Predictor Of Clinical Outcome Research Articles

Usefulness of frailty assessment using the revised Japanese version of the Cardiovascular Health Study on the prediction of clinical outcomes in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement.

Frailty assessment is essential for deciding the treatment strategy for patients with aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). Recently, the revised Japanese version of the Cardiovascular Health Study (J-CHS) criteria has been proposed for the frailty assessment; however, it is unclear whether the criteria are useful for the risk stratification in these patients. We investigated the impact of frailty assessment using the revised J-CHS criteria on clinical outcomes in patients with AS undergoing TAVR. We examined 205 consecutive severe AS patients who underwent TAVR at two tertiary hospitals from May 2018 to December 2022. Frailty was defined by the revised J-CHS criteria (score ≥ 3) before TAVR. The primary outcome was major adverse cardiac or cerebrovascular events (MACCE). Among the studied patients, the mean age was 84years and 65% were female. Frailty was present in 51% of patients. During a median follow-up period of 1000 (interquartile range 677-1210) days, MACCE occurred in 22 patients. Frailty was significantly independently associated with higher risks of the MACCE adjusted for confounders related to nutritional status, severity of AS, comorbidities [hazard ratio (HR) 5.09, 95% confidence interval (CI) 1.70-15.23; HR 3.94, 95% CI 1.34-11.55; HR 3.12, 95% CI 1.14-8.53; HR 3.31, 95% CI 1.21-9.02, respectively]. Frailty determined by the revised J-CHS criteria was associated with clinical outcomes, suggesting these criteria would be useful for risk stratification in Japanese patients with AS undergoing TAVR.

Clinical Characteristics and Outcome Predictors in Drug-Resistant Tuberculosis: A Comprehensive Analysis

Background: Drug-resistant tuberculosis (DR-TB) poses significant challenges to public health, with poor outcomes frequently observed in affected patients. This study aims to evaluate the characteristics and factors associated with poor outcomes in patients with drug-resistant pulmonary tuberculosis at Liwa Hospital from January 2018 to May 2023. Methods: A retrospective, cross-sectional single-center analysis was conducted on 408 patients admitted to Liwa Hospital. Among these, 28 patients diagnosed with drug-resistant tuberculosis (DR-TB) were selected for detailed analysis based on their treatment outcomes and clinical data. Inclusion criteria encompassed patients aged 18 years or older with confirmed drug-resistant TB, while patients younger than 18, those with latent tuberculosis, and those with extra-pulmonary tuberculosis were excluded. Results: The majority of patients were between 18-40 years old (60.7%), predominantly male (85.7%), and Asian (96.4%). Comorbidities included diabetes (46.4%) and hypertension (21.4%). Clinical characteristics revealed cough (28.6%) and fever with cough (7.1%) as common symptoms. Primary resistance was observed in 92.9% of cases, with 96.4% being newly diagnosed TB cases. Adverse drug events were minimal, with 7.1% experiencing nausea and vomiting. Radiological findings showed unilateral TB in 53.6% and cavitary TB in 57.1% of cases. Laboratory analysis indicated elevated HbA1c (9.83 ± 3.25), CRP (25.94 ± 5.16 mg/L), and white blood cell count (9.94 ± 4.59 x 10^9 cells/L). Rifampicin resistance was the most prevalent (42.9%), followed by isoniazid resistance (25.0%). Regarding treatment outcomes, age, hypertension, and diabetes mellitus were found to be significantly associated with poor outcomes in patients (p=0.05). Conclusion: The study identified significant associations between treatment outcomes and age, hypertension, and diabetes status, with higher proportions of poor outcomes observed in patients. Comprehensive management strategies targeting these factors are essential to improve outcomes in patients with drug-resistant TB. Further research is warranted to develop tailored interventions for this population.

Clinical characteristic, laboratory biomarkers, treatment regimen and psychiatry problems predictors of outcomes of alopecia areata: a prospective study

Background Alopecia areata (AA) has multiple aetiology such as genetic and environmental triggers. Aims To assess the recovery rate of AA and examine the associated psychiatric problems. Additionally, the relationship between clinical, psychiatric, and laboratory biomarkers and alopecia outcomes were investigated, along with potential risk factors that could aid in treating alopecia. Patients and methods A prospective cohort research included 42 AA patients and 45 healthy controls. Group A (active disease), group B (inactive disease), and group C (healthy control) were based on illness outcomes after 3 months of treatment. The Severity of Alopecia Tool (SALT), treatment regimens, laboratory investigation Interleukins 19 and 33 (IL-19 and IL-33), Symptom Checklist 90, and post-traumatic stress disorder Checklist for DSM-5 (PCL-5) were evaluated. Results After 3 months of therapy, the incidence of inactive AA was found to be 57.14%. Being females with family history of dermatitis were highly related with active illness, while smoking and unmarried patients were associated with inactive disease. After 3 months of treatment, active illness had the highest mean IL-33 and IL-19 levels. Conclusion The active disease group exhibited the highest mean IL-33 and IL-19 levels at baseline following three months of treatment. Our patients had 7.1% somatization, 7.1% obsessive-compulsive symptoms, 4.8% depression, 4.8% anxiety, 15.9% anger-hostility, 35.7% phobic-anxiety, 26.2% paranoid ideation, 4.8% psychoticism, and 61.9% post-traumatic stress disorder. AA outcomes were linked to females, a family history of dermatological disorders, smoking, being single, and higher mean IL-33 and IL-19 levels. Psychosis was highly linked with active AA. Only khellin and Ultraviolet A improved AA results.

Long-Term Outcome of Motor Functional Neurological Disorder After Rehabilitation.

Functional neurological disorder (FND) is defined as the presence of neurological symptoms that are inconsistent with a neurological disease. We performed a single-center retrospective study aimed at determining the long-term outcome of FND patients receiving inpatient rehabilitation and the predictors of a good outcome. A multidisciplinary graded exercise program was provided with one or two daily physiotherapy and occupational therapy sessions on 5 days each week, as well as weekly psychological support. Outcome was assessed using the motor part of the Functional Independence Measure scale (FIM; maximum score of 91) at admission, discharge, and follow-up, with the last assessment performed by phone interview. The 30 included patients were aged 43.6±14.7 years (mean±standard deviation), comprised 70% females, and received a mean of 4 weeks of rehabilitation. The admission FIM score (80.2±8.3) was significantly lower than the discharge FIM score (86.9±4.6; p<0.001, Wilcoxon signed-rank test). No notable difference was observed between discharge and follow-up FIM scores (85.5±8.5, p=0.54). The mean follow-up of the 36-month FIM scores at discharge and follow-up was dichotomized as a good outcome in cases where all items were scored ≥6 (functional independence). Binomial logistic regression showed that absence of a comorbid psychiatric disorder (p=0.039, odds ratio=10.7) was a predictive factor for a good outcome at follow-up. Other variables (e.g., sex and age) were not significant predictors of clinical outcome (all p≥0.058). These results suggest inpatient intensive rehabilitation for motor FND is effective and produces favorable long-term results. Further studies with larger groups are warranted so that the management protocols can be standardized.

509. DOES SARCOPENIA AFFECT THE OUTCOME OF PATIENTS WITH ESOPHAGEAL CARCINOMA AFTER ESOPHAGECTOMY?

Abstract Background Sarcopenia is increasingly recognized as an independent predictor of clinical outcomes of cancer patients such as post-operative complications and prolonged hospital stays. Additionally, sarcopenia can also negatively impact overall survival because of reduced ability to tolerate treatments like neoadjuvant therapy and surgery. At particular risk among cancer patients is the esophageal cancer population because of tumor stenosis leading to dysphagia and impossibility of oral feeding in many patients. The purpose of the current study was to investigate the effect of preoperative sarcopenia on postoperative complications in patients undergoing esophagectomy for esophageal cancer. Methods This retrospective study includes all patients who underwent full-robotic abdominothoracic esophageal resection because of esophageal cancer at our institution between 06/2020 and 12/2022. The skeletal muscle index (SMI) was assessed using the preoperative computed tomographic staging scans by measuring the cross-sectional muscle area at the third lumbar vertebral level. Following cut off SMI values were used to define sarcopenia: men: 52,4 cm2/m2, women: 38,5 cm2/m2 according to Prado et al (Lancet Oncol, 2008). Recorded parameters included demographic data, neo-adjuvant treatment, histologic findings, postoperative course and overall- and disease-free survival. Results A total of 113 cases were included in this preliminary analysis. 97 patients (86%) were classified as having sarcopenia. Of these, 38 patients (40%) had a preoperatively or during esophageal resection implemented percutaneous endoscopic jejunostomy (PEJ) tube to ensure enteral nutrition. Despite age, groups were comparable regarding neoadjuvant treatment and histologic findings (mean age sarcopenic patients: 66y vs. 61y non-sarcopenic patients, p = 0.03). There was no difference in the incidence of occurrence of anastomotic leakage, pulmonary complications, need for re-operation, length of (ICU) stay and overall- and disease-free survival between sarcopenic and non-sarcopenic patients. Conclusion Incidence of sarcopenia is very high among esophageal cancer patients. In our study population, however, preoperative sarcopenia failed to predict complications or long-term outcome after esophagectomy for esophageal cancer. 40% of the sarcopenic patients received a PEJ. This relatively high proportion of implemented PEJ could have contributed to the observed comparable outcomes between sarcopenic and non-sarcopenic patients. This observation underlines the importance of prehabilitation and nutritional support for patients with preoperative sarcopenia.

Baseline SUVmax is correlated with tumor hypoxia and patient outcomes in nasopharyngeal carcinoma.

To evaluate the prognostic significance of the maximum standardized uptake value (SUVmax) in nasopharyngeal carcinoma (NPC), establish a gene signature that correlates with SUVmax, and explore the underlying biological behaviors associated with these correlations for the prediction of clinical outcomes. A cohort of 726 patients with NPC was examined to identify correlations between SUVmax and various clinical variables. RNA sequencing was performed to identify genes related to SUVmax, and these genes were used to develop an SUV signature. Additionally, transcriptome enrichment analysis was conducted to investigate the potential biological behaviors underlying the observed correlations. Higher SUVmax was associated with an increased tumor burden and worse prognosis. The SUV signature, which consisted of 10 genes, was positively correlated with SUVmax, and it predicted worse survival outcomes. This signature was highly expressed in malignant epithelial cells and associated with hypoxia and resistance to radiotherapy. Additionally, the signature was negatively correlated with immune function. SUVmax is a valuable prognostic indicator in NPC, with higher values predicting worse outcomes. The SUV signature offers further prognostic insights, linking glucose metabolism to tumor aggressiveness, treatment resistance, and immune function, and it could represent a potential biomarker for NPC.

Prediction of Clinical Outcomes in Psychotic Disorders Using Artificial Intelligence Methods: A Scoping Review

Prediction of Clinical Outcomes in Psychotic Disorders Using Artificial Intelligence Methods: A Scoping Review

Single-cell RNA Sequencing Analysis Reveals Cancer-associated Fibroblast Signature for Prediction of Clinical Outcomes and Immunotherapy in Gastric Cancer.

Gastric cancer (GC) is a significant worldwide health concern and is a leading cause of cancer-related mortality. Immunotherapy has arisen as a promising strategy to stimulate the patient's immune system in combating cancer cells. Nevertheless, the effectiveness of immunotherapy in individuals with gastric cancer (GC) is not yet optimal. Thus, it is crucial to discover biomarkers capable appof predicting the advantages of immunotherapy for tailored treatment. The tumor microenvironment (TME) and its constituents, including cancer-associated fibroblasts (CAFs), exert a substantial influence on immune responses and treatment outcomes. In this investigation, we utilized single-cell RNA sequencing to profile CAFs in GC and established a scoring method, referred to as the CAF score (CAFS), for the prediction of patient prognosis and response to immunotherapy. Through our analysis, we successfully identified distinct subgroups within CAFs based on CAF score (CAFS), namely CAFS-high and CAFS-low subgroups. Notably, we noted that individuals within the CAFS-high subgroup experienced a lessF favorable prognosis and displayed diminished responsiveness to immunotherapy in contrast to the CAFS low subgroup. Furthermore, we analyzed the mutation and immune characteristics of these subgroups, identifying differentially mutated genes and immune cell compositions. We established that CAFS could forecast treatment advantages in patients with gastric cancer, both for chemotherapy and immunotherapy. Its efficacy was additionally confirmed in contrast to other biomarkers, including Tumor Immune Dysfunction and Exclusion (TIDE) and Immunophenotypic Score (IPS). These findings emphasize the clinical relevance and potential utility of CAFS in guiding personalized treatment strategies for gastric cancer.

Optical coherence tomography predictors of clinical outcomes after stent implantation: the ILUMIEN IV trial.

Observational registries have suggested that optical coherence tomography (OCT) imaging-derived parameters may predict adverse events after drug-eluting stent (DES) implantation. The present analysis sought to determine the OCT predictors of clinical outcomes from the large-scale ILUMIEN IV trial. ILUMIEN IV was a prospective, single-blind trial of 2487 patients with diabetes or high-risk lesions randomized to OCT-guided versus angiography-guided DES implantation. All patients underwent final OCT imaging (blinded in the angiography-guided arm). From more than 20 candidates, the independent OCT predictors of 2-year target lesion failure (TLF; the primary endpoint), cardiac death or target-vessel myocardial infarction (TV-MI), ischaemia-driven target lesion revascularization (ID-TLR), and stent thrombosis were analysed by multivariable Cox proportional hazard regression in single treated lesions. A total of 2128 patients had a single treated lesion with core laboratory-analysed final OCT. The 2-year Kaplan-Meier rates of TLF, cardiac death or TV-MI, ID-TLR, and stent thrombosis were 6.3% (n = 130), 3.3% (n = 68), 4.3% (n = 87), and 0.9% (n = 18), respectively. The independent predictors of 2-year TLF were a smaller minimal stent area (per 1 mm2 increase: hazard ratio 0.76, 95% confidence interval 0.68-0.89, P < .0001) and proximal edge dissection (hazard ratio 1.77, 95% confidence interval 1.20-2.62, P = .004). The independent predictors of cardiac death or TV-MI were smaller minimal stent area and longer stent length; of ID-TLR were smaller intra-stent flow area and proximal edge dissection; and of stent thrombosis was smaller minimal stent expansion. In the ILUMIEN IV trial, the most important OCT-derived post-DES predictors of both safety and effectiveness outcomes were parameters related to stent area, expansion and flow, proximal edge dissection, and stent length.

Clinical and echocardiographic predictors of outcome in liver transplant patients.

Liver transplant (LT) candidates undergo transthoracic echocardiography (TTE) before surgery to assess cardiac function and evaluate the echocardiographic probability of pulmonary hypertension (PHT). The improvement of pulmonary artery systolic pressure (PAPS) after transplant is associated with higher survival rates in patients with mild or moderate PHT. Although studies analyze the outcomes of LT in patients treated for PHT, the prognostic value of PAPS in patients without PHT in the follow-up is unknown. The aim of our study is to evaluate pre- and post-LT cardiac function, right ventricular function, pulmonary artery pressure, and their association with long-term mortality. 102 patients who underwent LT between 2011 and 2018 were compared for echocardiographic and hemodynamic parameters pre- and post-LT. After LT, systolic blood pressure, heart rate (HR), and PASP significantly increased, while tricuspid annular plane systolic excursion/PAPS decreased. Moreover, the higher difference in HR and PASP between pre- and post-LT was highlighted in those patients who died during the follow-up period after LT. Among all the parameters tested, in the multi-variable Cox regression for mortality, left ventricular ejection fraction and PASP difference were predictors of mortality. This study highlights the importance of TTE in LT screening as a tool to stratify patients at higher risk of death due to advanced cirrhotic cardiomyopathy and the importance of the change of echocardiographic parameters, in particular right and left ventricular hemodynamics, during the follow-up period. These parameters could be used to guide a more aggressive therapy.

Unraveling the Predictive Value of the Novel Global Immune-Nutrition-Inflammation Index (GINI) on Survival Outcomes in Patients with Grade 4 Adult-Type Diffuse Gliomas

Background: This investigation evaluated the predictive and prognostic efficacy of the newly developed global immune-nutrition-inflammation index (GINI) in patients with grade 4 adult-type diffuse gliomas, comparing it with other established indices such as the systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and pan-immune-inflammation value (PIV). Method: A retrospective cohort included 198 patients diagnosed with isocitrate dehydrogenase (IDH)-mutant gr4 (grade 4) astrocytoma and IDH-wt (wilde-type) glioblastoma (GBM) gr4 treated with surgical resection, radiotherapy, and temozolomide. Patients were stratified into two groups based on their GINI values: low GINI (&lt;5815) and high GINI (≥5815). The primary endpoint was overall survival (OS). Results: High GINI was significantly associated with older age, poor performance status, multifocal tumors, and higher SII, SIRI, and PIV values (p &lt; 0.005). The GINI demonstrated strong correlations with SII (r = 0.694), SIRI (r = 0.516), and PIV (r = 0.657) (p &lt; 0.001). Patients with high GINI exhibited poorer OS (5.0 vs. 17.0 months) and PFS (5.0 vs. 13.0 months) in comparison to those with low GINI. Kaplan–Meier survival analysis revealed significantly prolonged OS and PFS among patients with low GINI (p &lt; 0.001). Multivariate analysis identified high GINI as an independent negative risk factor for both PFS and OS. Conclusions: GINI is a robust predictor of clinical outcomes in IDH-mutant gr4 astrocytoma and IDH-wt GBM gr4, highlighting the crucial impact of nutrition and cancer cachexia. It shows superior prognostic value relative to the SII, SIRI, and PIV.

Long-term clinical recovery and treatment resistance in first-episode psychosis: a 10-year follow-up study.

Illness trajectories in people with first-episode psychosis (FEP) vary significantly over time. Identifying early-course parameters predicting outcomes is essential, but long-term data still needs to be provided. We conducted a 10-year follow-up study of a comprehensive first-episode psychosis (FEP) cohort investigating the prevalence of clinical recovery (CR) and treatment resistance (TR) after ten years, as well as clinical, demographic, and pre-illness predictors of long-term outcomes. 102 participants with FEP DSM-IV Schizophrenia spectrum disorders were recruited within their first year of treatment. The Treatment Response and Resistance in Psychosis Working Group (TRRIP) and the Remission in Schizophrenia Working Group (RSWG) criteria were used to define TR and CR, respectively. At 10-year follow-up, 29 (29%) of the participants were classified as in CR, while 32 (31%) were classified as TR. We also identified a larger middle group (n = 41, 40%) consisting of participants in partial recovery. 7% of all participants had tried Clozapine at the 10-year follow-up. Logistic regression analyses identified insidious onset (OR = 4.16) and baseline disorganized symptoms (OR = 2.96) as significantly associated with an increased risk of developing TR. Good premorbid academic adjustment (OR = 1.60) and acute onset (OR = 3.40) were associated with an increased chance of CR. We identified three long-term outcome groups by using recent consensus definitions. We also identified the potential importance of assessing baseline disorganized symptoms and monitoring patients with insidious onset more closely. Further, the findings suggest that clinicians should pay close attention to early-course parameters and provide adequate treatment to improve long-term outcomes of FEP.

Clinical outcomes of reperfusion therapy in patients with site-specific basilar artery occlusion

BackgroundDespite its low incidence, basilar artery occlusion (BAO) remains a major therapeutic challenge since severe disability and death occur in about 80% of patients. Specific site of BAO (proximal, middle,...

A deep neural network approach to heart murmur detection using spectrogram and peak interval features

Congenital heart disease affects about 1% of newborns, posing risks like heart failure and mortality. Developing countries often lack resources for diagnosis and treatment. The George B. Moody PhysioNet Challenge 2022 aims to develop systems for detecting murmurs and clinical outcome events using phonocardiogram (PCG) data, offering a cost-effective method for diagnosing cardiac diseases without invasive procedures. We proposed a deep learning model for this task and achieved the 5th rank out of 40 teams in both Track 1 (murmur detection) and Track 2 (clinical outcome prediction). This paper describes our methods and additional experiments. To extract features from the PCG, we employed techniques including Constant Q Transform (CQT) and Mel-scaled spectrogram (Mel-spectrogram) to generate two-dimensional representations in the frequency–time domain. Additionally, we extracted the Peak Interval (PI) feature, which measures the distance between peaks in the PCG data. This feature is useful because the peak intervals should be shorter in PCG recordings with murmurs. We also considered the sequence and mean of PI as additional features. Our proposed system, titled ‘Phonocardiogram-based Heart murmur Detection using Spectrogram and PI features (SpectroHeart),’ employs the Mel-spectrogram and PI features to detect heart murmurs and assess clinical outcomes. We believe that our deep learning-based system has great potential for automatically detecting heart signals from PCG.

Construction of a prognostic model for colon cancer by combining endoplasmic reticulum stress responsive genes

Endoplasmic reticulum stress may affect the occurrence and development of cancer. However, its effect on the prognosis of colon cancer (CC) patients is not clear yet. Herein, based on TCGA database, we screened 15 endoplasmic reticulum stress responsive genes (ERSRGs) associated with the prognosis of CC patients by Cox regression. By LASSO and multivariate Cox regression analyses, a prognostic risk assessment model involving 12 genes (DNAJB2, EIF4A1, YPEL4, COQ10A, IRX3, ASPHD1, NTRK2, TRIM39, XBP1, GRIN2B, LRRC59, and RORC) was built. The survival curves indicated that patients in the low-risk group had good prognosis. ROC curves demonstrated a good performance of this 12-gene prognostic model, and the Riskscore could be considered as an independent prognostic factor. Patients in low-risk group benefit more from immune checkpoint inhibitor and immune checkpoint blockade (ICB) treatment. Besides, the enrichment analysis suggested a remarkable difference in Ca2+ signaling in both groups. Finally, based on the cMAP database, we identified several potential drugs that could target high-risk groups, such as Dasatinib, GNF-2, Saracatinib, and WZ-1-84. To sum up, our research constructed an ERSRGs-characteristic prognostic model. The model is a promising biomarker for prediction of clinical outcomes and immune therapy response of CC patients. SignificanceBased on the transcriptomic data of colon cancer in the TCGA database, this study screens 12 endoplasmic reticulum stress-related genes (ERSRGs), including DNAJB2, EIF4A1, YPEL4, COQ10A, IRX3, ASPHD1, NTRK2, TRIM39, XBP1, asphD1, NTRK2. GRIN2B, LRRC59, and RORC, and a prognostic model was constructed. This model can be used as a predictor of prognosis and immunotherapy response in colon cancer patients. At the same time, model-based prediction of drugs can also be a potential option for colon cancer treatment in the future.

Predictors of clinical and functional outcomes of acute ischemic stroke after various types of treatment

Predictors of clinical and functional outcomes of acute ischemic stroke after various types of treatment

Low Levels of Adropin Predict Adverse Clinical Outcomes in Outpatients with Newly Diagnosed Prediabetes after Acute Myocardial Infarction.

Adropin-a multifunctional peptide with tissue-protective capacity that regulates energy homeostasis, sensitivity to insulin and inflammatory response-seems to show an inverse association with the presence of cardiovascular and renal diseases, obesity and diabetes mellitus in the general population. The purpose of the study is to elucidate whether adropin may be a plausible predictive biomarker for clinical outcomes in post-ST elevation of myocardial infarction (STEMI) patients with newly diagnosed prediabetes according to the American Diabetes Association criteria. A total of 1214 post-STEMI patients who received percutaneous coronary intervention were identified in a local database of the private hospital "Vita Center" (Zaporozhye, Ukraine). Between November 2020 and June 2024, we prospectively enrolled 498 patients with prediabetes in this open prospective cohort study and followed them for 3 years. The combined clinical endpoint at follow-up was defined as cardiovascular death due to acute myocardial infarction, heart failure, sudden death due to arrhythmia or cardiac surgery, and/or all-cause death. We identified 126 clinical events and found that serum levels of adropin < 2.15 ng/mL (area under the curve = 0.836; 95% confidence interval = 0.745-0.928; sensitivity = 84.9%; specificity = 72.7%; likelihood ratio = 3.11; p = 0.0001) predicted clinical outcomes. Multivariate logistic regression showed that a Gensini score ≥ 32 (Odds ratio [OR] = 1.07; p = 0.001), adropin ≤ 2.15 ng/mL (OR = 1.18; p = 0.001), use of SGLT2i (OR = 0.94; p = 0.010) and GLP-1 receptor agonist (OR = 0.95; p = 0.040) were independent predictors of clinical outcome. Kaplan-Meier plots showed that patients with lower adropin levels (≤2.15 ng/mL) had worse clinical outcomes compared to patients with higher adropin levels (>2.15 ng/mL). In conclusion, low levels of adropin (≤2.15 ng/mL) independently predicted clinical outcomes in post-STEMI patients with newly detected prediabetes and improved the discriminative ability of the Gensini score for 3-year follow-up events. Future clinical studies are needed to clarify whether adropin is a promising molecule to be incorporated into conventional risk scores for the prediction of MACCEs after STEMI.

Day 100 Recovery of Absolute Number of Inhibitory KIR2DL2 and Activating NKp30 Natural Killer Cells Predicts Survival Post-Autologous Stem Cell Transplantation in Lymphomas.

The infusion autograft absolute number of inhibitory killer immunoglobulin-like receptor (KIR) 2DL2 and activating natural killer (NK)p30 cells are predictors of clinical outcomes in lymphoma patients undergoing autologous peripheral blood hematopoietic stem cell transplantation (APBHSCT). To assess if the long-term recovery of these NK cell subsets still holds clinical relevance, we set up to investigate their prognostic ability at day 100 post-APBHSCT. This was a retrospective single-institution study including 107 patients from our prior phase III trial who had a clinical assessment at day 100 post-APBHSCT. The median follow-up from day 100 was 168.19 months (interquartile range: 156.85-181.28 months). Patients with day 100 inhibitory KIR2DL2 < 0.08 cells/µL and activating NKp30 ≥ 0.19 cells/µL experienced superior overall survival (OS) and progression-free survival (PFS). A multivariate analysis revealed both the day 100 inhibitory KIR2DL2 [OS: HR = 1.449, 95%CI, 1.231-1.895, p < 0.013; and PFS: HR = 2.069, 95%CI, 1.134-3.775, p < 0.021] and activating NKp30 [OS: HR = 4.985, 95%CI, 2.614-9.506, p < 0.0001; and PFS: HR = 4.661, 95%CI, 2.598-8.393, p < 0.0001] were independent predictors for OS and PFS. Inhibitory KIR2DL2 and activating NKp30 NK cells at day 100 are prognostic immune biomarkers in lymphoma patients treated with APBHSCT.

Cerebral ischemia biomarkers: Their roles in early diagnosis and prognosis with potential clinical applications

Cerebral ischemia, caused by a disruption in blood supply to the brain, remains a significant cause of morbidity and mortality worldwide. Identifying reliable biomarkers for the early diagnosis and prognosis of cerebral ischemia is crucial for timely intervention and improved patient outcomes. This review aims to provide a comprehensive overview of the current knowledge on cerebral ischemia biomarkers, focusing on their potential role in early detection and prediction of clinical outcomes. Specifically, we discuss the current advances in the field of cerebral ischemia biomarkers, which serve as essential tools for early diagnosis and monitoring of ischemic stroke. We examine several promising biomarkers, including omics data, genetic (FOXF2 and ATP5H), physiological and neuroinflammatory biomarkers, neuroimaging markers, blood-based biomarkers (proteins, microRNAs, and metabolites), and newer modalities such as exosomes, microvesicles, and cell-free deoxyribonucleic acid (cfDNA). In addition, we highlight the challenges and future directions in translating these biomarkers into clinical practice. Standardization and reproducibility, methodological limitations, and cost and accessibility are critical challenges in the translation of biomarkers into clinical practice. Addressing these challenges requires multi-stakeholder collaborations and coordinated efforts to establish standardized protocols, improve analytical methods, and develop cost-effective biomarker assays. The use of point-of-care testing devices or miniaturized lab-on-a-chip technologies can reduce costs and improve accessibility, particularly in low-resource settings. Furthermore, collaborations between academia, industry, and regulatory agencies can facilitate the translation of biomarkers by addressing regulatory and reimbursement hurdles that affect the affordability and availability of these tests.

NG2 is a target gene of MLL-AF4 and underlies glucocorticoid resistance in MLL-r B-ALL by regulating NR3C1 expression

AbstractB-cell acute lymphoblastic leukemia (B-ALL) is the most common pediatric cancer, with long-term overall survival rates of ∼85%. However, B-ALL harboring rearrangements of the MLL gene (also known as KMT2A), referred to as MLLr B-ALL, is common in infants and is associated with poor 5-year survival (<30%), frequent relapses, and refractoriness to glucocorticoids (GCs). GCs are an essential part of the treatment backbone for B-ALL, and GC resistance is a major clinical predictor of poor outcome. Elucidating the mechanisms of GC resistance in MLLr B-ALL is, therefore, critical to guide therapeutic strategies that deepen the response after induction therapy. Neuron-glial antigen-2 (NG2) expression is a hallmark of MLLr B-ALL and is minimally expressed in healthy hematopoietic cells. We recently reported that NG2 expression is associated with poor prognosis and that anti-NG2 immunotherapy strongly reduces/delays relapse in MLLr B-ALL xenograft models. Despite its contribution to MLLr B-ALL pathogenesis and its diagnostic utility, the role of NG2 in MLLr-mediated leukemogenesis/chemoresistance remains elusive. Here, we show that NG2 is an epigenetically regulated direct target gene of the leukemic MLL-AF4 fusion protein. NG2 negatively regulates the expression of the GC receptor NR3C1 and confers GC resistance to MLLr B-ALL cells in vitro and in vivo. Mechanistically, NG2 interacts with FLT3 to render ligand-independent activation of FLT3 signaling (a hallmark of MLLr B-ALL) and downregulation of NR3C1 via AP-1–mediated transrepression. Collectively, our study elucidates the role of NG2 in GC resistance in MLLr B-ALL through FLT3/AP-1–mediated downregulation of NR3C1, providing novel therapeutic avenues for MLLr B-ALL.