Individualized Treatment Strategies Research Articles

Identification of key genes to predict response to chemoradiotherapy and prognosis in esophageal squamous cell carcinoma.

Chemoradiotherapy is a crucial treatment modality for esophageal squamous cell carcinoma (ESCC). This study aimed to identify chemoradiotherapy sensitivity-related genes and analyze their prognostic value and potential associations with the tumor microenvironment in ESCC. Utilizing the Gene Expression Omnibus database, we identified differentially expressed genes between ESCC patients who achieved complete and incomplete pathological responses following chemoradiotherapy. Prognostic genes were then screened, and key genes associated with chemoradiotherapy sensitivity were determined using random survival forest analysis. We examined the relationships between key genes, infiltrating immune cells, and immunoregulatory genes. Additionally, drug sensitivity and enrichment analyses were conducted to assess the impact of key genes on chemotherapy responses and signaling pathways. A prognostic nomogram for ESCC was developed incorporating key genes, and its effectiveness was evaluated. Genome-wide association study data were employed to investigate chromosomal pathogenic regions associated with key genes. Three key genes including ATF2, SLC27A5, and ALOXE3 were identified. These genes can predict the sensitivity of ESCC patients to neoadjuvant chemoradiotherapy and hold significant clinical relevance in prognostication. These genes were also found to be significantly correlated with certain immune cells and immunoregulatory genes within the tumor microenvironment and were involved in critical tumor-related signaling pathways, including the epithelial-mesenchymal transition and P53 pathways. A nomogram was established to predict the prognosis of ESCC by integrating key genes with clinical stages, demonstrating favorable predictability and reliability. This study identified three key genes that predict chemoradiotherapy sensitivity and prognosis and are involved in multiple tumor-related biological processes in ESCC. These findings provide predictive biomarkers for chemoradiotherapy response and support the development of individualized treatment strategies for ESCC patients.

EVALUATING THE EFFICACY OF STATINS, ASPIRIN, AND ANTIHYPERTENSIVE THERAPY IN PREVENTING RECURRENT CARDIOVASCULAR EVENTS IN POST-MYOCARDIAL INFARCTION PATIENTS: A META-ANALYSIS

Background: Myocardial infarction (MI) remains a leading cause of global morbidity and mortality, significantly burdening healthcare systems. Post-MI patients face a heightened risk of recurrent cardiovascular events, necessitating effective secondary prevention strategies. Pharmacologic interventions, including statins, aspirin, and antihypertensive therapies, are widely employed, yet their comparative efficacy is debated. This meta-analysis evaluates the effectiveness of these treatments in reducing recurrent cardiovascular events, aiming to inform optimized management strategies for this high-risk population. Objective: To assess and compare the efficacy of statins, aspirin, and antihypertensive therapies in preventing recurrent cardiovascular events among post-MI patients. Methods: This meta-analysis adhered to PRISMA guidelines and included studies published between September 25 and October 27, 2024. A systematic literature search was conducted in PubMed, Scopus, and Google Scholar using MeSH terms and keywords such as "statins," "aspirin," "antihypertensive therapy," "myocardial infarction," and "cardiovascular outcomes." Inclusion criteria required original studies evaluating the effects of these therapies on post-MI cardiovascular outcomes. Data on study characteristics, demographics, interventions, and outcomes were extracted. A random-effects model was applied for pooled analysis, with results presented as odds ratios (ORs) or hazard ratios (HRs) and mean differences (MDs) alongside 95% confidence intervals (CIs). Heterogeneity was assessed using the I² statistic, with sensitivity analyses performed to evaluate result robustness. Results: Nine studies were included, encompassing 3,950 patients. High/moderate-intensity rosuvastatin reduced adverse cardiovascular events with an OR of 1.85 (95% CI: 1.65–2.10). Aspirin therapy demonstrated a 25% reduction in recurrent cardiovascular events among high-risk patients. Beta-blockers improved survival post-MI with an HR of 2.05 (95% CI: 1.85–2.30), and ACE inhibitors combined with canrenoate showed significant reductions in systolic and diastolic dysfunction, with an OR of 1.95 (95% CI: 1.70–2.20). Combination therapies of zofenopril and amlodipine yielded an OR of 1.75 (95% CI: 1.55–1.95). Overall heterogeneity was high (Q = 152.77, I² = 86.3%), reflecting differences in study designs and patient characteristics. Conclusion: This meta-analysis highlights the efficacy of statins, aspirin, and antihypertensive therapies in reducing recurrent cardiovascular events in post-MI patients. Pharmacologic therapies remain the cornerstone of management, but integrating dietary interventions may enhance long-term outcomes. Further large-scale, randomized studies across diverse populations are recommended to refine individualized treatment strategies and explore optimal combinations.

Frailty as a predictor of mortality and morbidity after cholecystectomy: A systematic review and meta-analysis of cohort studies.

Although cholecystectomy is a common surgery, it carries higher risks of postoperative complications and mortality for older adults. Age alone is not a reliable predictor of postoperative outcomes, whereas frailty may provide a more accurate assessment of a patient's health and functional status. Frailty, characterized by physical deterioration and reduced resilience, has been shown to predict mortality, prolonged recovery, and morbidity after various surgeries, including cholecystectomy. Thus, incorporating frailty evaluations into preoperative assessments can improve patient outcomes by individualizing treatment strategies. This systematic review and meta-analysis aims to evaluate how well frailty predicts postoperative outcomes following cholecystectomy. In accordance with PRISMA guidelines, we searched PubMed, Embase, and Web of Science on August 14th, 2024, without restrictions on publication year or language. The quality of the studies was assessed using the Newcastle-Ottawa scale, and meta-analysis was conducted using odds ratios with 95% confidence intervals as the effect size, employing a random-effects model. Nine cohort studies comprising a total of 128,421 participants were included. The pooled results showed significantly higher odds of short-term mortality (OR: 5.54, 95% CI: 1.65-18.60, p = 0.006), postoperative morbidity (OR: 2.65, 95% CI: 1.51-4.64, p = 0.001), major morbidity (OR: 3.61, 95% CI: 1.52-8.59), and respiratory failure (OR: 3.85, 95% CI: 1.08-13.79) among frail patients. Additionally, frail patients had longer hospital stays (mean difference: 2.98 days, 95% CI: 1.91-4.04) and significantly higher odds of postoperative infection and sepsis. However, no association was evident with reoperation rates. This study highlights the value of utilizing frailty assessment tools in preoperative settings for predicting outcomes after cholecystectomy. These tools could improve decision-making in both emergency and elective situations, aiding in the choice between surgical and medical management, as well as between open and laparoscopic procedures tailored to each patient.

Phenotype-Genotype Correlation in Morquio A Syndrome: Protocol for a Meta-Analysis.

Mucopolysaccharidosis type IVA (MPS IVA), also known as Morquio A syndrome, is a rare lysosomal storage disease characterized by autosomal recessive inheritance of mutations in the N-acetylgalactosamine-6-sulfatase (GALNS) gene. This leads to a deficiency of the GALNS enzyme, causing the accumulation of glycosaminoglycans in tissues. Morquio A syndrome primarily affects the skeletal system and joints but can also impact various organs, resulting in symptoms such as hearing and vision loss, respiratory issues, spinal cord compression, heart diseases, and hepatomegaly. The genotype-phenotype relationship is diverse, with studies highlighting variants associated with classic, nonclassic, or intermediate phenotypes. Understanding these genetic factors is crucial for predicting disease prognosis and tailoring effective treatment strategies for individuals with Morquio A syndrome. The aim of this meta-analysis is to comprehend the relationship between the severity of the phenotype and the genotype of patients with MPS IVA, considering factors such as the type of variant and its location in the different domains of the protein. This meta-analysis will include articles featuring participants of all genders and age groups who have a molecular diagnosis of MPS IVA and a description of the phenotype. Literature published in English, Spanish, and Portuguese will be considered. Exclusion criteria will encompass studies lacking full-text availability and those involving patients with an MPS IVA diagnosis but without phenotype information. The databases to be searched include PubMed, MEDLINE, ScienceDirect, and Scopus. The screening of literature, paper selection, and data extraction will involve 2 independent reviewers, who will conduct the process blindly. In the event of disagreements between the 2 reviewers at any stage, resolution will be sought through discussion or with the involvement of an additional reviewer. The final selection of manuscripts will be based on consensus. The results of the review will be presented using descriptive statistics, and the information will be organized in either diagrammatic or tabular formats, following the guidelines provided by the Joanna Briggs Institute. Genotype-phenotype relationships will be analyzed using IBM SPSS Statistics, using chi-square tests, Fisher exact tests, and regression analysis to interpret the data. A literature search conducted in January 2024 produced 760 results. The review is expected to be completed by the end of 2024. This meta-analysis will gather and analyze information on the phenotype-genotype relationship in patients diagnosed with MPS IVA. The data collection and resulting analyses will make a substantial contribution to understanding the underlying mechanism of the disease, enabling the prediction of the syndrome's progression and severity. DERR1-10.2196/56649.

Spectral CT-based nomogram for preoperative prediction of Lauren classification in locally advanced gastric cancer: a prospective study.

To develop a nomogram based on clinical features and spectral quantitative parameters to preoperatively predict the Lauren classification for locally advanced gastric cancer (LAGC). Patients diagnosed with LAGC by postoperative pathology who underwent abdominal triple-phase enhanced spectral computed tomography (CT) were prospectively enrolled in this study between June 2023 and December 2023. All the patients were categorized into intestinal- and diffuse-type groups according to the Lauren classification. Traditional characteristics, including demographic information, serum tumor markers, gastroscopic pathology, and image semantic features, were collected. Spectral quantitative parameters, including iodine concentration (IC), effective atomic number (Zeff), and slope of the energy spectrum curve from 40 keV to 70 keV (λ), were measured three times for each patient by two blinded radiologists in arterial/venous/delayed phases (AP/VP/DP). Differences in traditional features and spectral quantitative parameters between the two groups were compared using univariable analysis. Independent predictors of the Lauren classification of LAGC were screened using multivariable logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was used to assess the discriminating capability. Ultimately, the nomogram, including clinical features and spectral CT quantitative parameters, was developed. Gender, nIC in AP (APnIC), and λ in DP (λd) were independent predictors for Lauren classification. The nomogram based on these indicators produced the best performance with an area under the curve of 0.841 (95% confidence interval: 0.749-0.932), specificity of 85.3%, accuracy of 76.4%, and sensitivity of 68.4%. The nomogram based on clinical features and spectral CT quantitative parameters exhibits great potential in the preoperative and non-invasive assessment of Lauren classification for LAGC. Question Can the proposed nomogram, integrating clinical features and spectral quantitative parameters, preoperatively predict the Lauren classification in locally advanced gastric cancer (LAGC)? Findings The nomogram, based on gender, arterial phase normalized iodine concentration, and slope of the energy spectrum curve in the delayed phase showed satisfactory predictive ability. Clinical relevance The established nomogram could contribute to guiding individualized treatment strategies and risk stratification in patients by predicting the Lauren classification for LAGC before surgery.

Outcomes of Conservative Treatments Evaluations for Lumbar Radiculopathy

Background: Lumbar Radiculopathy (LR) is a condition characterized by motor, reflex and sensory changes, often causing significant pain and disability. Conservative treatments are commonly recommended as initial management options. This study aims to evaluate the outcomes of various conservative treatments for LR. Materials and methods: This prospective cohort study involved 100 patients diagnosed with LR who underwent conservative treatments between January 2023 and December 2023 at our Physical Medicine Department, Institute of Applied Health Sciences (IAHS). Treatments included physical therapy, NSAIDs, epidural steroid injections and activity modification. Baseline data, including demographic information, pain intensity (VAS) functional status (ODI) and quality of life (SF-36), were collected. Follow-up assessments were conducted at 6 weeks, 3 months and 6 months. Primary outcomes were changes in VAS, ODI and SF-36 scores. Secondary outcomes included patient satisfaction and the need for additional interventions. Data were analyzed using descriptive statistics, paired t-tests and ANOVA. Results: The mean age of participants was 45.3 years, with a slight male predominance (56%). At baseline, mean VAS was 7.8, ODI was 45.6 and SF-36 was 62.5. Significant reductions in VAS (2.6), ODI (18.7), and improvements in SF-36 physical (80.3) and mental (81.7) scores were observed at 6 months (p<0.05). Patient satisfaction at 6 months was highest for epidural injections (90%), followed by NSAIDs (85%), physical therapy (80%) and activity modification (70%). The need for additional interventions decreased to 8%. The incidence of adverse events was low, with physical therapy showing the lowest rates. Initial ODI score was a significant predictor of positive outcomes (p=0.03). Conclusion: Conservative treatments for LR are effective in reducing pain and disability and improving quality of life. All treatment modalities showed comparable efficacy, with low adverse event rates, supporting their use as first-line treatments. Initial disability levels should be considered in treatment planning to optimize outcomes. Further research is needed to refine predictive models and enhance individualized treatment strategies. IAHS Medical Journal Vol 7(1), June 2024; 80-85

Anticoagulation vs Antiplatelets Across Subgroups of Embolic Stroke of Undetermined Source: A Meta-Analysis of Randomized Controlled Trials.

The term "embolic stroke of undetermined source" (ESUS) encompasses a substantial but heterogeneous population of patients with ischemic stroke, underscoring the importance of identifying personalized treatment strategies. In subgroups of patients randomized in ESUS trials, we evaluated the effectiveness of anticoagulation compared with antiplatelet therapy in secondary ischemic stroke prevention. A study-level meta-analysis was conducted on randomized controlled trials of patients with ESUS, comparing anticoagulation with antiplatelet therapy. The primary efficacy outcome was recurrent ischemic stroke, and safety outcomes were major bleeding and death. Subgroups assessed were age, sex, presence of patent foramen ovale (PFO), left atrial enlargement (LAE), and atrial cardiopathy. Pooled risk ratios (RRs) were meta-analyzed. Cochrane Risk of Bias Tool 2.0 was used for risk-of-bias assessment. A total of 7 randomized controlled trials involving 14,804 patients were analyzed, with 7,406 patients treated with anticoagulation and 7,398 treated with antiplatelet therapy. Compared with antiplatelet therapy, anticoagulation was associated with a similar rate of recurrent ischemic stroke (RR 0.91, 95% CI 0.80-1.05; I2 = 0%). In ESUS with PFO, anticoagulation was associated with significantly lower risk of ischemic stroke (RR 0.59, 95% CI 0.35-0.98; I2 = 0%). Heterogeneity was present in those with LAE: antiplatelet therapy was superior in trials allowing cardiac monitoring after randomization (RR 6.65, 95% CI 1.26-35.08; I2 = 0%), but anticoagulation was superior in trials prohibiting cardiac monitoring after randomization (RR 0.25 95% CI 0.07-0.89). Subgroups based on age, sex, or presence of atrial cardiopathy did not benefit from anticoagulation over antiplatelet therapy. In this meta-analysis, an empiric anticoagulation approach is not beneficial for patients with ESUS. This finding highlights the importance of an individualized treatment strategy. Such a strategy should include prolonged cardiac monitoring for atrial fibrillation, particularly in patients with moderate-to-severe LAE. Anticoagulation treatment showed promise in patients with medically treated PFO. Other subgroups did not benefit from anticoagulation therapy. Large prospective studies within ESUS subgroups are needed to validate our findings.

Spontaneous cerebrospinal fluid rhinorrhoea: a case report and literature review

BackgroundCerebrospinal fluid rhinorrhea is a rare condition characterized by the abnormal leakage of cerebrospinal fluid from the intracranial space into the sinonasal cavity. It includes various etiologies, including traumatic, iatrogenic, and spontaneous causes, each with distinct epidemiological and clinical characteristics.Case presentationA 40-year-old Asian female presented with a three-month history of watery discharge from her left nostril and dull headaches localized to the left side of her head. Despite the initial diagnosis of allergic rhinitis, symptoms persisted, leading to further evaluation and eventual diagnosis of cerebrospinal fluid rhinorrhea. Detailed history, physical examination, and diagnostic tests including fluid analysis and imaging confirmed the diagnosis. The patient underwent a successful surgical repair after failed conservative management, highlighting the importance of timely intervention.ConclusionCerebrospinal fluid rhinorrhea poses significant risks if left untreated, including meningitis. Prompt recognition, accurate diagnosis, and individualized treatment strategies are crucial in mitigating complications and improving patient outcomes. A multidisciplinary approach, incorporating both conservative and surgical interventions tailored to the underlying cause, is essential for the successful management of cerebrospinal fluid rhinorrhea.

INNV-19. MULTIMODAL THERAPY FOR BRAF V600E MUTANT MELANOMA BRAIN METASTASES: CHARACTERIZATION OF CHRONOLOGICAL TREATMENT STRATEGIES AND ASSOCIATIONS WITH OVERALL SURVIVAL

Abstract BACKGROUND B-raf proto-oncogene (BRAF)-mutant melanoma brain metastases (BRAF MBM) are associated with poor prognosis. Amidst our large institutional experience treating patients with BRAF MBM with multimodality therapy, our aim was to identify disease and treatment-related prognostic features, accounting for longitudinal sequence of events, to inform clinical decision-making. METHODS We retrospectively reviewed electronic health records of 100 patients with primary cutaneous melanoma diagnosed with BRAF MBM. Demographic, disease, and clinical factors including treatment sequencing were tabulated. Descriptive statistics were used to summarize the study population and non-parametric tests were used to evaluate differences across groups. A multivariable Cox regression identified factors associated with overall survival (OS) following BRAF MBM diagnosis. RESULTS Median follow-up was 22 months and median OS was 33.5 months. Patients received an average [standard deviation (SD)] of 3.36 [1.06] unique therapies. After adjustment for covariates, greater number of brain metastases at initial diagnosis (hazard ratio (HR) 2.3 [1.14-4.62], p=0.01 for 3-10 metastases and HR 2.54 [1.01-6.36], p=0.04 for >10 metastases, respectively), receipt of combination IO and targeted therapy prior to BRAF MBM diagnosis (HR 2.91 [1.08-7.86], p=0.03), and receipt of no unique subsequent therapy after initial management strategy (HR 3.89 [1.48-10.16], p=0.005) were significantly associated with worse OS. CONCLUSIONS Despite heterogeneity in individual treatment sequences, patients with greater intracranial disease burden and those receiving combination targeted and immunotherapy prior to BRAF MBM diagnoses had the worst outcomes. Dynamic changes in therapy resistance may inform optimal treatment strategies for individuals with BRAF MBM.

Integrating transcriptomic data and digital pathology for NRG-based prediction of prognosis and therapy response in gastric cancer

Background Cancer is characterized by its ability to resist cell death, and emerging evidence suggests a potential correlation between non-apoptotic regulated cell death (RCD), tumor progression, and therapy response. However, the prognostic significance of non-apoptotic RCD-related genes (NRGs) and their relationships with immune response in gastric cancer (GC) remain unclear. Methods In this study, RNA-seq gene expression and clinical information of GC patients were acquired from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Cox and LASSO regression analyses were used to construct the NRG signature. Moreover, we developed a deep learning model based on ResNet50 to predict the NRG signature from digital pathology slides. The expression of signature hub genes was validated using real-time quantitative PCR and single-cell RNA sequencing data. Results We identified 13 NRGs as signature genes for predicting the prognosis of patients with GC. The high-risk group, characterized by higher NRG scores, demonstrated a shorter overall survival rate, increased immunosuppressive cell infiltration, and immune dysfunction. Moreover, associations were observed between the NRG signature and chemotherapeutic drug responsiveness, as well as immunotherapy effectiveness in GC patients. Furthermore, the deep learning model effectively stratified GC patients based on the NRG signature by leveraging morphological variances, showing promising results for the classification of GC patients. Validation experiments demonstrated that the expression level of SERPINE1 was significantly upregulated in GC, while the expression levels of GPX3 and APOD were significantly downregulated. Conclusion The NRG signature and its deep learning model have significant clinical implications, highlighting the importance of individualized treatment strategies based on GC subtyping. These findings provide valuable insights for guiding clinical decision-making and treatment approaches for GC.

Zebrafish patient-derived xenograft system for predicting carboplatin resistance and metastasis of ovarian cancer

AimsOvarian cancer (OC) remains a significant challenge in oncology due to high rates of drug resistance and disease relapse following standard treatment with surgery and platinum-based chemotherapy. Despite the widespread use of these treatments, no effective biomarkers currently exist to identify which patients will respond favorably to therapy. This study introduces a zebrafish patient-derived xenograft (PDX) system, capable of replicating both the carboplatin response and metastatic behavior observed in OC patients, within a rapid 3-day assay period. MethodsTwo OC cell lines: carboplatin-sensitive (A2780) and resistant (OVCAR8) were used to assess differential responses to treatment in murine and zebrafish xenograft models. Tumor tissues from 16 OC patients were implanted into zebrafish embryos to test carboplatin responses and predict metastasis. Additionally, eight clinical OC samples were directly implanted into zebrafish embryos as part of a proof-of-concept demonstration. ResultsThe zebrafish xenografts accurately reflected the carboplatin sensitivity and resistance patterns seen in in vitro and murine models. The zebrafish PDX model demonstrated a 67 % success rate for implantation and a 100 % success rate for engraftment. Notably, the model effectively distinguished between metastatic and non-metastatic disease, with an area under the ROC curve (AUC) of 0.818. Furthermore, the zebrafish PDX model showed a high concordance with patient-specific responses to carboplatin. ConclusionsThis zebrafish PDX model offers a fast, accurate, and clinically relevant platform for evaluating carboplatin response and predicting metastasis in OC patients. It holds significant potential for advancing personalized medicine, allowing for more precise therapeutic outcome predictions and individualized treatment strategies.

Prognostic characteristics and drug sensitivity analysis of hepatocellular carcinoma based on histone modification-related genes: a multi-omics integrated study revealing potential therapeutic targets and individualized treatment strategies.

Hepatocellular carcinoma (HCC) ranks among the most prevalent and lethal malignancies worldwide. Histone modifications (HMs) play a pivotal role in the initiation and progression of HCC. However, our understanding of HMs in HCC remains limited due to the disease's heterogeneity and the complexity of HMs. We integrated multi-omics data from multiple cohorts, including single-cell RNA sequencing, bulk RNA sequencing, and clinical information. Weighted gene co-expression network analysis (WGCNA) and consensus clustering were employed to identify histone-related genes. We developed a histone modification-related signature (HMRS) using 117 machine learning methods. Comprehensive analyses of molecular characteristics, immune landscape, and drug sensitivity associated with the HMRS were performed. Through integrative analysis, we defined 110 histone-related genes and identified 45 HCC-HM-related genes (HCC-HMRgenes). The HMRS demonstrated robust prognostic value across multiple cohorts. Patients with high HMRS scores exhibited distinct genomic alterations, including higher tumor heterogeneity and TP53 mutations. The high-risk group showed enrichment in cell cycle, DNA repair, and metabolic pathways. Immune landscape analysis revealed significant differences in immune cell infiltration and pathway activities between high- and low-risk groups. Drug sensitivity prediction suggested potential therapeutic strategies for different risk groups. Our study provides a comprehensive understanding of HMs in HCC and establishes a robust prognostic signature. The HMRS not only stratifies patients into distinct risk groups but also offers insights into underlying molecular mechanisms, immune characteristics, and potential therapeutic strategies, paving the way for personalized medicine in HCC.

Construction of a novel mitochondrial oxidative stress-related genes prognostic system and molecular subtype characterization for breast cancer

PurposeBreast cancer (BRCA) is the most common malignant tumor among women, characterized by high incidence rates and mortality rates. Oxidative stress and immunity, particularly in relation to mitochondria, have emerged as pivotal factors in breast carcinogenesis. Nonetheless, limited research has explored the specific contribution of mitochondrial oxidative stress to the prognosis of BRCA.MethodIn this study, we conducted univariate and multivariate Cox regression analyses to pinpoint independent prognostic genes associated with mitochondrial oxidative stress (MOSRGs) and their correlation with BRCA clinical outcomes. Subsequently, we developed a robust and accurate MOS scoring system for BRCA patients based on these identified independent prognostic MOSRGs.ResultOur findings were further substantiated by immune infiltration and somatic mutation analyses, providing additional evidence that the MOS scoring system holds predictive value for clinical outcomes in patients and correlates directly with three subtypes of BRCA. In vitro experiments in the MCF7 cell and breast tissue further verified the mRNA and protein expression level of independent prognostic genes, validating the consistency of the MOS prognostic signatures in BRCA.ConclusionThis research has unveiled a novel prognostic scoring system, providing valuable insights for improving patient prognosis assessment and developing individualized treatment strategies in BRCA patients.

The Management of Interstitial Lung Disease in the ICU: A Comprehensive Review.

Interstitial lung disease (ILD) encompasses a diverse group of parenchymal lung diseases characterized by varying degrees of inflammation and/or fibrosis. Patients with ILD frequently require hospitalization, with many needing intensive care unit (ICU) admission, most often due to respiratory failure. The diagnosis and management of ILD in the ICU present unique challenges. Diagnosis primarily relies on chest CT imaging to identify fibrosis and inflammation. Acute exacerbations, whether in idiopathic pulmonary fibrosis (IPF) or non-IPF ILD, require careful evaluation of potential triggers and differential diagnoses. Bronchoalveolar lavage may provide valuable information, such as the identification of infections, but carries risks of complications. Biopsies, whether transbronchial or surgical, can also be informative but pose significant procedural risks. Corticosteroids are the cornerstone of treatment for acute exacerbations of IPF, with higher doses potentially benefiting non-IPF ILD. Additional immunosuppressive agents may be used in cases with evidence of inflammation. Oxygen supplementation, particularly with high-flow nasal cannula, is often employed to manage severe hypoxemia, while noninvasive ventilation can be useful for worsening hypoxemia and/or hypercapnia. When mechanical ventilation is used, it is recommended to target low tidal volumes to minimize lung injury; high PEEP may be less effective and even associated with increased mortality. Prone positioning can improve oxygenation in severely hypoxemic patients. In addition to ventilatory strategies, careful fluid management and addressing concomitant pulmonary hypertension are essential components of care. Extracorporeal membrane oxygenation is a high-risk intervention reserved for the most severe cases. Lung transplantation may be considered for end-stage ILD patients in the ICU, with outcomes dependent on the urgency of transplantation and the patient's overall condition. Managing ILD in the ICU requires a multidisciplinary approach, and despite recent advances, mortality remains high, emphasizing the need for continued research and individualized treatment strategies.

Predictive modeling of preoperative acute heart failure in older adults with hypertension: a dual perspective of SHAP values and interaction analysis

BackgroundIn older adults with hypertension, hip fractures accompanied by preoperative acute heart failure significantly elevate surgical risks and adverse outcomes, necessitating timely identification and management to improve patient outcomes.Research objectiveThis study aims to enhance the early recognition of acute heart failure in older hypertensive adults prior to hip fracture surgery by developing a predictive model using logistic regression (LR) and machine learning methods, optimizing preoperative assessment and management.MethodsEmploying a retrospective study design, we analyzed hypertensive older adults who underwent hip fracture surgery at Hebei Medical University Third Hospital from January 2018 to December 2022. Predictive models were constructed using LASSO regression and multivariable logistic regression, evaluated via nomogram charts. Five additional machine learning methods were utilized, with variable importance assessed using SHAP values and the impact of key variables evaluated through multivariate correlation analysis and interaction effects.ResultsThe study included 1,370 patients. LASSO regression selected 18 key variables, including sex, age, coronary heart disease, pulmonary infection, ventricular arrhythmias, acute myocardial infarction, and anemia. The logistic regression model demonstrated robust performance with an AUC of 0.753. Although other models outperformed it in sensitivity and F1 score, logistic regression’s discriminative ability was significant for clinical decision-making. The Gradient Boosting Machine model, notable for a sensitivity of 95.2%, indicated substantial capability in identifying patients at risk, crucial for reducing missed diagnoses.ConclusionWe developed and compared efficacy of predictive models using logistic regression and machine learning, interpreting them with SHAP values and analyzing key variable interactions. This offers a scientific basis for assessing preoperative heart failure risk in older adults with hypertension and hip fractures, providing significant guidance for individualized treatment strategies and underscoring the value of applying machine learning in clinical settings.

Common laboratory results-based artificial intelligence analysis achieves accurate classification of plasma cell dyscrasias.

Plasma cell dyscrasias encompass a diverse set of disorders, where early and precise diagnosis is essential for optimizing patient outcomes. Despite advancements, current diagnostic methodologies remain underutilized in applying artificial intelligence (AI) to routine laboratory data. This study seeks to construct an AI-driven model leveraging standard laboratory parameters to enhance diagnostic accuracy and classification efficiency in plasma cell dyscrasias. Data from 1,188 participants (609 with plasma cell dyscrasias and 579 controls) collected between 2018 and 2023 were analyzed. Initial variable selection employed Kruskal-Wallis and Wilcoxon tests, followed by dimensionality reduction and variable prioritization using the Shapley Additive Explanations (SHAP) approach. Nine pivotal variables were identified, including hemoglobin (HGB), serum creatinine, and β2-microglobulin. Utilizing these, four machine learning models (gradient boosting decision tree (GBDT), support vector machine (SVM), deep neural network (DNN), and decision tree (DT) were developed and evaluated, with performance metrics such as accuracy, recall, and area under the curve (AUC) assessed through 5-fold cross-validation. A subtype classification model was also developed, analyzing data from 380 cases to classify disorders such as multiple myeloma (MM) and monoclonal gammopathy of undetermined significance (MGUS). 1. Variable selection: The SHAP method pinpointed nine critical variables, including hemoglobin (HGB), serum creatinine, erythrocyte sedimentation rate (ESR), and β2-microglobulin. 2. Diagnostic model performance: The GBDT model exhibited superior diagnostic performance for plasma cell dyscrasias, achieving 93.5% accuracy, 98.1% recall, and an AUC of 0.987. External validation reinforced its robustness, with 100% accuracy and an F1 score of 98.5%. 3. Subtype Classification: The DNN model excelled in classifying multiple myeloma, MGUS, and light-chain myeloma, demonstrating sensitivity and specificity above 90% across all subtypes. AI models based on routine laboratory results significantly enhance the precision of diagnosing and classifying plasma cell dyscrasias, presenting a promising avenue for early detection and individualized treatment strategies.

Long-term follow-up of anti-TNF treatment in adult and pediatric DADA2 patients: Insights from real-world data.

Our objective was to investigate real-world outcomes and treatment strategies in individuals affected by DADA2 using over 10-year period real-life experience. This descriptive analysis encompassed all adult/pediatric patients with DADA2 from our Vasculitis Research Center prospective database. Patients on anti-TNF therapy have been specifically examined, analyzing the treatment's duration, indications, and outcomes. Treatment responses were based on physicians' assessments and categorized as full response (symptom-free with normal acute phase reactants) or partial/no response. Totally 32 patients (Adult/Childhood age: 19/13) were analyzed. Anti-TNF agents were prescribed to 27 of the 32 patients. Over a median follow-up of 58 months on anti-TNF therapy, 10 patients (35.7%) exhibited a complete response, predominantly in cases with nervous system or skin involvement. Partial responses were observed in the other 10 patients (35.7%). Currently, 20/ 27 patients remain on anti-TNF treatment. Among the seven who are not on anti-TNF now: five died (four of them with a late diagnosis, one could not continue due to cardiomyopathy), one refused treatment and one had a cure after bone marrow transplantation. We have become aware that four patients increased their dose interval and one returned to the normal interval after an increase in CRP. The first patient was diagnosed in 2013 and over the last 10 years, 6/32 (18.8%) of the patients died. Anti-TNF treatment is beneficial for vasculitic and inflammatory lesions. The clinical course of patients is diverse, especially if the diagnosis is delayed, with a mortality rate of up to 20% over a 10-year period.

Abstract 203: Awake n‐BCA Embolization Of Complex Subcortical AVM In Elderly Patient With Cardiac Comorbidities: Case Report

Introduction Cerebral arteriovenous malformations (AVM) are an abnormal tangle of blood vessels in the brain that connects arteries to veins directly. This can lead to a variety of symptoms, including headaches, hemorrhages, seizures, and progressive neurological deficits. Effective treatment requires a multidisciplinary, individualized approach to maximize positive outcomes. We present the successful case of an 86‐year‐old male with a complex cardiac history who developed acute‐onset weakness and refractory focal motor seizures due to a large subcortical AVM in an eloquent location, treated with n‐Butyl Cyanoacrylate (nBCA) embolization while awake. Results 86‐yo male with a significant cardiac history, including hypertension, persistent atrial fibrillation on Xarelto, and heart failure, presented to the emergency department (ED) two hours after developing left facial droop, dysarthria, followed by a left‐sided focal motor seizure. Computerized tomography (CT) scan of the brain revealed a hypodense area in the right fronto‐parietal lobe, associated with vasogenic edema. Magnetic resonance imaging (MRI) indicated a possible AVM, with subtle nodular enhancement along the cortex and evidence of prior microhemorrhages. A diagnostic cerebral angiogram confirmed the presence of a Spetzler‐Martin grade 2 pial AVM in the posterior right frontal region, with a nidus measuring 6.2 mm by 4.29 mm. The AVM was supplied by the distal arterial pedicle from the inferior branch of the middle cerebral artery (MCA) and drained into the vein of Trolard. No aneurysm, varix, or venous congestion was identified. Following optimization of the patient's heart failure and seizure management, a multidisciplinary team discussed treatment options with the patient and his family. Given the AVM's eloquent location, n‐Butyl Cyanoacrylate (nBCA) embolization was performed while the patient was awake to allow for continuous neurological monitoring. Propofol was slowly injected into the arterial pedicle supplying the nidus, followed by a thorough neurological examination, which revealed no deficits. The nBCA embolization was then completed. Post‐procedural angiography showed significant obliteration of the AVM nidus and reduced arteriovenous shunting. The patient did not experience any parenchymal perfusion defects, thromboembolic complications, or vascular injuries. He was monitored in the neurointensive care unit and exhibited only mild left‐sided weakness and facial droop. Repeat CT imaging was stable. At a five‐month follow‐up, a cerebral angiogram demonstrated complete obliteration of the AVM, with no residual shunting. The patient remained neurologically intact and seizure‐free. A follow‐up angiogram is planned for six to twelve months to monitor for ongoing stability. Conclusion The successful treatment of this complex cerebral AVM using n‐BCA embolization in an awake state underscores the importance of a carefully tailored, multidisciplinary approach to managing such cases. Performing the procedure while the patient is awake allowed for continuous neurological monitoring, significantly reducing the risk of inadvertent damage. This case illustrates that, even in patients with significant comorbidities and high procedural risks, a well‐coordinated, individualized treatment strategy can lead to favorable outcomes. Ongoing follow‐up will be essential to maintain long‐term stability and address any potential complications.

The pleiotropic spectrum of proximal 16p11.2 CNVs.

Recurrent genomic rearrangements at 16p11.2 BP4-5 represent one of the most common causes of genomic disorders. Originally associated with increased risk for autism spectrum disorder, schizophrenia, and intellectual disability, as well as adiposity and head circumference, these CNVs have since been associated with a plethora of phenotypic alterations, albeit with high variability in expressivity and incomplete penetrance. Here, we comprehensively review the pleiotropy associated with 16p11.2 BP4-5 rearrangements to shine light on its full phenotypic spectrum. Illustrating this phenotypic heterogeneity, we expose many parallels between findings gathered from clinical versus population-based cohorts, which often point to the same physiological systems, and emphasize the role of the CNV beyond neuropsychiatric and anthropometric traits. Revealing the complex and variable clinical manifestations of this CNV is crucial for accurate diagnosis and personalized treatment strategies for carrier individuals. Furthermore, we discuss areas of research that will be key to identifying factors contributing to phenotypic heterogeneity and gaining mechanistic insights into the molecular pathways underlying observed associations, while demonstrating how diversity in affected individuals, cohorts, experimental models, and analytical approaches can catalyze discoveries.

Predicting Early Treatment Effectiveness in Bell's Palsy Using Machine Learning: A Focus on Corticosteroids and Antivirals.

Facial nerve paralysis, particularly Bell's palsy, manifests as a rapid onset of unilateral facial weakness or paralysis. Despite most patients recovering within three to six months, a significant proportion experience poor recovery. This study utilized six machine learning models to investigate the effectiveness of early treatment in Bell's palsy. We applied data from 17hospitals in Scotland to predict treatment outcomes. Patients were randomized into four groups: Prednisolone (corticosteroids), Acyclovir (antivirals), both, and placebo. Outcomes, defined as full resolution of symptoms, were assessed using the House-Brackmann scale at 3 and 9 months post-treatment. We employed six different machine learning models to predict recovery outcomes and evaluated model performance using AUC, precision, recall, and F1-score. Among 493 patients, 72.6% recovered after three months and 89.5% after nine months. Logistic regression demonstrated the highest predictive performance for both 3-month (AUC = 0.751) and 9-month recovery (AUC = 0.720). Additionally, several models achieved Precision levels exceeding 0.9. We further employed the best-performing logistic regression for feature ranking, indicating that the patient's age and prednisolone administration are the most significant predictors of recovery. The results highlight the potential of machine learning models in predicting the effectiveness of early treatment. This study conducted a comprehensive comparison of six different machine learning models, with the logistic regression showing the highest predictive performance for both 3-month and 9-month recovery. Additionally, feature ranking using logistic regression supported the importance of Prednisolone in treatment. Notably, our findings revealed the significance of age in prognosis evaluation for the first time. This suggests that future research should further develop age-specific prognostic models, enabling clinicians to tailor individualized treatment strategies more effectively. This previously unrecognized discovery provides a foundation for prognostic analysis in Bell's palsy patients.