Dissecting Mismatch Negativity: Early and Late Subcomponents for Detecting Deviants in Local and Global Sequence Regularities.

Mismatch negativity (MMN) is commonly recognized as a neural signal of prediction error evoked by deviants from the expected patterns of sensory input. Studies show that MMN diminishes when sequence patterns become more predictable over a longer timescale. This implies that MMN is composed of multiple subcomponents, each responding to different levels of temporal regularities. To probe the hypothesized subcomponents in MMN, we record human electroencephalography during an auditory local-global oddball paradigm where the tone-to-tone transition probability (local regularity) and the overall sequence probability (global regularity) are manipulated to control temporal predictabilities at two hierarchical levels. We find that the size of MMN is correlated with both probabilities and the spatiotemporal structure of MMN can be decomposed into two distinct subcomponents. Both subcomponents appear as negative waveforms, with one peaking early in the central-frontal area and the other late in a more frontal area. With a quantitative predictive coding model, we map the early and late subcomponents to the prediction errors that are tied to local and global regularities, respectively. Our study highlights the hierarchical complexity of MMN and offers an experimental and analytical platform for developing a multitiered neural marker applicable in clinical settings.

Obesity, Inflammation, and Clinical Outcomes in COVID-19: A Multicenter Prospective Cohort Study.

CONTEXT: Obesity is a risk factor for coronavirus disease 2019 (COVID-19)-related outcomes; however, the mechanism remains unclear. OBJECTIVE: The objective of this analysis was to determine whether inflammation mediates the association between obesity and COVID-19 outcomes. DESIGN: The International Study of Inflammation in Covid-19 (ISIC): A Prospective Multi-Center Observational Study Examining the Role of Biomarkers of Inflammation in Predicting Covid-19 Related Outcomes in Hospitalized Patients. SETTING: Ten hospitals in the United States and Europe. PARTICIPANTS: Adults hospitalized specifically for COVID-19 between February 1, 2020, through October 19, 2022. MAIN OUTCOME MEASURES: Inflammatory biomarkers, including soluble urokinase plasminogen activator receptor (suPAR), were measured at admission. Associations were examined between body-mass index (BMI, kg/m2) and a composite of death, need for mechanical ventilation, and renal replacement therapy, stratified by pre- and post-Omicron variants. The contribution of inflammation to the relationship between obesity and outcomes was assessed. RESULTS: Among 4644 participants (mean age 59.3, 45.6% male, 21.8% BMI≥35), those with BMI>40 (n=485) had 55% higher odds of the composite outcome (95% CI[1.21 to 1.98]) compared to non-obese individuals (BMI<30, n=2358) in multivariable analysis. In multiple mediation analysis, only suPAR remained a significant mediator between BMI and composite outcome. Associations were amplified for participants younger than 65 years and with pre-Omicron variants. CONCLUSION: Obesity is associated with worse outcomes in COVID-19, notably in younger participants and in the pre-Omicron era. Inflammation, as measured by suPAR, is a significant mediator of the association between obesity and COVID-19 outcomes.

Feasibility and Performance of Continuous Glucose Monitoring to Guide Computerized Insulin Infusion Therapy in Cardiovascular Intensive Care Unit.

BACKGROUND: We evaluated the feasibility of real-time continuous glucose monitoring (CGM) for titrating continuous intravenous insulin infusion (CII) to manage hyperglycemia in postoperative individuals in the cardiovascular intensive care unit and assessed their accuracy, nursing acceptance, and postoperative individual satisfaction. METHODS: Dexcom G6 CGM devices were applied to 59 postsurgical patients with hyperglycemia receiving CII. A hybrid approach combining CGM with periodic point-of-care blood glucose (POC-BG) tests with two phases (initial-ongoing) of validation was used to determine CGM accuracy. Mean and median absolute relative differences and Clarke Error Grid were plotted to evaluate the CGM accuracy. Surveys of nurses and patients on the use of CGMs experience were conducted and results were analyzed. RESULTS: In this cohort (mean age 64, 32% female, 32% with diabetes) with 864 paired POC-BG and CGM values analyzed, mean and median absolute relative difference between POC-BG and CGM values were 13.2% and 9.8%, respectively. 99.7% of paired CGM and POC-BG were in Zones A and B of the Clarke Error Grid. Responses from nurses reported CGMs being very or quite convenient (n = 28; 93%) and it was favored over POC-BG testing (n = 28; 93%). Majority of patients (n = 42; 93%) reported their care process using CGM as being good or very good. CONCLUSION: This pilot study demonstrates the feasibility, accuracy, and nursing convenience of adopting CGM via a hybrid approach for insulin titration in postoperative settings. These findings provide robust rationale for larger confirmatory studies to evaluate the benefit of CGM in postoperative care to improve workflow, enhance health outcomes, and cost-effectiveness.

Intubation Decision Based on Illness Severity and Mortality in COVID-19: An International Study.

OBJECTIVES: To evaluate the impact of intubation timing, guided by severity criteria, on mortality in critically ill COVID-19 patients, amidst existing uncertainties regarding optimal intubation practices. DESIGN: Prospective, multicenter, observational study conducted from February 1, 2020, to November 1, 2022. SETTING: Ten academic institutions in the United States and Europe. PATIENTS: Adults (≥ 18 yr old) confirmed with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and hospitalized specifically for COVID-19, requiring intubation postadmission. Exclusion criteria included patients hospitalized for non-COVID-19 reasons despite a positive SARS-CoV-2 test. INTERVENTIONS: Early invasive mechanical ventilation (EIMV) was defined as intubation in patients with less severe organ dysfunction (Sequential Organ Failure Assessment [SOFA] < 7 or Pa o2 /F io2 ratio > 250), whereas late invasive mechanical ventilation (LIMV) was defined as intubation in patients with SOFA greater than or equal to 7 and Pa o2 /F io2 ratio less than or equal to 250. MEASUREMENTS AND MAIN RESULTS: The primary outcome was mortality within 30 days of hospital admission. Among 4464 patients, 854 (19.1%) required mechanical ventilation (mean age 60 yr, 61.7% male, 19.3% Black). Of those, 621 (72.7%) were categorized in the EIMV group and 233 (27.3%) in the LIMV group. Death within 30 days after admission occurred in 278 patients (42.2%) in the EIMV and 88 patients (46.6%) in the LIMV group ( p = 0.28). An inverse probability-of-treatment weighting analysis revealed a statistically significant association with mortality, with patients in the EIMV group being 32% less likely to die either within 30 days of admission (adjusted hazard ratio [HR] 0.68; 95% CI, 0.52-0.90; p = 0.008) or within 30 days after intubation irrespective of its timing from admission (adjusted HR 0.70; 95% CI, 0.51-0.90; p = 0.006). CONCLUSIONS: In severe COVID-19 cases, an early intubation strategy, guided by specific severity criteria, is associated with a reduced risk of death. These findings underscore the importance of timely intervention based on objective severity assessments.

SuPAR, biomarkers of inflammation, and severe outcomes in patients hospitalized for COVID-19: The International Study of Inflammation in COVID-19.

Severe coronavirus disease 2019 (COVID-19) is a hyperinflammatory syndrome. The biomarkers of inflammation best suited to triage patients with COVID-19 are unknown. We conducted a prospective multicenter observational study of adult patients hospitalized specifically for COVID-19 from February 1, 2020 to October 19, 2022. Biomarkers measured included soluble urokinase plasminogen activator receptor (suPAR), C-reactive protein, interleukin-6, procalcitonin, ferritin, and D-dimer. In-hospital outcomes examined include death and the need for mechanical ventilation. Patients admitted in the United States (US, n = 1962) were used to compute area under the curves (AUCs) and identify biomarker cutoffs. The combined European cohorts (n = 1137) were used to validate the biomarker cutoffs. In the US cohort, 356 patients met the composite outcome of death (n = 197) or need for mechanical ventilation (n = 290). SuPAR was the most important predictor of the composite outcome and had the highest AUC (0.712) followed by CRP (0.642), ferritin (0.619), IL-6 (0.614), D-dimer (0.606), and lastly procalcitonin (0.596). Inclusion of other biomarkers did not improve discrimination. A suPAR cutoff of 4.0 ng/mL demonstrated a sensitivity of 95.4% (95% CI: 92.4%-98.0%) and negative predictive value (NPV) of 92.5% (95% CI: 87.5%-96.9%) for the composite outcome. Patients with suPAR < 4.0 ng/mL comprised 10.6% of the cohort and had a 0.8% probability of the composite outcome. Applying this cutoff to the validation cohort yielded a sensitivity of 93.8% (90.4%-96.7%) and NPV of 95.5% (93.1%-97.8%) for the composite outcome. Among commonly measured biomarkers, suPAR offered stronger discriminatory ability and may be useful in triaging low-risk patients with COVID-19.

Residential Address Amplifies Health Disparities and Risk of Infection in Individuals With Diabetic Foot Ulcers.

OBJECTIVE: To determine the association between social determinants of health (SDOH) and a diagnosis of diabetic foot ulcer (DFU) infection. RESEARCH DESIGN AND METHODS: Targeted interrogation of electronic health record data using novel search engines to analyze individuals with a DFU infection during a 5-year period (2013-2017) was performed. We extracted geolocated neighborhood data and SDOH characteristics from the National Neighborhood Data Archive and used univariate and multiple logistic regression to evaluate associations with outcomes in the population with diabetes. RESULTS: Among 4.3 million people overall and 144,564 individuals with diabetes seen between 2013 and 2017, 8,351 developed DFU, of which cases 2,252 were complicated by a DFU infection. Sex interactions occurred, as men who experienced a DFU infection more frequently identified as having nonmarried status than their female counterparts. For the population with DFU infection, there were higher rates for other SDOH, including higher neighborhood disadvantaged index score, poverty, nonmarriage, and less access to physician/allied health professionals (all P < 0.01). In multiple logistic regression, those individuals who developed DFU infection came from neighborhoods with greater Hispanic and/or foreign-born concentrations (odds ratio 1.11, P = 0.015). CONCLUSIONS: We found significant differences in neighborhood characteristics driving a higher risk for DFU infection in comparisons with the grouping of individuals with diabetes overall, including increased risk for individuals with Hispanic and/or foreign-born immigration status. These data strongly support the need to incorporate SDOH, particularly ethnic and immigration status, into triage algorithms for DFU risk stratification to prevent severe diabetic foot complications and move beyond biologic-only determinants of health.

Cardiovascular Risk Stratification of Patients Undergoing Hematopoietic Stem Cell Transplantation: The CARE-BMT Risk Score.

BACKGROUND: Evidence guiding the pre-hematopoietic stem cell transplantation (HSCT) cardiovascular evaluation is limited. We sought to derive and validate a pre-HSCT score for the cardiovascular risk stratification of HSCT candidates. METHODS AND RESULTS: We leveraged the CARE-BMT (Cardiovascular Registry in Bone Marrow Transplantation) study, a contemporary multicenter observational study of adult patients who underwent autologous or allogeneic HSCT between 2008 and 2019 (N=2435; mean age at transplant of 55 years; 4.9% Black). We identified the subset of variables most predictive of post-HSCT cardiovascular events, defined as a composite of cardiovascular death, myocardial infarction, heart failure, stroke, atrial fibrillation or flutter, and sustained ventricular tachycardia. We then developed a point-based risk score using the hazard ratios obtained from Cox proportional hazards modeling. The score was externally validated in a separate cohort of 919 HSCT recipients (mean age at transplant 54 years; 20.4% Black). The risk score included age, transplant type, race, coronary artery disease, heart failure, peripheral artery disease, creatinine, triglycerides, and prior anthracycline dose. Risk scores were grouped as low-, intermediate-, and high-risk, with the 5-year cumulative incidence of cardiovascular events being 4.0%, 10.3%, and 22.4%, respectively. The area under the receiver operating curves for predicting cardiovascular events at 100 days, 5 and 10 years post-HSCT were 0.65 (95% CI, 0.59-0.70), 0.73 (95% CI, 0.69-0.76), and 0.76 (95% CI, 0.69-0.81), respectively. The model performed equally well in autologous and allogeneic recipients, as well as in the validation cohort. CONCLUSIONS: The CARE-BMT risk score is easy to calculate and could help guide referrals of high-risk HSCT recipients to cardiovascular specialists before transplant and guide long-term monitoring.

Current understanding of the contribution of lactate to the cardiovascular system and its therapeutic relevance.

Research during the past decades has yielded numerous insights into the presence and function of lactate in the body. Lactate is primarily produced via glycolysis and plays special roles in the regulation of tissues and organs, particularly in the cardiovascular system. In addition to being a net consumer of lactate, the heart is also the organ in the body with the greatest lactate consumption. Furthermore, lactate maintains cardiovascular homeostasis through energy supply and signal regulation under physiological conditions. Lactate also affects the occurrence, development, and prognosis of various cardiovascular diseases. We will highlight how lactate regulates the cardiovascular system under physiological and pathological conditions based on evidence from recent studies. We aim to provide a better understanding of the relationship between lactate and cardiovascular health and provide new ideas for preventing and treating cardiovascular diseases. Additionally, we will summarize current developments in treatments targeting lactate metabolism, transport, and signaling, including their role in cardiovascular diseases.

Magnetic Properties and Microstructure of FePt(BN, X, C) (X = Ag, Re) Films.

A sputtered FePt(BN, Re, C) film, here boron nitride (BN), was compared to a reference sample FePt(BN, Ag, C). Intrinsically, these films illustrate a high anisotropy field (Hk) and perpendicular magnetocrystalline anisotropy (Ku),although the reference sample shows a higher value (Hk = 69.5 kOe, Ku = 1.74 × 107 erg/cm3) than the FePt(BN, Re, C) film (Hk = 66.9 kOe, Ku = 1.46 × 107 erg/cm3). However, the small difference in the anisotropy constant (K2/K1) ratio presents a close tendency in the angular dependence of the switching field. Extrinsically, the out-of-plane coercivity for the reference sample is 32 kOe, which is also higher than the FePt(BN, Re, C) film (Hc = 27 kOe), and both films present lower remanence (Mr(parallel)/Mr(perpendicular) = 0.08~0.12), that is, the index for perpendicular magnetic anisotropy. The higher perpendicular magnetization for both films was due to highly (001) textured FePt films, which was also evidenced by the tight rocking width of 4.1°/3.0° for (001)/(002) X-ray diffraction peaks, respectively, and high-enough ordering degree. The reference sample was measured to have a higher ordering degree (S = 0.84) than FePt(BN, Re, C) (S = 0.63). As a result, the Ag segregant shows stronger ability to promote the ordering of the FePt film; however, the FePt(BN, Re, C) film still has comparable magnetic properties without Ag doping. From the surface and elemental composition analysis, the metallic Re atoms found in the FePt lattice result in a strong spin-orbital coupling between transition metal Fe (3d electron) and heavy metals (Re, Pt) (5d electron) and we conducted high magnetocrystalline anisotropy (Ku). Above is the explanation that the lower-ordered FePt(BN, Re, C) film still has high-enough Ku and out-of-plane Hc. Regarding the microstructure, both the reference sample and FePt(BN, Re, C) show granular structure and columnar grains, and the respective average grain size and distributions are 6.60 nm (12.5%) and 11.2 nm (15.9%). The average widths of the grain boundaries and the aspect ratio of the columnar grain height are 2.05 nm, 1.00 nm, 2.35 nm, and 1.70 nm, respectively.

Evolution of Care and Outcomes Across Surges in Hospitalized Patients with Coronavirus Disease 2019.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has unfolded in distinct surges. Understanding how surges differ may reveal important insights into the evolution of the pandemic and improve patient care. METHODS: We leveraged the Michigan Medicine COVID-19 Cohort, a prospective observational study at an academic tertiary medical center that systematically enrolled 2309 consecutive patients hospitalized for COVID-19, comprising 5 distinct surges. RESULTS: As the pandemic evolved, patients hospitalized for COVID-19 tended to have a lower burden of comorbidities and a lower inflammatory burden as measured by admission levels of C-reactive protein, ferritin, lactate dehydrogenase, and D-dimer. Use of hydroxychloroquine and azithromycin decreased substantially after Surge 1, while use of corticosteroids and remdesivir markedly increased (P < .001 for all). In-hospital mortality significantly decreased from 18.3% in Surge 1 to 5.3% in Surge 5 (P < .001). The need for mechanical ventilation significantly decreased from 42.5% in Surge 1 to 7.0% in Surge 5 (P < .001), while the need for renal replacement therapy decreased from 14.4% in Surge 1 to 2.3% in Surge 5 (P < .001). Differences in patient characteristics, treatments, and inflammatory markers accounted only partially for the differences in outcomes between surges. CONCLUSIONS: The COVID-19 pandemic has evolved significantly with respect to hospitalized patient populations and therapeutic approaches, and clinical outcomes have substantially improved. Hospitalization after the first surge was independently associated with improved outcomes, even after controlling for relevant clinical covariates.

Case Report: Transcatheter closure of a giant post-traumatic femoral arteriovenous fistula using ventricular septal occluder.

Giant femoral arteriovenous fistulas are comparatively uncommon, typically treated through covered stents, coil embolization, and open surgical repair. Nevertheless, these options may not be appropriate for all patients. Herein, we describe a case of traumatic femoral arteriovenous fistulas that led to drastic dilatation of the femoral arteriovenous system and considerable heart failure symptoms due to prolonged lack of treatment. Given the intricate anatomical location of the fistula and the patient's severe cardiac dysfunction, surgical repair is often unfeasible. Consequently, we adopted an innovative approach in this case, utilizing a ventricular septal occluder device for fistula closure. This constitutes the first report of an arteriovenous fistula transcatheter closure with a septal occluder.

Relationship Between Preexisting Cardiovascular Disease and Death and Cardiovascular Outcomes in Critically Ill Patients With COVID-19.

BACKGROUND: Preexisting cardiovascular disease (CVD) is perceived as a risk factor for poor outcomes in patients with COVID-19. We sought to determine whether CVD is associated with in-hospital death and cardiovascular events in critically ill patients with COVID-19. METHODS: This study used data from a multicenter cohort of adults with laboratory-confirmed COVID-19 admitted to intensive care units at 68 centers across the United States from March 1 to July 1, 2020. The primary exposure was CVD, defined as preexisting coronary artery disease, congestive heart failure, or atrial fibrillation/flutter. Myocardial injury on intensive care unit admission defined as a troponin I or T level above the 99th percentile upper reference limit of normal was a secondary exposure. The primary outcome was 28-day in-hospital mortality. Secondary outcomes included cardiovascular events (cardiac arrest, new-onset arrhythmias, new-onset heart failure, myocarditis, pericarditis, or stroke) within 14 days. RESULTS: Among 5133 patients (3231 male [62.9%]; mean age 61 years [SD, 15]), 1174 (22.9%) had preexisting CVD. A total of 1178 (34.6%) died, and 920 (17.9%) had a cardiovascular event. After adjusting for age, sex, race, body mass index, history of smoking, and comorbidities, preexisting CVD was associated with a 1.15 (95% CI, 0.98-1.34) higher odds of death. No independent association was observed between preexisting CVD and cardiovascular events. Myocardial injury on intensive care unit admission was associated with higher odds of death (adjusted odds ratio, 1.93 [95% CI, 1.61-2.31]) and cardiovascular events (adjusted odds ratio, 1.82 [95% CI, 1.47-2.24]), regardless of the presence of CVD. CONCLUSIONS: CVD risk factors, rather than CVD itself, were the major contributors to outcomes in critically ill patients with COVID-19. The occurrence of myocardial injury, regardless of CVD, and its association with outcomes suggests it is likely due to multiorgan injury related to acute inflammation rather than exacerbation of preexisting CVD. REGISTRATION: NCT04343898; https://clinicaltrials.gov/ct2/show/NCT04343898.

A quantitative model reveals a frequency ordering of prediction and prediction-error signals in the human brain.

The human brain is proposed to harbor a hierarchical predictive coding neuronal network underlying perception, cognition, and action. In support of this theory, feedforward signals for prediction error have been reported. However, the identification of feedback prediction signals has been elusive due to their causal entanglement with prediction-error signals. Here, we use a quantitative model to decompose these signals in electroencephalography during an auditory task, and identify their spatio-spectral-temporal signatures across two functional hierarchies. Two prediction signals are identified in the period prior to the sensory input: a low-level signal representing the tone-to-tone transition in the high beta frequency band, and a high-level signal for the multi-tone sequence structure in the low beta band. Subsequently, prediction-error signals dependent on the prior predictions are found in the gamma band. Our findings reveal a frequency ordering of prediction signals and their hierarchical interactions with prediction-error signals supporting predictive coding theory.

New Insights into TETs in Psychiatric Disorders.

Psychiatric disorders are complex and heterogeneous disorders arising from the interaction of multiple factors based on neurobiology, genetics, culture, and life experience. Increasing evidence indicates that sustained abnormalities are maintained by epigenetic modifications in specific brain regions. Over the past decade, the critical, non-redundant roles of the ten-eleven translocation (TET) family of dioxygenase enzymes have been identified in the brain during developmental and postnatal stages. Specifically, TET-mediated active demethylation, involving the iterative oxidation of 5-methylcytosine to 5-hydroxymethylcytosine and subsequent oxidative derivatives, is dynamically regulated in response to environmental stimuli such as neuronal activity, learning and memory processes, and stressor exposure. Here, we review the progress of studies designed to provide a better understanding of how profiles of TET proteins and 5hmC are powerful mechanisms by which to explain neuronal plasticity and long-term behaviors, and impact transcriptional programs operative in the brain that contribute to psychiatric disorders.

Clinical characteristics of severe aortic stenosis patients combined with diabetes mellitus after transcatheter aortic valve replacement and short-term outcome. / ç»å¯¼ç®¡ä¸»åŠ¨è„‰ç“£ç½®æ¢æœ¯åŽé‡åº¦ä¸»åŠ¨è„‰ç“£ç‹­çª„æ‚£è€ åˆå¹¶ç³–å°¿ç— çš„ä¸´åºŠç‰¹å¾åŠå ¶çŸ­æœŸé¢„åŽ.

OBJECTIVES: Type 2 diabetes (T2DM) is a common comorbidity in patients with degenerative aortic stenosis (AS).As a key item of the American Society of Thoracic Surgeons (STS) score, it has a vital impact on the clinical prognosis of traditional thoracic surgery. T2DM has an adverse effect on the morbidity and mortality of cardiovascular diseases. At the same time, studies have shown that T2DM are associated with myocardial hypertrophy and remodeling, decreased left ventricular function, and worsening heart failure symptoms in the AS patients. Transcatheter aortic valve replacement (TAVR) as an interventional method to replace the aortic valve has better safety for middle and high risk patients in surgery, but the impact of T2DM on the clinical outcome of TAVR in AS patients is not clear.By analyzing the clinical and image characteristics of patients with AS and T2DM who received TAVR treatment, so as to explore the effect of T2DM on the perioperative complications and prognosis of TAVR. METHODS: A total of 100 consecutive patients with severe AS, who underwent TAVR treatment and were followed up for more than 1 month, were selectedin the Second Xiangya Hospital of Central South University from January 2016 to December 2020.Among them, 5 patients who were treated with TAVR due to simple severe aortic regurgitation were not included, therefore a total of 95 patients with severe aortic stenosis were enrolled in this study.The age of the patients was (72.7±4.8) years old, and there were 58 males (61.1%), and the patients with moderate or above aortic regurgitation had 30 cases (31.6%). The patients were divided into a diabetic group and a non-diabetic group according to whether they were combined with T2DM.There was no statistical difference in age, gender, body mass index (BMI), STS score, and New York Heart Association (NYHA) cardiac function classification between the 2 groups (all P>0.05). The primary end point was defined as a composite event consisting of all-cause death and stroke one month after surgery, and the secondary end point was defined as TAVR-related complications immediately after surgery and one month after surgery.The preoperative clinical data, cardiac ultrasound data, CT data, postoperative medication and the incidence of each endpoint event were compared between the 2 groups.The predictive model of adverse events was constructed by single factor and multivariate logistic regression. RESULTS: Compared with the non-diabetic group, the diabetic group had high blood pressure and chronic renal insufficiency.There was no significant difference in preoperative ultrasound echocardiography between the 2 groups. Preoperative CT evaluation found that the anatomical structure of the aortic root in the diabetic group was smaller than that in the non-diabetic group, and there was no significant difference in the incidence of bicuspid aortic valve between the 2 groups (all P<0.05). In terms of postoperative medication, the use of statins in the diabetes group was significantly higher than that in the non-diabetic group. In the diabetes group, 6 patients (37.5%) received insulin therapy, and 9 patients (56.3%) received oral medication alone.Univariate logistic regression analysis showed that the all-cause death and stroke compound events was increased in the diabetes group in 30 days after TAVR (OR=6.86; 95% CI: 2.14 to 21.79; P<0.01). Heart disease (OR=2.80; 95% CI: 0.99 to 7.88; P<0.05) and chronic renal insufficiency (OR=3.75; 95% CI: 1.24 to 11.34; P<0.05) were also risk factors for all-cause death and stroke compound events.In a multivariate analysis, after adjusting for age, gender, BMI, comorbidities, N-terminal pro-B type natriuretic peptide (NT-proBNP), total calcification score, ejection fraction, and degree of aortic regurgitation, T2DM was still a risk factor for all-cause death and stroke compound events in 30 days after TAVR (OR=12.68; 95% CI: 1.76 to 91.41; P<0.05). CONCLUSIONS: T2DM is a risk factor for short-term poor prognosis in patients with symptomatic severe AS after TAVR treatment. T2DM should play an important role in the future construction of the TAVR surgical risk assessment system, but the conclusions still need to be further verified by long-term follow-up of large-scale clinical studies.

Inflammation, Hyperglycemia, and Adverse Outcomes in Individuals With Diabetes Mellitus Hospitalized for COVID-19.

OBJECTIVE: Diabetes mellitus (DM) is a major risk factor for severe coronavirus disease 2019 (COVID-19) for reasons that are unclear. RESEARCH DESIGN AND METHODS: We leveraged the International Study of Inflammation in COVID-19 (ISIC), a multicenter observational study of 2,044 patients hospitalized with COVID-19, to characterize the impact of DM on in-hospital outcomes and assess the contribution of inflammation and hyperglycemia to the risk attributed to DM. We measured biomarkers of inflammation collected at hospital admission and collected glucose levels and insulin data throughout hospitalization. The primary outcome was the composite of in-hospital death, need for mechanical ventilation, and need for renal replacement therapy. RESULTS: Among participants (mean age 60 years, 58.2% males), those with DM (n = 686, 33.5%) had a significantly higher cumulative incidence of the primary outcome (37.8% vs. 28.6%) and higher levels of inflammatory biomarkers than those without DM. Among biomarkers, DM was only associated with higher soluble urokinase plasminogen activator receptor (suPAR) levels in multivariable analysis. Adjusting for suPAR levels abrogated the association between DM and the primary outcome (adjusted odds ratio 1.23 [95% CI 0.78, 1.37]). In mediation analysis, we estimated the proportion of the effect of DM on the primary outcome mediated by suPAR at 84.2%. Hyperglycemia and higher insulin doses were independent predictors of the primary outcome, with effect sizes unaffected by adjusting for suPAR levels. CONCLUSIONS: Our findings suggest that the association between DM and outcomes in COVID-19 is largely mediated by hyperinflammation as assessed by suPAR levels, while the impact of hyperglycemia is independent of inflammation.

Quantitative Image Analysis as an Adjunct to Manual Scoring of ER, PgR, and HER2 in Invasive Breast Carcinoma.

OBJECTIVES: Biomarker expression evaluation for estrogen receptor (ER), progesterone receptor (PgR), and human epidermal growth factor receptor 2 (HER2) is an essential prognostic and predictive parameter for breast cancer and critical for guiding hormonal and neoadjuvant therapy. This study compared quantitative image analysis (QIA) with pathologists' scoring for ER, PgR, and HER2. METHODS: A retrospective analysis was undertaken of 1,367 invasive breast carcinomas, including all histopathology subtypes, for which ER, PgR, and HER2 were analyzed by manual scoring and QIA. The resulting scores were compared, and in a subset of HER2 cases (n = 373, 26%), scores were correlated with available fluorescence in situ hybridization (FISH) results. RESULTS: Concordance between QIA and manual scores for ER, PgR, and HER2 was 93%, 96%, and 90%, respectively. Discordant cases had low positive scores (1%-10%) for ER (n = 33), were due to nonrepresentative region selection (eg, ductal carcinoma in situ) or tumor heterogeneity for PgR (n = 43), and were of one-step difference (negative to equivocal, equivocal to positive, or vice versa) for HER2 (n = 90). Among HER2 cases where FISH results were available, only four (1.0%) showed discordant QIA and FISH results. CONCLUSIONS: QIA is a computer-aided diagnostic support tool for pathologists. It significantly improves ER, PgR, and HER2 scoring standardization. QIA demonstrated excellent concordance with pathologists' scores. To avoid pitfalls, pathologist oversight of representative region selection is recommended.

Angiotensin-Converting Enzyme Inhibitors, Angiotensin II Receptor Blockers, and Outcomes in Patients Hospitalized for COVID-19.

Background Use of angiotensin-converting enzyme inhibitors and angiotensin receptor blockers (ACEi/ARB) is thought to affect COVID-19 through modulating levels of angiotensin-converting enzyme 2, the cell entry receptor for SARS-CoV2. We sought to assess the association between ACEi/ARB, biomarkers of inflammation, and outcomes in patients hospitalized for COVID-19. Methods and Results We leveraged the ISIC (International Study of Inflammation in COVID-19), identified patients admitted for symptomatic COVID-19 between February 1, 2020 and June 1, 2021 for COVID-19, and examined the association between in-hospital ACEi/ARB use and all-cause death, need for ventilation, and need for dialysis. We estimated the causal effect of ACEi/ARB on the composite outcomes using marginal structural models accounting for serial blood pressure and serum creatinine measures. Of 2044 patients in ISIC, 1686 patients met inclusion criteria, of whom 398 (23.6%) patients who were previously on ACEi/ARB received at least 1 dose during their hospitalization for COVID-19. There were 215 deaths, 407 patients requiring mechanical ventilation, and 124 patients who required dialysis during their hospitalization. Prior ACEi/ARB use was associated with lower levels of soluble urokinase plasminogen activator receptor and C-reactive protein. In multivariable analysis, in-hospital ACEi/ARB use was associated with a lower risk of the composite outcome of in-hospital death, mechanical ventilation, or dialysis (adjusted hazard ratio 0.49, 95% CI [0.36-0.65]). Conclusions In patients hospitalized for COVID-19, ACEi/ARB use was associated with lower levels of inflammation and lower risk of in-hospital outcomes. Clinical trials will define the role of ACEi/ARB in the treatment of COVID-19. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT04818866.