.4%) and had a greater comorbidity burden than men, as assessed using the Elixhauser Comorbidity Score. Thirty-day readmission rates were higher in women than men in both PEA/asystole (20.8% versus 19.6%) and ventricular tachycardia/ventricular fibrillation arrests (19.4% versus 17.1%). Among ventricular tachycardia/ventricular fibrillation arrest survivors, women were more likely than men to be readmitted because of noncardiac causes, predominantly infectious, respiratory, and gastrointestinal illnesses. Among PEA/asystole survivors, women were at higher risk for all-cause (adjusted odds ratio [aOR], 1.07; [95% CI, 1.03-1.11]), cardiac-cause (aOR, 1.15; [95% CI, 1.06-1.25]), and noncardiac-cause (aOR, 1.13; [95% CI, 1.04-1.22]) readmission. During the index hospitalization, women were less likely than men to receive therapeutic procedures, including coronary angiography and targeted therapeutic management. While the crude case fatality rate was higher in women, in both ventricular tachycardia/ventricular fibrillation (51.8% versus 47.4%) and PEA/asystole (69.3% versus 68.5%) arrests, sex was not independently associated with increased crude case fatality after adjusting for differences in baseline characteristics. Conclusions Women are at increased risk of readmission following cardiac arrest, independent of comorbidities and therapeutic interventions.

Background/aims: To explore if retinal findings are associated with COVID-19 infection., Methods: In this prospective cross-sectional study, we recruited participants positive for COVID-19 by nasopharyngeal swab, with no medical history. Subjects underwent retinal imaging with an automated imaging device (3D OCT-1 Maestro, Topcon, Tokyo, Japan) to obtain colour fundus photographs (CFP) and optical coherence tomographic (OCT) scans of the macula. Data on personal biodata, medical history and vital signs were collected from electronic medical records., Results: 108 patients were recruited. Mean age was 36.0±5.4 years. 41 (38.0%) had symptoms of acute respiratory infection (ARI) at presentation. Of 216 eyes, 25 (11.6%) had retinal signs-eight (3.7%) with microhaemorrhages, six (2.8%) with retinal vascular tortuosity and two (0.93%) with cotton wool spots (CWS). 11 eyes (5.1%) had hyper-reflective plaques in the ganglion cell-inner plexiform layer layer on OCT, of which two also had retinal signs visible on CFP (CWS and microhaemorrhage, respectively). There was no significant difference in the prevalence of retinal signs in symptomatic versus asymptomatic patients (12 (15.0%) vs 13 (9.6%), p=0.227). Patients with retinal signs were significantly more likely to have transiently elevated blood pressure than those without (p=0.03)., Conclusion: One in nine had retinal microvascular signs on ocular imaging. These signs were observed even in asymptomatic patients with normal vital signs. These retinal microvascular signs may be related to underlying cardiovascular and thrombotic alternations associated with COVID-19 infection., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

Conventional methods for the surveillance of hepatocellular carcinoma (HCC) by imaging, with and without serum tumor markers, are suboptimal with regard to accuracy. We aimed to develop and validate a reliable serum biomarker panel for the early detection of HCC using a proteomic technique. This multicenter case-control study comprised 727 patients with HCC and patients with risk factors but no HCC. We developed a multiple reaction monitoring-mass spectrometry (MRM-MS) multimarker panel using 17 proteins from the sera of 398 patients. Area under the receiver operating characteristics curve (AUROC) values of this MRM-MS panel with and without α-fetoprotein (AFP) and protein induced by vitamin K absence or antagonist-II (PIVKA-II) were compared. The combination and standalone MRM-MS panels had higher AUROC values than AFP in the training (0.940 and 0.929 vs 0.775, both P < 0.05), test (0.894 and 0.893 vs 0.593, both P < 0.05), and confirmation sets (0.961 and 0.937 vs 0.806, both P < 0.05) in detecting small single HCC. The combination and standalone MRM-MS panels had significantly higher AUROC values than the GALAD score (0.945 and 0.931 vs 0.829, both P < 0.05). Our proteome 17-protein multimarker panel distinguished HCC patients from high-risk controls and had high accuracy in the early detection of HCC., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

Purpose: Adequate postoperative pain control following total knee arthroplasty (TKA) is required to achieve optimal patient recovery. However, the postoperative recovery may lead to an unnaturally extended opioid use, which has been associated with adverse outcomes. This study hypothesizes that machine learning models can accurately predict extended opioid use following primary TKA., Methods: A total of 8873 consecutive patients that underwent primary TKA were evaluated, including 643 patients (7.2%) with extended postoperative opioid use (> 90 days). Electronic patient records were manually reviewed to identify patient demographics and surgical variables associated with prolonged postoperative opioid use. Five machine learning algorithms were developed, encompassing the breadth of state-of-the-art machine learning algorithms available in the literature, to predict extended opioid use following primary TKA, and these models were assessed by discrimination, calibration, and decision curve analysis., Results: The strongest predictors for prolonged opioid prescription following primary TKA were preoperative opioid duration (100% importance; p < 0.01), drug abuse (54% importance; p < 0.01), and depression (47% importance; p < 0.01). The five machine learning models all achieved excellent performance across discrimination (AUC > 0.83), calibration, and decision curve analysis. Higher net benefits for all machine learning models were demonstrated, when compared to the default strategies of changing management for all patients or no patients., Conclusion: The study findings show excellent model performance for the prediction of extended postoperative opioid use following primary total knee arthroplasty, highlighting the potential of these models to assist in preoperatively identifying at risk patients, and allowing the implementation of individualized peri-operative counselling and pain management strategies to mitigate complications associated with prolonged opioid use., Level of Evidence: IV., (© 2021. The Author(s) under exclusive licence to European Society of Sports Traumatology, Knee Surgery, Arthroscopy (ESSKA).)

Realization of memristor-based neuromorphic hardware system is important to achieve energy efficient bigdata processing and artificial intelligence in integrated device system-level. In this sense, uniform and reliable titanium oxide (TiO x ) memristor array devices are fabricated to be utilized as constituent device element in hardware neural network, representing passive matrix array structure enabling vector-matrix multiplication process between multisignal and trained synaptic weight. In particular, in situ convolutional neural network hardware system is designed and implemented using a multiple 25 × 25 TiO x memristor arrays and the memristor device parameters are developed to bring global constant voltage programming scheme for entire cells in crossbar array without any voltage tuning peripheral circuit such as transistor. Moreover, the learning rate modulation during in situ hardware training process is successfully achieved due to superior TiO x memristor performance such as threshold uniformity (≈2.7%), device yield (> 99%), repetitive stability (≈3000 spikes), low asymmetry value of ≈1.43, ambient stability (6 months), and nonlinear pulse response. The learning rate modulable fast-converging in situ training based on direct memristor operation shows five times less training iterations and reduces training energy compared to the conventional hardware in situ training at ≈95.2% of classification accuracy., (© 2022 The Authors. Advanced Science published by Wiley-VCH GmbH.)

Purpose: This study aimed to develop and validate machine-learning models for the prediction of recurrent infection in patients following revision total knee arthroplasty for periprosthetic joint infection., Methods: A total of 618 consecutive patients underwent revision total knee arthroplasty for periprosthetic joint infection. The patient cohort included 165 patients with confirmed recurrent periprosthetic joint infection (PJI). Potential risk factors including patient demographics and surgical characteristics served as input to three machine-learning models which were developed to predict recurrent periprosthetic joint. The machine-learning models were assessed by discrimination, calibration and decision curve analysis., Results: The factors most significantly associated with recurrent PJI in patients following revision total knee arthroplasty for PJI included irrigation and debridement with/without modular component exchange (p < 0.001), > 4 prior open surgeries (p < 0.001), metastatic disease (p < 0.001), drug abuse (p < 0.001), HIV/AIDS (p < 0.01), presence of Enterococcus species (p < 0.01) and obesity (p < 0.01). The machine-learning models all achieved excellent performance across discrimination (AUC range 0.81-0.84)., Conclusion: This study developed three machine-learning models for the prediction of recurrent infections in patients following revision total knee arthroplasty for periprosthetic joint infection. The strongest predictors were previous irrigation and debridement with or without modular component exchange and prior open surgeries. The study findings show excellent model performance, highlighting the potential of these computational tools in quantifying increased risks of recurrent PJI to optimize patient outcomes., Level of Evidence: IV., (© 2021. The Author(s) under exclusive licence to European Society of Sports Traumatology, Knee Surgery, Arthroscopy (ESSKA).)

The preservation of the posterior cruciate ligament in cruciate retaining (CR) total knee arthroplasty (TKA) designs has the potential to restore healthy knee biomechanics; however, concerns related to kinematic asymmetries during functional activities still exist in unilateral TKA patients. As there is a limited data available regarding the ability of the contemporary CR TKA design with concave medial and convex lateral tibial polyethylene bearing components to restore healthy knee biomechanics, this study aimed to investigate in vivo three-dimensional knee kinematics in CR TKA patients during strenuous knee flexion activities and gait. Using a combined computer tomography and dual fluoroscopic imaging system approach, in vivo kinematics of 15 unilateral CR TKA patients (comparison of replaced and contralateral nonreplaced knee) were evaluated during sit-to-stand, step-ups, single-leg deep lunge, and level walking. The patient cohort was followed-up at an average of 24.5 months ( ± 12.6, range 13-42) from surgical procedure. Significantly smaller internal knee rotation angles were observed for the contemporary CR TKA design during step-ups (2.6 ± 5.8 vs. 6.3 ± 6.6 degrees, p  < 0.05) and gait (0.6 ± 4.6 vs. 6.3 ± 6.8 degrees, p  < 0.05). Significantly larger proximal and anterior femoral translations were measured during sit-to-stand (34.7 ± 4.5 vs. 29.9 ± 3.1 mm, p  < 0.05; -2.5 ± 2.9 vs. -8.1 ± 4.4 mm, p  < 0.05) and step-ups (34.1 ± 4.5 vs. 30.8 ± 2.9 mm, p  < 0.05; 2.2 ± 3.2 vs. -3.5 ± 4.5 mm, p  < 0.05). Significantly smaller ranges of varus/valgus and internal/external rotation range of motion were observed for CR TKA, when compared with the nonoperated nee, during strenuous activities and gait. The preservation of the posterior cruciate ligament in the contemporary asymmetric bearing geometry CR TKA design with concave medial and convex lateral tibial polyethylene bearing components has the potential to restore healthy knee biomechanics; however, the study findings demonstrate that native knee kinematics were not fully restored in patients with unilateral asymmetric tibial polyethylene bearing geometry CR TKA during functional activities., Competing Interests: None declared., (Thieme. All rights reserved.)

Glycoproteins have many important biological functions. In particular, aberrant glycosylation has been observed in various cancers, such as liver cancer. A well-known glycoprotein biomarker is α-fetoprotein (AFP), a surveillance biomarker for hepatocellular carcinoma (HCC) that contains a glycosylation site at asparagine 251. The low diagnostic sensitivity of AFP led researchers to focus on AFP-L3, which has the same sequence as conventional AFP but contains a fucosylated glycan. AFP-L3 has high affinity for Lens culinaris agglutinin (LCA) lectin, prompting many groups to use it for detecting AFP-L3. However, a few studies have identified more effective lectins for fractionating AFP-L3. In this study, we compared the amounts of enriched AFP-L3 with five fucose-specific lectins─LCA, Lotus tetragonolobus lectin (LTL), Ulex europaeus agglutinin I (UEA I), Aleuria aurantia lectin (AAL), and Aspergillus oryzae lectin (AOL)─to identify better lectins and improve HCC diagnostic assays using mass spectrometry (MS). Our results indicate that LTL was the most effective lectin for capturing AFP-L3 species, yielding approximately 3-fold more AFP-L3 than LCA from the same pool of HCC serum samples. Thus, we recommend the use of LTL for AFP-L3 assays, given its potential to improve the diagnostic sensitivity in patients having limited results by conventional LCA assay. The MS data have been deposited to the PeptideAtlas (PASS01752).

Background: Revision total hip arthroplasty (THA) is associated with increased morbidity, mortality, and healthcare costs due to a technically more demanding surgical procedure when compared with primary THA. Therefore, a better understanding of risk factors for early revision THA is essential to develop strategies for mitigating the risk of patients undergoing early revision. This study aimed to develop and validate novel machine learning (ML) models for the prediction of early revision after primary THA., Methods: A total of 7,397 consecutive patients who underwent primary THA were evaluated, including 566 patients (6.6%) with confirmed early revision THA (<2 years from index THA). Electronic patient records were manually reviewed to identify patient demographics, implant characteristics, and surgical variables that may be associated with early revision THA. Six ML algorithms were developed to predict early revision THA, and these models were assessed by discrimination, calibration, and decision curve analysis., Results: The strongest predictors for early revision after primary THA were Charlson Comorbidity Index, body mass index >35 kg/m2, and depression. The six ML models all achieved excellent performance across discrimination (area under the curve >0.80), calibration, and decision curve analysis., Conclusion: This study developed ML models for the prediction of early revision surgery for patients after primary THA. The study findings show excellent performance on discrimination, calibration, and decision curve analysis for all six candidate models, highlighting the potential of these models to assist in clinical practice patient-specific preoperative quantification of increased risk of early revision THA., (Copyright © 2022 by the American Academy of Orthopaedic Surgeons.)

Background: Total hip arthroplasty (THA) done in the aging population is associated with osteoporosis-related complications. The altered bone density in osteoporotic patients is a risk factor for revision surgery. This study aimed to develop and validate machine learning (ML) models to predict revision surgery in patients with osteoporosis after primary noncemented THA., Methods: We retrospectively reviewed a consecutive series of 350 patients with osteoporosis (T-score less than or equal to -2.5) who underwent primary noncemented THA at a tertiary referral center. All patients had a minimum 2-year follow-up (range: 2.1 to 5.6). Four ML algorithms were developed to predict the probability of revision surgery, and these were assessed by discrimination, calibration, and decision curve analysis., Results: The overall incidence of revision surgery was 5.2% at a mean follow-up of 3.7 years after primary noncemented THA in osteoporotic patients. Revision THA was done because of periprosthetic fracture in nine patients (50%), aseptic loosening/subsidence in five patients (28%), periprosthetic joint infection in two patients (11%) and dislocation in two patients (11%). The strongest predictors for revision surgery in patients after primary noncemented THA were female sex, BMI (>35 kg/m2), age (>70 years), American Society of Anesthesiology score (≥3), and T-score. All four ML models demonstrated good model performance across discrimination (AUC range: 0.78 to 0.81), calibration, and decision curve analysis., Conclusion: The ML models presented in this study demonstrated high accuracy for the prediction of revision surgery in osteoporotic patients after primary noncemented THA. The presented ML models have the potential to be used by orthopaedic surgeons for preoperative patient counseling and optimization to improve the outcomes of primary noncemented THA in osteoporotic patients., (Copyright © 2022 by the American Academy of Orthopaedic Surgeons.)

Suicide is a leading cause of death worldwide, presenting a serious public health problem. We aimed to investigate the biological basis of suicide completion using proteomics on postmortem brain tissue. Thirty-six postmortem brain samples (23 suicide completers and 13 controls) were collected. We evaluated the proteomic profile in the prefrontal cortex (Broadmann area 9, 10) using tandem mass tag-based quantification with liquid chromatography-tandem mass spectrometry. Bioinformatics tools were used to elucidate the biological mechanisms related to suicide. Subgroup analysis was conducted to identify common differentially expressed proteins among clinically different groups. Of 9801 proteins identified, 295 were differentially expressed between groups. Suicide completion samples were mostly enriched in the endocannabinoid and apoptotic pathways (CAPNS1, CSNK2B, PTP4A2). Among the differentially expressed proteins, GSTT1 was identified as a potential biomarker among suicide completers with psychiatric disorders. Our findings suggest that the previously under-recognized endocannabinoid system and apoptotic processes are highly involved in suicide., (© 2022. The Author(s).)

Background: Highly sensitive and accurate malaria diagnostic tools are essential to identify asymptomatic low parasitaemia infections. This study evaluated the performance of histidine-rich protein 2 (HRP-2) based rapid diagnostic tests (RDTs), microscopy and loop-mediated isothermal amplification (LAMP) for the detection of asymptomatic Plasmodium spp. infections in Northern Côte d'Ivoire, using nested polymerase chain reaction (nPCR) as reference., Methods: A household-based survey was carried out in July 2016, in the health district of Korhogo, involving 1011 adults without malaria symptom nor history of fever during the week before recruitment. The fresh capillary blood samples were collected to detect Plasmodium infections using on HRP-2-based RDTs, microscopy and LAMP and stored as dried blood spots (DBS). A subset of the DBS (247/1011, 24.4%) was randomly selected for nPCR analyses. Additionally, venous blood samples, according to LAMP result (45 LAMP positive and 65 LAMP negative) were collected among the included participants to perform the nested PCR used as the reference., Results: The prevalence of asymptomatic Plasmodium spp. infections determined by RDT, microscopy, and LAMP were 4% (95% confidence interval (CI) 2.8-5.3), 5.2% (95% CI 3.9-6.6) and 18.8% (95% CI 16.4-21.2), respectively. Considering PCR on venous blood as reference, performed on 110 samples, the sensibility and specificity were, respectively, 17.8% (95% CI 6.1-29.4) and 100% for RDT, 20.0% (95% CI 7.8-32) and 100% for microscopy, and 93.3% (95% CI 85.7-100) and 95.4% (95% CI 92.2-100) for LAMP., Conclusion: In Northern Côte d'Ivoire, asymptomatic Plasmodium infection was found to be widely distributed as approximately one out of five study participants was found to be Plasmodium infected. LAMP appears currently to be the only available diagnostic method that can identify in the field this reservoir of infections and should be the method to consider for potential future active case detection interventions targeting elimination of these infections., (© 2022. The Author(s).)

Alzheimer disease (AD) is a leading cause of dementia that has gained prominence in our aging society. Yet, the complexity of diagnosing AD and measuring its invasiveness poses an obstacle. To this end, blood-based biomarkers could mitigate the inconveniences that impede an accurate diagnosis. We developed models to diagnose AD and measure the severity of neurocognitive impairment using blood protein biomarkers. Multiple reaction monitoring-mass spectrometry, a highly selective and sensitive approach for quantifying targeted proteins in samples, was used to analyze blood samples from 4 AD groups: cognitive normal control, asymptomatic AD, prodromal AD), and AD dementia. Multimarker models were developed using 10 protein biomarkers and apolipoprotein E genotypes for amyloid beta and 10 biomarkers with Korean Mini-Mental Status Examination (K-MMSE) score for predicting Alzheimer disease progression. The accuracies for the AD classification model and AD progression monitoring model were 84.9% (95% CI 82.8 to 87.0) and 79.1% (95% CI 77.8 to 80.5), respectively. The models were more accurate in diagnosing AD, compared with single APOE genotypes and the K-MMSE score. Our study demonstrates the possibility of predicting AD with high accuracy by blood biomarker analysis as an alternative method of screening for AD., (© 2022. The Author(s).)

TurboID is a new and efficient proximity labeling system that was first developed in living mammalian cells. TurboID is a modified bacterial biotin ligase that can be fused to a bait protein, which can then modify proximal interacting proteins with biotin. Prey proteins subsequently labeled with biotin tags will be pulled down with streptavidin-coated beads and identified by mass spectrometry-based proteomics. TurboID has been recently applied to living plant cells and provided promising results in identification of interacting proteins. Mitogen-activated protein kinase 4 (MPK4) is important for plant growth, development, and defense; however, the molecular mechanisms underlying the range of MPK4 functions are not completely known. Here we use modern proteomics together with the TurboID in a proof-of-concept study to profile the MPK4 interactome and uncover the functions of MPK4 in plant signaling cascades., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Purpose: To propose guidelines for lung stereotactic body radiation therapy (SBRT) when using Acuros XB (AXB) equivalent to the existing ones developed for convolution algorithms such as analytic anisotropic algorithm (AAA), considering the difference between the algorithms., Methods: A retrospective analysis was performed on 30 lung patients previously treated with SBRT. The original AAA plans, which were developed using dynamic conformal arcs, were recalculated and then renormalized for planning target volume (PTV) coverage using AXB. The recalculated and renormalized plans were compared to the original plans based on V100% and V90% PTV coverage, as well as V105%, conformality index, D 2cm , Rx/D max , R50, and D min . These metrics were analyzed nominally and on variations according to RTOG and NRG guidelines. Based on the relative difference between each metric in the AAA and AXB plans, new guidelines were developed. The relative differences in our cohort were compared to previously documented AAA to AXB comparisons found in the literature., Results: AAA plans recalculated in AXB had a significant reduction in most dosimetric metrics. The most notable changes were in V100% (4%) and the conformality index (7.5%). To achieve equal PTV coverage, AXB required an average of 1.8% more monitor units (MU). This fits well with previously published data. Applying the new guidelines to the AXB plans significantly increased the number of minor violations with no change in major violations, making them comparable to those of the original AAA plans., Conclusion: The relative difference found between AAA and AXB for SBRT lung plans has been shown to be consistent with previous works. Based on these findings, new guidelines for lung SBRT are recommended when planning with AXB., (© 2021 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.)

Aims: Cardiogenic shock (CS) is associated with significant mortality, and there is a movement towards regional 'hub-and-spoke' triage systems to coordinate care and resources. Limited data exist on outcomes of patients treated at CS transfer hubs., Methods and Results: Cardiogenic shock hospitalizations were obtained from the Nationwide Readmissions Database 2010-2014. Centres receiving any interhospital transfers with CS in a given year were classified as CS transfer 'hubs'; those without transfers were classified as 'spokes.' In-hospital mortality was compared among three cohorts: (A) direct admissions to spokes, (B) direct admissions to hubs, and (C) interhospital transfer to hubs. Among hospitals treating CS, 70.6% were classified as spokes and 29.4% as hubs. A total of 130 656 (31.7%) hospitalizations with CS were direct admission to spokes, 253 234 (61.4%) were direct admissions to hubs, and 28 777 (7.0%) were transfer to hubs. CS mortality was 47.8% at spoke hospitals and was lower at hub hospitals, both for directly admitted (39.3%, P < 0.01) and transferred (33.4%, P < 0.01) patients. Hospitalizations at hubs had higher procedural frequency (including coronary artery bypass graft, right heart catheterization, mechanical circulatory support), greater length of stay, and greater costs. On multivariable analysis, direct admission to CS hubs [odds ratio (OR) 0.86, 95% confidence interval (CI) 0.84-0.89, P < 0.01] and transfer to hubs (OR 0.72, 95% CI 0.69-0.76, P < 0.01) were both associated with lower mortality., Conclusion: While acknowledging the limited ability of the Nationwide Readmissions Database to classify CS severity on presentation, treatment of CS at transfer hubs was associated with significantly lower mortality within this large real-world sample., (© 2021 European Society of Cardiology.)

Hepatocellular carcinoma (HCC) is a malignant cancer with one of the highest mortality rates. Des-γ-carboxyprothrombin (DCP) is an HCC serologic surveillance marker that can complement the low sensitivity of alpha-fetoprotein (AFP). DCP exists in the blood as a mixture of proteoforms from an impaired carboxylation process at glutamic acid (Glu) residues within the N-terminal domain. The heterogeneity of DCP may affect the accuracy of measurements because DCP levels are commonly determined using an immunoassay that relies on antibody reactivity to an epitope in the DCP molecule. In this study, we aimed to improve the DCP measurement assay by applying a mass spectrometry (MS)-based approach for a more inclusive quantification of various DCP proteoforms. We developed a multiple-reaction monitoring-MS (MRM-MS) assay to quantify multiple noncarboxylated peptides included in the various des-carboxylation states of DCP. We performed the MRM-MS assay in 300 patients and constructed a robust diagnostic model that simultaneously monitored three noncarboxylated peptides. The MS-based quantitative assay for DCP had reliable surveillance power, which was evident from the area under the receiver operating characteristic curve (AUROC) values of 0.874 and 0.844 for the training and test sets, respectively. It was equivalent to conventional antibody-based quantification, which had AUROC values at the optimal cutoff (40 mAU/mL) of 0.743 and 0.704 for the training and test sets, respectively. The surveillance performance of the MS-based DCP assay was validated using an independent validation set consisting of 318 patients from an external cohort, resulting in an AUROC value of 0.793. Conclusion: Due to cost effectiveness and high reproducibility, the quantitative DCP assay using the MRM-MS method is superior to antibody-based quantification and has equivalent performance., (© 2021 The Authors. Hepatology Communications published by Wiley Periodicals LLC on behalf of the American Association for the Study of Liver Diseases.)

Background: Cardiovascular disease is the leading cause of death for women in the United States. Revascularization is considered the standard of care for treatment of ST-segment elevation myocardial infarction (STEMI) and is known to reduce readmission. However there is a paucity of data that examines the sex-dependent impact of revascularization on readmission. We aimed to investigate sex differences in revascularization rates, 30-day readmission rates, and primary cause of readmissions following STEMIs., Methods: STEMI hospitalizations were selected in the Nationwide Readmissions Database from 2010 to 2014. Revascularization rates, 30-day readmission rates, and primary cause of readmission were examined. Interaction between sex and revascularization was assessed. Multivariable regression analysis was performed to identify predictors of 30-day readmission and revascularization for both sexes., Results: 219,944 women and 489,605 men were admitted with STEMIs. Women were more likely to be older, and have more comorbidities. Women were less likely to undergo revascularization by percutaneous coronary intervention (adjusted odds ratio [OR]: 0.68; 95% confidence interval [CI]: 0.66-0.70) or coronary artery bypass graft surgery (adjusted OR 0.40; CI 0.39-0.44). Women had higher 30-day readmission rates (15.7% vs. 10.8%, p < 0.001; OR 1.20, CI 1.17-1.23), and revascularization in women was not associated with a decreased likelihood of 30-day readmission. The primary cardiac cause of readmission in women was heart failure., Conclusion: Compared to men, women with STEMIs had lower rates of revascularization and higher rates of 30-day readmission. When revascularized, women were still more likely to be readmitted as compared to non-revascularized women., Competing Interests: Declaration of competing interest The authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Although abdominal aortic aneurysms (AAA) are more common in men, women with AAA have increased morbidity and mortality. Additionally, there are discrepancies among professional society guidelines for AAA screening in women. In this retrospective study from the Nationwide Inpatient Sample (NIS) database from 2003 to 2014, we compared rates of AAA repair (rupture and elective) and AAA-related mortality in men vs. women to identify predictors of death among men and women with AAA. We divided the population into 1) AAA rupture 2) elective AAA repair. The main outcomes included temporal trends in AAA rupture, rupture-related death, AAA repair, in-hospital death, and predictors of AAA-related death. There were 570,253 discharge records for AAA admissions between 2003 and 2014, including 22.8% women and 77.2% men. Women had a higher proportion of rupture (18.4% vs 12.6%, p <0.01). A smaller proportion of women underwent endovascular aortic repair (EVAR) compared with men in the ruptured AAA (13.9% vs. 20.3%, p <0.01) and elective repair (55.7% vs. 67.4%, p <0.01) cohorts. Within the ruptured cohort, a higher proportion of women did not receive repair (46.4% vs. 26.1%, p <0.01). On multivariable analysis, female gender was a significant predictor of death with rupture (OR 1.39, 95% CI 1.16 to 1.66) and elective repair (OR 1.74, 95% CI 1.36 to 2.22), with both elective EVAR (OR 2.52, 95% CI 2.06 to 3.09) and elective open aortic repair (OAR; OR 1.50, 95% CI 1.33 to 1.68). Propensity score matching confirmed a higher risk of death in women in both the rupture (OR 1.19, 95% CI 1.09 to 1.30) and elective repair (OR 1.50, 95% CI 1.35 to 1.67) cohorts. In conclusion, AAA poses significant morbidity and mortality, especially in women. Women were more likely to die before repair with AAA rupture and female gender was an independent predictor of mortality in both the rupture and elective repair groups., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The association between malignancy and readmission after Takotsubo syndrome (TTS) hospitalization has not been fully described. We sought to examine the rates, cause, and cost of 30-day readmissions of TTS, with or without malignancy, by utilizing Nationwide Readmissions Databases from 2010 to 2014. We identified 61,588 index hospitalizations for TTS. TTS patients with malignancy tended to be older (70.6 ± 0.2 vs. 66.1 ± 0.1, p < 0.001), and the overall burden of comorbidities was higher than in those without malignancy. TTS patients with malignancy had significantly higher 30-day readmission rates than those without malignancy (15.9% vs. 11.0%; odds ratio (OR), 1.35; 95% confidence interval (CI), 1.18-1.56). Non-cardiac causes were the most common causes of readmission for TTS patients with malignancy versus without malignancy (75.5% vs. 68.1%, p < 0.001). The 30-day readmission rate due to recurrent TTS was very low in both groups (0.4% and 0.5%; p = 0.47). The total costs were higher by 25% ( p < 0.001) in TTS patients with vs. without malignancy. In summary, among patients hospitalized with TTS, the presence of malignancy was associated with increased risk of 30-day readmission and increased costs. These findings highlight the importance of optimized management for TTS patients with malignancy.

As the workforce shrinks, the demand for automatic, labor-saving, anomaly detection technology that can perform maintenance on advanced equipment such as vehicles has been increasing. In a vehicular environment, noise in the cabin, which directly affects users, is considered an important factor in lowering the emotional satisfaction of the driver and/or passengers in the vehicles. In this study, we provide an efficient method that can collect acoustic data, measured using a large number of microphones, in order to detect abnormal operations inside the machine via deep learning in a quick and highly accurate manner. Unlike most current approaches based on Long Short-Term Memory (LSTM) or autoencoders, we propose an anomaly detection (AD) algorithm that can overcome the limitations of noisy measurement and detection system anomalies via noise signals measured inside the mechanical system. These features are utilized to train a variety of anomaly detection models for demonstration in noisy environments with five different errors in machine operation, achieving an accuracy of approximately 90% or more.

Background: There are limited data on the characteristics of 30-day readmission after hospitalization with coronavirus disease 2019 (COVID-19)., Objectives: To examine the rate, timing, causes, predictors and outcomes of 30-day readmission after COVID-19 hospitalization., Methods: From 13 March to 9 April 2020, all patients hospitalized with COVID-19 and discharged alive were included in this retrospective observational study. Multivariable logistic regression was used to identify the predictors of 30-day readmission, and a restricted cubic spline function was utilized to assess the linearity of the association between continuous predictors and 30-day readmission., Results: A total of 1062 patients were included in the analysis, with a median follow-up time of 62 days. The mean age of patients was 56.5 years, and 40.5% were women. At the end of the study, a total of 48 (4.5%) patients were readmitted within 30 days of discharge, and a median time to readmission was 5 days. The most common primary diagnosis of 30-day readmission was a hypoxic respiratory failure (68.8%) followed by thromboembolism (12.5%) and sepsis (6.3%). The patients with a peak serum creatinine level of ≥1.29 mg/dL during the index hospitalization, compared to those with a creatinine of <1.29 mg/dL, had 2.4 times increased risk of 30-day readmission (adjusted odds ratio: 2.41; 95% CI: 1.23-4.74). The mortality rate during the readmission was 22.9%., Conclusion: With 4.5% of the thirty-day readmission rate, COVID-19 survivors were readmitted early after hospital discharge, mainly due to morbidities of COVID-19. One in five readmitted COVID-19 survivors died during their readmission., (© 2021 The Association for the Publication of the Journal of Internal Medicine.)

Because major depressive disorder (MDD) and bipolar disorder (BD) manifest with similar symptoms, misdiagnosis is a persistent issue, necessitating their differentiation through objective methods. This study was aimed to differentiate between these disorders using a targeted proteomic approach. Multiple reaction monitoring-mass spectrometry (MRM-MS) analysis was performed to quantify protein targets regarding the two disorders in plasma samples of 270 individuals (90 MDD, 90 BD, and 90 healthy controls (HCs)). In the training set (72 MDD and 72 BD), a generalizable model comprising nine proteins was developed. The model was evaluated in the test set (18 MDD and 18 BD). The model demonstrated a good performance (area under the curve (AUC) >0.8) in discriminating MDD from BD in the training (AUC = 0.84) and test sets (AUC = 0.81) and in distinguishing MDD from BD without current hypomanic/manic/mixed symptoms (90 MDD and 75 BD) (AUC = 0.83). Subsequently, the model demonstrated excellent performance for drug-free MDD versus BD (11 MDD and 10 BD) (AUC = 0.96) and good performance for MDD versus HC (AUC = 0.87) and BD versus HC (AUC = 0.86). Furthermore, the nine proteins were associated with neuro, oxidative/nitrosative stress, and immunity/inflammation-related biological functions. This proof-of-concept study introduces a potential model for distinguishing between the two disorders.

Introduction: Poor sleep is a pervasive problem for hospitalized patients and can contribute to adverse health outcomes., Methods: We aimed to improve self-reported sleep for patients on a general medicine ward as measured by the Richards-Campbell Sleep Questionnaire (RCSQ) as well as the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) question addressing quietness at night. We utilized a non-pharmacologic sleep hygiene bundle composed of a short script with sleep hygiene prompts, such as whether patients would like the shades closed or the lights turned off, as well as a sleep package including an eye mask, earplugs, lavender scent pad, and non-caffeinated tea. Relaxing music was played at bedtime and signs promoting the importance of quietness at night were placed around the unit. Front-line champions were identified to aid with implementation., Results: A total of 931 patients received the intervention. In a sample of surveyed patients, we observed an increase in the RCSQ global score from 6.0 (IQR 3.0-7.0) to 6.2 (IQR 4.0-7.8) from the pre- to post- intervention periods (p = 0.041), as well as increases in three of the five individual survey components. Additionally, HCAHPS "quietness at night" score increased on the unit from 34.1% pre-intervention to 42.5% post-intervention., Conclusion: A nonpharmacologic sleep hygiene protocol paired with provider education and use of champions was associated with modest improvements in patients' perceived sleep and unit HCAHPS scores., (Copyright © 2021 The Joint Commission. Published by Elsevier Inc. All rights reserved.)

Background: Adverse local tissue reactions (ALTRs) in metal-on-polyethylene (MoP) total hip arthroplasty (THA) with head-neck taper corrosion are multifactorial, involving implant and patient factors. This study aimed to identify any potential clinical risk factors associated with failed MoP THA due to head-neck taper corrosion., Methods: A series of 146 MoP THA patients was investigated: (1) ALTR (n = 42) on metal artifact sequence MRI and (2) non-ALTR (n = 104). Both cohorts were compared regarding femoral neck shaft angle, acetabular implant orientation, component size, femoral head offset, measurement of medial and vertical femoral offsets, and femoral stem alloy., Results: The occurrence of ALTR was associated with increased radiographic femoral stem offset (36.0 ± 7.7 mm versus 40.8 ± 7.3 mm, P = 0.008), increased femoral head offset (0.7 ± 3.4 versus 4.5 ± 3.7, P < 0.001), and the use of Ti-12Mo-6Zr-2Fe alloy stems (P = 0.041). The presence of ALTR was notably associated with higher chromium (2.0 versus 0.5 μg/L) and cobalt (7.4 versus 0.7 μg/L, P < 0.001)., Discussion: This study identified increased femoral head and stem offset and the use of Ti-12Mo-6Zr-2Fe alloy stems as risk factors for clinically relevant ALTR due to head-neck taper corrosion in MoP THA patients. This provides evidenced-based practical information for surgeons in identifying "at-risk" symptomatic MoP THA patients with head-neck taper corrosion for systematic risk stratification., (Copyright © 2020 by the American Academy of Orthopaedic Surgeons.)

Purpose: To develop and validate a protein-based, multi-marker panel that provides superior pancreatic ductal adenocarcinoma (PDAC) detection abilities with sufficient diagnostic performance., Experimental Design: A total of 959 plasma samples from patients at multiple medical centers were used. To construct an optimal, diagnostic, multi-marker panel, we applied data preprocessing procedure to biomarker candidates. The multi-marker panel was developed using a training set comprised of 261 PDAC cases and 290 controls. Subsequent evaluations were performed in a validation set comprised of 65 PDAC cases and 72 controls. Further validation was performed in an independent set comprised of 75 PDAC cases and 47 controls., Results: A multi-marker panel containing 14 proteins was developed. The multi-marker panel achieved AUCs of 0.977 and 0.953 for the training set and validation set, respectively. In an independent validation set, the multi-marker panel yielded an AUC of 0.928. The diagnostic performance of the multi-marker panel showed significant improvements compared with carbohydrate antigen (CA) 19-9 alone (training set AUC = 0.977 vs. 0.872, P < 0.001; validation set AUC = 0.953 vs. 0.832, P < 0.01; independent validation set AUC = 0.928 vs. 0.771, P < 0.001). When the multi-marker panel and CA 19-9 were combined, the diagnostic performance of the combined panel was improved for all sets., Conclusions: This multi-marker panel and the combined panel showed statistically significant improvements in diagnostic performance compared with CA 19-9 alone and has the potential to complement CA 19-9 as a diagnostic marker in clinical practice., (©2021 American Association for Cancer Research.)

Background: Pseudo-Wellens syndrome is a rare entity characterized by the presence of electrocardiogram (ECG) changes of Wellens syndrome but without the stenosis of the left anterior descending (LAD) coronary artery. In previous reports, pseudo-Wellens syndrome most commonly resulted from recreational drug use or unidentified etiologies. We present a unique case of pseudo-Wellens syndrome due to sepsis-induced cardiomyopathy and a review of the literature., Case Presentation: A 62-year-old Caucasian woman was admitted for sepsis from left foot cellulitis. Laboratory data were notable for elevated lactate of 2.5 mmol/L and evidence of acute kidney injury. She developed chest pain on the third day of hospitalization. ECG showed symmetric T-wave inversion in leads V1-V4. Serial troponin I levels were within normal limits. Chest imaging showed no pulmonary embolism. Echocardiogram showed ejection fraction of 25%, left ventricular diastolic diameter of 4.6 cm, and multiple segmental wall motion abnormalities. Cardiac catheterization showed patent coronary arteries. The hospital course was complicated by transient sinus bradycardia and hypotension. She was hospitalized for a total of 17 days. ECG prior to discharge showed resolution of T-wave changes., Conclusion: Pseudo-Wellens syndrome may result from myocardial ischemia due to vasospasm or myocardial edema from external insults. In our case, we suspect sepsis-related cytokine production resulting in cardiomyopathy and pseudo-Wellens syndrome. The clinical manifestations were indistinguishable between Wellens and pseudo-Wellens syndrome. Physicians should include the diagnosis of pseudo-Wellens syndrome when considering the presence of LAD coronary artery occlusion given risk stratifications.

Background The independent prognostic value of troponin and other biomarker elevation among patients with coronavirus disease 2019 (COVID-19) are unclear. We sought to characterize biomarker levels in patients hospitalized with COVID-19 and develop and validate a mortality risk score. Methods and Results An observational cohort study of 1053 patients with COVID-19 was conducted. Patients with all of the following biomarkers measured-troponin-I, B-type natriuretic peptide, C-reactive protein, ferritin, and d-dimer (n=446) -were identified. Maximum levels for each biomarker were recorded. The primary end point was 30-day in-hospital mortality. Multivariable logistic regression was used to construct a mortality risk score. Validation of the risk score was performed using an independent patient cohort (n=440). Mean age of patients was 65.0±15.2 years and 65.3% were men. Overall, 444 (99.6%) had elevation of any biomarker. Among tested biomarkers, troponin-I ≥0.34 ng/mL was the only independent predictor of 30-day mortality (adjusted odds ratio, 4.38; P <0.001). Patients with a mortality score using hypoxia on presentation, age, and troponin-I elevation, age (HA 2 T 2 ) ≥3 had a 30-day mortality of 43.7% while those with a score <3 had mortality of 5.9%. Area under the receiver operating characteristic curve of the HA 2 T 2 score was 0.834 for the derivation cohort and 0.784 for the validation cohort. Conclusions Elevated troponin and other biomarker levels are commonly seen in patients hospitalized with COVID-19. High troponin levels are a potent predictor of 30-day in-hospital mortality. A simple risk score can stratify patients at risk for COVID-19-associated mortality.

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Background: The accurate diagnosis of periprosthetic joint infection (PJI) in the setting of adverse local tissue reactions in patients with metal-on-polyethylene (MoP) total hip arthroplasty (THA) secondary to head-neck taper junction corrosion is challenging as it frequently has the appearance of purulence. The aim of this study is to evaluate the utility of erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and synovial fluid markers in diagnosing PJI in failed MoP THA due to head-neck taper corrosion., Methods: A total of 89 consecutive patients with MoP THA with head-neck taper corrosion in 2 groups was evaluated: (1) infection group (n = 11) and (2) noninfection group (n = 78). All patients had highly crossed polyethylene with cobalt chromium femoral heads and had preoperative synovial fluid aspiration. In addition, serum cobalt and chromium levels were analyzed., Results: The optimal cutoff value for synovial white blood cell was 2144 with 93% sensitivity and 84% specificity. Neutrophil count optimal cutoff value was 82% with 93% sensitivity and 82% specificity. Receiver operating characteristic analysis of ESR and CRP determined optimal cutoff at 57 mm/h and 35 mg/L with 57% sensitivity and 94% specificity and 93% sensitivity and 76% specificity, respectively. There were no significant differences in metal ion levels between the infected and noninfected groups., Conclusion: The results of this study suggest that ESR and CRP are useful in excluding PJI, whereas both synovial white blood cell count and neutrophil percentage in hip aspirate are useful markers for diagnosing infection in MoP THA patients with head-neck taper corrosion associated adverse local tissue reaction., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Adverse local tissue reaction (ALTR) associated with mechanically assisted crevice corrosion of metal-on-polyethylene (MoP) head-neck modular total hip arthroplasty (THA), similarly observed in the metal-on-metal bearing, is a growing concern in MoP THA patients. Given the complex pathogenesis as well as variable clinical presentation, the diagnosis can be challenging. This article focuses on providing surgeons with an evidence-based update on (1) implant, surgical, and patient risk factors associated with ALTRs; (2) clinical systematic evaluation; and (3) surgical management options for ALTRs in MoP THA patients based on the currently available evidence.