Prognostic Predictor In Patients Research Articles

Etiological stratification and prognostic assessment of haemophagocytic lymphohistiocytosis by machine learning on onco-mNGS data and clinical data

IntroductionHemophagocytic lymphohistiocytosis (HLH) is a rare, complicated and life threatening hyperinflammatory syndrome that maybe triggered by various infectious agents, malignancies and rheumatologic disorders. Early diagnosis and identification of the cause is essential to initiate appropriate treatment and improve the quality of life and survival of patients. The recently developed Onco-mNGS technology can be successfully used for simultaneous detection of infections and tumors.MethodsIn the present study, 92 patients with clinically confirmed HLH were etiologically subtyped for infection, tumor and autoimmunity based on CNV and microbial data generated by Onco-mNGS technology, and a predictive model was developed and validated for the differential diagnosis of the underlying disease leading to secondary HLH. Furthermore, the treatment outcomes of patients with HLH triggered by EBV infection and non-EBV infection were evaluated, respectively.ResultsThe current study demonstrated that the novel Onco-mNGS can identify the infection and malignancy- related triggers among patients with secondary HLH. A random forest classification model based on CNV profile, infectious pathogen spectrum and blood microbial community was developed to better identify the different HLH subtypes and determine the underlying triggers. The prognosis for treatment of HLH patients is not only associated with CNV, but also with the presence of pathogens and non- pathogens in peripheral blood. Higher CNV burden along with frequent deletions on chromosome 19, higher pathogen burden and lower non-pathogenic microbes were prognosis factors that significantly related with unfavorable treatment outcomes.DiscussionOur study provided comprehensive knowledge in the triggers and prognostic predictors of patients with secondary HLH, which may help early diagnosis and appropriate targeted therapy, thus improving the survival and prognosis of the patients.

The controlling nutritional status score as a new prognostic predictor in patients with cervical cancer receiving radiotherapy: a propensity score matching analysis

BackgroundAs assessment tools of nutritional status, the controlling nutritional status (CONUT) and modified controlling nutritional status (mCONUT) score are associated with survival in various cancers. We aimed to investigate the association between the CONUT/mCONUT score’s prognostic value and survival time in patients with FIGO stage IIB–IIIB cervical cancer treated with radiotherapy.MethodsIn this retrospective study, 165 patients between September 2013 and September 2015 were analyzed, and the optimal CONUT/mCONUT score cut-off values were determined using receiver operating characteristic curves. Propensity score matching (PSM) was used to minimize selection bias. The Kaplan–Meier method and a Cox proportional hazard model were used to assess the CONUT/mCONUT score’s predictive value linked to survival time. Two nomograms were created to predict the overall survival (OS) and progression-free survival (PFS).ResultsThe cut-off values for CONUT and mCONUT score were both 2. Five-year OS and PFS rates were higher in a low CONUT score group than in a high CONUT score group (OS: 81.1% vs. 53.8%, respectively, P < 0.001; PFS: 76.4% vs. 48.2%, respectively; P < 0.001). A high CONUT score was associated with decreased OS (hazard ratio (HR) 2.93, 95% CI 1.54–5.56; P = 0.001) and PFS (HR 2.77, 95% CI 1.52–5.04; P < 0.001). High CONUT scores influenced OS in the PSM cohort. A high mCONUT score was not associated with decreased OS and PFS in Cox regression analysis.ConclusionThe CONUT score is a promising indicator for predicting survival in patients with cervical cancer receiving radiotherapy.

Comparison of Clinical Outcomes in Patients with Acute Lower Limb Ischaemia Undergoing Endovascular Therapy and Open Surgical Revascularisation: A Large Scale Analysis in Japan

The recommended revascularisation methods for acute limb ischaemia (ALI), which is caused by embolism and atherosclerotic thrombosis, include endovascular therapy (EVT) and open surgical revascularisation (OSR); however, treatment choices based on patient characteristics remain controversial. This retrospective analysis from the Japanese Registry of All Cardiac and Vascular Diseases - Diagnosis Procedure Combination database (April 2012 to March 2020) evaluated differences in clinical outcomes and identified prognostic predictors in patients with ALI. This study analysed 10 977 patients with lower limb ALI. EVT was defined as catheter directed thrombolysis, percutaneous thrombectomy, or percutaneous angioplasty with balloon dilatation and or stenting. OSR was defined as Fogarty thrombectomy, bypass surgery, or thromboendarterectomy. The EVT and OSR groups were compared after propensity score matching (PSM) considering ten clinical covariates. The EVT group had more patients at higher risk of atherosclerotic disease than the OSR group. The OSR group had more patients at a higher risk of embolism, including atrial fibrillation and atrial flutter, than the EVT group. In the EVT group, 20.4% of patients underwent catheter directed thrombolysis using urokinase, the only thrombolytic agent available in Japan that is covered under insurance. After PSM, in hospital mortality (odds ratio [OR] 1.33, 95% confidence interval [CI] 1.11 - 1.59; p = .002), major amputation rate (OR 1.43, 95% CI 1.19 - 1.72; p < .001), major amputation and or death rate (OR 1.42, 95% CI 1.24 - 1.62; p < .001), and total hospitalisation cost (1.16 vs. 0.97 million yen; p < .001) were statistically significantly higher in the EVT group than in the OSR group. In interaction analyses, peripheral artery disease (PAD) was a factor responsible for reducing OSR efficacy in terms of major amputation and or death rate (with PAD, OR 0.94, 95% CI 0.68 - 1.29; without PAD, OR 1.56, 95% CI 1.34 - 1.82; p = .004). In Japan, EVT was a less effective primary treatment for patients with ALI than OSR, except for those with PAD.

Thoracic sarcopenia was a poor prognostic predictor in patients receiving immunotherapy retain-->for advanced non-small-cell retain-->lung cancer

Sarcopenia, as measured at the level of the third lumbar (L3) has been shown to predict the survival of cancer patients. However, many patients with advanced non-small cell lung cancer (NSCLC) do not undergo routine abdominal imaging. The objective of this study was to investigate the association of thoracic sarcopenia with survival outcomes among patients who underwent immunotherapy for NSCLC. In this retrospective study, patients who initiated immunotherapy for advanced NSCLC from 2019 to 2022 were enrolled. and detailed patient data were collected. Cross sectional skeletal muscle area was calculated at the fifth thoracic vertebra (T5) on pretreatment chest computed tomography (CT) scan. Gender-specific lowest quartile values was used to define sarcopenia. The risk factors were analyzed using Cox analyses. The log-rank test and the random survival forest (RSF) were used to compare progression free survival (PFS). The model's performance was assessed using calibration curve and the receiver operating characteristic curve (ROC). A total of 242 patients was included (discovery cohort n=194, validation cohort n=48). In the discovery cohort, patients with sarcopenia exhibited significantly poorer PFS (p<0.001) than patients without sarcopenia. Univariate cox regression revealed that sarcopenia, lung cancer stage, body mass index, smoking status, and neutrophil-to-lymphocyte ratio were predictors of poor PFS. A RSF model was constructed based on the aforementioned parameters, to evaluate the model's efficacy, the ROC curve was utilized. with an area under the curve for predicting 6-month PFS of 0.68 and for 12-month PFS of 0.69. The prediction models for survival outcomes built by the discovery cohort showed similar performance in the validation cohort. Sarcopenia at T5 is independent prognostic factors in patients who received immunotherapy for advanced NSCLC.

Sleep disturbance as a poor prognostic predictor in patients with advanced non-small-cell lung cancer treated with immune checkpoint inhibitors: A prospective study

BackgroundSleep disturbances are highly prevalent in oncology and often exacerbate symptoms, leading to reduced quality of life, which in turn may further affect the tolerability and efficacy of oncological treatments. Sleep disturbance and cancer have an intimate and complicated relationship, and may be a negative predictor of cancer treatment. The present study aimed to characterize the relationship between sleep disturbance and immune checkpoint inhibitor (ICI) therapy in patients with advanced non-small cell lung cancer (NSCLC). MethodsData from 171 patients with advanced NSCLC, who underwent ICI treatment between December 2020 and October 2022, were analysed in our prospective study. Sleep disturbances were evaluated according to the Pittsburgh Sleep Quality Index (PSQI), with a cut-off value of 5, to investigate the impact of sleep disturbance on the survival of patients with NSCLC and the efficacy of ICI treatment. ResultsThe median progression-free survival (PFS) was10.4 months (9 5% confidence interval [CI]:9.84–10.97). Univariate and multivariate analyses revealed that sleep disturbance and depressive symptom predicted worse prognosis with shortened PFS. Patients who experienced sleep disturbance exhibited a significant reduction in PFS (9.2 vs. 11.8 months; HR: 1.83 [9 5% CI 1.27–2.6 5]; p = 0.001), as did those with depressive states (HR 1.5 5 [9 5% CI 1.06–2.28]; p = 0.02 5). Additionally, patients with sleep disturbance and depressive symptoms exhibited significantly lower objective response rates and disease control rates. ConclusionSleep disturbance could be a factor for prognosis in patients with advanced NSCLC undergoing first- or second-line treatment with ICIs, including shorter PFS and reduced efficacy.

Radiomics nomogram based on CT radiomics features and clinical factors for prediction of Ki-67 expression and prognosis in clear cell renal cell carcinoma: a two-center study

ObjectivesTo develop and validate a radiomics nomogram combining radiomics features and clinical factors for preoperative evaluation of Ki-67 expression status and prognostic prediction in clear cell renal cell carcinoma (ccRCC).MethodsTwo medical centers of 185 ccRCC patients were included, and each of them formed a training group (n = 130) and a validation group (n = 55). The independent predictor of Ki-67 expression status was identified by univariate and multivariate regression, and radiomics features were extracted from the preoperative CT images. The maximum relevance minimum redundancy (mRMR) and the least absolute shrinkage and selection operator algorithm (LASSO) were used to identify the radiomics features that were most relevant for high Ki-67 expression. Subsequently, clinical model, radiomics signature (RS), and radiomics nomogram were established. The performance for prediction of Ki-67 expression status was validated using area under curve (AUC), calibration curve, Delong test, decision curve analysis (DCA). Prognostic prediction was assessed by survival curve and concordance index (C-index).ResultsTumour size was the only independent predictor of Ki-67 expression status. Five radiomics features were finally identified to construct the RS (AUC: training group, 0.821; validation group, 0.799). The radiomics nomogram achieved a higher AUC (training group, 0.841; validation group, 0.814) and clinical net benefit. Besides, the radiomics nomogram provided a highest C-index (training group, 0.841; validation group, 0.820) in predicting prognosis for ccRCC patients.ConclusionsThe radiomics nomogram can accurately predict the Ki-67 expression status and exhibit a great capacity for prognostic prediction in patients with ccRCC and may provide value for tailoring personalized treatment strategies and facilitating comprehensive clinical monitoring for ccRCC patients.

Prognostic impact of cytokines and chemokines in bronchoalveolar lavage fluid on acute exacerbation of fibrosing interstitial lung disease

Background and objectiveAcute exacerbation of fibrosing interstitial lung disease (AE-FILD) is a serious condition with a high mortality rate. We aimed to comprehensively analyze cytokines in bronchoalveolar lavage fluid and their association with the clinical course of AE-FILD. MethodsWe retrospectively enrolled 60 patients with AE-FILD who underwent bronchoalveolar lavage. We comprehensively measured 44 cytokines and chemokines in the obtained bronchoalveolar lavage fluid using a Luminex analyzer. Patients were grouped into those who died within 90 days (non-survival group) and survived beyond 90 days (survival group) to investigate the association of the levels of cytokines and chemokines with mortality. ResultsThe levels of matrix metalloproteinase 1 (p = 0.003), granulocyte-macrophage colony-stimulating factor (p = 0.040), interleukin 6 (p = 0.047), interleukin 8 (p = 0.050), monocyte chemoattractant protein-1 (p = 0.043), and eotaxin (p = 0.044) were significantly higher in the non-survival group than in the survival group. In the receiver operating characteristic analysis, their areas under the curve were 0.80, 0.68, 0.71, 0.70, 0.70, and 0.72, respectively. Using machine learning with these six cytokines and chemokines, the predictive accuracy for the survival group was 0.94. ConclusionsOur study demonstrated that several cytokines and chemokines in bronchoalveolar lavage fluid could be prognostic predictors in patients with AE-FILD.

Ubiquitination-Related Gene Signature, Nomogram and Immune Features for Prognostic Prediction in Patients with Head and Neck Squamous Cell Carcinoma.

The objective of this research was to create a prognostic model focused on genes related to ubiquitination (UbRGs) for evaluating their clinical significance in head and neck squamous cell carcinoma (HNSCC) patients. The transcriptome expression data of UbRGs were obtained from The Cancer Genome Atlas (TCGA) database, and weighted gene co-expression network analysis (WGCNA) was used to identify specific UbRGs within survival-related hub modules. A multi-gene signature was formulated using LASSO Cox regression analysis. Furthermore, various analyses, including time-related receiver operating characteristics (ROCs), Kaplan-Meier, Cox regression, nomogram prediction, gene set enrichment, co-expression, immune, tumor mutation burden (TMB), and drug sensitivity, were conducted. Ultimately, a prognostic signature consisting of 11 gene pairs for HNSCC was established. The Kaplan-Meier curves indicated significantly improved overall survival (OS) in the low-risk group compared to the high-risk group (p < 0.001), suggesting its potential as an independent and dependable prognostic factor. Additionally, a nomogram with AUC values of 0.744, 0.852, and 0.861 at 1-, 3-, and 5-year intervals was developed. Infiltration of M2 macrophages was higher in the high-risk group, and the TMB was notably elevated compared to the low-risk group. Several chemotherapy drugs targeting UbRGs were recommended for low-risk and high-risk patients, respectively. The prognostic signature derived from UbRGs can effectively predict prognosis and provide new personalized therapeutic targets for HNSCC.

Prognostic prediction of patients having classical papillary thyroid carcinoma with a 4 mRNA-based risk model

Prognostic prediction of patients having classical papillary thyroid carcinoma with a 4 mRNA-based risk model

The N6-methyladenosine methylation landscape stratifies breast cancer into two subtypes with distinct immunological characteristics.

N6-methyladenosine (m6A) methylation modification affects the tumorigenesis and metastasis of breast cancer (BC). This study investigated the association between m6A regulator-mediated methylation modification patterns and characterization of the tumour microenvironment in BC, as well as their prognostic importance. Public gene expression data and clinical annotations were collected from The Cancer Genome Atlas (TCGA) database, the Gene Expression Omnibus website and the METABRIC program. We analysed the genetic expression, gene-gene interactions, gene mutations and copy number variations using R software. The data were screened for risk genes using the Cox risk regression model, and we developed an algorithm for risk score and its predictive value. Compared to adjacent normal tissue, we identified 16 differentially expressed m6A regulators in BC, including six writers and 10 readers. Under unsupervised clustering, two distinguished modification patterns were identified, cluster C1 and C2. Compared to m6A cluster C2, cluster C1 was found to be more involved in immune-related pathways, with a relatively higher immune score and stromal score (P < 0.05). Patients were divided into two groups based on their risk scores for survival analysis. The patients in the high-risk score group had significantly worse overall survival than patients in the low-risk score group, (P < 0.0001). The TCGA database validation revealed the same prognostic tendency. In summary, our study showed distinct m6A regulator modification patterns contribute to the immunological heterogeneity and diversity of BC. The development of m6A gene signatures and the m6A score aid in the prognostic prediction of patients with BC.

FT4-to-FT3 ratio is a novel prognostic marker in subacute combined spinal cord degeneration patients.

The FT4-to-FT3 ratio (FFR) variations in patients with subacute combined spinal cord degeneration (SCSD) as a potentially useful prognostic indicator are still unknown. This study aimed to investigate the changes of FFR as a potentially valuable prognostic predictor in patients with SCSD. This study included 144 consecutive SCSD patients who received standard diagnostic and therapeutic procedures between January 2015 and December 2021 and were admitted to the Department of Neurology at the First Affiliated Hospital of Bengbu Medical University. At the time of admission, we gathered data on all patients' demographics, daily routines, previous chronic conditions, medication histories, and other clinical details. For the purpose of measuring FFR, blood samples were specifically taken within 48 h of admission. The degree of neurological impairment of patients was assessed using the functional disability scale at the time of admission. At 6 months following discharge, the Modified Rankin Scale (mRS) was used to evaluate the clinical prognosis. To evaluate the relationship between the FFR and the risks of a poor outcome (mRS > 2), univariate and multivariate logistic regression analysis was utilized. The significance of the FT4/FT3 ratio in predicting the clinical outcomes in SCSD patients 6 months after discharge was assessed using the area under curve-receiver operating characteristic (AUC-ROC). About 90 patients (62.5%) of the 144 patients had poor outcomes, while 54 (37.5%) had favorable outcomes. Higher FFR at admission was independently linked to higher odds of a poor outcome, according to a logistic analysis. With an optimized cutoff value of >2.843, the FFR exhibited the maximum accuracy for predicting a poor outcome, according to the AUC‒ROC curve (AUC 0.731, P < 0.001; sensitivity, 77.8%; specificity, 83.3%). FFR was identified as an independent predictor of poor outcomes by multivariate logistic regression (OR, 2.244; 95% CI, 1.74-2.90; P < 0.001). We discovered that in patients who had a bad result 6 months after discharge, the FFR had dramatically increased at the time of admission, providing a unique prognostic marker in patients with SCSD.

Deep learning-based multi-model prediction for disease-free survival status of patients with clear cell renal cell carcinoma after surgery: a multicenter cohort study.

Although separate analysis of individual factor can somewhat improve the prognostic performance, integration of multimodal information into a single signature is necessary to stratify patients with clear cell renal cell carcinoma (ccRCC) for adjuvant therapy after surgery. A total of 414 patients with whole slide images, computed tomography images, and clinical data from three patient cohorts were retrospectively analyzed. The authors performed deep learning and machine learning algorithm to construct three single-modality prediction models for disease-free survival of ccRCC based on whole slide images, cell segmentation, and computed tomography images, respectively. A multimodel prediction signature (MMPS) for disease-free survival were further developed by combining three single-modality prediction models and tumor stage/grade system. Prognostic performance of the prognostic model was also verified in two independent validation cohorts. Single-modality prediction models performed well in predicting the disease-free survival status of ccRCC. The MMPS achieved higher area under the curve value of 0.742, 0.917, and 0.900 in three independent patient cohorts, respectively. MMPS could distinguish patients with worse disease-free survival, with HR of 12.90 (95% CI: 2.443-68.120, P <0.0001), 11.10 (95% CI: 5.467-22.520, P <0.0001), and 8.27 (95% CI: 1.482-46.130, P <0.0001) in three different patient cohorts. In addition, MMPS outperformed single-modality prediction models and current clinical prognostic factors, which could also provide complements to current risk stratification for adjuvant therapy of ccRCC. Our novel multimodel prediction analysis for disease-free survival exhibited significant improvements in prognostic prediction for patients with ccRCC. After further validation in multiple centers and regions, the multimodal system could be a potential practical tool for clinicians in the treatment for ccRCC patients.

Does Serum Uric Acid to Creatinine Ratio Predict Mortality Risk in Patients With Heart Failure?

Previous studies have established a positive correlation between serum uric acid to creatinine (SUA/Cr) ratio and cardiovascular disease, but the relationship between SUA/Cr ratio and the prognosis of heart failure (HF) remains unknown. This study investigated the potential of SUA/Cr ratio as a prognostic predictor for patients with HF. This single-center prospective cohort study enrolled 2,122 patients with HF between March 2013 and June 2017. All patients were divided into 3 groups according to SUA/Cr ratio tertiles and were followed up with until December 31, 2022. The association between SUA/Cr ratio and the prognosis of HF was assessed using the Cox proportional hazards model. The mean (SD) age and mean (SD) SUA/Cr ratio of the study cohort (66% male) were 59.3 (14.7) years and 4.71 (2.09), respectively. During a median follow-up period of 15 months (range, 11-26 months), 390 end-point events were observed. Prognosis analysis revealed that a high SUA/Cr ratio was associated with an increased mortality risk of HF (hazard ratio, 1.62 [95% CI, 1.26-2.09]; P < .001) compared with the SUA/Cr ratio in the lowest tertile. After adjusting for covariates, the hazard ratio for mortality risk of HF was 1.71 (95% CI, 1.23-2.37; P = .001). Subgroup analysis showed that mortality risk increased in direct proportion with the SUA/Cr ratio in female patients, patients with a history of hypertension and β-blocker use, and patients with UA levels below 428 μmol/L and creatinine levels less than 97 mg/dL. Stratification by age; by history of diabetes, hyperlipidemia, and smoking; and by level of fasting plasma glucose, however, had no obvious effect on the association between SUA/Cr ratio and HF prognosis. Patients with higher SUA/Cr ratios had reduced left ventricular ejection fraction and increased left ventricular end-diastolic diameter. A high SUA/Cr ratio was an independent risk factor for the mortality risk of HF.

Incremental value of myocardial global longitudinal strain in predicting major adverse cardiac events among patients with hypertrophic cardiomyopathy.

Endocardial global longitudinal strain (endo-GLS) measured with echocardiography (echo) has been demonstrated to be associated with myocardial fibrosis (MF) and is a prognostic predictor in patients with hypertrophic cardiomyopathy (HCM). Late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) imaging showed that MF is primarily located in the myocardial layer of the extremely hypertrophic septal or ventricular wall. We hypothesized that GLS of the myocardial layer (myo-GLS) is more strongly correlated with the extent of LGE (%LGE) and is a more powerful prognostic factor than endo-GLS. A total of 177 inpatients (54.0 [IQR: 43.0, 64.0] years, female 37.3%) with HCM were retrospectively included from May 2019 to April 2021. Among them, 162 patients underwent echocardiographic examination and contrast-enhanced CMR within 7 days. Myo-GLS and %LGE were blindly assessed in a core laboratory. All the patients were followed after they were discharged. During a mean follow-up of 33.77 [IQR 30.05, 35.40] months, 14 participants (7.91%) experienced major adverse cardiac events (MACE). The MACE (+) group showed lower absolute endo-GLS and myo-GLS than the MACE (-) group. Myo-GLS was more associated with %LGE (r=-.68, P<.001) than endo-GLS (r=-.64, P<.001). Cox multivariable analysis indicated that absolute myo-GLS was independently associated with MACE (adjusted hazard ratio=.75, P<.05). Myo-GLS was better than endo-GLS at detecting MACE (+) patients (-8.64%, AUC.939vs. - 16.375%, AUC.898, P<.05). Myo-GLS is a stronger predictor of MACE than endo-GLS in patients with HCM and is highly correlated with %LGE.

Clinical Features and Prognostic Predictors in Patients with Renal Transplant Complicated by SARS-CoV-2 Infection, a Retrospective Single-Center Study.

This study examines the clinical outcomes and prognostic factors of COVID-19 in renal transplant recipients. Given their immunosuppressed status, these patients are at higher risk of severe complications from COVID-19. The study aims to provide healthcare professionals with critical insights for diagnosing and managing this vulnerable population. This retrospective cohort study included adult renal transplant recipients diagnosed with COVID-19. Data on demographics, medical history, laboratory results, and patient outcomes were analyzed to identify clinical characteristics and prognostic factors. This study included 115 renal transplant recipients with COVID-19, predominantly male, with a mortality rate of 10.4% (12 deaths). The overall vaccination rate was 20%. Univariate analysis showed significant differences between survivors and non-survivors in initial serum creatinine levels, and percentages of neutrophils, monocytes, and lymphocytes, along with CRP levels on day 3. Additionally, CRP levels, hemoglobin, and platelet counts on day 7 also differed significantly. Multivariate analysis identified CRP levels on days 3 and 7, day 7 hemoglobin and platelet counts, and concurrent bacterial infections as independent risk factors for mortality. Elevated CRP levels, renal impairment, and bacterial co-infections play a significant role in the outcomes of COVID-19 in kidney transplant recipients. This study highlights the importance of monitoring these factors for early identification and management of high-risk patients.

Prognosis value of galectin-3 in patients with dilated cardiomyopathy: a meta-analysis.

Accurate prediction and assessment of myocardial fibrosis (MF) and adverse cardiovascular events (MACEs) are crucial in patients with dilated cardiomyopathy (DCM). Several studies indicate that galectin-3 (gal-3) as a promising prognostic predictor in patients with DCM. A comprehensive search was conducted in PubMed, EMBASE, the Cochrane Library, and Web of Science for relevant studies up to August 2023. The hazard ratios (HRs) of gal-3 for MACEs in DCM patients, and for MACEs in LGE(+) versus LGE(-) groups, were evaluated. Statistical analysis was performed using STATA SE 14.0 software. Seven studies, encompassing 945 patients, met the eligibility criteria. In DCM patients, abnormally elevated gal-3 levels were indicative of an increased MACEs risk (HR = 1.10, 95% CI [1.00-1.21], I2 = 65.7%, p=0.008). Compared with the LGE(-) group, the level of gal-3 in LGE(+) group was higher (HR = 1.12, 95% CI [1.05-1.19], I2 = 31.4%, p=0.233), and the combination of gal-3 and LGE significantly improved the prediction of MACEs. Sensitivity analysis confirmed the robustness of all results. This study's findings suggest that elevated gal-3 levels significantly correlate with increased MACE risk in DCM, highlighting its potential as a biomarker. However, significant heterogeneity among studies necessitates further research to ascertain gal-3's predictive and diagnostic value in DCM prognosis, particularly in conjunction with LGE. CRD42023471199.

Eosinophil Recovery Time Is Associated with Clinical Outcomes in Patients with Type A Acute Aortic Dissection: a Retrospective Cohort Study.

Type A acute aortic dissection (TA-AAD) patients are prone to life-threatening complications and death. This study aimed to analyze the association between eosinophil (EOS) recovery and clinical outcomes in TA-AAD. A total of 274 patients with TA-AAD were eligible for inclusion, and 54 patients died within 1month. The patients with poor clinical outcomes showed significantly lower EOS count within 8days after surgery. The time-dependent ROC analysis showed that EOS recovery days predicted 1-month death with an AUC of 0.886 and a cutoff of 6days. EOS recovery within 6days was associated with a lower incidence of postoperative infection, a poorer prognosis, and a lower risk of 1-month and 6-month mortality than those requiring more recovery days. Collectively, postoperative early recovery of EOS predicted lower mortality and better prognosis and may be applied as an effective, rapid, and simple tool for the risk stratification and prognostic prediction of patients with TA-AAD.Clinical trial registration number: NCT05409677.

Prognostic mutation signature would serve as a potential prognostic predictor in patients with diffuse large B-cell lymphoma

The present study aimed to elucidate the prognostic mutation signature (PMS) associated with long-term survival in a diffuse large B-cell lymphoma (DLBCL) cohort. All data including derivation and validation cohorts were retrospectively retrieved from The Cancer Genome Atlas (TCGA) database and whole-exome sequencing (WES) data. The Lasso Cox regression analysis was used to construct the PMS based on WES data, and the PMS was determined using the area under the receiver operating curve (AUC). The predictive performance of eligible PMS was analyzed by time-dependent receiver operating curve (ROC) analyses. After the initial evaluation, a PMS composed of 94 PFS-related genes was constructed. Notably, this constructed PMS accurately predicted the 12-, 36-, and 60-month PFS, with AUC values of 0.982, 0.983, and 0.987, respectively. A higher level of PMS was closely linked to a significantly worse PFS, regardless of the molecular subtype. Further evaluation by forest plot revealed incorporation of international prognostic index or tumor mutational burden into PMS increased the prediction capability for PFS. The drug-gene interaction and pathway exploration revealed the PFS-related genes were associated with DNA damage, TP53, apoptosis, and immune cell functions. In conclusion, this study utilizing a high throughput genetic approach demonstrated that the PMS could serve as a prognostic predictor in DLBCL patients. Furthermore, the identification of the key signaling pathways for disease progression also provides information for further investigation to gain more insight into novel drug-resistant mechanisms.

Glioblastoma and Internal Carotid Artery Calcium Score: A Possible Novel Prognostic Partnership?

Purpose: Clinical evidence suggests an association between comorbidities and outcome in patients with glioblastoma (GBM). We hypothesised that the internal carotid artery (ICA) calcium score could represent a promising prognostic biomarker in a competing risk analysis in patients diagnosed with GBM. Methods: We validated the use of the ICA calcium score as a surrogate marker of the coronary calcium score in 32 patients with lung cancer. Subsequently, we assessed the impact of the ICA calcium score on overall survival in GBM patients treated with radio-chemotherapy. Results: We analysed 50 GBM patients. At the univariate analysis, methyl-guanine-methyltransferase gene (MGMT) promoter methylation (p = 0.048), gross total tumour resection (p = 0.017), and calcium score (p = 0.011) were significant prognostic predictors in patients with GBM. These three variables also maintained statistical significance in the multivariate analysis. Conclusions: the ICA calcium score could be a promising prognostic biomarker in GBM patients.

Outcome predictors of post-COVID conditions in the European Academy of Neurology COVID-19 registry.

Several neurological manifestations are part of the post-COVID condition. We aimed to: (1) evaluate the 6-month outcome in the cohort of patients with neurological manifestations during the COVID-19 acute phase and surviving the infection, and find outcome predictors; (2) define the prevalence and type of neurological symptoms persistent at six months after the infection. Data source was an international registry of patients with COVID-19 infection and neurological symptoms, signs or diagnoses established by the European Academy of Neurology. Functional status at six-month follow-up was measured with the modified Rankin scale (mRS), and defined as: "stable/improved" if the mRS at six months was equal as or lower than the baseline score; "worse" if it was higher than the baseline score. By October 30, 2022, 1,003 lab-confirmed COVID-19 patients were followed up for a median of 6.5months. Compared to their pre-morbid status, 522 patients (52%) were stable/improved, whereas 465 (46%) were worse (functional status missing for 16). Age, hospitalization, several pre-COVID-19 comorbidities, and COVID-19 general complications were predictors of a worse status. Amongst neurological manifestations, stroke carried the highest risk for worse outcome (OR 5.96), followed by hyperactive delirium (2.8), and peripheral neuropathies (2.37). On the other hand, hyposmia/hypogeusia (0.38), headache (0.40), myalgia (0.45), and COVID-19 vaccination (0.52) were predictors of a favourable prognosis. Persisting neurological symptoms or signs were reported by 316/1003 patients (31.5%), the commonest being fatigue (n = 133), and impaired memory or concentration (n = 103). Our study identified significant long-term prognostic predictors in patients with COVID-19 and neurological manifestations.