Prognosis Factors Research Articles

The Prognosis in Children With Pneumonia of Respiratory Syncytial Virus Co-detection With Airway Dominant Flora.

Airway bacterial microbiota influences the prognosis in children with respiratory syncytial virus infection. The study aimed to investigate the effect of the airway-dominant bacterial microbiota on disease severity in children with pneumonia of respiratory syncytial virus infection. A retrospective study was conducted in the Children's Hospital of Chongqing Medical University, which involved a cohort of patients with respiratory syncytial virus (RSV)-infected pneumonia from January 2012 to December 2021. Patients were assigned to a normal flora group or to a dominant flora group (with the top 5 individual bacteria) based on the nasopharyngeal aspirates culture and matched using propensity-score matching. Univariate analysis and multivariate analysis were performed to estimate the risk factors of poor prognosis in dominant flora. Five thousand five hundred and twelve patients in the normal flora and 4556 in the dominant flora were included ( Escherichia coli 514, Streptococcus pneumoniae 1516, Staphylococcus aureus 506, Moraxella catarrhalis 509 and Haemophilus influenzae 1516, respectively). The dominant flora had more patients developing severe pneumonia, needing mechanical ventilation/tracheal intubation (up to 15.8% in the S. aureus ) and admission to the intensive care unit (up to 4.5% in the E. coli ) than in the normal flora (28.5% vs. 25.9%; P = 0.001; 9.8% vs. 5.4%; P < 0.001; 2.0% vs. 1.2%; P <0.001). And the hospitalization was longer in the dominant flora than in the normal flora [8 (6-9) vs. 8 (7-9) days; P < 0.001], the E. coli and S. aureus had the longest hospitalization [8 (7-10) days]. Several factors were associated with critical illness in Dominant flora according to multivariate analysis ( P < 0.001), including age (OR: 0.965; CI: 0.954-0.976; P < 0.001), anhelation (OR: 0.530; CI: 0.446-0.631; P < 0.001), disorders of consciousness (OR: 0.055; CI: 0.016-0.185; P < 0.001) as well as assisted respiration (OR: 0.115; CI: 0.097-0.138; P < 0.001), C-reactive protein >10 mg/L (OR: 0.686; CI: 0.560-0.839; P < 0.001), SpO 2 <90% (OR: 0.366; CI: 0.214-0.628; P < 0.001), pulmonary consolidation (OR: 0.511; CI: 0.364-0.717; P < 0.001) and pulmonary atelectasis (OR: 0.362; CI: 0.236-0.555; P < 0.001). The airway-dominant bacterial microbiota influenced disease severity and comorbidities in children with RSV-infected pneumonia. Clinicians should pay attention to the nasopharyngeal aspirate culture, especially after detecting S. aureus and E. coli in RSV-infected children with pneumonia, closely observe the disease progression and take timely measures to avoid adverse outcomes.

Comparative study of machine learning and statistical survival models for enhancing cervical cancer prognosis and risk factor assessment using SEER data.

Cervical cancer is a common malignant tumor of the female reproductive system and the leading cause of death among women worldwide. The survival prediction method can be used to effectively analyze the time to event, which is essential in any clinical study. This study aims to bridge the gap between traditional statistical methods and machine learning in survival analysis by revealing which techniques are most effective in predicting survival, with a particular emphasis on improving prediction accuracy and identifying key risk factors for cervical cancer. Women with cervical cancer diagnosed between 2013 and 2015 were included in our study using data from the Surveillance, Epidemiology, and End Results (SEER) database. Using this dataset, the study assesses the performance of Weibull, Cox proportional hazards models, and Random Survival Forests in terms of predictive accuracy and risk factor identification. The findings reveal that machine learning models, particularly Random Survival Forests (RSF), outperform traditional statistical methods in both predictive accuracy and the discernment of crucial prognostic factors, underscoring the advantages of machine learning in handling complex survival data. However, for a survival dataset with a small number of predictors, statistical models should be used first. The study finds that RSF models enhance survival analysis with more accurate predictions and insights into survival risk factors but highlights the need for larger datasets and further research on model interpretability and clinical applicability.

Specific cancer types and prognosis in patients with variations in the KEAP1-NRF2 system: A retrospective cohort study.

The KEAP1-NRF2 system induces the expression of antioxidant genes in response to various types of oxidative stress. Some cancer cells activate this system, which increases their malignancy through genetic mutations. We performed a retrospective cohort study using the C-CAT database, which contains the gene-panel sequence data from 60,056 cases of diagnosed solid tumors. We analyzed somatic mutations in NRF2 and KEAP1 genes and their associations with clinical outcomes. Variants in the NRF2 gene were clustered in exon 2, which encodes the DLG and ETGE motifs essential for KEAP1 interaction. The NRF2 variants were frequently observed in esophageal and lung squamous cell carcinoma with frequencies of 35.9% and 19.6%, respectively. Among these mutations, the NRF2 variants in the ETGE motif were indicators of a worse prognosis. KEAP1 variants were found in 2.5% of all cases. The variants were frequent in lung cancer and showed a worse prognosis in lung and other types of adenocarcinomas. We then conducted gene expression analysis using TCGA data. While cancers with DLG and ETGE variants were similar in terms of gene expression profiles, there were significant differences between cancers with KEAP1 and NRF2 variants. Our results indicate that genetic alteration of the KEAP1-NRF2 pathway is a major factor in patient prognosis for each cancer type and its genetic variant. Variants in NRF2 and KEAP1 genes can characterize the biological basis of each cancer type and are involved in carcinogenesis, resistance to therapy, and other biological differences.

A prognostic prediction model for acute pulmonary embolism.

Acute pulmonary embolism (APE) is a very common and important medical emergency in intensive care units with an unfavorable prognosis. This study aims to explore the prognostic factors of APE and to construct a prognostic prediction model. A retrospective analysis was conducted on 252 APE patients in the emergency department of our hospital from January 2020 to March 2024. The initial observation endpoint was set as the mortality status of patients within 30 days of admission. Cox multivariate regression analysis was used to identify independent risk factors for prognosis. Based on these factors, a nomogram predictive model was constructed and evaluated using R software. Within 30 days of admission, 42 patients died with an overall mortality rate of 16.6% (42/252). Binary Cox multivariate regression analysis indicated that age ≥ 62.5 (HR: 2.64, 95% CI: 1.23-5.63, p = 0.012), right ventricular dysfunction (RVD) (HR: 4.58, 95% CI: 1.76-11.96, p = 0.002), white blood cell count (WBC) ≥ 13.1 (HR: 2.35, 95% CI: 1.20-4.60, p = 0.013), albumin/fibrinogen ratio (AFR) < 9.15 (HR: 3.36, 95% CI: 1.76-6.42, p < 0.001), Prognostic Nutritional Index (PNI) < 50.3 (HR: 4.35, 95% CI: 1.62-11.71, p = 0.004), and Systemic Inflammation Response Index (SIRI) ≥ 1.05 (HR: 7.21, 95% CI: 3.38-15.37,p < 0.001) were independent risk factors for mortality. The nomogram model based on these factors demonstrated a good predictive value for 30-day mortality, with an AUC of 0.908. The nomogram model based on age, RVD, WBC, AFR, PNI, and SIRI has a well prognostic value for APE patients.

Impact of excessive daytime sleepiness on the progression of freezing of gait in de novo Parkinson's disease: a cohort study.

Excessive daytime sleepiness (EDS) and freezing of gait (FOG) are prevalent non-motor and motor symptoms in patients with Parkinson's disease (PD), significantly impacting their quality of life. However, the correlation between EDS and FOG progression inde novoPD patients remains controversial. A total of 328 participants from the Parkinson's Progression Markers Initiative (PPMI) were divided into two groups: 43 with EDS (EDS group) and 285 without EDS (nEDS group). The cumulative incidence of FOG was assessed at the 5-year follow-up using Kaplan-Meier and log-rank tests. Multivariate Cox proportional hazards models were used to assess the impact of EDS on FOG progression in PD patients, with validation for robustness through sensitivity and subgroup analyses. The EDS group experienced a higher incidence of FOG throughout the 5-year follow-up than did the nEDS group. Multivariate Cox proportional hazards models showed significantly association between EDS severity and enhanced risk of developing FOG (HR = 1.076, 95% CI:1.007 ~ 1.149, P = 0.031). For sensitivity analysis, parallel analyseswere performedby substituting the independent variable with categorical variables, which yielded analogous outcomes (HR = 1.837, 95% CI:1.063 ~ 3.174,P = 0.029). Furthermore, subgroup analyses based on sex, age, TD/PIGD classification, depressive symptoms, cognitive impairment, mean caudate nucleus uptake level, mean putamen nucleus uptake level and CSF Aβ-42 level revealed no significant interactions between subgroups (allPvalues for interaction were > 0.05). EDS is a potential prognosis factor for the progression of FOG in patients with PD.

Research progress on the distribution patterns and surgical dissection of central lymph nodes in left-sided colon cancer

Lymphatic metastasis is one of the main pathways of colorectal cancer spread and also a crucial factor in patient long-term prognosis. Lymph node dissection in the possible tumor drainage area, particularly the central group of lymph nodes at the root of the tumor-associated supplying artery, is a key and challenging aspect of surgical techniques. Currently, the patterns of lymphatic drainage and the distribution of central lymph nodes in left-sided colon cancer are not well illustrated, and there is no consensus on the necessity and extent of central lymph node dissection. This has led to significant variability in the extent of lymph node dissection among different surgeons in clinical practice, a lack of quality control standards for surgical procedures, and impacts on postoperative treatment strategy and long-term outcomes. Moreover, current research on lymphatic drainage and metastasis is primarily based on traditional anatomy, whereas individualized, precise approaches to lymph node dissection have not been realized. The application of preoperative and intraoperative lymph node imaging techniques based on functional anatomy in colorectal cancer patients is still under exploration.

Individualized evaluation of risk and prognosis in uterine leiomyosarcoma patients with synchronous distant metastases: a real-world retrospective study.

Uterine leiomyosarcoma (uLMS) accounts for roughly 70% of all uterine sarcomas, with recurrence and mortality rates notably higher than those of other uterine tumors. The prognosis of uLMS patients who have distant metastases remains poor. The objective of this study was to determine independent risk variables related to distant metastases in patients with uLMS and prognostic factors for those with distant metastases. Subsequently, two practical nomograms were developed and validated to assess the probability of distant metastases and predict survival outcomes for these with distant metastases, respectively. A real-world retrospective study was carried out using data from patients diagnosed with primary uLMS in the Surveillance, Epidemiology, and End Results (SEER) database spanning the years 2010 to 2015. Univariate andmultivariate logistic regression analyses were utilized to identify clinicopathological characteristics related to the risk of distant metastases, while univariate and multivariate Cox regressions were employed to determine prognostic factors. Then, a risk nomogram incorporating independent risk variables and a prognostic nomogram integrating independent prognostic factors were established in the training cohort and validated for accuracy in the validation cohort, respectively. Receiver operating characteristic (ROC) curves, area under the curve (AUC), and calibration curves were utilized to measure the accuracy of nomograms, while decision curve analysis (DCA) curves were employed to assess their clinical benefit capacity. Based on the median total point derived from the prognostic nomogram, patients were stratified into high- and low-risk groups. The differentiation ability of the prognostic nomogram was evaluated using Kaplan-Meier survival analysis with the log-rank test. The study encompassed 1,362 patients diagnosed with uLMS, among whom 337 cases (24.7%) manifested synchronous distant metastases at the initial diagnosis. Univariate and multivariate logistic regression analyses identified race, histological grade, T stage, N stage, tumor size, surgery, and chemotherapy as independent risk factors for distant metastases in uLMS patients. The outcomes of both univariate and multivariate Cox analyses indicated that surgery and chemotherapy emerged as independent protective factors for prognosis in uLMS patients with distant metastases, whereas higher histological grade and T stage were identified as independent risk factors. The risk nomogram incorporating independent risk variables and the prognostic nomogram integrating independent prognostic factors could respectively predict the risk of metastases and the prognosis very effectively in both training and validation cohorts. In summary, we developed the novel well-validated risk nomogram to precisely assess the probability of metastases in uLMS patients and prognostic nomogram to predict the prognosis of those with distant metastases, providing decision-making guidance for tailoring individualized clinical management of these patients.

Predictive Factors for Poor Prognosis in Non-Surgical Treatment of Proximal Humerus Fractures in Elderly Patients.

Proximal humerus fractures (PHF) are common in the elderly, accounting for significant morbidity and mortality. Non-surgical treatment is a common option for low-demand elderly patients, but it can lead to unsatisfactory functional outcomes in some cases.The identification of predictive factors for poor prognosis in non-surgical management remains unclear. This study aimed to determine the predictive factors for poor prognosis in elderly patients treated non-surgically for displaced PHF and to assess associated complications. A retrospective cohort study was conducted involving patients aged 60 years or older with displaced PHF treated non-surgically from May 2020 to January 2023 at a reference hospital for orthopedic trauma. The primary outcome was functional assessment using the American Shoulder and Elbow Surgeons (ASES) scale at 12 months. Predictive factors such as metaphyseal fracture comminution, Pain Catastrophizing Scale (PCS) scores, and radiographic criteria were analyzed. Multivariate regression analyses were performed to identify independent predictors of poor outcomes. Out of 140 initially selected patients, 103 met the inclusion criteria and completed the follow-up. The mean ASES score was 71.3±25.4 points. Multivariate analysis identified metaphyseal comminution (p < 0.001) and PCS scores ≥ 30 (p < 0.001) as significant predictors of poorer functional outcomes. Complications were observed in 17.4% of patients, including osteonecrosis (6.7%), nonunion (4.9%), and persistent pain and stiffness (5.8%). Metaphyseal comminution and high PCS scores are significant predictors of poor prognosis in elderly patients undergoing non-surgical treatment for displaced PHF. These findings highlight the importance of considering both biomechanical and psychological factors when managing proximal humerus fractures in this population. Further studies with larger sample sizes and prospective designs are needed to validate these findings and refine treatment strategies.

Gut microbiota dysbiosis and neurological function recovery after intracerebral hemorrhage: an analysis of clinical samples.

We aimed to investigate the microbial community composition in patients with intracerebral hemorrhage (ICH) and its effect on prognosis. We designed two clinical cohort studies to explore the gut dysbiosis after ICH and their relationship with neurological function prognosis. First, fecal samples from patients with ICH at three time points: T1 (within 24 h of admission), T2 (3 days after surgery), and T3 (7 days after surgery), and healthy volunteers were subjected to 16S rRNA sequencing using Illumina high-throughput sequencing technology. When differential gut microbiota was identified, the correlation between clinical indicators and microbiotas was analyzed. Subsequently, the patients with ICH were categorized into GOOD and POOR groups based on their Glasgow Outcome Scale Extended (GOS-E) score, and the disparities in gut microbiota between the two groups were assessed. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors. The composition and diversity of the gut microbiota in patients with ICH were different from those in the control group and changed dynamically with the extension of the course of cerebral hemorrhage. The abundances of Enterococcaceae, Clostridiales incertae sedis XI, and Peptoniphilaceae were significantly increased in patients with ICH, whereas Bacteroidaceae, Ruminococcaceae, Lachnospiraceae, and Veillonellaceae were significantly reduced. The relative abundance of Enterococcus gradually increased with the extension of the duration of ICH after surgery, and the abundance of Bacteroides gradually decreased. The abundance of Enterococcus before surgery was found to be negatively associated with patient neurological function prognosis. The original ICH score and Lachnospiraceae status were independent risk factors for predicting the prognosis of neurological function in patients with ICH (P < 0.05). Changes in the gut microbiota diversity in patients with ICH were related to prognosis. Lachnospiraceae may have a protective effect on prognosis.IMPORTANCEAcute central nervous system injuries like hemorrhagic stroke are major global health issues. While surgical hematoma removal can alleviate brain damage, severe cases still have a high 1-month mortality rate of up to 40%. Gut microbiota significantly impacts health, and treatments like fecal microbiota transplantation (FMT) and probiotics can improve brain damage by correcting gut microbiota imbalances caused by ischemic stroke. However, few clinical studies have explored this relationship in hemorrhagic stroke. This study investigated the impact of cerebral hemorrhage on the composition of gut microbiota, and we found that Lachnospiraceae were the independent risk factors for poor prognosis in intracerebral hemorrhage (ICH). The findings offer potential insights for the application of FMT in patients with ICH, and it may improve the prognosis of patients.

The Impact of Body Composition on Mortality and Hospital Length of Stay after Endovascular and Open Aortic Aneurysm Repair: A Retrospective Cohort Study.

Background: Sarcopenia is an indicator of preoperative frailty and a patient-specific risk factor for poor prognosis in elderly surgical patients. Some studies have explored the prognostic significance of body composition parameters in relation to perioperative mortality after aortic repair and to mid- and long-term survival following endovascular aneurysm repair (EVAR). This study aimed to comprehensively investigate the effects of various body composition parameters, including but not limited to sarcopenia, on short- and long-term mortality as well as the length of hospital stay in two large cohorts of patients undergoing open surgical aortic repair (OSR) or EVAR. Methods: A single-institution retrospective cohort study included patients who underwent EVAR or OSR from January 2010 to December 2017. Several parameters of body composition on axial CT angiography images were analyzed, such as skeletal muscle area (SMA) with derived skeletal muscle index (SMI), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT). Results: 477 patients were included: 250 treated by OSR and 227 by EVAR; the mean age was 70.8 years (OSR) and 76.3 years (EVAR), with a mean follow-up of 54 months. Sarcopenia was associated with a prolonged length of hospital stay in EVAR patients but not in OSR patients (β coefficient 3.22; p-value 0.022 vs. β coefficient 0.391; p-value 0.696). Sarcopenia was an elevated one-year mortality risk post-EVAR compared to those without sarcopenia (p-value for the log-rank test 0.05). SMA and SMI were associated with long-term mortality in EVAR patients even after adjusting for multiple confounders (HR 0.98, p-value 0.003; HR 0.97, p-value 0.032). The analysis of the OSR cohort did not show a significant correlation between short- and long-term mortality and sarcopenia indicators. Conclusions: The results suggest that body composition could predict increased mortality and longer hospital stays in patients undergoing EVAR procedures. These findings were not confirmed in the cohort of patients who underwent OSR. Patients with sarcopenia and pre-operative malnutrition should be critically assessed to define the indication for treatment in this predominantly elderly and morbid cohort, despite EVAR procedures being less invasive. Body composition evaluation is an inexpensive and reproducible tool that can contribute to an improved decision-making process by identifying patients who will benefit most from EVAR, ensuring a more personalized and cost-effective treatment strategy. Further studies are planned to explore the added value of integrating body composition into a comprehensive risk stratification before aortic surgery.

Quantitative changes in platelet count in response to different pathogens: an analysis of patients with sepsis in both retrospective and prospective cohorts

Background Thrombocytopenia is commonly observed in patients with sepsis and is an independent risk factor for poor prognosis. However, the changes of platelet count caused by different pathogens can vary significantly. Our study aims to evaluate the quantitative changes in platelet count in response to various pathogens. Material and Methods We retrospectively analysed data of 3044 patients with sepsis from Medical Information Mart for Intensive Care (MIMIC, 2008–2019) database and prospectively collected data of 364 patients with sepsis from our local cohort of the Shandong Bloodstream Infection and Sepsis Collaboration Study (SBISC, 2020–2022). Propensity score matching (PSM) was employed to control for baseline differences in variables, except for the causative pathogen. Results Multivariate logistic analyses of both original and PSM populations identified Candida, Escherichia, Klebsiella, and Serratia species posing a higher risk for thrombocytopenia compared to others. Restricted cubic spline (RCS) curves showed L- or U-shaped associations between platelet count and 28-mortality with various cut-off values among different pathogens: ranging from 96 × 109/L in Candida species − 190 × 109/L in Klebsiella species. Conclusion Our present findings indicate a pathogen-specific effect on platelet count, highlighting the importance of monitoring thrombocytopenia in patients infected with above microorganisms. Clinicians need to consider pathogen-specific thresholds when intervene on platelet count.

Serum Klotho Is Elevated in Patients with Acute Myocardial Infarction and Could Predict Poor In-Hospital Prognosis.

Klotho has emerged as a potential protective factor for cardiovascular diseases recently. Nevertheless, the levels of serum Klotho in acute coronary syndrome (ACS) have not been reported. Hence, we undertook a study to investigate the potential correlation between serum Klotho and ACS patients. This observational cohort study was conducted at Peking University People's Hospital between May 2016 and April 2020. Upon admission, we collected the patients' clinical data and conducted ELISA tests to measure their serum Klotho levels. A total of 349 patients were enrolled in this study, including 14 patients with UA and 335 patients with AMI. We observed that serum Klotho levels were obviously higher in the AMI group compared to the UA group (median 479.8 vs. 233.8 pg/mL, p = 0.035). In addition, serum Klotho levels were positively correlated with cardiac function and more pronounced in patients who died in the hospital (median 721.1 vs. 468.3 pg/mL, p < 0.001). A logistic regression analysis indicated that age ≥ 78 years old, HR ≥ 90 bpm, Killip classification ≥ 3 grade, and serum Klotho > 645.0 pg/mL were risk factors for poor prognosis. Serum Klotho is obviously increased in patients with AMI and with a positive correlation with cardiac function, and its elevation could serve as a predictor of poor prognosis in ACS patients.

Clinicopathological Features and Outcomes of Perioperative Treatment for Small Cell Carcinoma of the Bladder

Small cell carcinoma of the bladder (SCCB) is a rare malignant tumor of the bladder. This study aims to explore its clinicopathological features and prognostic factors and to explore the role of perioperative treatment methods. The clinical data of SCCB patients admitted to West China Hospital, Sichuan University over 8 years from January 2016 to January 2024 were collected. The clinicopathological features of SCCB were summarized. The survival outcomes and prognostic factors were analyzed. The effect of perioperative treatment on the improvement in prognosis was explored. A total of 31 confirmed cases of SCCB were enrolled. We observed a number of clinicopathologic features. All cases had advanced clinical staging, with the T staging status being above T2 in all cases, and distant metastasis was found in 23% of the newly diagnosed cases. A high proportion of the SCCB cases were combined with other histologic types, with 96% showing combination with urothelial carcinoma (UC). The SCCB patients had a poor prognosis, presenting a median survival of 12 months, 1-year overall survival (OS) of 57.9%, and 3-year OS of 27.6%. Patients with extensive-stage SCCB had a significantly worse prognosis than those with limited-stage SCCB did (median OS time of 17.0 months vs. 4.4 months, P<0.05). In limited-stage SCCB, the median OS of patients who underwent radical cystectomy (RC) was 19.9 months, while that of the patients who did not undergo RC was 15.2 months (P<0.05). The OS of patients who received perioperative therapy in combination with RC had longer OS than those who received only RC did (P<0.05). Among these, patients recevied neoadjuvant therapy (NAT) had a significantly longer OS than patients who didn't receive NAT (P<0.05). Subgroup analysis revealed that patients who were responsive to neoadjuvant therapy had longer disease-free survival and longer OS than those who were not responsive did (P<0.05). Lymph node metastasis was an independent factor of poor prognosis (hazard ratio [HR]=15.21, 95% confidence interval [CI]: 1.732-133.912, P=0.014). NAT prior to RS was an independent protective factor, significantly reducing the risk of death compared with RC alone (HR=0.03, 95% CI: 0.001-0.724, P=0.031). RC is an effective treatment that prolongs the survival of patients with limited-stage SCCB. RS combined with NAT can further improve their survival.

Plasma Cytokines Pattern as a Prognostic Marker for Esophageal Squamous Cell Carcinoma via Unsupervised Clustering Analyses

Introduction: Cytokines such as tumor necrosis factor-alpha (TNF-α), interleukin 6 (IL6), interferon-gamma (IFN-γ), interleukin 17-alpha (IL17-α), and interleukin 33 (IL33) play critical roles in immune responses and may impact cancer prognosis in future. However, few studies have simultaneously explored the prognostic impact of these cytokines for cancer. In this study, we aim to apply the unsupervised clustering analysis to approach the correlation between the expression of these cytokines and the subsequent prognosis of patients with esophageal squamous cell carcinoma (ESCC). Methods: A robust clustering algorithm was used, the Gaussian mixture method (GMM), through the mclust R package to group patients based on the expression of their cytokines in plasma or tumors. The 324 NTU patients were grouped into 4 clusters, and the 179 GSE53625 patients were grouped into 3 clusters based on expression in plasma and tumors, respectively. Five- and 3-year overall survival (OS) and progression-free survival (PFS) curves of each cluster were compared. Univariate and multivariate Cox regression analyses were also performed. Results: We successfully distinguished the multimodal distribution of cytokines through GMM clustering and discovered the relationship between cytokines and clinical outcomes. We observed that NTU-G3 and NTU-G4 subgroups showed most variation in 5-, 3-year OS and 5-, 3-year PFS with NTU-G3 being associated with poorer prognosis compared to NTU-G4 (p = 0.016, 0.0052, 0.0575, and 0.0168, respectively). NTU-G3 was characterized with higher TNF-α (median = 3.855, N = 78) and lower IL33 (median = 0.000, N = 78), while NTU-G4 showed lower TNF-α (median = 1.76, N = 51) and higher IL33 (median = 1.070, N = 51). The difference was statistically significant for TNF-α and IL33, with p = 0.0002 and p < 0.0001, respectively. A multivariate Cox-regression analysis revealed that GMM clustering and T/N stage were independent factors for prognosis, suggesting that the prognosis might be dependent on these cytokines. Conclusions: Our data suggest that expression patterns of IL33 and TNF-α in plasma might serve as a convenient marker to predict the prognosis of ESCC in the future.

Clinical characteristics and prognostic factors of pulmonary and extrapulmonary cryptococcosis

BackgroundCryptococcosis is progressively acknowledged among people, irrespective of the human with or without immunodeficiency virus (HIV). This change in epidemiology has been recorded in recent years, prompting closer examination and a broader understanding of the disease manifestations and risk factors.MethodsThe data of cryptococcal infections in China during 11 years were retrospectively analyzed. According to the position of infection, the patients were categorized into the pulmonary infection group and extrapulmonary infection group. The composition of the two groups was compared, and the potential risk factors of disseminated infection were analyzed. Logistic regression was used to analyze the prognostic risk factors of the disease.ResultsA total of 165 patients were enrolled. 113 (68.5%) were male, and the age was 47.49 (18–82) years. 101 cases (61.2%) had a normal immune function and 64 cases (38.8%) had impaired immune function. 45 patients had extrapulmonary infection, involving the central nervous system, bone and joint, skin and bloodstream, and 120 patients had simple pulmonary infection. The mortality of the extrapulmonary infection group (48.9%) was significantly higher than that of the pulmonary infection group (0.8%). According to univariate logistic regression analysis, immune status (hazard ratio [HR], 4.476; 95% confidence interval [CI], 1.725–11.618; P = 0.002), infection position ([HR], 113.826; [CI], 14.607-886.967; P < 0.001), white blood cell count, ([HR],1.209;[CI], 1.054–1.386; P = 0.007), hemoglobin ([HR], 0.970; [CI], 0.955–0.986; P < 0.001), platelet count ([HR], 0.993; [CI], 0.987–0.999; P = 0.026), neutrophil percentage ([HR], 1.115; [CI], 1.065–1.168; P < 0.001), lymphocyte percentage ([HR], 0.875; [CI], 0.827–0.927; P < 0.001), neutrophil-to-lymphocyte Ratio (NLR) ([HR], 1.144; [CI], 1.072–1.221; P < 0.001), monocyte percentage ([HR], 0.752; [CI], 0.618–0.915; P = 0.004) were related to the prognosis. Multivariate logistic regression analysis showed that the infection position was remained related to the prognosis with statistical significance ([HR], 0.018; [CI], 0.001–0.384; P = 0.001).ConclusionExtrapulmonary infection of Cryptococcosis is an important risk factor for prognosis. High levels of neutrophils and NLR, and low levels of lymphocytes and monocytes may lead to disseminated infection of Cryptococcosis. Further studies are needed to reduce the occurrence rate of extrapulmonary infection and mortality.

EGFR-Tyrosine Kinase Inhibitor Combined with Radiotherapy in 105 Patients of Lung Adenocarcinoma with Brain Metastasis: A Retrospective Study of Prognostic Factor Analysis

Introduction: This study aimed to retrospectively analyse the response and prognosis factors for patients with lung adenocarcinoma exhibiting brain metastasis and epidermal growth factor receptor (EGFR) mutations, who were treated with a combination of EGFR-tyrosine kinase inhibitor (TKI) and brain radiotherapy (RT). Methods: Clinicopathological data of patients with lung adenocarcinoma were collected from January 2021 to January 2024 at the First Affiliated Hospital of Hebei North University. Statistical analysis was performed using SPSS version 26.0, with significance set at p < 0.05. Results: A total of 105 patients were included. The overall survival (OS) rates at 1, 2, and 3 years were 82.9%, 61.2%, and 33.7%, respectively. The progression-free survival 1 (PFS1) rates at 1, 2, and 3 years were 62.7%, 36.6%, and 22.1%, respectively. The progression-free survival 2 (PFS2) rates at 1, 2, and 3 years were 80.8%, 54.6%, and 31.4%, respectively. The median OS, PFS1, and PFS2 were 29.8, 18.0, and 28.1 months, respectively. Cox multivariate analysis identified gene mutation status and brain radiation dose as independent prognostic factors for OS. For PFS1, gene mutation status, brain radiation dose, and initial treatment response were independent prognostic factors. Clinical stage, gene mutation status, brain radiation dose, and initial treatment response were independent prognostic factors for PFS2. Conclusion: The combination of TKIs and brain RT is effective for patients with lung adenocarcinoma with EGFR mutations and brain metastases. Patients with exon 19 Del or exon 21 L858R mutations and brain radiation doses ≥40 Gy exhibit longer OS, PFS1, and PFS2. Additionally, complete remission + partial remission is associated with extended PFS1 and PFS2, while patients in stage IVA show longer PFS2.

The early prognostic value of the 1–4-day BCM/PA trend after admission in neurocritical patients

The purpose of this study was to investigate early stage dynamic changes in relevant indicators in neurocritical patients to identify biomarkers that can predict a poor prognosis at an early stage (1–4 days after admission). This study retrospectively collected clinical data, inflammatory indicators, and nutritional indicators from 77 patients at the neurology intensive care unit. The 3-month modified Rankin scale score was used as the outcome indicator. A linear mixed model was used to analyze changes in inflammatory indicators and nutritional indicators in neurocritical patients over time from 1–4 days after admission. Logistic regression was used to determine the independent risk factors for a poor prognosis in neurocritical patients and to construct a predictive model. The predictive efficacy of the model was verified using leave-one-out cross-validation and decision curve analysis methods. The analysis results showed that 1–4 days after admission, the inflammatory indicators of white blood cell and absolute monocyte counts and the nutritional indicators of body cell mass(BCM), fat-free mass, body cell mass/phase angle (BCM/PA), intracellular water, extracellular water, and skeletal muscle index increased overall, while the nutritional indicators of albumin and visceral fat area decreased overall. The logistic multivariate regression model showed that the Charlson comorbidity index (CCI) (odds ratio (OR) = 2.526, 95% CI [1.202, 5.308]), hemoglobin (Hb)(on admission)-Hb(min) (OR = 1.049, 95% CI [1.015, 1.083), BCM(on admission) (OR = 0.794, 95% CI [0.662, 0.952]), and the change in BCM/PA 1–4 days after admission (OR = 1.157, 95% CI [1.070, 1.252]) were independent risk factors for a poor prognosis in neurocritical patients. The predictive analysis showed that the predictive power of Model 1 with BCM/PA (area under the curve (AUC) = 0.95, 95% CI (0.90, 0.99)) was 93%, 65%, 141%, and 133% higher than that of Model 2 without BCM/PA, the CCI, the APACHE II score, and the NRS2002 score (all P < 0.05), respectively. The CCI, Hb(on admission)-Hb(min), BCM(on admission), and an increase in BCM/PA 1–4 days after admission were independently associated with a poor prognosis in neurocritical patients. Of these variables, BCM/PA may be a valid indicator for early stage prediction of a poor prognosis in neurocritical patients.

Predicting ICU Readmission from Electronic Health Records via BERTopic with Long Short Term Memory Network Approach.

Background: The increasing rate of intensive care unit (ICU) readmissions poses significant challenges in healthcare, impacting both costs and patient outcomes. Predicting patient readmission after discharge is crucial for improving medical quality and reducing expenses. Traditional analyses of electronic health record (EHR) data have primarily focused on numerical data, often neglecting valuable text data. Methods: This study employs a hybrid model combining BERTopic and Long Short-Term Memory (LSTM) networks to predict ICU readmissions. Leveraging the MIMIC-III database, we utilize both quantitative and text data to enhance predictive capabilities. Our approach integrates the strengths of unsupervised topic modeling with supervised deep learning, extracting potential topics from patient records and transforming discharge summaries into topic vectors for more interpretable and personalized predictions. Results: Utilizing a comprehensive dataset of 36,232 ICU patient records, our model achieved an AUROC score of 0.80, thereby surpassing the performance of traditional machine learning models. The implementation of BERTopic facilitated effective utilization of unstructured data, generating themes that effectively guide the selection of relevant predictive factors for patient readmission prognosis. This significantly enhanced the model's interpretative accuracy and predictive capability. Additionally, the integration of importance ranking methods into our machine learning framework allowed for an in-depth analysis of the significance of various variables. This approach provided crucial insights into how different input variables interact and impact predictions of patient readmission across various clinical contexts. Conclusions: The practical application of BERTopic technology in our hybrid model contributes to more efficient patient management and serves as a valuable tool for developing tailored treatment strategies and resource optimization. This study highlights the significance of integrating unstructured text data with traditional quantitative data to develop more accurate and interpretable predictive models in healthcare, emphasizing the importance of individualized care and cost-effective healthcare paradigms.

Lymphocyte to high density lipoprotein ratio can predict the short-term prognosis of hepatitis B virus-related acute-on-chronic liver failure patients

BackgroundAcute-on-chronic liver failure (ACLF) is a syndrome characterized by systemic inflammation, leading to high short-term mortality. The lymphocyte to high-density lipoprotein ratio (LHR) has been introduced as a novel marker of inflammation. However, its role as a prognostic inflammatory biomarker in the context of hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) has received limited attention. MethodsWe retrospectively included 272 patients with HBV-ACLF who met the definition of APALC. Data on clinical features and laboratory tests were collected from medical records within 24 h. Logistic regression was used to identify risk factors for poor short-term prognosis, and LHR-based prediction (LHRB) models were constructed based on risk factors. Furthermore, the accuracy of the LHRB model was validated through rigorous testing. ResultsIn the survival and death groups, there were statistical differences in their CTP, MELD, MELD-Na, COSSH-ACLF II scores, and LHR. Multivariate logistic regression identified seven predictors significantly associated with 28-day mortality. Furthermore, statistically significant differences in short-term mortality and certain clinical laboratory tests for poor prognosis were observed between the high and low LHR groups. To assess the predictive performance of various models in terms of short-term mortality, the area under the receiver operating characteristic curve (AUROC) was calculated. The AUROC values for the CTP, MELD, MELD-Na, COSSH-ACLF II, and LHRB models were found to be 0.725, 0.788, 0.772, 0.871, and 0.877, respectively. The results in the validation group were similar to those in the training group, and the validation results suggested excellent performance of the LHRB model. ConclusionLHR levels have the potential to serve as indicators for the prognosis of HBV-ACLF. Additionally, the recently developed LHRB model offers an accessible risk assessment tool.

Anti-melanoma differentiation-associated gene-5 antibody-positive dermatomyositis with liver dysfunction: a warning sign of higher death risk.

This study aimed to investigate and analyze the clinical and immunological features of patients with anti-melanoma differentiation-associated gene-5 antibody-positive dermatomyositis (MDA5 + DM) complicated with clinical liver dysfunction. A cohort of 85 patients diagnosed with MDA5 + DM admitted into Peking University People's Hospital from 2006 to 2023 were retrospectively enrolled in this study. Clinical characteristics and survival status were collected and analyzed. Clinical liver dysfunction occurred in 28% (24/85) of MDA5 + DM patients. Patients with clinical liver dysfunction were more likely to have muscle impairment (83.3% vs. 52.5%, P = 0.009) and rapidly progressive ILD (72.7% vs. 47.4%, P = 0.027). Lactate dehydrogenase (LDH) (378.5 (296.0,453.8) U/L vs. 280.0 (218.0,355.0) U/L, P = 0.002) and ferritin (FER) (883.0 (279.8,2100.5) ng/mL vs. 293.5.0 (84.0,862.7) ng/mL, P = 0.040) were significantly elevated and total numbers of lymphocytes (827.2 ± 517.2 /μL vs. 1301.8 ± 720.9 /μL, P = 0.042), and CD4 + T cells (403.8 ± 315.9 /μL vs. 548.6 ± 257.7 /μL, P = 0.045) were significantly decreased in patients with clinical liver function. Muscle weakness (OR 5.184, 95% CI 1.305, 20.595, P = 0.019) was identified as an independent risk factor for clinical liver dysfunction. Clinical liver dysfunction was identified as an independent risk factor for poor prognosis in patients with MDA5 + DM (HR = 4.030, 95% Cl 1.233, 13.176, P = 0.021), with an 18-month survival rate of 69%. Liver dysfunction is one of the extramuscular manifestations in patients with MDA5 + DM and might be associated with a poor prognosis.