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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Survival outcomes of patients with head and neck squamous cell cancer with hepatitis B virus infection: An analysis from an endemic tertiary center

Abstract Background Hepatitis B virus (HBV) affects the occurrence and survival outcome of various malignant disorders. The study aimed to evaluate the survival outcome of head and neck squamous cell cancer (HNSCC) patients with or without HBV infection. Methods This study included patients with HNSCC who visited Taichung Veterans General Hospital from 2007 to 2015. HBV infection was defined by hepatitis B surface antigen (HBsAg) seropositivity. By propensity score matching, we compared survival outcomes, including progression‐free survival (PFS) and overall survival (OS), among patients with or without HBV infection. Results The prevalence of HBV infection in our cohort was 12.3%. Among the 1,015 patients included in the matched analysis, a higher risk of baseline liver cirrhosis (11.3% vs. 3.4%, p < 0.001) and initial hepatic dysfunction (10.8% vs. 5.4%, p = 0.005) rates were observed than those without HBV infection at baseline. The 5‐year OS was 43.1% and 53.2% ( p < 0.001) and the 5‐year PFS was 37.4% and 42.3% ( p = 0.007) in patients with and without HBV infection, respectively. The incidence of subsequent hepatic dysfunction showed no difference between patients with and without HBV infection (29.6% vs. 26.8%, p = 0.439). Conclusions Patients with HNSCC and HBV infection were younger and had a higher risk of cirrhosis compared to those without HBV infection. Moreover, HBV infection significantly influenced the OS and PFS outcomes but not subsequent hepatic dysfunction in patients with HNSCC.

Lai, Cheng‐Lun↗
DOE OSTI2023

Gut microbiome dynamics and associations with mortality in critically ill patients

Abstract Background Critical illness and care within the intensive care unit (ICU) leads to profound changes in the composition of the gut microbiome. The impact of such changes on the patients and their subsequent disease course remains uncertain. We hypothesized that specific changes in the gut microbiome would be more harmful than others, leading to increased mortality in critically ill patients. Methods This was a prospective cohort study of critically ill adults in the ICU. We obtained rectal swabs from 52 patients and assessed the composition the gut microbiome using 16 S rRNA gene sequencing. We followed patients throughout their ICU course and evaluated their mortality rate at 28 days following admission to the ICU. We used selbal, a machine learning method, to identify the balance of microbial taxa most closely associated with 28-day mortality. Results We found that a proportional ratio of four taxa could be used to distinguish patients with a higher risk of mortality from patients with a lower risk of mortality (p = .02). We named this binarized ratio our microbiome mortality index (MMI). Patients with a high MMI had a higher 28-day mortality compared to those with a low MMI (hazard ratio, 2.2, 95% confidence interval 1.1–4.3), and remained significant after adjustment for other ICU mortality predictors, including the presence of the acute respiratory distress syndrome (ARDS) and the Acute Physiology and Chronic Health Evaluation (APACHE II) score (hazard ratio, 2.5, 95% confidence interval 1.4–4.7). High mortality was driven by taxa from theAnaerococcus(genus) andEnterobacteriaceae(family), while lower mortality was driven byParasutterellaandCampylobacter(genera). Conclusions Dysbiosis in the gut of critically ill patients is an independent risk factor for increased mortality at 28 days after adjustment for clinically significant confounders. Gut dysbiosis may represent a potential therapeutic target for future ICU interventions.

Gastroenterology & Hepatology↗
DOE OSTI2022

Prospective Study Reveals Host Microbial Determinants of Clinical Response to Fecal Microbiota Transplant Therapy in Type 2 Diabetes Patients

Increasing evidence shows that alterations in gut microbiome (GM) contribute to the development of type 2 diabetes mellitus (T2DM), and fecal microbiota transplantation (FMT) successfully treats various human diseases. However, the benefits of FMT therapy to T2DM patients remain unknown. We enrolled 17 patients with T2DM for nonblinded, one-armed intervention trial of FMT. A total of 20 healthy individuals were recruited as the baseline control. HbA1c% and metabolic parameter change were evaluated in 17 T2DM patients 12 weeks after they received FMT from healthy donors. The GM composition was characterized by 16S rRNA gene amplicon sequencing from fecal samples prior to and 12 weeks after FMT treatment. We found that the GM of T2DM patients was reconstituted by FMT. We observed a statistically significant decrease in HbA1c% (from 7.565 ± 0.148 to 7.190 ± 0.210, p<0.01), blood glucose (from 8.483 ± 0.497 to 7.286 ± 0.454 mmol/L, p<0.01), and uric acid (from 309.4 ± 21.5 to 259.1 ± 15.8 µmol/L, p<0.01) while a significant increase in postprandial C-peptide (from 4.503 ± 0.600 to 5.471 ± 0.728 ng/ml, p<0.01) at 12 weeks after FMT. Closely evaluating the changes in these assays, we found individual variability in response to FMT treatment. Out of 17 T2DM patients, 11 were found to significantly improve T2DM symptoms. The FMT responders have significantly higher levels of the family Rikenellaceae and the genus Anaerotruncus (family Ruminococcaceae) in their pretreated fecal in comparison to nonresponders, which could predict the clinical response with an area under the curve of 0.83. Our findings suggest that certain T2DM patients can potentially benefit from FMT, and the pretreated abundance of Rikenellaceae and Anaerotruncus in the fecal of patients may serve as potential biomarkers for selecting T2DM patients to receive FMT.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Psychometric property study of the Affective Lability Scale-short form in Chinese patients with mood disorders

Introduction This study aimed to investigate the psychometric properties of the Affective Lability Scale-short form (ALS-SF) among Chinese patients with mood disorders, and to compare ALS-SF subscale scores between patients with major depressive disorder (MDD) and patients with bipolar disorder (BD) depression. Methods A total of 344 patients with mood disorders were included in our study. Participants were measured through a set of questionnaires including the Chinese version of ALS-SF, Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7-item (GAD-7), and NEO-Five Factor Inventory (NEO-FFI). Exploratory factor analysis and confirmatory factor analysis were applied to examine the psychometric properties of ALS-SF. Besides, correlation and regression analyses were performed to explore the relationship between affective lability and depression, anxiety, and neuroticism. Independent samples t -tests were used to compare the subscale scores of ALS-SF between the MDD and BD depression groups. Results Results of factor analysis indicated that the model of ALS-SF was consistent with ALS-SF. The ALS-SF showed a solid validity and high internal consistency (Cronbach’s alpha = 0.861). In addition, each subscale of ALS-SF was significantly correlated with PHQ-9, GAD-7, and NEO-FFI neuroticism subscale, except for the anger subscale showed no significant correlation with PHQ-9. Besides, the depression/elation and anger factor scores in patients with BD depression were higher than in patients with MDD. Conclusion Our study suggests that the Chinese version of ALS-SF has good reliability and validity for measuring affective lability in Chinese patients with mood disorders. Assessing affective lability would assist clinicians to distinguish between MDD and BP depression and may decrease the risks of misdiagnosis.

Ma, Mohan↗
DOE OSTI2024

Assessing heterogeneity of patient and health system delay among TB in a population with internal migrants in China

Backgrounds The diagnostic delay of tuberculosis (TB) contributes to further transmission and impedes the implementation of the End TB Strategy. Therefore, we aimed to describe the characteristics of patient delay, health system delay, and total delay among TB patients in Shanghai, identify areas at high risk for delay, and explore the potential factors of long delay at individual and spatial levels. Method The study included TB patients among migrants and residents in Shanghai between January 2010 and December 2018. Patient and health system delays exceeding 14 days and total delays exceeding 28 days were defined as long delays. Time trends of long delays were evaluated by Joinpoint regression. Multivariable logistic regression analysis was employed to analyze influencing factors of long delays. Spatial analysis of delays was conducted using ArcGIS, and the hierarchical Bayesian spatial model was utilized to explore associated spatial factors. Results Overall, 61,050 TB patients were notified during the study period. Median patient, health system, and total delays were 12 days (IQR: 3–26), 9 days (IQR: 4–18), and 27 days (IQR: 15–43), respectively. Migrants, females, older adults, symptomatic visits to TB-designated facilities, and pathogen-positive were associated with longer patient delays, while pathogen-negative, active case findings and symptomatic visits to non-TB-designated facilities were associated with long health system delays (LHD). Spatial analysis revealed Chongming Island was a hotspot for patient delay, while western areas of Shanghai, with a high proportion of internal migrants and industrial parks, were at high risk for LHD. The application of rapid molecular diagnostic methods was associated with reduced health system delays. Conclusion Despite a relatively shorter diagnostic delay of TB than in the other regions in China, there was vital social-demographic and spatial heterogeneity in the occurrence of long delays in Shanghai. While the active case finding and rapid molecular diagnosis reduced the delay, novel targeted interventions are still required to address the challenges of TB diagnosis among both migrants and residents in this urban setting.

Sun, Ruoyao↗
DOE OSTI2021

Diagnosing Malaria Patients with Plasmodium falciparum and vivax Using Deep Learning for Thick Smear Images

We propose a new framework, PlasmodiumVF-Net, to analyze thick smear microscopy images for a malaria diagnosis on both image and patient-level. Our framework detects whether a patient is infected, and in case of a malarial infection, reports whether the patient is infected by Plasmodium falciparum or Plasmodium vivax. PlasmodiumVF-Net first detects candidates for Plasmodium parasites using a Mask Regional-Convolutional Neural Network (Mask R-CNN), filters out false positives using a ResNet50 classifier, and then follows a new approach to recognize parasite species based on a score obtained from the number of detected patches and their aggregated probabilities for all of the patient images. Reporting a patient-level decision is highly challenging, and therefore reported less often in the literature, due to the small size of detected parasites, the similarity to staining artifacts, the similarity of species in different development stages, and illumination or color variations on patient-level. We use a manually annotated dataset consisting of 350 patients, with about 6000 images, which we make publicly available together with this manuscript. Our framework achieves an overall accuracy above 90% on image and patient-level.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

COVID ‐19 outcomes in patients with cancer: Findings from the University of California health system database

Abstract Background The interaction between cancer diagnoses and COVID‐19 infection and outcomes is unclear. We leveraged a state‐wide, multi‐institutional database to assess cancer‐related risk factors for poor COVID‐19 outcomes. Methods We conducted a retrospective cohort study using the University of California Health COVID Research Dataset, which includes electronic health data of patients tested for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) at 17 California medical centers. We identified adults tested for SARS‐CoV‐2 from 2/1/2020–12/31/2020 and selected a cohort of patients with cancer. We obtained demographic, clinical, cancer type, and antineoplastic therapy data. The primary outcome was hospitalization within 30d after the first positive SARS‐CoV‐2 test. Secondary outcomes were SARS‐CoV‐2 positivity and severe COVID‐19 (intensive care, mechanical ventilation, or death within 30d after the first positive test). We used multivariable logistic regression to identify cancer‐related factors associated with outcomes. Results We identified 409,462 patients undergoing SARS‐CoV‐2 testing. Of 49,918 patients with cancer, 1781 (3.6%) tested positive. Patients with cancer were less likely to test positive (RR 0.70, 95% CI: 0.67–0.74, p < 0.001). Among the 1781 SARS‐CoV‐2‐positive patients with cancer, BCR/ABL‐negative myeloproliferative neoplasms (RR 2.15, 95% CI: 1.25–3.41, p = 0.007), venetoclax (RR 2.96, 95% CI: 1.14–5.66, p = 0.028), and methotrexate (RR 2.72, 95% CI: 1.10–5.19, p = 0.032) were associated with greater hospitalization risk. Cancer and therapy types were not associated with severe COVID‐19. Conclusions In this large, diverse cohort, cancer was associated with a decreased risk of SARS‐CoV‐2 positivity. Patients with BCR/ABL‐negative myeloproliferative neoplasm or receiving methotrexate or venetoclax may be at increased risk of hospitalization following SARS‐CoV‐2 infection. Mechanistic and comparative studies are needed to validate findings.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Extrapolation of Efficacy from Adults to Pediatric Patients of Drugs for Treatment of Partial Onset Seizures: A Regulatory Perspective

The US Food and Drug Administration (FDA) has concluded that the efficacy of drugs approved for the treatment of partial onset seizures (POS) in adults can be extrapolated to pediatric patients 1 month of age and above and that independent efficacy trials in this pediatric population are no longer needed. This paper focuses on the dosing, pharmacokinetic (PK), exposure‐response, and clinical information that were leveraged from the approved drugs for the treatment of POS to conduct analyses that supported extrapolation of efficacy in pediatric patients. Clinical data from trials for eight drugs (levetiracetam, oxcarbazepine, topiramate, lamotrigine, gabapentin, perampanel, tiagabine, and vigabatrin) approved in both adults and pediatric patients for the treatment of POS were analyzed. Comparisons of exposures at approved doses, placebo response, and model‐based exposure‐response relationships were performed. Based on disease similarity, similar response to intervention, and similar exposure‐response relationships in adults and pediatric patients, it was concluded that extrapolation of efficacy in pediatric patients aged 1 month and above is acceptable. PK analysis to determine pediatric dose and regimens that provide drug exposure similar to that known to be effective in adult patients with POS will be required, along with long‐term open‐label safety data in pediatric patients.

Pharmacology & Pharmacy↗
DOE OSTI2025

miss-SNF: a multimodal patient similarity network integration approach to handle completely missing data sources

Abstract Motivation Precision medicine leverages patient-specific multimodal data to improve prevention, diagnosis, prognosis, and treatment of diseases. Advancing precision medicine requires the non-trivial integration of complex, heterogeneous, and potentially high-dimensional data sources, such as multi-omics and clinical data. In the literature, several approaches have been proposed to manage missing data, but are usually limited to the recovery of subsets of features for a subset of patients. A largely overlooked problem is the integration of multiple sources of data when one or more of them are completely missing for a subset of patients, a relatively common condition in clinical practice. Results We propose miss-Similarity Network Fusion (miss-SNF), a novel general-purpose data integration approach designed to manage completely missing data in the context of patient similarity networks. miss-SNF integrates incomplete unimodal patient similarity networks by leveraging a non-linear message-passing strategy borrowed from the SNF algorithm. miss-SNF is able to recover missing patient similarities and is “task agnostic”, in the sense that can integrate partial data for both unsupervised and supervised prediction tasks. Experimental analyses on nine cancer datasets from The Cancer Genome Atlas (TCGA) demonstrate that miss-SNF achieves state-of-the-art results in recovering similarities and in identifying patients subgroups enriched in clinically relevant variables and having differential survival. Moreover, amputation experiments show that miss-SNF supervised prediction of cancer clinical outcomes and Alzheimer’s disease diagnosis with completely missing data achieves results comparable to those obtained when all the data are available. Availability and implementation miss-SNF code, implemented in R, is available at https://github.com/AnacletoLAB/missSNF.

Biochemistry & Molecular Biology↗
DOE OSTI2023

2022 Prentice Award Lecture: Advancing Retinal Imaging and Visual Function in Patient Management and Disease Mechanisms

Patient-based research plays a key role in probing basic visual mechanisms. Less-well recognized is the role of patient-based retinal imaging and visual function studies in elucidating disease mechanisms, which are accelerated by advances in imaging and function techniques and are most powerful when combined with the results from histology and animal models. A patient's visual complaints can be one key to patient management, but human data are also key to understanding disease mechanisms. Unfortunately, pathological changes can be difficult to detect. Before advanced retinal imaging, the measurement of visual function indicated the presence of pathological changes that were undetectable with existing clinical examination. Over the past few decades, advances in retinal imaging have increasingly revealed the unseen. This has led to great strides in the management of many diseases, particularly diabetic retinopathy and macular edema, and age-related macular degeneration. It is likely widely accepted that patient-based research, as in clinical trials, led to such positive outcomes. Both visual function measures and advanced retinal imaging have clearly demonstrated differences among retinal diseases. Contrary to initial thinking, sight-threatening damage in diabetes occurs to the outer retina and not only to the inner retina. This has been clearly indicated in patient results but has only gradually entered the clinical classifications and understanding of disease etiology. There is strikingly different pathophysiology for age-related macular degeneration compared with photoreceptor and retinal pigment epithelial genetic defects, yet research models and even some treatments confuse these. It is important to recognize the role that patient-based research plays in probing basic visual mechanisms and elucidating disease mechanisms, combining these findings with the concepts from histology and animal models. Thus, this article combines sample instrumentation from my laboratory and progress in the fields of retinal imaging and visual function.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Association of Serum Bile Acid and Unsaturated Fatty Acid Profiles with the Risk of Diabetic Retinopathy in Type 2 Diabetic Patients

Aim: We aimed to identify the ability of serum bile acids (BAs) and unsaturated fatty acids (UFAs) profiles to predict the development of diabetic retinopathy (DR) in type 2 diabetes mellitus (T2DM) patients. Methods: We first used univariate and multivariate analysis to compare 15 serum BA and 11 UFA levels in healthy control (HC) group (n = 82), T2DM patients with DR (n = 58) and T2DM patients without DR (n = 60). Forty T2DM patients were considered for validation. Then, the receiver operating characteristic curve (ROC) and decision curve analysis were used to assess the diagnostic value and clinical benefit of serum biomarkers alone, clinical variables alone or in combination, and the area under the curve (AUC), integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were used to further assess whether the addition of biomarkers significantly improved the predictive ability of the model. Results: Orthogonal partial least squares-discriminant analysis (OPLS-DA) of serum BAs and UFAs separated the three cohorts including HC, T2DM patients with or without DR. The difference in serum BA and UFA profiles of T2DM patients with or without DR was mainly manifested in the three metabolites of taurolithocholic acid (TLCA), tauroursodeoxycholic acid (TUDCA) and arachidonic acid (AA). Together, they had an AUC of 0.785 (0.918 for validation cohort) for predicting DR in T2DM patients. After adjusting for numerous confounding factors, TLCA, TUDCA, and AA were independent predictors that differentiated T2DM with or without DR. The results of AUC, IDI, and NRI demonstrated that adding these three biomarkers to a model with clinical variables statistically increased their predictive value and were replicated in our independent validation cohort. Conclusion: These findings highlight the association of three metabolites, TLCA, TUDCA and AA, with DR and may indicate their potential value in the pathogenesis of DR.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

DeepCare: Improving Patient Care using Deep Learning on Electronic Health Records

Coordinating patient care using electronic health records (EHR) data presents an exciting but formidable opportunity in data extraction, analysis and modeling. Traditional methods use a manual feature driven approach to model patients with age, family history and symptoms to predict disease outcomes. We propose a novel approach to model patients based on their streaming electronic health records data combined with information from medical knowledge bases, which has been gained over years of medical research. Using a combination of representation learning and long short term memory (LSTM) networks we plan to model patient evolution over time, leading to more accurate and individualized predictive models for patient’s diseases. Our approach will be transformative in providing critical decision support for patient care, enabling accurate understanding and evolution of diseases in patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Development of a prediction model for radiotherapy response among patients with head and neck squamous cell carcinoma based on the tumor immune microenvironment and hypoxia signature

Abstract Introduction The immune system and hypoxia are major factors influencing radiosensitivity in patients with different cancer types. This study aimed at developing a model to predict radiotherapy response in patients with head and neck squamous cell carcinoma (HNSCC) based on the tumor immune microenvironment and hypoxia signature. Materials and Methods We first evaluated the hypoxia status and tumor immune microenvironment in the Cancer Genome Atlas (TCGA) cohort by using transcriptomic data. Differentially expressed genes (DEGs) were identified between the “high immunity and low hypoxia” and “low immunity and high hypoxia” groups and those DEGs significantly associated with disease‐specific survival in the univariate Cox regression analysis were selected as the prognostic DEGs. We selected the immune hypoxia–related genes (IHRGs) by intersecting prognostic DEGs with immune and hypoxia gene sets. We used the IHRGs to train a multivariate Cox regression model in the TCGA cohort, based on which we calculated the IHRG prognostic index (IHRGPI) for each patient and validated its efficacy in predicting radiotherapy response in the Gene Expression Omnibus cohorts. Furthermore, we explored potential mechanisms and effective combinational treatment strategies for different IHRGPI groups. Results Five IHRGs were used to construct the IHRGPI, which was used to dichotomize the cohorts. The patients with lower IHRGPI showed a better radiotherapy response across different cohorts and endpoints, including overall survival, progression‐free survival, and recurrence‐free survival ( p < 0.05). Patients with higher IHRGPI showed greater hypoxia and lesser immune cell infiltration. A lower IHRGPI indicated a better immunotherapy response, while a higher IHRGPI indicated a better chemotherapy response. Conclusions IHRGPI is promising for predicting radiotherapy response and guiding combinational treatment strategies in patients with HNSCC.

Zhu, Guang‐Li↗
DOE OSTI2022

Prognostic importance of the preoperative New‐Naples prognostic score for patients with gastric cancer

Abstract Background The wide applicability of the Naples prognostic score (NPS) is still worthy of further study in gastric cancer (GC). This study aimed to construct a New‐NPS based on the differences in immunity and nutrition in patients with upper and lower gastrointestinal tumors to help obtain an individualized prediction of prognosis. Methods This study retrospectively analyzed patients who underwent radical gastrectomy from April 2014 to September 2016. The cutoff values of the preoperative neutrophil‐to‐lymphocyte ratio (NLR), lymphocyte‐to‐monocyte ratio (LMR), serum albumin (Alb), and total cholesterol (TC) were calculated by ROC curve analysis. ROC and t‐ROC were used to evaluate the accuracy of the prognostic markers. The Kaplan–Meier method and log‐rank test were used to analyze the overall survival probability. Univariate and multivariate analyses based on Cox risk regression were used to show the independent predictors. The nomogram was made by R studio. The predictive accuracy of nomogram was assessed using a calibration plot, concordance index (C‐index), and decision curve. Results A total of 737 patients were included in training cohort, 411 patients were included in validation cohort. ROC showed that the New‐NPS was more suitable for predicting the prognosis of GC patients. NPS = 2 indicated a poor prognosis. Multivariate analysis showed that CEA ( P = 0.026), Borrmann type ( P = 0.001), pTNM ( P < 0.001), New‐NPS ( P < 0.001), and nerve infiltration ( P = 0.035) were independent risk factors for prognosis. Conclusion The New‐NPS based on the cutoff values of NLR, LMR, Alb, and TC is not only suitable for predicting prognosis but can also be combined with clinicopathological characteristics to construct a nomogram model for GC patients.

Wang, Hao↗
DOE OSTI2023

The Association Between Baseline Hepatic or Renal Function and Clinical Outcomes for Patients With Non–Small Cell Lung Cancer Treated With a PD –1/PD– L1 Blocking Antibody Using Real–World and Trial Data

Clinical trials have demonstrated the benefit of PD-1/PD-L1 blocking antibodies for the treatment of patients with advanced non-small cell lung cancer (NSCLC) in defined patient populations that often exclude patients with moderate or severe hepatic or renal impairment. We assessed the association between overall survival (OS) and baseline organ function in patients with advanced NSCLC treated with PD-1/PD-L1 blocking antibodies in real-world data (RWD; patient-level data from electronic health records) and pooled clinical trial data submitted to the US Food and Drug Administration (FDA). The Kaplan–Meier estimator was used to estimate OS in different subgroups based on organ function. Unadjusted and adjusted Cox proportional hazards models were used to estimate the association between OS and organ function. In this hypothesis-generating study, baseline renal impairment did not appear to be associated with OS, while patients with baseline liver impairment had shorter OS. RWD provided information on a broader range of renal and hepatic function than was evaluated in clinical trials and hold promise to complement trial data in better understanding populations not represented in clinical trials.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Effectiveness of supervised exercise, home-based exercise, or walk advice strategies on walking performance and muscle endurance in patients with intermittent claudication (SUNFIT trial): a randomized clinical trial

Abstract Aims Supervised exercise is a guideline-recommended treatment in intermittent claudication (IC). Hospital-based supervised exercise programmes (SEPs) are underutilized, while home-based structured exercise programmes (HSEPs) have attracted interest. The results from HSEP in IC are inconsistent and may confer no benefit over walk advice (WA) and be less effective than SEP. The aim of the study was to compare the effectiveness of best medical treatment, including Nordic pole WA alone, or WA + SEP or WA + HSEP for patients with IC. Methods and results This three-armed, multicentre randomized clinical trial enrolled patients with IC; all patients received best medical treatment including walking poles and the advice of regular Nordic pole walking (WA). For HSEP and SEP, additional exercise programmes were provided. The primarily investigated hypothesis was a non-inferiority analysis of SEP vs. HSEP regarding the 6-min walk test (6MWT) maximum distance, with a pre-defined non-inferiority margin of 50 m. Supporting outcomes included muscle endurance tests and the walking impairment questionnaire. Outcomes were assessed at baseline, 3, 6, and 12 months by a blinded evaluator. Altogether 166 patients (mean age 72 years; 59% males) were randomized. In HSEP and SEP, 24 and 26% patients, respectively, were fully exercise adherent. All three groups improved pain-free walking distance over time, but there were no significant intergroup differences. The intergroup 6MWT difference between SEP and HSEP from 0 to 12 months was –11.6 m, 95% confidence interval: –36.4 to 13.0 m (i.e. within the pre-specified non-inferiority margin). Conclusion The HSEP was non-inferior to SEP in patients with IC. There were no significant differences observed between the three groups at 1 year. Registration ClinicialTrials.gov: NCT02341716.

Sandberg, Anna (ORCID:0000000258432784)↗
DOE OSTI2023

Detection of Candida DNA in peritoneal fluids by PCR assay optimizing the diagnosis and treatment for intra-abdominal candidiasis in high-risk ICU patients: A prospective cohort study

Background Intra-abdominal candidiasis (IAC) is the predominant type of invasive candidiasis with high mortality in critically ill patients. This study aimed to investigate whether the polymerase chain reaction (PCR) assay for detecting Candida DNA in peritoneal fluids (PF) is useful in diagnosing and management of IAC in high-risk patients in intensive care unit (ICU). Methods A prospective single-center cohort study of surgical patients at high risk for IAC was conducted in the ICU. PF was collected from the abdominal drainage tubes (within 24 h) or by percutaneous puncture. Direct PF smear microscopy, PF culture, blood culture, and serum (1–3)-β-D-glucan were performed in all patients. For Candida PCR assay, the ITS1/ITS4 primers that targeted the ITS1-5.8 s-ITS2 regions were used for PCR, and sequencing analysis was used to identify the pathogen at the species level. IAC was defined according to the 2013 European consensus criteria. Results Among 83 patients at high risk for IAC, the IAC criteria were present in 17 (20.5%). The sensitivity and specificity of the Candida PCR assay were 64.7 and 89.4%, respectively, and the area under the receiver operating characteristic curve was 0.77 (95% CI: 0.63–0.91). In this cohort, the positive predictive value and negative predictive value were 90.8% (95% CI: 80.3–96.2%) and 61.1% (95% CI: 36.1–81.7%), respectively. Diagnostic consistency was moderate (kappa 0.529, p < 0.001) according to the 2013 European consensus criteria. Conclusion Detection of Candida DNA in PF using PCR can be considered an adjunct to existing routine diagnostic tools which may optimize the diagnosis and antifungal treatment of IAC in high-risk patients in the ICU.

Xie, Min↗
DOE OSTI2021

The Influence of Patient–Provider Language Concordance in Cancer Care: Results of the Hispanic Outcomes by Language Approach (HOLA) Randomized Trial

Delivering linguistically competent care is critical to serving patients who have limited English proficiency (LEP) and represents a key national strategy to help reduce health disparities. Current acceptable standards of communication with patients who have LEP include providers communicating through professional interpretive services or bilingual providers speaking the patients’ preferred language directly. This randomized clinical trial tests the effect of patient-provider language concordance on patient satisfaction.

62 RADIOLOGY AND NUCLEAR MEDICINE↗