Major Medical Center Research Articles

Evaluation of the GATIS score for predicting prognosis in rectal neuroendocrine neoplasms

The GATIS score, developed by Zeng et al , represents a significant advancement in predicting the prognosis of patients with rectal neuroendocrine neoplasms (R-NENs). This study, which included 1408 patients from 17 major medical centres in China over 12 years, introduces a novel prognostic model based on the tumour grade, T stage, tumour size, age, and the prognostic nutritional index. Compared with traditional methods such as the World Health Organization classification and TNM staging systems, the GATIS score has superior predictive power for overall survival and progression-free survival. With a C-index of 0.915 in the training set and 0.812 in the external validation set, the GATIS score’s robustness and reliability are evident. The study’s use of a large, multi-centre cohort and rigorous validation processes underscore its significance. The GATIS score offers clinicians a powerful tool to accurately predict patient outcomes, guide treatment decisions, and improve follow-up strategies. This development represents a crucial step forwards in the management of R-NENs, addressing the complexity and variability of these tumours and setting a new benchmark for future research and clinical practice.

Abstract 4137587: Need for Testing Standardization and Improved Treatment of Elevated Lipoprotein(a) at a Large Urban Academic Medical Center

Background: Lipoprotein(a) [Lp(a)] is causally linked to ASCVD events and aortic stenosis. Some guidelines now recommend screening of Lp(a) at least once in an adult’s lifetime. Currently, there is inconsistency in measurement modality (mg/dL vs. nmol/L), but most guidelines recommending testing in nmol/L due to less variability and improved standardization. We sought to determine the Lp(a) measurement practices, including testing modality and downstream interventions, at a large academic medical institution. Methods: We evaluated all patient encounter data at UT Southwestern Medical Center (UTSW) between January 1, 2017 to December 31, 2021 for any Lp(a) measurement. High Lp(a) was defined as >50mg/dL or >125 nmol/L. Aggregate data were used to summarize patient demographics, relevant ASCVD co-morbidities, and lipid lowering prescriptions. Chart-review was conducted on patients with high Lp(a) to assess referrals to specialty clinics. Results: From 2017 to 2021, there were 1,065 Lp(a) measurements among 938 patients, representing fewer than 0.1% of all patients with labs at UTSW. Most were ordered by cardiologists (71%). Lp(a) tests ordered by cardiologists increased 69% annually but remained stagnant for other specialties (figure 1, lines). Median Lp(a) levels across all tests were 17mg/dL and 43nmol/L. Lp(a) was high in 30% of all initial tests. A higher proportion of tests ordered in 2021 by cardiologists (84%) were in nmol/L, the recommended standard, compared with other specialties (55%) (figure 1, bars). Patients with high Lp(a) found by a non-cardiologist were infrequently referred to cardiology (16%), and 53% of patients with high Lp(a) were prescribed lipid lowering therapy within 3 months. Conclusion: Lp(a) testing at a major academic medical center was rare and only marginally increased during the 5-year study period. Measurement frequency and assay varied widely between specialties, and there were potential opportunities for downstream interventions. In addition to improving awareness of Lp(a), there is an opportunity to standardize practice patterns regarding its measurement and implications.

QOL-04. THE UNDER-UTILIZATION OF PALLIATIVE CARE SERVICES BY PATIENTS WITH GLIOBLASTOMA HIGHLIGHTS THE IMPORTANCE OF DISCUSSIONS AROUND PALLIATIVE CARE: A CROSS-SECTIONAL STUDY WITH CARE PARTNERS OF PATIENTS WITH GBM RECRUITED FROM FACEBOOK SUPPORT GROUPS

Abstract Glioblastoma (GBM) is a terminal brain cancer that has a rapid onset and results in symptoms such as headaches, vomiting, seizures, anxiety, depression, agitation, speech impairment, memory impairment, infections, brain bleeds, mobility changes, changes in sleep patterns, and cognitive changes. Palliative care helps patients diagnosed with an incurable or chronic disease manage physical, social, and psychological symptoms and has been shown to increase survival for patients with cancer. Previous data of former care partners of patients with GBM indicated only 30% of patients used palliative care whereas 90% used hospice. To better understand the reasons for underutilization of palliative care patients with GBM, 38-question survey about the use of palliative care, type of medical center where treatment occurred, and discussions with care team members about palliative care was given to current care partners recruited from Facebook support groups in February 2024. Inclusion criteria: current primary care partner of a patient with GBM, over the age of 18, and willing to participate (IRB exempt; H24-0393). The care partner was excluded if their patient was no longer living. Of the 77 current care partners, 56 reported they did not use palliative care as part of their care team. The use of palliative care was similar among care facilities (community hospital, major medical center, university hospital, brain tumor center). When care team members discussed palliative care with patients and their care partners (n=21), 71% of the dyads used palliative care. When care team members did not discuss palliative care (n=56), the use of palliative care was much lower at 7%. Interestingly, 55% of respondents reported they would benefit from knowing more about ways to increase physical and emotional support. This data suggests discussions around palliative care increase the use of palliative care services among patients with GBM and their care partners.

Heartfelt Impact: A Descriptive Analysis of Ceftaroline-Containing Regimens in Endocarditis due to Methicillin-Resistant Staphylococcus aureus.

Infective endocarditis (IE) due to methicillin-resistant Staphylococcus aureus (MRSA) is characterized by frequent treatment failure to first-line agents and high mortality, necessitating use of alternative management strategies. Ceftaroline fosamil (CPT) is a cephalosporin antibiotic with activity against MRSA but without regulatory approval for the indication of IE. This study describes clinical experience with CPT-based regimens utilized in MRSA-IE. This is a retrospective, observational, descriptive analysis of patients from two major urban medical centers in Detroit, Michigan from 2011 to 2023. Included adult patients (≥ 18years) had ≥ 1 positive blood culture for MRSA, met definitive clinical criteria for IE, and received CPT for ≥ 72h. The primary outcome was treatment failure, defined as a composite of 30-day all-cause mortality from index culture or failure to improve or resolve infectious signs/symptoms after CPT initiation. Seventy patients were included. The median (interquartile range [IQR]) age was 51 (34-63) years and 45.7% were male. Persons with injection drug use (PWID) made up 55.7% of the cohort and right-sided IE was the most prevalent subtype (50.0%). CPT was frequently employed second-line or later, often in combination with vancomycin (10.0%) or daptomycin (72.9%). Overall, 31.4% experienced treatment failure and 30-day all-cause mortality occurred in 15.7%. These findings illustrate the challenges posed by MRSA-IE, including frequent treatment failures, and highlight the utilization of CPT as salvage therapy. Comparative studies are needed to more clearly define its role in MRSA-IE.

Modelling an Integrated Fuzzy Based Decision Support System for an Anaesthetist during Pre-Operative Clinical Assessment

Pre-operative clinical assessment is a crucial responsibility for every anaesthetist before any major medical procedure. This assessment evaluates a patient’s suitability for anaesthesia and their overall physical condition to endure the stresses of surgery. This is especially vital given recent data linking many surgical deaths to improper anaesthesia administration, with a mortality rate of 20 deaths per 10,000 anaesthetics in developed countries. This paper proposes an integrated fuzzy-based decision support system to assist anaesthetists during pre-operative clinical assessments. The approach combines neural network algorithms to classify and normalize input data, which then feeds into a fuzzy logic system for multi-variable decision-making analysis. To evaluate this decision support system, patient anaesthesia assessment datasheets were sourced from Ibom Multi Specialist Hospital in Akwa Ibom State, along with an online dataset from electronic anaesthesia records (MetaVision, 1MDsoft) of adult patients undergoing surgery at a major academic medical center. The study focused on patients over 18 years old undergoing non-cardiac surgeries, taking into account factors such as urgency and type of anaesthesia. The next step involves a decision-making process that assesses patient suitability for surgical anaesthesia based on established rules and membership functions developed through the fuzzy inference system. The results from this integrated decision support system were found to be reliable and consistent with anaesthetists’ assessments. The system achieved an accuracy of 91.46%, as indicated by a ROC curve comparing sensitivity and specificity, demonstrating its effectiveness in evaluating patients for medical procedures. To enhance the training of future anaesthesiologists, the introduction of artificial intelligence into the curriculum is recommended, along with the application of evolutionary algorithms like genetic algorithms and programming. These strategies aim to significantly enrich the decision-making processes employed by anaesthetists. Keywords: Fuzzy logic, neural network, anaesthesia, artificial intelligence

Simulation with Monte Carlo methods to focus quality improvement efforts on interventions with the greatest potential for reducing PACU length of stay: a cross-sectional observational study

BackgroundTime and money are limited resources to pursue quality improvement (QI) goals. Computer simulation using Monte Carlo methods may help focus resources towards the most efficacious interventions to pursue.MethodsThis observational,...

Utility of polygenic risk score for prediction of dilated cardiomyopathy and modulation of severity of LV dysfunction among cases

Abstract Background Dilated cardiomyopathy (DCM) is a predominant cause of heart failure and a leading indication for cardiac transplantation. While rare genetic variants are established as causative factors in familial forms of the disease, recent genome-wide association studies (GWAS) have also underscored the significant contribution of common genetic variation to DCM. Polygenic scores (PGS) constructed from GWAS have demonstrated promise in risk stratification for a range of common diseases and may similarly have value for risk prediction in DCM. However, data regarding the clinical utility of PGS in DCM remains sparse. Purpose We aimed to evaluate the utility of PGS for prediction of DCM and its association with left ventricular ejection fraction (LVEF) and family history. We further aimed to assess the contribution of PGS in DCM patients with established causative rare variants (genotype-positive) and those without (genotype-negative). Methods We used a previously-constructed PGS, which was developed from a GWAS meta-analysis (8387 DCM cases and 939161 controls) and multi-trait analysis (MTAG) with cardiac MRI traits. In the present analysis, we calculated PGS for a newly assembled cohort of 978 DCM cases from a major university medical centre and 7207 controls from a national register. To evaluate the clinical utility of PGS, we built logistic regression models and assessed the association between PGS and DCM status. Subsequently, we performed subgroup analyses, including: i) individuals of European ancestry, ii) non-European ancestry, iii) males, iv) females, v) genotype-positive participants(n=193), and vi) genotype-negative participants (n=294). We then used linear and logistic regression models, respectively, to assess the associations of PGS with LVEF and documented family history of DCM. Results PGS demonstrated a significant enrichment among DCM cases compared to controls (OR per SD 1.93, P = 9.47E-68). This association persisted with consistent effect estimates - ranging from OR 1.5 to 2.2 - across all examined subgroups and demonstrated sufficient statistical significance (all P<1.58E-06) (Figure 1). Genotype-negative cases had a significantly higher PGS compared to genotype-positive individuals (P = 0.0015), although PGS was significantly enriched in both groups as compared to controls. Furthermore, among DCM cases, higher PGS was significantly associated with lower LVEF at first presentation (P=0.03, beta=-0.5% per SD) (Figure 2). There was no significant association found between PGS and family history. Conclusions PGS is strongly associated with risk of DCM, and may modulate the severity of LV dysfunction among DCM cases. Polygenic burden contributes to DCM risk in both genotype-positive and negative cases, although the contribution is stronger in patients without known causative rare variants. Overall, our results suggest a potential clinical applicability for PGS in DCM risk stratification.Figure 1.Association of PGS with DCMFigure 2.Association of PGS with LVEF

Smartphone Magnetometers for Assessing Programmable Shunt Valve Settings: A Proof-of-Concept Study.

Programmable shunt valves (PSVs) used to treat hydrocephalus require specialized valve-specific devices that determine their setting. However, these devices are typically only accessible in major medical centers. This study explores the feasibility of using smartphone magnetometers to assess PSV settings. We investigated 2 PSVs, the Codman Certas Plus and Medtronic Strata II, using 3 different smartphones. Free open-source software was used to measure magnetic flux densities of the shunts, and PSV-specific algorithms were developed to interpret these measurements. All measurements were performed ex vivo. We demonstrated that this method could accurately determine PSV settings with 100% accuracy in ex vivo blinded trials. The technique was effective even with a scalp analog simulating different skin thicknesses. This proof-of-concept study suggests that smartphones can be used for PSV assessment. However, further development and validation are needed to refine this method for clinical use. This technology could enhance PSV management accessibility, allowing for remote or at-home evaluations by trained individuals or caregivers, thus improving patient care in underserved areas.

The Impact of Cultural Dimensions and Quality of Life on Smartphone Addiction and Employee Performance: The Moderating Role of Quality of Life

AbstractSmartphones, while ubiquitous and beneficial, can lead to problematic use. This study investigates the intricate interplay between cultural dimensions, smartphone addiction, and employee performance. Through the lens of distraction theory, attachment Theory, coping theory combined with Hofstede's cultural dimensions, and self-regulation theory and quality of life, we examine how collectivism, individualism, uncertainty avoidance, and masculinity cultural dimensions influence smartphone addiction and its subsequent effect on employee performance. The findings, based on data collected from 233 employees at a major medical center in the Midwest region of the USA and employing structural equation modeling, reveal a significant cultural influence on smartphone addiction, ultimately leading to a decline in performance. However, quality of life emerges as a crucial moderator, mitigating the negative impact of smartphone addiction. This research offers valuable insights for information systems scholars, highlighting the importance of cultural context in understanding smartphone addiction. Furthermore, the study equips managers with practical knowledge to address smartphone addiction within a culturally diverse workforce. By implementing strategies that enhance employee quality of life, organizations can foster a more productive and engaged work environment.

Changes in Medication Adherence Across the Posttransplant Period in Pediatric Organ Transplant Recipients.

Limited research has explored immunosuppressant medication adherence over time in pediatric transplant patients, who often struggle with posttransplant regimen adherence, resulting in poor outcomes. This study investigated the longitudinal growth in immunosuppressive medication levels following transplantation. Medication level variability index (MLVI) scores from tacrolimus blood levels of pediatric organ transplant recipients at a major medical center were analyzed. Linear mixed effect models (LMEM) assessed individual MLVI change trajectories and predictors of growth, exploring both linear and curvilinear growth patterns posttransplant. A sample of 181 patients with at least 4 years of MLVI data were analyzed. Growth curve modeling identified the cubic model as the best fit for the quarterly MLVI values, which significantly decreased within the first 2 years posttransplant before stabilizing. Gender significantly predicted MLVI change, with females showing greater MLVI decreases, while age at transplant did not significantly predict changes. Significant variation in MLVI among individual patients was found in all models. The study demonstrated a significant decrease in MLVI values over time, indicating improved medication adherence in pediatric transplant patients, with females exhibiting more adherent growth patterns than males. Future research should aim to identify pediatric patients at high risk of nonadherence.

Risk assessment model used to predict discharge care after total hip and total knee arthroplasty: A population-based study

BackgroundTransfer to a post-acute care facility or hospital readmission after total joint arthroplasty represent additional costs and increased surgical and health care resource utilization. Accurate prediction of post-acute care factors could help providers to plan the patient's discharge destination and have a positive impact on postoperative outcomes and readmission rates. ObjectiveTo develop a risk assessment model to predict discharge care after total hip arthroplasty (THA) and total knee arthroplasty (TKA). DesignA retrospective longitudinal observational study. Settingsand participants: This study included 209 patients who underwent primary unilateral THA or TKA at a major academic medical center in Switzerland from January 2018 to December 2019. MethodsA collection of computerized- and paper-recorded data identified the discharge destination, socio-demographic factors, comorbidities, and other factors related to the patient. Univariate and multivariate analyses were performed to describe the predictors of post-surgical discharge destinations. ResultsThe characteristics associated with post-acute care after primary unilateral THA or TKA were the absence of a caregiver, advanced age, female gender, presence of walking aids, high ASA score, and comorbidity severity. A prediction model demonstrated that these six characteristics were associated 52 % with discharge to a post-acute care destination. ConclusionsThis study allowed us to identify predictors of discharge to a post-surgical destination. Predictive models can be efficiently used to better predict which patients are predisposed to post-acute care after hospital discharge. Further studies are needed to determine the optimal criteria for different destinations.

Keratin 17 and A2ML1 are negative prognostic biomarkers in non-small cell lung cancer

Although the overall prognosis for patients with non-small cell lung cancer (NSCLC) has improved over the past several decades, there are still survival differences that are not accurately defined by clinicopathological factors. Thus, there is an unmet clinical need to develop novel approaches to enhance prognostic accuracy for these patients. Keratin 17 (K17) is a negative prognostic biomarker in a wide range of cancer types, including pancreatic ductal adenocarcinoma, head and neck squamous cell carcinoma, and pulmonary adenocarcinoma (LUAD), but has yet to be investigated as a prognostic biomarker in primary lung squamous cell carcinoma (LSCC). Based on TCGA RNA-seq data, alpha-2-macroglobulin like 1 (A2ML1), a protease inhibitor, is highly correlated with K17 in other solid tumors, including pancreatic ductal adenocarcinoma and is also a prognostic biomarker for LSCC, although the prognostic accuracy of A2ML1 for LUAD has not been tested. Thus, we hypothesized that A2ML1 expression correlates with K17 expression and that K17/A2ML1 co-testing could provide complementary prognostic data for NSCLC. The aims of this study were to explore K17 and A2ML1 as dual prognostic biomarkers, using publicly available gene expression databases [The Cancer Genome Atlas (TCGA)] LSCC (n=266), LUAD (n=271)] and multiplexed immunohistochemistry (mIHC) on representative sections of LSCC (n=104) and LUAD (n=107) from two major academic medical centers. Our results suggest that using either mRNA or mIHC-based methods, combined K17 and A2ML1 testing provides information, independent of other clinicopathologic variables, that could impact treatment decisions for patients with NSCLC.

Enhancing Preoperative Diagnosis of Subscapular Muscle Injuries with Shoulder MRI-based Multimodal Radiomics

PurposeRotator cuff injury is a common ailment in the musculoskeletal system, with the subscapularis muscle being the largest and most robust muscle of the rotator cuff. The occurrence of subscapularis muscle tears is more frequent than previously reported. The main objective of this research is to harness the power of artificial intelligence to enhance the precision in diagnosing subscapularis muscle injuries via magnetic resonance imaging of the shoulder joint, prior to surgical intervention. This study seeks to integrate advanced artificial intelligence algorithms to analyze magnetic resonance imaging data, aiming to provide more accurate preoperative assessments, which can potentially lead to better surgical outcomes and patient care and promote technological progress in the field of medical imaging analysis. MethodThis is a multicenter study that involves 324 patients from a major medical center serving as both the training and testing groups, with an additional 60 patients from two other medical centers comprising the verifying group. The imaging protocol for all these subjects included a series of shoulder magnetic resonance imaging scans: T1-weighted coronal sequences, T2-weighted coronal, axial, and sagittal images. These comprehensive imaging modalities were utilized to thoroughly examine the shoulder joint's anatomical details and to detect any signs of subscapularis muscle damage. To enhance the diagnostic accuracy before surgical procedures, radiomic analysis was employed. This technique involves the extraction of a multitude of quantitative features from the magnetic resonance imaging, which can provide a more nuanced and data-driven approach to identifying subscapularis muscle injuries. The integration of radiomics in this study aims to offer a more precise preoperative assessment, potentially leading to improved surgical planning and patient outcomes. ResultIn the course of this study, a comprehensive extraction of 1197 radiomic features was performed for each imaging modality of every patient. The coronal T1-weighted modality, when assessed within the internal verifying cohort, delivered a diagnostic accuracy of 0.766, coupled with an AUC of 0.803. In the case of the T2-weighted modality, the coronal planes exhibited a diagnostic accuracy of 0.781 and an AUC of 0.844. The axial T2-weighted images recorded an accuracy of 0.719 and an AUC of 0.761, while the sagittal T2-weighted images scored an accuracy of 0.766 and an AUC of 0.821. The amalgamation of these imaging techniques through a multimodal strategy markedly enhanced the accuracy to 0.828, with an AUC of 0.916 for the internal verifying group. The diagnostic performance of the coronal T1-weighted modality in the external verifying cohort yielded an accuracy of 0.833, with an area under the curve (AUC) of 0.819. For the T2-weighted modality, the coronal imaging demonstrated an accuracy of 0.767 and an AUC of 0.794. The axial T2-weighted images had an accuracy of 0.783 and an AUC of 0.797, while the sagittal T2-weighted images achieved an accuracy of 0.833 and an AUC of 0.800. When combining the modalities, the multimodal approach significantly improved the accuracy to 0.867, with an AUC of 0.803 in the external verifying group, indicating a robust diagnostic capability. ConclusionOur study demonstrates that the application of multimodal radiomic techniques to shoulder magnetic resonance imaging significantly enhances the precision of preoperative diagnosis for subscapularis muscle injuries. This approach leverages the comprehensive data provided by various magnetic resonance imaging modalities to offer a more detailed and accurate assessment, which is crucial for surgical planning and patient care.

Evaluation of Skin of Color Curricular Content for Physician Assistant Education.

Physician assistants (PAs) are often members of dermatologic care teams. Adequate knowledge of dermatologic conditions in skin of color (SOC) is crucial to proper diagnosis, treatment, and patient satisfaction. The objective of this study was to increase PA students' objective knowledge of and comfort level with evaluating dermatologic conditions in SOC. Eligible participants included 36 PA students at a major metropolitan medical center during the 2022 to 2023 academic year. A preintervention survey, immediate postintervention survey, and 7-month follow-up postintervention survey were administered before and after a SOC lecture. The surveys concluded with a 10-question, image-based, multiple-choice examination. There was a significant increase in accurate diagnoses of acne scarring, eczema, psoriasis, rosacea, and seborrheic dermatitis in SOC (59.4% preintervention to 76.9% postintervention, P = .029). Student confidence, as rated on a scale of 1 (minimally confident) to 5 (extremely confident), in diagnosing these conditions increased from 2.97 to 3.52 (P = .036). Implementation of a SOC-specific dermatology lecture significantly increased the accuracy and confidence with which PA students diagnosed dermatologic conditions.

Comparative motility assessment of sperm retrieved from micro-testicular sperm extraction: A single-centre study comparing fresh and frozen-thawed sperm.

Microsurgical testicular sperm extraction (microTESE) is crucial for treating non-obstructive azoospermia (NOA), offering both 'fresh' and 'frozen' options. This study evaluates the impact of fresh versus frozen microTESE on the progression to intra-cytoplasmic sperm injection (ICSI) cycles, focusing on sperm motility. We conducted a retrospective analysis of microTESE procedures at a major medical centre from 2007 to 2021, excluding cases of obstructive azoospermia and cryptozoospermia. Patients were divided into two groups: fresh microTESE (Group FR) and frozen microTESE (Group FZ). Sperm motility was assessed, and ICSI outcomes were compared between groups. Out of 128 microTESE procedures on 113 NOA patients, 31 were fresh and 97 were frozen. Sperm was found in 67.7% of fresh cases and 45.3% of frozen cases. In fresh cases, 85.7% had motile sperm for ICSI, whereas in frozen cases, 81.8% had motile sperm initially, but only 52.7% retained motility post-thaw. Our findings indicate a significant drop in motile sperm availability for ICSI in frozen microTESE cases compared to fresh ones. This suggests a potential advantage of fresh microTESE for certain couples, despite the logistical challenges, highlighting the need for careful patient selection and counselling.

Ocular manifestations in ANCA-associated vasculitis: a comprehensive analysis from Chinese medical centers.

This study aimed to explore ocular manifestations in ANCA-associated vasculitis (AAV), focusing on granulomatosis with polyangiitis (GPA), eosinophilic granulomatosis with polyangiitis (EGPA), and microscopic polyangiitis (MPA) and to examine the associations with laboratory parameters and other systemic manifestations. This retrospective study reviewed data from 533 AAV patients across two major Chinese medical centers from January 2016 to November 2023. Data including diagnosis, cranial manifestations of disease, ocular complications, and laboratory parameters were analyzed. Univariate and multivariable logistic regression analyses assessed associations across disease manifestations. Machine learning models were also utilized to predict the risk of retinal/eye involvement in AAV patients. Among 533 patients (210 GPA, 217 MPA, 99 EGPA, and 7 unclassified AAV), ocular complications were observed in 20.64% of them, with a distribution of 36.67% in GPA, 7.37% in MPA, and 18.18% in EGPA. The most common ocular manifestations included scleritis and retro-orbital mass/dacryocystitis, which were notably prevalent in GPA patients. Retinal involvement was observed in 9.09% of EGPA cases. The machine learning models yielded that eosinophil percentage (EOS%), high-sensitivity C-reactive protein (hsCRP), and CD4 + T cell/CD8 + T cell ratio (T4/T8) can predict retinal involvement. Furthermore, the white blood cell, EOS%, APTT, IgA, hsCRP, PR3-ANCA, and T4/T8 can predict eye involvement. Ocular manifestations are a prevalent complication across all forms of AAV. Predictive models developed through machine learning offer promising tools for early intervention and tailored patient care. This necessitates a multidisciplinary approach, integrating rheumatology and ophthalmology expertise for optimal patient outcomes.

Disability Identity and Perceptions of Institutional Fairness and Climate in Academic Medicine

This cross-sectional study examines whether students and employees with or without disabilities at a major academic medical center in the US feel respected and are treated equitably at their institution

Myoglobin saturation as an intracellular indicator for transfusion need in oncology patients.

This study aims to demonstrate the potential of myoglobin saturation as an indicator of oxygen delivery adequacy to help determine the need for red cell transfusion. Modern blood management approaches have been established to optimise use of red blood cells for transfusions in patients with anaemia. However, most approaches make recommendations to transfuse based on haemoglobin or haematocrit levels and do not directly address adequacy of oxygen delivery. Intracellular oxygen determined by myoglobin saturation directly measures oxygen delivery at the tissue level. A custom built spectrometer system with an optical fibre probe was used in this pilot study to measure muscle cell myoglobin saturation noninvasively from the first digital interosseous muscles in patients undergoing planned red blood cell transfusion. Patients were recruited from both the in-patient and out-patient oncology service at a major university medical centre. Measurements were made immediately before, immediately after, and 24 h following transfusion. Clinical data and tissue oxygen values from the Somanetics INVOS system were also collected. Myoglobin saturation, and thus cellular oxygen increased in some, but not all patients receiving a transfusion, and was most pronounced in patients who initially had low myoglobin saturation compared with the group as a whole. Clinical decisions to transfuse based on haemoglobin or haematocrit thresholds alone are likely insufficient to optimise use of red blood cell transfusions. The combination of haemoglobin or haematocrit with myoglobin saturation may optimally determine who will benefit physiologically from a transfusion.

Utilizing multimodal radiomics technology from cervical MRI for diagnosis of cervical spinal cord injury and spinal cord concussion

The primary aim of this study is to assess the viability of employing multimodal radiomics techniques for distinguishing between cervical spinal cord injury and spinal cord concussion in cervical magnetic resonance imaging. This is a multicenter study involving 288 patients from a major medical center as the training group, and 75 patients from two other medical centers as the testing group. Data regarding the presence of spinal cord injury symptoms and their recovery status within 72 h were documented. These patients underwent sagittal T1-weighted and T2-weighted imaging using cervical magnetic resonance imaging. Radiomics techniques are used to help diagnose whether these patients have cervical spinal cord injury or spinal cord concussion. 1197 radiomics features were extracted for each modality of each patient. The accuracy of T1 modal in testing group is 0.773, AUC is 0.799. The accuracy of T2 modal in testing group is 0.707, AUC is 0.813. The accuracy of T1 + T2 modal in testing group is 0.800, AUC is 0.840. Our research indicates that multimodal radiomics techniques utilizing cervical magnetic resonance imaging can effectively diagnose the presence of cervical spinal cord injury or spinal cord concussion.

Phi and phiD predict adverse pathological features after radical prostatectomy for prostate cancer in Chinese population.

Anticipating the postoperative pathological stage and potential for adverse features of prostate cancer (PCa) patients before radical prostatectomy (RP) is crucial for guiding perioperative treatment. A cohort consisting of three sub-cohorts with a total of 709 patients has been enlisted from two major tertiary medical centres in China. The primary assessment parameters for adverse pathological features in this study are the pathological T stage, the AJCC prognostic stage groups and perineural invasion (PNI). Logistic regression analyses were performed to investigate the relationship between prostate specific antigen (PSA), its derivatives (incluing Prostate Health Index, phi and phi density, phiD), and the pathological outcomes after RP. Both phi and phiD showed a significant association with pathologic T stage of pT3 or above (phi, adjusted OR, AOR = 2.82, 95% confidence interval, 95% CI: 1.88-4.23, p < 0.001; phiD, AOR = 2.47, 95% CI: 1.76-3.48, p < 0.001) and PNI (phi, AOR = 2.15, 95% CI: 1.39-3.32, p < 0.001; phiD, AOR = 1.94, 95% CI: 1.38-2.73, p < 0.001). In a subgroup analysis with a total PSA value <10 ng/mL, phi and phiD continued to show a significant correlation with pT3 or above (phi, AOR = 4.70, 95% CI: 1.29-17.12, p = 0.019; phiD, AOR = 3.44, 95% CI: 1.51-7.85, p = 0.003), and phiD also maintained its predictive capability for PNI in this subgroup (AOR = 2.10, 95% CI: 1.17-3.80, p = 0.014). Sensitivity analysis indicated that the findings in the combined cohort are mainly influenced by one of the sub-cohorts, partially attributable to disparities in sample sizes between sub-cohorts. Combined analysis of phi(D) and multiparametric MRI (mpMRI) data yielded similar results. Preoperative measurement of serum phi and phiD is valuable for predicting the occurrence of adverse pathological features in Chinese PCa patients after RP.