Assessing the prognostic utility of clinical and radiomic features for COVID-19 patients admitted to ICU: challenges and lessons learned.

Severe cases of COVID-19 often necessitate escalation to the Intensive Care Unit (ICU), where patients may face grave outcomes, including mortality. Chest X-rays play a crucial role in the diagnostic process for evaluating COVID-19 patients. Our collaborative efforts with Michigan Medicine in monitoring patient outcomes within the ICU have motivated us to investigate the potential advantages of incorporating clinical information and chest X-ray images for predicting patient outcomes. We propose an analytical workflow to address challenges such as the absence of standardized approaches for image pre-processing and data utilization. We then propose an ensemble learning approach designed to maximize the information derived from multiple prediction algorithms. This entails optimizing the weights within the ensemble and considering the common variability present in individual risk scores. Our simulations demonstrate the superior performance of this weighted ensemble averaging approach across various scenarios. We apply this refined ensemble methodology to analyze post-ICU COVID-19 mortality, an occurrence observed in 21% of COVID-19 patients admitted to the ICU at Michigan Medicine. Our findings reveal substantial performance improvement when incorporating imaging data compared to models trained solely on clinical risk factors. Furthermore, the addition of radiomic features yields even larger enhancements, particularly among older and more medically compromised patients. These results may carry implications for enhancing patient outcomes in similar clinical contexts.

Ginsenoside RK1 Induces Ferroptosis in Hepatocellular Carcinoma Cells through an FSP1-Dependent Pathway.

BACKGROUND: Hepatocellular carcinoma (HCC), currently ranking as the third most lethal malignancy, poses a grave threat to human health. Ferroptosis, a form of programmed cell demise, has emerged as a promising therapeutic target in HCC treatment. In this study, we investigated the impact of ginsenoside RK1 on ferroptosis induction in HCC cells and elucidated the underlying mechanisms. METHODS: The HCC cell line HepG2 was utilized to evaluate the effects of ginsenoside RK1. Distinct dosages of ginsenoside RK1 (25 µM, 50 µM, and 100 µM) were selected based on half-maximal inhibitory concentration (IC50) values. Cellular viability was assessed using a CCK8 assay, cytotoxicity was measured via lactate dehydrogenase (LDH) release assay, and colony-forming ability was evaluated using the clone formation assay. Various inhibitors targeting apoptosis (Z-VAD-FMK 20 µM), necrosis (Nec-1, 10 µM), and ferroptosis (Fer-1, 10 µM; Lip-1, 1 µM) were employed to assess ginsenoside RK1's impact on cell demise. Intracellular levels of key ions, including glutathione (GSH), malondialdehyde (MDA), and iron ions, were quantified, and the protein expression levels of ferroptosis-related genes were evaluated. The sensitivity of HCC cells to ferroptosis induction by ginsenoside RK1 was examined following the overexpression and silencing of the aforementioned target genes. RESULTS: Ginsenoside RK1 exhibited an inhibitory effect on HCC cells with an IC50 value of approximately 20 µM. It attenuated cellular viability and colony-forming capacity in a dose-dependent manner, concurrently reducing intracellular GSH levels and increasing intracellular Malondialdehyde (MDA) and iron ion contents. Importantly, cell demise induced by ginsenoside RK1 was specifically counteracted by ferroptosis inhibitors. Furthermore, the modulation of Ferroptosis suppressor protein 1 (FSP1) expression influenced the ability of ginsenoside RK1 to induce ferroptosis. FSP1 overexpression or silencing enhanced or inhibited ferroptosis induction by ginsenoside RK1, respectively. CONCLUSIONS: Ginsenoside RK1 enhances ferroptosis in hepatocellular carcinoma through an FSP1-dependent pathway.

Modified Banxiaxiexin decoction benefitted chemotherapy in treating gastric cancer by regulating multiple targets and pathways.

ETHNOPHARMACOLOGICAL RELEVANCE: Chemotherapy tolerance weakened efficacy of chemotherapy drugs in the treating gastric cancer (GC). Banxiaxiexin decoction (BXXXD) was widely used in digestive diseases for thousands of years in Traditional Chinese medicine (TCM). In order to better treat GC, three other herbs were added to BXXXD to create a new prescription named Modified Banxiaxiexin decoction (MBXXXD). Although MBXXXD potentially treated GC by improving chemotherapy tolerance, the possible mechanisms were still unknown. AIM OF THE STUDY: To explore the therapeutic effect of MBXXXD on GC patients and explore the possible anti-cancer mechanism. MATERIALS AND METHODS: A randomized controlled trial (n = 146) was conducted to evaluate the clinical efficacy between MBXXXD + chemotherapy (n = 73) and placebo + chemotherapy (n = 73) in GC patients by testing overall survival, progression free survival, clinical symptoms, quality of life score, tumor markers, T cell subpopulation, and adverse reactions. Network pharmacology was conducted to discover the potential mechanism of MBXXXD in treating GC. Metabolic activity assay, cell clone colony formation and mitochondrial apoptosis were detected in human GC cell lines including AGS cell, KNM-45 cell and SGC7901 cell treated by MBXXXD. Multiple pathways including P53, AKT, IκB, P65, P38, ERK, JNK p-AKT, p-P65, p-P38, p-ERK and p-JNK in AGS cell, KNM-45 cell and SGC7901 cell treated by MBXXXD and GC patients treated by MBXXXD + chemotherapy were also detected. RESULTS: MBXXXD + chemotherapy promoted overall survival and progression free survival, improved clinical symptoms and quality of life score, increased T4 lymphocyte ratio and T8 lymphocyte ratio as well as T4/T8 lymphocyte ratio, and alleviated adverse reactions in GC patients. Network pharmacology predicted multiple targets and pathways of MBXXXD in treating GC including apoptosis, P53 pathway, AKT pathway, MAPK pathway. MBXXXD inhibited cell viability, decreased cell clone colony formation, and promoted mitochondrial apoptosis by producing reactive oxygen species (ROS), promoting mitochondrial permeability transition pore (MPTP) and the cleavage of pro-caspase-3 and pro-caspase-9, and decreasing mito-tracker red Chloromethyl-X-rosamine (CMXRos) in AGS cell, KNM-45 cell and SGC7901 cell. MBXXXD up-regulated the expression of P53 and IκB, and down-regulated the expression of p-AKT, p-P65, p-P38, p-ERK, p-JNK, AKT, P65, P38, ERK and JNK AGS cell, KNM-45 cell and SGC7901 cell treated by MBXXXD and GC patients treated by MBXXXD + chemotherapy. CONCLUSION: MBXXXD benefitted chemotherapy for GC by regulating multiple targets and pathways.

Ferroptosis: a new hunter of hepatocellular carcinoma.

Ferroptosis is an iron ion-dependent, regulatory cell death modality driven by intracellular lipid peroxidation that plays a key role in the development of HCC. Studies have shown that various clinical agents (e.g., sorafenib) have ferroptosis inducer-like effects and can exert therapeutic effects by modulating different key factors in the ferroptosis pathway. This implies that targeting tumor cell ferroptosis may be a very promising strategy for tumor therapy. In this paper, we summarize the prerequisites and defense systems for the occurrence of ferroptosis and the regulatory targets of drug-mediated ferroptosis action in HCC, the differences and connections between ferroptosis and other programmed cell deaths. We aim to summarize the theoretical basis, classical inducers of ferroptosis and research progress of ferroptosis in HCC cells, clued to the treatment of HCC by regulating ferroptosis network. Further investigation of the specific mechanisms of ferroptosis and the development of hepatocellular carcinoma and interventions at different stages of hepatocellular carcinoma will help us to deepen our understanding of hepatocellular carcinoma, with a view to providing new and more precise preventive as well as therapeutic measures for patients.

Interventions to improve medication adherence in adults with mental-physical multimorbidity in primary care: a systematic review.

BACKGROUND: Medication non-adherence is a notable contributor to healthcare inefficiency, resulting in poor medication management, impaired patient outcomes, and ineffective symptom control. AIM: To summarise interventions targeting medication adherence for adults with mental-physical multimorbidity in primary healthcare settings. DESIGN AND SETTING: A systematic review of the literature - published in any language and with any country of origin - was conducted. METHOD: MEDLINE, EMBASE, PsycInfo, Web of Science, Cochrane Library, and the Cumulated Index to Nursing and Allied Health Literature - more commonly known as CINAHL - were searched for relevant studies. Data were extracted and synthesised using narrative synthesis. The Effective Practice and Organisation of Care (EPOC) taxonomy was used to classify intervention types. Risk of bias was assessed using the National Heart, Lung, and Blood Institute's quality assessment tool for controlled intervention studies. RESULTS: Eleven studies, representing 2279 patients, were included. All interventions examined were classified into one EPOC domain, namely 'delivery arrangements'. All included studies examined patients who had a physical condition and depression. Seven studies examining interventions focused on coordination of care and management of care processes reported statistically significant improvements in medication adherence that were attributed to the intervention. Four studies considering the use of information and communication technology observed no changes in medication adherence. CONCLUSION: Interventions that coordinate and manage healthcare processes may help improve patients' adherence to medication regimes in those with mental-physical multimorbidity. However, it is still necessary to better understand how digital health technology can support patients in following their medication regimes. As the growing challenges of treating multimorbidity are faced, everyone involved in health services - from providers to policymakers - must be receptive to a more integrated approach to healthcare delivery.

Simultaneous selection and inference for varying coefficients with zero regions: a soft-thresholding approach.

Varying coefficient models have been used to explore dynamic effects in many scientific areas, such as in medicine, finance, and epidemiology. As most existing models ignore the existence of zero regions, we propose a new soft-thresholded varying coefficient model, where the coefficient functions are piecewise smooth with zero regions. Our new modeling approach enables us to perform variable selection, detect the zero regions of selected variables, obtain point estimates of the varying coefficients with zero regions, and construct a new type of sparse confidence intervals that accommodate zero regions. We prove the asymptotic properties of the estimator, based on which we draw statistical inference. Our simulation study reveals that the proposed sparse confidence intervals achieve the desired coverage probability. We apply the proposed method to analyze a large-scale preoperative opioid study.

Use of machine learning to assess the prognostic utility of radiomic features for in-hospital COVID-19 mortality.

As portable chest X-rays are an efficient means of triaging emergent cases, their use has raised the question as to whether imaging carries additional prognostic utility for survival among patients with COVID-19. This study assessed the importance of known risk factors on in-hospital mortality and investigated the predictive utility of radiomic texture features using various machine learning approaches. We detected incremental improvements in survival prognostication utilizing texture features derived from emergent chest X-rays, particularly among older patients or those with a higher comorbidity burden. Important features included age, oxygen saturation, blood pressure, and certain comorbid conditions, as well as image features related to the intensity and variability of pixel distribution. Thus, widely available chest X-rays, in conjunction with clinical information, may be predictive of survival outcomes of patients with COVID-19, especially older, sicker patients, and can aid in disease management by providing additional information.

Effects of "Taking the Waist as the Axis" Therapy on trunk postural control disorder after stroke: A randomized controlled trial.

Background: Sufficient attention to trunk rehabilitation after stroke is still lacking. Loss of trunk selective activity is considered to be the leading cause of trunk postural control disorder after stroke. "Taking the Waist as the Axis" Therapy (WAT) was developed as a combination of the concept of "Taking the Waist as the Axis" from Tai Chi and the rehabilitation of trunk dysfunction after stroke. The present clinical trial examined and assessed the effects of WAT on stroke patients. Methods: A total of 43 stroke hemiplegic patients with trunk postural control disorder, whose Trunk Impairment Scale (TIS) scoring between 8 and 18, participated in the present study and were allocated randomly to the experimental (n = 23) or control groups (n = 20). The experimental group received WAT plus conventional therapy, and the control group received "Trunk Selective Activity" Therapy (TSAT) plus conventional therapy. Both groups received treatment once daily and 5 times per week for 3 weeks. The Trunk Impairment Scale (TIS), Fugl-Meyer Assessment (FMA), Berg Balance Scale (BBS), change of Intra-abdominal Pressure (IAP), static balance ability assessment, rapid ventilation lung function test and the Modified Barthel Index (MBI) were evaluated before and after intervention for both groups. Results: The experimental group was superior to the control group in TIS [4 (2, 5) vs. 3 (1.25, 4), p = 0.030], change of IAP [-3 (-8, -1.33) vs. -0.02 (-3.08, 6), p = 0.011], FMA-upper extremity [10 (6, 18) vs. 1 (0, 3), p = 0.002], FMA-lower extremity [2 (1, 4) vs. 1 (0, 2), p = 0.009] and FMA [14 (7, 21) vs. 2 (0.25, 3.75), p = 0.001]. Within experimental group, forced vital capacity (FVC) [81.35 (63.30, 94.88) vs. 91.75 (79.40, 97.90), p = 0.02] was significantly improved. Conclusion: WAT was an effective trunk treatment after stroke, which significantly improved the patients' trunk posture control ability, motor function and forced vital capacity. However, the results still need to be interpreted with caution for the intervention only lasted for 3 weeks.

Data Integration in Causal Inference.

Integrating data from multiple heterogeneous sources has become increasingly popular to achieve a large sample size and diverse study population. This paper reviews development in causal inference methods that combines multiple datasets collected by potentially different designs from potentially heterogeneous populations. We summarize recent advances on combining randomized clinical trial with external information from observational studies or historical controls, combining samples when no single sample has all relevant variables with application to two-sample Mendelian randomization, distributed data setting under privacy concerns for comparative effectiveness and safety research using real-world data, Bayesian causal inference, and causal discovery methods.

Comprehensive evaluation of COVID-19 patient short- and long-term outcomes: Disparities in healthcare utilization and post-hospitalization outcomes.

BACKGROUND: Understanding risk factors for short- and long-term COVID-19 outcomes have implications for current guidelines and practice. We study whether early identified risk factors for COVID-19 persist one year later and through varying disease progression trajectories. METHODS: This was a retrospective study of 6,731 COVID-19 patients presenting to Michigan Medicine between March 10, 2020 and March 10, 2021. We describe disease progression trajectories from diagnosis to potential hospital admission, discharge, readmission, or death. Outcomes pertained to all patients: rate of medical encounters, hospitalization-free survival, and overall survival, and hospitalized patients: discharge versus in-hospital death and readmission. Risk factors included patient age, sex, race, body mass index, and 29 comorbidity conditions. RESULTS: Younger, non-Black patients utilized healthcare resources at higher rates, while older, male, and Black patients had higher rates of hospitalization and mortality. Diabetes with complications, coagulopathy, fluid and electrolyte disorders, and blood loss anemia were risk factors for these outcomes. Diabetes with complications, coagulopathy, fluid and electrolyte disorders, and blood loss were associated with lower discharge and higher inpatient mortality rates. CONCLUSIONS: This study found differences in healthcare utilization and adverse COVID-19 outcomes, as well as differing risk factors for short- and long-term outcomes throughout disease progression. These findings may inform providers in emergency departments or critical care settings of treatment priorities, empower healthcare stakeholders with effective disease management strategies, and aid health policy makers in optimizing allocations of medical resources.