Tool For Prognostic Assessment Research Articles

Relationship between the magnesium depletion score and all-cause and cardiovascular mortality among asthma patients: A Study based on the NHANES population from 2005-2018.

This study aimed to investigate the potential association between magnesium depletion score (MDS), a novel assessment of magnesium status in vivo, and all-cause and cardiovascular mortality in asthma patients. Using data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018, 4757 asthmatics were included in the study and were categorized into four groups based on their MDS levels (MDS=0, MDS=1, MDS=2, and MDS≥3). Survival differences between the different MDS groups were analysed using Kaplan-Meier curves, and weighted multivariate Cox regression models assessed the relationship between MDS and mortality. In addition, non-linear relationships between MDS and all-cause and cardiovascular mortality were explored using restricted cubic spline (RCS) regression models, and subgroup analyses were performed to validate the results. Kaplan-Meier curves showed that both all-cause and cardiovascular mortality were significantly higher in the group with higher levels of MDS (P < 0.001). After controlling for all confounders, asthmatics in the higher MDS group faced a higher risk of death compared with the lower MDS group, as evidenced by a 3.29-fold increase in all-cause mortality (95 % CI: 2.05, 5.29) and a 4.68-fold increase in cardiovascular mortality (95 % CI: 1.77, 12.35). Fully adjusted Cox regression models further confirmed the significant positive association of high MDS with the risk of all-cause and cardiovascular mortality.RCS plots revealed a linear dose-response relationship between MDS and mortality. In the subgroup analyses, no interaction factors other than cardiovascular disease were found to significantly influence the relationship between MDS and mortality. Higher levels of MDS independently predicted the risk of mortality, especially cardiovascular mortality, in US adults with asthma. Therefore, the MDS may become a cost-effective and widely applicable prognostic assessment tool for asthma, providing an important reference for clinical decision-making and patient management.

Spinal cord injury-specific prognostic risk assessment tool for development of type 2 diabetes.

Available diabetes risk calculators were developed for able-bodied individuals, but their metabolic profile is different from individuals with spinal cord injury. We aimed to develop a diabetes risk assessment tool specific to individuals with spinal cord injury. We used national Veterans Affairs data to identify patients with at least a 2-year history of spinal cord injury and no prior history of diabetes with a Veterans Heath Affairs visit from 2005-2007, and followed the 11,054 individuals that met inclusion criteria for up to 17 years to assess diabetes development. We used least absolute shrinkage and selection operator (LASSO) Cox regression to develop prognostic diabetes prediction models and evaluated these models on discrimination and calibration. 2937 subjects developed diabetes during follow-up; median follow-up time was 8.7 years (IQR 3.3, 15.4). The first model selected 17 predictors and demonstrated median discrimination of 0.70 (IQR 0.69, 0.72) at 15 years. The second, more parsimonious model with 4 selected predictors demonstrated median discrimination of 0.69 (IQR 0.68, 0.71) at 15 years. Both models demonstrated good calibration across predicted risk, with better calibration in the 17-predictor model. These spinal cord injury-specific risk calculators can be used by both patients and providers in assessing risk of diabetes development, and in shared decision making regarding surveillance and prevention.

Application of urinary peptide-biomarkers in trauma patients as a predictive tool for prognostic assessment, treatment and intervention timing

Treatment of severely injured patients represents a major challenge, in part due to the unpredictable risk of major adverse events, including death. Preemptive personalized treatment aimed at preventing these events is a crucial objective of patient management; however, the currently available scoring systems provide only moderate guidance. Biomarkers from proteomics/peptidomics studies hold promise for improving the current situation, ultimately enabling precision medicine based on individual molecular profiles. To test the hypothesis that peptide biomarkers could predict patient outcomes in severely injured patients, we initiated a pilot study involving consecutive urine sampling (on days 0, 2, 5, 10, and 14) and subsequent peptidome analysis using capillary electrophoresis coupled to mass spectrometry (CE-MS) of 14 severely injured patients and two additional intensive care unit patients. The urine peptidomes of these patients were compared to those of age- and sex-matched controls. Moreover, previously established urinary peptide-based classifiers, CKD273, AKI204, and Cov50, were applied to the obtained peptidome data, and the association of the classifier’s scores with a combined endpoint (death and/or kidney failure and/or respiratory insufficiency) was investigated. CE-MS peptidome analysis identified 191 significantly altered peptides in severely injured patients. A consistent increase in the abundance of peptides from A1AT, AHSG, and HBA1 was observed, while peptides derived from PIGR and UROM were consistently decreased. Most of the significant peptides (adjusted p < 0.05) were from COL1A1, and most were reduced in abundance. Two of the previously defined and validated peptidomic classifiers, CKD273 and AKI204, showed significant associations with the combined endpoint, which was not observed for the routine scores generally applied in the clinics. This prospective pilot study confirmed the hypothesis that urinary peptides provide information on patient outcomes and may guide personalized interventions in severely injured patients based on individual molecular changes. The results obtained allow the planning of a well-powered prospective trial investigating the value of urinary peptides in this context in more detail.

Improving Circulating Tumor Cell Detection Using Image Synthesis and Transformer Models in Cancer Diagnostics.

Cancer is the second leading cause of death, significantly threatening human health. Effective treatment options are often lacking in advanced stages, making early diagnosis crucial for reducing mortality rates. Circulating tumor cells (CTCs) are a promising biomarker for early detection; however, their automatic detection is challenging due to their heterogeneous size and shape, as well as their scarcity in blood. This study proposes a data generation method using the Segment Anything Model (SAM) combined with a copy-paste strategy. We develop a detection network based on the Swin Transformer, featuring a backbone network, scale adapter module, shape adapter module, and detection head, which enhances CTC localization and identification in images. To effectively utilize both generated and real data, we introduce an improved loss function that includes a regularization term to ensure consistency across different data distributions. Our model demonstrates exceptional performance across five evaluation metrics: accuracy (0.9960), recall (0.9961), precision (0.9804), specificity (0.9975), and mean average precision (mAP) of 0.9400 at an Intersection over Union (IoU) threshold of 0.5. These results are achieved on a dataset generated by mixing both public and local data, highlighting the robustness and generalizability of the proposed approach. This framework surpasses state-of-the-art models (ADCTC, DiffusionDet, CO-DETR, and DDQ), providing a vital tool for early cancer diagnosis, treatment planning, and prognostic assessment, ultimately enhancing human health and well-being.

Effect of POD24 on the prognosis of follicular and other indolent B-cell non-hodgkin lymphomas.

Indolent B-cell non-Hodgkin lymphomas(B-NHL) encompass a heterogeneous category of lymphomas characterized by a wide range of pathological subtypes. With the application of chemoimmunotherapy with rituximab (R-chemo), the prognosis of patients has improved considerably, with a 10-year survival rate of 60-80%. Despite these advancements, a significant number of patients still experience disease progression during or shortly after initial treatment. Those who progress within the first 24 months (POD24) continue to face a notably worse prognosis. This study aims to explore the significance of POD24 in predicting the prognosis of different subtypes of indolent B-cell NHL through a comprehensive literature review. The investigation extends to examining the existing prognostic assessment tools and evaluating the interrelationship between POD24 and these tools. By synthesizing relevant research findings, this study seeks to contribute to the current understanding of the role POD24 plays in prognostic evaluation and its potential implications in guiding clinical decision-making for patients with indolent B-cell NHL.

Predictive utility of the Rockall scoring system in patients suffering from acute nonvariceal upper gastrointestinal hemorrhage.

Acute non-variceal upper gastrointestinal bleeding (ANVUGIB) represents a significant clinical challenge due to its unpredictability and potentially severe outcomes. The Rockall risk score has emerged as a critical tool for prognostic assessment in patients with ANVUGIB, aiding in the prediction of rebleeding and mortality. However, its applicability and accuracy in the Chinese population remain understudied. To assess the prognostic value of the Rockall risk score in a Chinese cohort of patients with ANVUGIB. A retrospective analysis of 168 ANVUGIB patients' medical records was conducted. The study employed statistical tests, including the t-test, χ 2 test, spearman correlation, and receiver operating characteristic (ROC) analysis, to assess the relationship between the Rockall score and clinical outcomes, specifically focusing on rebleeding events within 3 months post-assessment. Significant associations were found between the Rockall score and various clinical outcomes. High Rockall scores were significantly associated with rebleeding events (r = 0.735, R 2 = 0.541, P < 0.001) and strongly positively correlated with adverse outcomes. Low hemoglobin levels (t = 2.843, P = 0.005), high international normalized ratio (t = 3.710, P < 0.001), active bleeding during endoscopy (χ 2 = 7.950, P = 0.005), large ulcer size (t = 6.348, P < 0.001), and requiring blood transfusion (χ 2 = 6.381, P = 0.012) were all significantly associated with rebleeding events. Furthermore, differences in treatment and management strategies were identified between patients with and without rebleeding events. ROC analysis indicated the excellent discriminative power (sensitivity: 0.914; specificity: 0.816; area under the curve: 0.933; Youden index: 0.730) of the Rockall score in predicting rebleeding events within 3 months. This study provides valuable insights into the prognostic value of the Rockall risk score for ANVUGIB in the Chinese population. The results underscore the potential of the Rockall score as an effective tool for risk stratification and prognostication, with implications for guiding risk-appropriate management strategies and optimizing care for patients with ANVUGIB.

Value analysis of ITLN1 in the diagnostic and prognostic assessment of colorectal cancer.

Colorectal cancer (CRC) remains the leading cause of cancer death worldwide. Less than half of the patients are diagnosed when the cancer is locally advanced. Several studies have shown that intelectin-1 (ITLN1) can serve as a key prognostic and therapeutic target for CRC. The purpose of this study was to investigate the clinical value of ITLN1 in CRC and to analyse its potential as a predictive biomarker for CRC. Colon adenocarcinoma (COAD) is the main type of CRC. COAD project in The Cancer Genome Atlas (TCGA) database served as the training cohort, and GSE39582 series in the Gene Expression Omnibus (GEO) database served as the external independent validation cohort. First, the difference in the expression level of ITLN1 between COAD tissue and normal tissue was analysed, and the results were verified via immunohistochemistry. The relationship between ITLN1 expression and the prognosis of COAD patients was evaluated via the heatmap and the Kaplan-Meier (KM) curve. The ITLN1 coexpressed gene set obtained by Pearson correlation analysis was used. The prognostic signatures that were significantly correlated with survival status were screened by Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. Finally, a nomogram related to ITLN1 was constructed based on the risk score of the prognostic signature and routine clinicopathological variables. ITLN1 is significantly underexpressed in tumour tissues and can be used as a valuable tool to distinguish COAD. The high-expression group of ITLN1 was verified to have a greater survival rate. ITLN1 is significantly associated with a good prognosis in COAD patients. Six candidate genes (ITLN1 and MORC2, SH2D7, LGALS4, ATOH1, and NAT2) were selected for use in the Cox-LASSO regression analysis to calculate the risk score. Finally, a nomogram was constructed with a comprehensive risk score and clinicopathologic factors to successfully predict and verify the 1-year, 3-year, and 5-year survival probability. Our study established ITLN1 as an effective tool for CRC screening, diagnosis, and prognostic assessment, provided a basis for further study of the molecular function of ITLN1, and provided new insights for the mechanistic exploration and treatment of CRC.

Killip scale reclassification according to lung ultrasound: Killip pLUS.

The Killip scale remains a fundamental tool for prognostic assessment in ST-segment elevation myocardial infarction (STEMI) due to its simplicity and predictive value. Lung ultrasound (LUS) has emerged as a valuable adjunct for diagnosing and predicting outcomes in heart failure (HF) and STEMI patients, even those with subclinical congestion. We created a new classification (Killip pLUS), which reclassifies Killip I and II patients into an intermediate category (Killip I pLUS) based on LUS results. This category included Killip I patients and ≥1 positive zone (≥3 B-lines) and Killip II with 0 positive zones. We aimed to evaluate this new classification by comparing it with the Killip scale and a previous LUS-based reclassification scale (LUCK scale). Lung ultrasound was performed within 24 h of admission in a multicentre cohort of 373 patients admitted for STEMI. In-hospital mortality and major adverse cardiovascular events within one year after admission, comprising mortality or readmission for HF, acute coronary syndrome, or stroke, were analysed. When predicting in-hospital mortality, the global comparison of these three classifications was statistically significant: Killip pLUS area under the curve (AUC) 0.90 (95% CI 0.85-0.95) vs. Killip AUC 0.85 (95% CI 0.73-0.96) vs. LUCK 0.83 (95% CI 0.70-0.95), P = 0.024. To predict events during follow-up, the comparison between scales was also significant: Killip pLUS 0.77 (95% CI 0.71-0.85) vs. Killip 0.72 (95% CI 0.65-0.79) vs. LUCK 0.73 (95% CI 0.66-0.81), P = 0.033. The Killip pLUS scale provides enhanced risk stratification compared to the Killip and LUCK scales while preserving simplicity.

Comparison of different 2D muscle indexes measured at the level of the 3rd lumbar vertebra in survival prediction in patients with renal cell carcinoma.

Low computed tomography (CT)-determined muscle mass, commonly determined with height-adjusted muscle indexes (MIs), predicts worse survival in several cancers and has been suggested as a prognostic assessment tool. Although several MIs measured at the level of the 3rd lumbar vertebra (L3) are commonly used, it remains unestablished how different L3-determined MIs perform in survival prognostication compared to each other. The objective of this study was to investigate the performance of different MIs for survival prognostication in renal cell carcinoma (RCC). We retrospectively enrolled 214 consecutive patients with RCC. We determined three L3-MIs (psoas muscle index (PMI), psoas muscle index and erector spinae index (PMI+ESI), and whole skeletal muscle index (SMI)) from preoperative CT scans. Categorization of those with low and normal muscle mass was based on the Youden Index sex-specific MI cut-offs. We determined sensitivity, specificity, and accuracy metrics for predicting 1-year, 5-year, and overall survival (OS) using Cox regression models. Low PMI, PMI+ESI, and SMI significantly predicted decreased 1-year, 5-year, and OS in uni- and multivariate models. PMI+ESI and SMI were more accurate than PMI in males, and PMI and PMI+ESI were more accurate than SMI in females in the prediction of 1-year survival. However, there were no differences in accuracies between MIs in 5-year and OS prediction. PMI+ESI performed well overall in short-term prognostication, but there were no differences between the MIs in long-term prognostication. We recommend the use of PMI+ESI for muscle evaluation, particularly when SMI cannot be evaluated.

Inflammaging score as a potential prognostic tool for cancer: A population-based cohort study

This study aimed to develop a clinically applicable inflammaging score by combining the inflammatory status and age of patients. Kaplan-Meier analysis was used to compare survival differences among patients with different grades of inflammation scores. Cox proportional hazard regression analysis was used to explore the relationship between the inflammaging score and survival. As the age of patients increased, their levels of systemic inflammation gradually increased. A unique inverse relationship was found between the level of inflammation and cancer prognosis during the ageing process. Mediation analysis indicated that systemic inflammation mediates 10.1%–17.8% of the association between ageing and poor prognosis. With an increase in the inflammaging score from grades I to V, the survival rate showed a gradient decline. The inflammation score could effectively stratify the prognosis of patients with lung, bronchial, gastrointestinal, and other types of cancers. Compared with grade I, the hazard ratios for grades II-V were 1.239, 1.604, 1.724, and 2.348, respectively. In the external validation cohort, the inflammaging score remained an independent factor affecting the prognosis of patients with cancer. The inflammaging score, which combines ageing and inflammation, is a robust prognostic assessment tool for cancer patients.

Development and validation of a nomogram for predicting specific mortality risk: A study of competing risk model based on real endometrial cancer patients.

This study aimed to construct a competing risk prediction model for predicting specific mortality risks in endometrial cancer patients from the SEER database based on their demographic characteristics and tumor information. We collected relevant clinical data on patients with histologically confirmed endometrial cancer in the SEER database between 2010 and 2015. Univariate and multivariate competing risk models were used to analyze the risk factors for endometrial cancer-specific death, and a predictive nomogram was constructed. C-index and receiver operating characteristic curve (ROC) at different time points were used to verify the accuracy of the constructed nomogram. There were 26 109 eligible endometrial cancer patients in the training cohort and 11 189 in the validation cohort. Univariate and multivariate analyses revealed that Age, Marriage, Grade, Behav, FIGO, Size, Surgery, SurgOth, Radiation, ParaAortic_Nodes, Peritonea, N positive, DX_liver, and DX_lung were independent prognostic factors for specific mortality in endometrial cancer patients. Based on these factors, a nomogram was constructed. Internal validation showed that the nomogram had a good discriminative ability (C-index = 0.883 [95% confidence interval [CI]: 0.881-0.884]), and the 1-, 3-, and 5-year AUC values were 0.901, 0.886 and 0.874, respectively. External validation indicated similar results (C-index = 0.883 [95%CI: 0.882-0.883]), and the 1-, 3-, and 5- AUC values were 0.908, 0.885 and 0.870, respectively. We constructed a competing risk model to predict the specific mortality risk among endometrial cancer patients. This model has favorable accuracy and reliability and can provide a reference for the development and update of endometrial cancer prognostic risk assessment tools.

Electromyography Analysis of the Masseter Muscle's Activity in the Management of Oral Submucous Fibrosis.

Introduction Oral submucous fibrosis (OSMF) is a persistent, collagen metabolic disorder distinguished by the presence of fibrosis of the connective tissue stroma in the oral mucosa with a higher malignant potential rate for oral cancer. This study aimed to analyze the utility of electromyography (EMG) as the prognostic assessment tool in the management of OSMF with conventional intralesional corticosteroid therapy. Materials and methods This study included 20 OSMF cases of age range 20 to 80 years without systemic comorbidities to assess pre-treatment and post-treatment changes with intralesional corticosteroid therapy as an intervention and to determine if it could be assessed using electromyographic study. Clinical and histopathological grading of OSMF was done. The five clinical parameters were evaluated for measuring treatment prognosis. Among them, mouth opening, tongue protrusion, and burning sensation assessments were quantitative parameters, and palpable fibrotic bands and mucosa colour were qualitative parameters. As OSMF involves changes in muscle plane in moderately advanced and advanced cases, EMG was used as an assessment tool for measuring muscle activity. Among the muscles of mastication, the masseterand temporalis were selected for evaluation. Twenty age and gender-matched healthy controls were required for this study as there are no standardized normal values for amplitude and onset of activity in muscle analysis. The EMG activity of the right and left temporalis and masseter muscles were recorded using surface electrodes and were correlated with five clinical assessment parameters. Results In the right masseter, the rest amplitude of 1.6010 µV of the OSMFwas statistically significant (p-value: 0.050) when compared with 4.1275 µV of the control. The clench amplitude of 133.370 µV of the OSMFwas statistically significant (p-value: 0.062) when compared with 94.310 µV of the control. In the left masseter, the rest amplitude of 1.6695 µV of the OSMFwas statistically significant (p-value 0.066) when compared with 2.5735 µV of the control. In the left masseter, the onset of muscle action of 62.670 ms of the OSMFwas statistically significant (p-value: 0.017) when compared with 131.835 ms of the control. The clench amplitude differences in the right masseter of 133.370 µV pre-treatment, and 102.775 µV post-treatment were statistically significant (p-value: 0.007). The clench amplitude in the left masseter of 102.535 µV pre-treatment, and 92.090 µV post-treatment were statistically significant (p-value: 0.036). The correlation was seen between tongue protrusion and rest amplitude in the right masseter in OSMF (r = 0.376, p-value: 0.023). Conclusion There was a correlation between tongue protrusion and rest amplitude in the right masseter muscle in OSMF patients before treatment. In the right and left masseter, during rest, the amplitude of the OSMF group was lesser than that of the control group. During clench, in the right masseter, the amplitude of the OSMF group was higher than that of the control group. During clench in the left masseter, the onset of muscle action was lesser in the OSMF group than in the control group. After treatment, there was a reduction in clench amplitude in OSMF patients from their pretreatment values signifying muscle relaxation and a better onset of muscle action.

Using machine learning algorithms based on patient admission laboratory parameters to predict adverse outcomes in COVID-19 patients

Amidst the global COVID-19 pandemic, the urgent need for timely and precise patient prognosis assessment underscores the significance of leveraging machine learning techniques. In this study, we present a novel predictive model centered on routine clinical laboratory test data to swiftly forecast patient survival outcomes upon admission. Our model integrates feature selection algorithms and binary classification algorithms, optimizing algorithmic selection through meticulous parameter control. Notably, we developed an algorithm coupling Lasso and SVM methodologies, achieving a remarkable area under the ROC curve of 0.9277 with the use of merely 8 clinical laboratory parameters collected upon admission. Our primary contribution lies in the utilization of straightforward laboratory parameters for prognostication, circumventing data processing intricacies, and furnishing clinicians with an expeditious and precise prognostic assessment tool.

Prognostic value of the geriatric nutritional risk index and other hematological markers on long-term survival in the geriatric population.

The prognostic value of hematological markers has not been extensively explored in the geriatric population, particularly in the presence of the frailty phenotype among hospitalized individuals. Therefore, our study aimed to assess the influence of the frailty phenotype in hospitalized geriatric individuals on hematological markers and their impact on short- and long-term outcomes. This is a secondary analysis of a prospective cohort study. This study involved hospitalized individuals who were followed during their hospitalization and for nearly 2 years after discharge. At baseline, Fried's frailty phenotype was assessed, as well as hematological markers, including neutrophil-lymphocyte ratio, monocyte-lymphocyte ratio, neutrophil-monocyte ratio, platelet-lymphocyte ratio, systemic inflammation index, prognostic nutritional index, geriatric nutritional risk index (GNRI), and C-reactive protein-albumin ratio. The phase angle derived from bioelectrical impedance analysis was likewise considered a prognostic biomarker. Our main outcomes were hospital length of stay and mortality during follow-up. Frailty occurred in 43.2% of the population. Individuals with the frailty phenotype exhibited worse hematological markers and lower phase angle values. Low GNRI and elevated C-reactive protein-albumin ratio values were independently associated with mortality (hazard ratio = 6.88, 95% confidence interval 2.0-23.6; hazard ratio = 2.2, 95% confidence interval 1.1-4.4). Only higher values of the systemic inflammation index were independently associated with prolonged hospital stays. Hematological markers may serve as a feasible tool for prognostic assessment. Individuals with the frailty phenotype and low GNRI represented a worst-case scenario. Geriatr Gerontol Int 2024; 24: 312-318.

A ubiquitination-related risk model for predicting the prognosis and immunotherapy response of gastric adenocarcinoma patients.

Ubiquitination is crucial for the growth of cancer. However, the role of ubiquitination-related genes (URGs) in stomach adenocarcinoma (STAD) remains unclear. Differentially expressed URGs (DE-URGs) were examined in the whole TCGA-STAD dataset, and the prognosis-related genes were discovered from the The Cancer Genome Atlas (TCGA) training set. Prognostic genes were discovered using selection operator regression analysis and absolute least shrinkage (LASSO). A multivariate Cox analysis was further employed, and a polygene-based risk assessment system was established. Signatures were verified using the Gene Expression Omnibus (GEO) database record GSE84433 and the TCGA test set. Using the MEXPRESS dataset, a detailed analysis of gene expression and methylation was carried out. Using the DAVID database, DE-URG function and pathway enrichment was examined. The identified 163 DE-URGs were significantly associated with pathways related to protein ubiquitination, cell cycle, and cancer. A prognostic signature based on 13 DE-URGs was constructed, classifying patients into two risk groups. Compared to low-risk patients, people at high risk had considerably shorter survival times. Cox regression analyses considered prognostic parameters independent of age and risk score and were used to generate nomograms. Calibration curves show good agreement between nomogram predictions and observations. Furthermore, the results of the MEXPRESS analysis indicated that 13 prognostic DE-URGs had an intricate methylation profile. The enhanced Random Forest-based model showed greater efficacy in predicting prognosis, mutation, and immune infiltration. The in vitro validation, including CCK8, EdU, Transwell, and co-culture Transwell, proved that RNF144A was a potent oncogene in STAD and could facilitate the migration of M2 macrophages. In this research, we have created a genetic model based on URGs that can appropriately gauge a patient's prognosis and immunotherapy response, providing clinicians with a reliable tool for prognostic assessment and supporting clinical treatment decisions.

Prognostic value of minimal residual disease profiling in resectable hepatocellular carcinoma.

530 Background: Detecting post-surgical residual disease is a critical clinical requirement in resectable hepatocellular carcinoma (HCC). Previous studies focused on specific genomic regions have indicated that ctDNA holds promise as a tool for prognostic assessment. Nevertheless, these methods exhibited limited sensitivity and failed to meet the minimal residual disease (MRD) threshold. Here we report the prognostic value of MRD profiling in HCC patients who have undergone hepatectomy. Methods: This retrospective study involved 88 HCC patients who underwent surgical resections in China, from January to May in 2016. During surgery, tumor and normal tissue specimens were collected. Plasma samples were obtained 7 days post-surgery. PredicineBEACON, a baseline tissue- or blood-informed MRD assay, was used for MRD profiling. This entailed identifying tumor-specific mutations through whole exon sequencing of tissue samples. Subsequently, a personalized MRD panel, selecting up to 50 mutations via bioinformatics pipelines merged with a fixed panel featuring 500 tumor actionable hotspots, was created for each patient. To detect MRD in post-surgery plasma samples, we employed ultra-deep sequencing at a coverage of 100,000X, utilizing the designed panel. Results: In the cohort of 88 patients, the distribution based on Barcelona Clinic Liver Cancer (BCLC) staging was as follows: 79.5% stage A (N=70), 12.5% stage B (N=11), and 8.0% stage C (N=7,). The MRD assay identified 36 patients as MRD+ and 52 patients as MRD-. We observed significant correlations between MRD status and both relapse-free survival (RFS) and overall survival (OS). For MRD+ patients, the median RFS was 17.1 months, while it was not reached for MRD- patients (p=0.0013). Likewise, the median OS for MRD+ patients was 40.1 months, in contrast to it not being reached for MRD- patients (p=0.0012). The MRD positivity rate stood at 100% in stage C patients, a significantly higher percentage compared to the rates observed in stage B (36.4%, p=0.0256) and stage A (36.2%, p=0.0042). Significantly, MRD status emerged as a pivotal prognostic differentiator among clinically low-risk patients in stage A: among MRD+ patients, the median RFS was 23.3 months, whereas it was not reached for MRD- patients (p=0.05). Additionally, the median OS of both MRD+ and MRD- was not reached but their survival curves showed significant differences (p=0.038). Conclusions: This study demonstrated the clinical utility of ctDNA MRD assay in patients with resectable HCC, as notably evident in the robust detection of MRD using plasma samples collected 7 days after surgery. Furthermore, the assessment of post-surgical MRD status provided valuable prognostic insights into both patient survival and the risk of disease relapse. ctDNA MRD status played a pivotal role as a prognostic differentiator, particularly among clinically low-risk patients.

Identification and validation of a prognostic risk-scoring model for AML based on m7G-associated gene clustering.

Acute myeloid leukemia (AML) patients still suffer from poor 5-year survival and relapse after remission. A better prognostic assessment tool is urgently needed. New evidence demonstrates that 7-methylguanosine (m7G) methylation modifications play an important role in AML, however, the exact role of m7G-related genes in the prognosis of AML remains unclear. The study obtained AML expression profiles and clinical information from TCGA, GEO, and TARGET databases. Using the patient data from the TCGA cohort as the training set. Consensus clustering was performed based on 29 m7G-related genes. Survival analysis was performed by KM curves. The subgroup characteristic gene sets were screened using WGCNA. And tumor immune infiltration correlation analysis was performed by ssGSEA. The patients were classified into 3 groups based on m7G-related genebased cluster analysis, and the differential genes were screened by differential analysis and WGCNA. After LASSO regression analysis, 6 characteristic genes (including CBR1, CCDC102A, LGALS1, RD3L, SLC29A2, and TWIST1) were screened, and a prognostic risk-score model was constructed. The survival rate of low-risk patients was significantly higher than that of high-risk patients (p < 0.0001). The area under the curve values at 1, 3, and 5 years in the training set were 0.871, 0.874, and 0.951, respectively, indicating that this predictive model has an excellent predictive effect. In addition, after univariate and multivariate Cox regression screening, histograms were constructed with clinical characteristics and prognostic risk score models to better predict individual survival. Further analysis showed that the prognostic risk score model was associated with immune cell infiltration. These findings suggest that the scoring model and essential risk genes could provide potential prognostic biomarkers for patients with acute myeloid leukemia.

Influence of Posture on Gait Parameters in Severe Symptomatic Lumbar Stenosis Before and After Decompression Surgery

BackgroundWe searched to quantify the influence of sagittal vertical axis (SVA) on the improvement of spatiotemporal gait parameters using a gait motion analysis (GMA) before and after decompression surgery in patients suffering from lumbar stenosis (LSS). MethodsThirty-nine patients with severe LSS planned for lumbar decompression underwent a full body biplanar radiographs (EOS®) to quantify the SVA, and have benefited from a three-dimensional GMA one month before surgery (M0) and 6 month (M6) after surgery. The first step of this study was to confirm the validation of three dimensional SVA (3D SVA) for posture analysis. An analysis of modification of the 3D SVA and spatio-temporal gait parameters was then carried out in order to identify any correlation. ResultsDecompression surgery did not significantly improve 3D SVA between M0 and M6 (respectively 49.1 (50.3) versus 49.84 (19.02), p=0.42). Concerning spatio-temporal parameters, we found significant difference for all parameters between M0 and M6. A strong correlation (R2>0.65) between static SVA (EOS®) and 3D SVA was demonstrated using a statistical regression equation. There was also a statistically significant correlation between SVA (static and 3D) and improvement in spatiotemporal gait parameters after decompression surgery. ConclusionThis study analyses the relationship between postural change (SVA) and improvement in gait parameters measured during GMA before and after decompression surgery for lumbar spinal stenosis. This specific analysis of gait parameters may represent a prognostic assessment tool for the recovery of patients undergoing surgery for a lumbar spinal stenosis.

Development and external validation of dual online tools for prognostic assessment in elderly patients with high-grade glioma: a comprehensive study using SEER and Chinese cohorts.

Elderly individuals diagnosed with high-grade gliomas frequently experience unfavorable outcomes. We aimed to design two web-based instruments for prognosis to predict overall survival (OS) and cancer-specific survival (CSS), assisting clinical decision-making. We scrutinized data from the SEER database on 5,245 elderly patients diagnosed with high-grade glioma between 2000-2020, segmenting them into training (3,672) and validation (1,573) subsets. An additional external validation cohort was obtained from our institution. Prognostic determinants were pinpointed using Cox regression analyses, which facilitated the construction of the nomogram. The nomogram's predictive precision for OS and CSS was gauged using calibration and ROC curves, the C-index, and decision curve analysis (DCA). Based on risk scores, patients were stratified into high or low-risk categories, and survival disparities were explored. Using multivariate Cox regression, we identified several prognostic factors for overall survival (OS) and cancer-specific survival (CSS) in elderly patients with high-grade gliomas, including age, tumor location, size, surgical technique, and therapies. Two digital nomograms were formulated anchored on these determinants. For OS, the C-index values in the training, internal, and external validation cohorts were 0.734, 0.729, and 0.701, respectively. We also derived AUC values for 3-, 6-, and 12-month periods. For CSS, the C-index values for the training and validation groups were 0.733 and 0.727, with analogous AUC metrics. The efficacy and clinical relevance of the nomograms were corroborated via ROC curves, calibration plots, and DCA for both cohorts. Our investigation pinpointed pivotal risk factors in elderly glioma patients, leading to the development of an instrumental prognostic nomogram for OS and CSS. This instrument offers invaluable insights to optimize treatment strategies.

The Impact of Elevated Troponin Levels on Clinical Outcomes in Patients with Acute Ischemic Stroke: A Systematic Review.

The association between high cardiac troponin (cTn) levels and stroke characteristics and outcomes remains unclear. This systematic review aimed to determine the prevalence and clinical implications of elevated cTn levels in patients with acute ischemic stroke (AIS). We conducted a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) 2020 guidelines. A comprehensive search of PubMed, Google Scholar, Science Direct, and Research Gate databases was conducted to identify relevant studies published in English up to May 2023. This study included all reports on serum cTn levels and AIS. Two independent reviewers assessed study quality and bias using study-specific tools before inclusion. The systematic review included a total of 14 articles with 16906 participants, including one systematic review, one randomized controlled trial (RCT), and 12 observational studies. The results of this systematic review indicate that the prevalence of high cTn levels is averaged at 17.9%, or 1 in 5 individuals, who have an AIS. The review emphasizes the detrimental effects of increased cTn levels on outcomes for in-hospital and all-cause mortality as well as cardiovascular outcomes in patients with AIS. These results demonstrate that serum cTn has the potential to be a useful tool for risk classification and prognostic assessment in individuals with AIS. AIS patients with elevated serum cTn at baseline have an increased risk of mortality. Early and routine evaluation of serum cTn may contribute to the timely detection of co-morbid cardiovascular injury and prevent unfavorable outcomes in patients with AIS.