Stratification Of Patients Research Articles

Large phenotypic diversity by genotype in patients with GNE myopathy: 10years after the establishment of a national registry in Japan.

GNE myopathy is an ultra-rare autosomal recessive distal myopathy caused by pathogenic variants of the GNE gene, which encodes a key enzyme in sialic acid biosynthesis. The present study aimed to examine the long-term progression of GNE myopathy, genotype-phenotype correlations, and complications to provide useful information for predicting patient progression and designing clinical trials using a large collection of registry data over a 10-year period. We analyzed 220 Japanese patients with GNE myopathy from a national registry in Japan. Diagnoses were confirmed by genetic curators based on genetic analysis reports. We analyzed registration sheets and annually updated items completed by attending physicians. In total, 197 of 220 participants (89.5%) carried p.D207V or p.V603L in at least one allele. The median disease duration to loss of ambulation was estimated to be 10 years in p.V603L homozygotes (n = 48), whereas more than 90% of p.D207V/p.V603L compound heterozygotes were estimated to be ambulatory even 20 years after disease onset according to Kaplan-Meier analysis (p < 0.001). Moreover, participants with a younger age of onset lost ambulation earlier regardless of genotype. A decline in respiratory function was observed as the disease progressed, particularly in p.V603L homozygotes, whereas none of the p.D207V/p.V603L compound heterozygotes showed a decline. The present study demonstrated large differences in disease progression and respiratory function between genotypes. Moreover, age of onset was found to be an indicator of disease severity regardless of genotype in GNE myopathy patients. These results may help stratify patients in clinical trials and predict disease progression.

New Paradigms in the Clinical Management of Li-Fraumeni Syndrome.

Approximately 8.5%-16.2% of childhood cancers are associated with a pathogenic/likely pathogenic germline variant-a prevalence that is likely to rise with improvements in phenotype recognition, sequencing, and variant validation. One highly informative, classical hereditary cancer predisposition syndrome is Li-Fraumeni syndrome (LFS), associated with germline variants in the TP53 tumor suppressor gene, and a >90% cumulative lifetime cancer risk. In seeking to improve outcomes for young LFS patients, we must improve the specificity and sensitivity of existing cancer surveillance programs and explore how to complement early detection strategies with pharmacology-based risk-reduction interventions. Here, we describe novel precision screening technologies and clinical strategies for cancer risk reduction. In particular, we summarize the biomarkers for early diagnosis and risk stratification of LFS patients from birth, noninvasive and machine learning-based cancer screening, and drugs that have shown the potential to be repurposed for cancer prevention.

Heart rate variability and stroke or systemic embolism in patients with atrial fibrillation

BackgroundStroke remains one of the most serious complications in atrial fibrillation (AF) patients and has been linked to disturbances of the autonomic nervous system. ObjectiveWe hypothesized that impaired cardiac autonomic function might be associated with an enhanced stroke risk in AF patients. MethodsWe enrolled 1922 AF patients who were either in sinus rhythm (SR-group, n=1121) or AF (AF-group, n=801) on a 5-minute resting ECG recording. HRV triangular index (HRVI), standard deviation of normal-to-normal intervals, root mean square root of successive differences of normal-to-normal intervals, mean heart rate, 5-min total power and power in the high frequency, low frequency and very low frequency range were calculated. We constructed Cox regression models to examine the association of HRV parameters with the composite endpoint of stroke or systemic embolism. ResultsMean age was 71±8 years in the SR group and 75±8 in the AF group. 37 patients in the SR group (3.4%) and 60 patients in the AF group (8.0%) experienced a stroke or systemic embolism during a follow-up time of 5 years. In patients with SR, HRVI <15 was the strongest HRV parameter to be associated with stroke or systemic embolism (hazard ratio 3.04; 95% confidence interval 1.3-7.0; p=0.009) after adjustment for multiple confounders. In the AF group, we found no HRV parameter to be associated with the composite endpoint. ConclusionHRVI measured during SR on a single 5-minute ECG recording is independently associated with stroke or systemic embolism in AF patients. HRV analysis in SR may help to improve risk stratification in AF patients.

The value of combined detection D-dimer and NLR in judging the severity and short-term prognosis of acute cardiogenic cerebral embolism in elderly patients

ObjectiveTo assess the utility of combined neutrophil-to-lymphocyte ratio (NLR) and D-dimer detection in determining the severity and short-term prognosis of acute cardiogenic cerebral embolism in older adults. MethodsA total of 202 elderly patients with NVAF who were hospitalized in the Third Affiliated Hospital of Anhui Medical University from April 1, 2020, to April 1, 2023, were selected and divided into the observation group (69 patients with NVAF combined with ACCE) and the control group (133 patients with NVAF alone) according to whether they had acute cardiogenic cerebral embolism. According to the National Institutes of Health Stroke Scale (NIHSS), the observation group was divided into mild, moderate, and severe cerebral infarction groups: 26 cases (MICI group), 29 cases (MOCI group) and 14 cases (SCI group), respectively. According to the modified Rankin scale (mRS) after 3 months, 30 cases were divided into the good prognosis group and 39 cases were divided into the poor prognosis group. The D-dimer and NLR levels were detected in the two groups. Logistic regression was used to analyze whether the two factors were factors affecting the short-term prognosis of patients with acute cardiogenic cerebral embolism, and the ROC curve was drawn to evaluate the value of the two combined tests on the short-term prognosis of patients with acute cardiogenic cerebral embolism ResultsThe levels of D-dimer and NLR in peripheral blood in SCI group [1.82 (0.68-6.71) mg/l, 4.55 (2.31-6.68)] were higher than those in MOCI group [1.16 (0.65-1.90) mg/l, 3.84 (3.14-6.87)] and MICI group [0.53(0.32-0.90) mg/l, 2.46(2.09-3.79)]; The difference between groups was statistically significant (P<0.05). Logistic regression analysis showed that D-dimer and NLR were independent risk factors for poor prognosis in patients with acute cardiogenic cerebral embolism (OR values were 1.772 and 1.603, and 95%CI were 1.060-2.963 and 1.100-2.338, respectively, both P<0.05). The AUC of D-dimer combined with NLR for predicting poor prognosis of acute cardiogenic cerebral embolism was 0.812, which is better than D-dimer and NLR alone. ConclusionPeripheral blood D-dimer combined with NLR detection is helpful for the risk stratification and short-term prognosis assessment of patients with acute cardiogenic cerebral embolism. Clinical detection is of great significance for the prevention and monitoring of disease development.

Machine learning model for prediction of permanent stoma after anterior resection of rectal cancer: A multicenter study

BackgroundThe conversion from a temporary to a permanent stoma (PS) following rectal cancer surgery significantly impacts the quality of life of patients. However, there is currently a lack of practical preoperative tools to predict PS formation. The purpose of this study is to establish a preoperative predictive model for PS using machine learning algorithms to guide clinical practice. MethodsIn this retrospective study, we analyzed clinical data from a total of 655 patients who underwent anterior resection for rectal cancer, with 552 patients from one medical center and 103 from another. Through machine learning algorithms, five predictive models were developed, and each was thoroughly evaluated for predictive performance. The model with superior predictive accuracy underwent additional validation using both an independent testing cohort and the external validation cohort. The Shapley Additive exPlanations (SHAP) approach was employed to elucidate the predictive factors influencing the model, providing an in-depth visual analysis of its decision-making process. ResultsEight variables were selected for the construction of the model. The support vector machine (SVM) model exhibited superior predictive performance in the training set, evidenced by an AUC of 0.854 (95 % CI:0.803–0.904). This performance was corroborated in both the testing set and external validation set, where the model demonstrated an AUC of 0.851 (95%CI:0.748–0.954) and 0.815 (95%CI:0.710–0.919), respectively, indicating its efficacy in identifying the PS. ConclusionsThe model(https://yangsu2023.shinyapps.io/psrisk/) indicated robust predictive performance in identifying PS after anterior resection for rectal cancer, potentially guiding surgeons in the preoperative stratification of patients, thus informing individualized treatment plans and improving patient outcomes.

Association between red blood cell distribution width and the all-cause mortality of patients with aortic stenosis: A retrospective study

BackgroundIt is essential to assess the risk stratification of patients with aortic stenosis (AS). ObjectiveTo clarify the predictive value of red blood cell distribution width (RDW) in AS patients using a large cohort from the MIMIC-IV database. MethodsRestricted cubic spline, the Kaplan-Meier method, and logistic and Cox regression analyses were used to explore the association between RDW and all-cause mortality in AS patients. Multivariate adjustments, propensity score matching and weighting, and subgroup analysis were conducted to exclude confounding factors. Receiver operating characteristic (ROC) and decision curve analysis (DCA) curves were drawn to evaluate the predictive performance of RDW. Results1,148 patients with AS were included. Their death risks gradually increased with the elevation of RDW. Multivariate-adjusted 90-day (OR: 2.12; HR: 1.90; p = 0.001) and 1-year (OR: 2.07; HR: 1.97; p < 0.001) all-cause mortalities were significantly higher in patients with RDW≥14.7 %, which remained robust after propensity score matching and subgroup analysis. For AS patients with high RDW, those < 75 years old had higher death risks than those ≥ 75 years old. The area under the ROC curve of RDW were 0.741 and 0.75 at 90-day and 1-year follow-ups, respectively, exhibiting comparable performance to acute physiology score III and outperforming other critical illness scores in predicting the prognosis of AS patients. DCA curves also illustrated that RDW had a wide range of net benefits. ConclusionsHigh RDW was independently associated with increased 90-day and 1-year all-cause mortalities of AS patients, with strong predictive capability of prognosis.

Translational PET Imaging of Nectin-4 Expression in Multiple Different Cancers with 68Ga-N188.

Nectin cell adhesion molecule 4 (nectin-4) is a transmembrane protein overexpressed on a variety of cancers and plays an important role in oncogenic and metastatic processes. The nectin-4-targeted antibody-drug conjugate enfortumab vedotin has been approved for treating locally advanced or metastatic urothelial cancer, but the efficacy in other types of cancer remains to be explored. The aim of this study was to evaluate the feasibility of nectin-4-targeted PET imaging with 68Ga-N188 as a noninvasive method to quantify membranous nectin-4 expression in multiple tumor types-an approach that may provide insight for patient stratification and treatment selection. Methods: Sixty-two patients with 16 types of cancer underwent head-to-head 68Ga-N188 and 18F-FDG PET/CT imaging for initial staging or detection of recurrence and metastases. Correlation between lesion SUVmax and nectin-4 expression determined by immunohistochemistry staining was analyzed in 36 of 62 patients. Results: The SUVmax of 68Ga-N188 had a positive correlation with membranous nectin-4 expression in the various tumor types tested (r = 0.458; P = 0.005), whereas no association was observed between the SUVmax and cytoplasmic nectin-4 expression. The detection rates for patient-based analysis of 68Ga-N188 and 18F-FDG PET/CT examinations were comparable (95.00% [57/60] vs. 93.33% [56/60]). In patients with pancreatic cancer, 68Ga-N188 exhibited a potential advantage for detecting residual or locally recurrent tumors; this advantage may assist in clinical decision-making. Conclusion: The correlation between nectin-4-targeted 68Ga-N188 PET imaging and membranous nectin-4 expression indicates the potential of 68Ga-N188 as an effective tool for selecting patients who may benefit from enfortumab vedotin treatment. The PET imaging results provided evidence to explore nectin-4-targeted therapy in a variety of tumors. 68Ga-N188 may improve the restaging of pancreatic cancer but requires further evaluation in a powered, prospective setting.

Immune-monitoring of myelodysplastic neoplasms: Recommendations from the i4MDS consortium.

Advancements in comprehending myelodysplastic neoplasms (MDS) have unfolded significantly in recent years, elucidating a myriad of cellular and molecular underpinnings integral to disease progression. While molecular inclusions into prognostic models have substantively advanced risk stratification, recent revelations have emphasized the pivotal role of immune dysregulation within the bone marrow milieu during MDS evolution. Nonetheless, immunotherapy for MDS has not experienced breakthroughs seen in other malignancies, partly attributable to the absence of an immune classification that could stratify patients toward optimally targeted immunotherapeutic approaches. A pivotal obstacle to establishing "immune classes" among MDS patients is the absence of validated accepted immune panels suitable for routine application in clinical laboratories. In response, we formed International Integrative Innovative Immunology for MDS (i4MDS), a consortium of multidisciplinary experts, and created the following recommendations for standardized methodologies to monitor immune responses in MDS. A central goal of i4MDS is the development of an immune score that could be incorporated into current clinical risk stratification models. This position paper first consolidates current knowledge on MDS immunology. Subsequently, in collaboration with clinical and laboratory specialists, we introduce flow cytometry panels and cytokine assays, meticulously devised for clinical laboratories, aiming to monitor the immune status of MDS patients, evaluating both immune fitness and identifying potential immune "risk factors." By amalgamating this immunological characterization data and molecular data, we aim to enhance patient stratification, identify predictive markers for treatment responsiveness, and accelerate the development of systems immunology tools and innovative immunotherapies.

Consensus gene modules strategy identifies candidate blood-based biomarkers for primary Sjögren's disease

Primary Sjögren disease (pSD) is an autoimmune disease characterized by lymphoid infiltration of exocrine glands leading to dryness of the mucosal surfaces and by the production of autoantibodies. The pathophysiology of pSD remains elusive and no treatment with demonstrated efficacy is available yet. To better understand the biology underlying pSD heterogeneity, we aimed at identifying Consensus gene Modules (CMs) that summarize the high-dimensional transcriptomic data of whole blood samples in pSD patients. We performed unsupervised gene classification on four data sets and identified thirteen CMs. We annotated and interpreted each of these CMs as corresponding to cell type abundances or biological functions by using gene set enrichment analyses and transcriptomic profiles of sorted blood cell subsets. Correlation with independently measured cell type abundances by flow cytometry confirmed these annotations. We used these CMs to reconcile previously proposed patient stratifications of pSD. Importantly, we showed that the expression of modules representing lymphocytes and erythrocytes before treatment initiation is associated with response to hydroxychloroquine and leflunomide combination therapy in a clinical trial. These consensus modules will help the identification and translation of blood-based predictive biomarkers for the treatment of pSD.

An integrated signature of clinical metrics and immune-related genes as a prognostic indicator for ST-segment elevation myocardial infarction patient survival

BackgroundThe immune-inflammatory pathway plays a critical role in myocardial infarction development. However, few studies have systematically explored immune-related genes in relation to myocardial infarction prognosis using bioinformatic analysis. Our study aims to identify differentially expressed immune-related genes(DEIRGs) in ST-segment elevation myocardial infarction (STEMI) patients and investigate their association with clinical outcomes. Materials and methodsWe conducted a systematic review of Gene Expression Omnibus datasets, selecting GSE49925, GSE60993, and GSE61144 for analysis. DEIRGs were identified using GEO2R and overlapped across the chosen datasets. Functional enrichment analysis elucidated the DEIRGs' biological functions and pathways. We established an optimal prognostic prediction model using LASSO penalized Cox proportional hazards regression. The signature's clinical utility was evaluated through survival analysis, ROC curve assessment, and decision curve analysis. Additionally, we constructed a prognostic nomogram for survival rate prediction. External validation was performed using our own plasma samples. ResultsThe resulting prognostic signature integrated two dysregulated DEIRGs (S100A12 and IL2RB) and two clinical variables (serum creatinine level and Gensini score). This signature effectively stratified patients into low- and high-risk groups. Survival analysis, ROC curve analysis, and decision curve analysis demonstrated its robust predictive performance and clinical utility within the first two years post-disease onset. External validation confirmed significant outcome differences between risk groups. ConclusionsOur study establishes a prognostic signature that combines DEIRGs and clinical variables for STEMI patients. The signature exhibits promising predictive capabilities for patient stratification and survival risk assessment.

Real World Application of WIfI Scores in Peripheral Arterial Disease Patients

The Society for Vascular Surgery wound, ischemia, and foot infection (WIfI) classification system aims to risk stratify patients with chronic limb threatening ischemia (CLTI), predicting both amputation rates and the need for revascularization. However, real-world utilization of the system and whether it accurately predicts outcomes following open revascularization and peripheral interventions is unclear. Therefore, we sought to determine the adoption of the WIfI classification system within a contemporary statewide collaborative as well as the impact of patient factor, and WIfI risk assessment on short- and long-term outcomes. Using data from a large statewide collaborative, we identified patients with CLTI undergoing open surgical revascularization or peripheral vascular intervention (PVI) between 2016 - 2022. The primary exposure was preoperative clinical WIfI stage. Patients were categorized according to the SVS Lower Extremity Threatened Limb Classification System into clinical WIfI stages1, 2, 3, or 4. The primary outcomes were 30-day and 1-year amputation and mortality. Multivariable logistic regression was performed to estimate the association of WIfI stage on post-revascularization outcomes. In the cohort of 17,417 patients, 83.4% (n=14,529) had WIfI stage documented. Peripheral vascular interventions (PVIs) were performed on 57.6% of patients, and 42.4% underwent an open surgical revascularization (OSR). 49.5% of patients were classified as stage 1, 19.3% stage 2, 12.8% stage 3 and 18.3% of patients met stage 4 criteria. Stage 3 and 4 patients had higher rates of diabetes, congestive heart failure, and renal failure, and were less likely to be current or former smokers. One-half of stage 3 patients underwent OSR, while stage 1 patients were most likely to have received a PVI (64%). As WIfI stage increased from 1 to 4, 1-year mortality increased from 12% to 21% (p<0.001), 30-day amputation rates increased from 5% to 38% (p<0.001), and 1-year amputation rates increased from 15% to 55% (p<0.001). Finally, patients who did not have WIfI scores classified had significantly higher 30-day and 1-year mortality, as well as higher 30-day and 1-year amputation rates. The Society for Vascular Surgery WIfI clinical stage is significantly associated with 1-year amputation rates in patients with CLTI following lower extremity revascularization. As nearly 55% of stage 4 patients require a major amputation within one year of intervention, this study supports use of the WIfI classification system in clinical decision making for patients with CLTI.

An anoikis-related lncRNA signature may predict the prognosis, immune infiltration, and drug sensitivity in esophageal cancer

BackgroundEsophageal cancer (EC) is a prevalent malignancy with heterogeneous outcomes. This study explores the significance of anoikis-related long non-coding RNAs (lncRNAs) in EC, aiming to unravel their molecular roles and clinical implications. MethodsTranscriptome and clinical data were obtained from TCGA database for EC samples. We identified anoikis-related genes and lncRNAs by Pearson correlation analysis. The risk score model hinged on prognostic lncRNAs filtered from multiple steps. Risk scores were calculated using the derived formula, and categorized patients into low- and high-risk groups. Model robustness was assessed through Kaplan-Meier (KM) survival analysis and Receiver Operating Characteristic (ROC) curve, with clinical utility achieved via a constructed nomogram. We also explored the interplay between the risk score and immune cell infiltration, and investigated drug sensitivity. ResultsWe identified 2365 anoikis-related lncRNAs through co-expression analysis, including 1415 significant lncRNAs differentially expressed between normal and tumor samples. A risk score model was constructed from ten prognostic lncRNAs. The risk score model effectively stratified patients based on the median score, and its predictive capacity was validated through KM survival, ROC curve analyses, and the external GSE53622 dataset. The nomogram provided a practical tool for individualized prognosis evaluation. We unveiled significant correlations between specific immune cell subsets and the risk score. Eosinophils and common lymphoid progenitors exhibited positive associations, while endothelial cells and myeloid dendritic cells showed negative correlations. Drug sensitivity analysis revealed potential sensitive drugs for EC treatment that aligned with the risk subgroups. ConclusionThis study established an anoikis-related lncRNAs risk score model that may predict the prognosis, immune infiltration, and drug sensitivity in EC, in hope of facilitating tailored patient management.

Factor Eight Inhibitor Bypassing Activity as First Line Therapy for Coagulopathy in Cardiac Surgery

ObjectiveTo compare the outcomes of Factor Eight Inhibitor Bypassing Activity (FEIBA) versus Fresh Frozen Plasma (FFP) as the primary treatment for postoperative coagulopathy in cardiac surgery patients. DesignA retrospective, propensity-matched study. SettingA single, tertiary hospital. ParticipantsPatients who underwent non-coronary open-heart surgery with cardiopulmonary bypass between 2015 and 2023. InterventionsNone. Measurements and Main ResultsWe stratified patients into two groups based on whether they received intraoperative FFP or FEIBA, while cases using both were excluded. We analyzed 434 cases, with 197 receiving FFP and 237 receiving FEIBA. After propensity-matching, there was no significant difference in the proportion of the patients who required pRBC transfusions (p=0.08). However, of those who required pRBC transfusions, patients in the FEIBA group required significantly less units of pRBC (p<0.001). Significantly less patients in the FEIBA group required platelet (p<0.001) and cryoprecipitate (p<0.001) transfusions. The FEIBA group showed reduced prolonged postoperative intubation (p=0.05), reduced ICU length of stay (p=0.04), and lower 30-day readmission rates (p=0.03). There were no differences in rates of thrombotic complications between the two cohorts. ConclusionsIn the initial treatment of post-cardiopulmonary bypass coagulopathy, FEIBA may be more effective than FFP in reducing blood product transfusions and readmission rates. Further studies are needed to explore the potential routine use of FEIBA as first line agent in this patient population.

Baseline and end-of-treatment host serum biomarkers predict relapse in adults with pulmonary tuberculosis

BackgroundThere is a need for new tools for monitoring of the response to TB treatment. Such tools may allow for tailored treatment regimens, and stratify patients initiating TB treatment into different risk groups. We evaluated combinations between previously published host biomarkers and new candidates, as tools for monitoring TB treatment response, and prediction of relapse. MethodsSerum samples were collected at multiple time points, from patients initiating TB treatment at research sites situated in South Africa (ActionTB study), Brazil and Uganda (TBRU study). Using a multiplex immunoassay platform, we evaluated the concentrations of selected host inflammatory biomarkers in sera obtained from clinically cured patients with and without subsequent relapse within 2 years of TB treatment completion. ResultsA total of 130 TB patients, 30 (23%) of whom had confirmed relapse were included in the study. The median time to relapse was 9.7 months in the ActionTB study (n=12 patients who relapsed), and 5 months (n=18 patients who relapsed) in the TBRU study. Serum concentrations of several host biomarkers changed during TB treatment with IL-6, IP-10, IL-22 and complement C3 showing potential individually, in predicting relapse. A six-marker signature comprising of TTP, BMI, sICAM-1, IL-22, IL-1β and complement C3, predicted relapse, prior to the onset of TB treatment with 89% sensitivity and 94% specificity. Furthermore, a 3-marker signature (Apo-CIII, IP-10 and sIL-6R) predicted relapse in samples collected at the end of TB treatment with sensitivity of 71% and specificity of 74%. A previously identified baseline relapse prediction signature (TTP, BMI, TNF-β, sIL-6R, IL-12p40 and IP-10) also showed potential in the current study. ConclusionSerum host inflammatory biomarkers may be useful in predicting relapse in TB patients prior to the initiation of treatment. Our findings have implications for tailored patient management and require prospective evaluation in larger studies.

Genetic-based patient stratification in Alzheimer’s disease

Alzheimer's disease (AD) shows a high pathological and symptomatological heterogeneity. To study this heterogeneity, we have developed a patient stratification technique based on one of the most significant risk factors for the development of AD: genetics. We addressed this challenge by including network biology concepts, mapping genetic variants data into a brain-specific protein–protein interaction (PPI) network, and obtaining individualized PPI scores that we then used as input for a clustering technique. We then phenotyped each obtained cluster regarding genetics, sociodemographics, biomarkers, fluorodeoxyglucose-positron emission tomography (FDG-PET) imaging, and neurocognitive assessments. We found three clusters defined mainly by genetic variants found in MAPT, APP, and APOE, considering known variants associated with AD and other neurodegenerative disease genetic architectures. Profiling of these clusters revealed minimal variation in AD symptoms and pathology, suggesting different biological mechanisms may activate the neurodegeneration and pathobiological patterns behind AD and result in similar clinical and pathological presentations, even a shared disease diagnosis. Lastly, our research highlighted MAPT, APP, and APOE as key genes where these genetic distinctions manifest, suggesting them as potential targets for personalized drug development strategies to address each AD subgroup individually.

The association of cardiometabolic, diet and lifestyle parameters with plasma glucagon-like peptide-1: An IMI DIRECT study.

The role of glucagon-like peptide-1(GLP-1) in Type 2 diabetes (T2D) and obesity is not fully understood. We investigate the association of cardiometabolic, diet and lifestyle parameters on fasting and postprandial GLP-1 in people at risk of, or living with, T2D. We analysed cross-sectional data from the two Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohorts, cohort 1(n=2127) individuals at risk of diabetes; cohort 2 (n=789) individuals with new-onset of T2D. Our multiple regression analysis reveals that fasting total GLP-1 is associated with an insulin resistant phenotype and observe a strong independent relationship with male sex, increased adiposity and liver fat particularly in the prediabetes population. In contrast, we showed that incremental GLP-1 decreases with worsening glycaemia, higher adiposity, liver fat, male sex and reduced insulin sensitivity in the prediabetes cohort. Higher fasting total GLP-1 was associated with a low intake of wholegrain, fruit and vegetables inpeople with prediabetes, and with a high intake of red meat and alcohol in people with diabetes. These studies provide novel insights into the association between fasting and incremental GLP-1, metabolic traits of diabetes and obesity, and dietary intake and raise intriguing questions regarding the relevance of fasting GLP-1 in the pathophysiology T2D.

Evaluation of metabolic parameters of microsatellites stable and instable colorectal cancer patients via PET/CT

Aims: Microsatellite instability has been determined as an important indicator in selecting chemotherapy drugs in colorectal cancer. Within the scope of this research, we aimed to elucidate the pathology reports and determine whether the metabolic parameters detected by PET/CT differ in MSI-positive and negative patients. Methods: A total of 35 patients were analyzed retrospectively. The patient population consisted of patients who applied to the Nuclear Medicine Department with a diagnosis of colon or rectum cancer, underwent PET/CT imaging for staging purposes, and were operated on. Results: A total of 35 colon or rectum cancer patients were included in this retrospective analysis. When microsatellite instability was analyzed among the patients, it was found that female patients comprised 4 microsatellite instability-positive and 16 microsatellite instability-negative individuals. On the other hand, 5 of the males were microsatellite instability positive, and 10 were microsatellite instability negative. The mean SUVmax value was 16.4±8.2, SUVmean was 8.1±1.9, TLG was 392.4±520.8, and MTV was 26.5±25.4 in the microsatellite instability-positive individuals. On the other hand, the mean SUVmax value was 22.7±9.7, SUVmean was 5.2±2.2, TLG was 316.4±325.7, and MTV was 21.7±21.7 in the microsatellite instability-negative individuals. Conclusion: With the advancement of image analysis technology, MTV, and TLG, volumetric indexes derived from 18F-FDG PET have been proposed for risk stratification of cancer patients. Regarding the outcomes of this research, the semiquantitative and metabolic parameters obtained by PET/CT are not different in colorectal cancer cases with instable and stable microsatellites.

Physical performance strongly predicts all-cause mortality risk in a real-world population of older diabetic patients: machine learning approach for mortality risk stratification.

Prognostic risk stratification in older adults with type 2 diabetes (T2D) is important for guiding decisions concerning advance care planning. A retrospective longitudinal study was conducted in a real-world sample of older diabetic patients afferent to the outpatient facilities of the Diabetology Unit of the IRCCS INRCA Hospital of Ancona (Italy). A total of 1,001 T2D patients aged more than 70 years were consecutively evaluated by a multidimensional geriatric assessment, including physical performance evaluated using the Short Physical Performance Battery (SPPB). The mortality was assessed during a 5-year follow-up. We used the automatic machine-learning (AutoML) JADBio platform to identify parsimonious mathematical models for risk stratification. Of 977 subjects included in the T2D cohort, the mean age was 76.5 (SD: 4.5) years and 454 (46.5%) were men. The mean follow-up time was 53.3 (SD:15.8) months, and 209 (21.4%) patients died by the end of the follow-up. The JADBio AutoML final model included age, sex, SPPB, chronic kidney disease, myocardial ischemia, peripheral artery disease, neuropathy, and myocardial infarction. The bootstrap-corrected concordance index (c-index) for the final model was 0.726 (95% CI: 0.687-0.763) with SPPB ranked as the most important predictor. Based on the penalized Cox regression model, the risk of death per unit of time for a subject with an SPPB score lower than five points was 3.35 times that for a subject with a score higher than eight points (P-value <0.001). Assessment of physical performance needs to be implemented in clinical practice for risk stratification of T2D older patients.

Predicting short-term thromboembolic risk following Roux-en-Y gastric bypass using supervised machine learning.

Roux-en-Y gastric bypass (RYGB) is a widely recognized bariatric procedure that is particularly beneficial for patients with class III obesity. It aids in significant weight loss and improves obesity-related medical conditions. Despite its effectiveness, postoperative care still has challenges. Clinical evidence shows that venous thromboembolism (VTE) is a leading cause of 30-d morbidity and mortality after RYGB. Therefore, a clear unmet need exists for a tailored risk assessment tool for VTE in RYGB candidates. To develop and internally validate a scoring system determining the individualized risk of 30-d VTE in patients undergoing RYGB. Using the 2016-2021 Metabolic and Bariatric Surgery Accreditation Quality Improvement Program, data from 6526 patients (body mass index ≥ 40 kg/m2) who underwent RYGB were analyzed. A backward elimination multivariate analysis identified predictors of VTE characterized by pulmonary embolism and/or deep venous thrombosis within 30 d of RYGB. The resultant risk scores were derived from the coefficients of statistically significant variables. The performance of the model was evaluated using receiver operating curves through 5-fold cross-validation. Of the 26 initial variables, six predictors were identified. These included a history of chronic obstructive pulmonary disease with a regression coefficient (Coef) of 2.54 (P < 0.001), length of stay (Coef 0.08, P < 0.001), prior deep venous thrombosis (Coef 1.61, P < 0.001), hemoglobin A1c > 7% (Coef 1.19, P < 0.001), venous stasis history (Coef 1.43, P < 0.001), and preoperative anticoagulation use (Coef 1.24, P < 0.001). These variables were weighted according to their regression coefficients in an algorithm that was generated for the model predicting 30-d VTE risk post-RYGB. The risk model's area under the curve (AUC) was 0.79 [95% confidence interval (CI): 0.63-0.81], showing good discriminatory power, achieving a sensitivity of 0.60 and a specificity of 0.91. Without training, the same model performed satisfactorily in patients with laparoscopic sleeve gastrectomy with an AUC of 0.63 (95%CI: 0.62-0.64) and endoscopic sleeve gastroplasty with an AUC of 0.76 (95%CI: 0.75-0.78). This simple risk model uses only six variables to assist clinicians in the preoperative risk stratification of RYGB patients, offering insights into factors that heighten the risk of VTE events.

Treatment-Free Remission in Chronic Myeloid Leukemia.

With the discovery of tyrosine kinase inhibitors (TKIs), overall survival in patients with chronic myeloid leukemia (CML) now approaches that of the general population. While these TKIs have proven to be lifesaving, remaining on them lifelong creates both physical and financial burdens for patients. Recently, multiple trials have begun looking into the efficacy of trialing patients off these TKIs to see if they can sustain treatment-free remission (TFR). TFR eligibility is currently limited to a small population of patients with both robust and sustained responses to TKIs. Currently, for those who attempt a trial of TFR, the average success rates are promising, with anywhere from 38 to 54% of patients experiencing sustained TFR. For those who fail to maintain sustained TFR, safety results to date are reassuring, with almost all patients successfully responding to the re-initiation of TKIs, with death and disease progression being very rare complications. Moving forward, research is being conducted to more accurately risk stratify patients at diagnosis and pair them with optimized upfront treatment regimens aimed at increasing candidacy for the trial of TFR.