Clinical Metrics Research Articles

Performance of an AI-powered visualization software platform for precision surgery in breast cancer patients.

Surgery remains the primary treatment modality in the management of early-stage invasive breast cancer. Artificial intelligence (AI)-powered visualization platforms offer the compelling potential to aid surgeons in evaluating the tumor's location and morphology within the breast and accordingly optimize their surgical approach. We sought to validate an AI platform that employs dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to render three-dimensional (3D) representations of the tumor and 5 additional chest tissues, offering clear visualizations as well as functionalities for quantifying tumor morphology, tumor-to-landmark structure distances, excision volumes, and approximate surgical margins. This retrospective study assessed the visualization platform's performance on 100 cases with ground-truth labels vetted by 2 breast-specialized radiologists. We assessed features including automatic AI-generated clinical metrics (e.g., tumor dimensions) as well as visualization tools including convex hulls at desired margins around the tumor to help visualize lumpectomy volume. The statistical performance of the platform's automated features was robust and within the range of inter-radiologist variability. These detailed 3D tumor and surrounding multi-tissue depictions offer both qualitative and quantitative comprehension of cancer topology and may aid in formulating an optimal surgical approach for breast cancer treatment. We further establish the framework for broader data integration into the platform to enhance precision cancer care.

Abstract 4121793: A Pressure-Volume Loops Approach Predicts Outcomes After Double Switch Operation For Congenitally Corrected Transposition Of The Great Arteries with Intact Ventricular Septum

Background: Double switch operation (DSO) for congenitally corrected transposition of the great arteries with intact ventricular septum (ccTGA) has a high rate of post-DSO LV dysfunction. Hypothesis: LV pressure-volume area (PVA), a surrogate of myocardial O 2 consumption, is a superior marker of LV preparedness and is associated with adverse outcomes after DSO. Aims: 1. Derive a mathematical relationship to estimate LV PVA (ePVA) from catheterization (pressure) and imaging (volumetric) data, using directly measured PVA (mPVA) as reference 2. Assess if lower ratio of LV ePVA to RV ePVA (as an internal control) is associated with adverse outcome after DSO. Methods: Aim 1: Using conductance catheter derived invasive subpulmonary LV PV loops, mPVA was recorded as the sum of stroke work (SW) and potential energy (PE). A mathematical relationship was established with standard catheterization/imaging data to estimate ePVA. Aim 2: In a retrospective cohort, LV:RV ePVA ratio was calculated as above, and along with standard clinical metrics, assessed for relationship with a composite outcome of ≥ moderate LV dysfunction, transplant, or death post-DSO. Results: Aim 1: In 20 PV loop studies in 18 pre-DSO patients, there was a strong linear correlation between measured and estimated SW and PE (R 2 > 0.9 and p<0.0001 for both). ePVA yielded high agreement and low bias compared to mPVA (mean bias 0.5±11%). Aim 2: Composite outcome occurred in 6/42 DSO patients (14%). LV:RV ePVA ratio (0.57 [0.49, 0.61] vs 0.90 [0.73, 1.1], p<0.001) and LV:RV pressure ratio (0.80 [0.77, 0.87] vs 1.13 [1.01, 1.23], p<0.001) were lower in those with adverse outcome. There were no differences in other pre-operative parameters. On time to event analysis, lower LV:RV ePVA ratio was the strongest determinant (HR 39, 95% CI 15-100; C Index 0.94), while lower LV:RV pressure ratio was the only other predictor (HR 24, 95% CI 13-42; C Index 0.88). In 8 patients with borderline pressure ratios of 0.77-0.88, ePVA ratio was an excellent discriminator - 3 patients with ePVA ratio of ≥0.67 had good outcomes, whereas 5 patients with ePVA ratio <0.67 had adverse outcomes. Conclusion: LV:RV ePVA ratio >0.67 is a strong and novel predictor of LV preparedness for DSO in patients with ccTGA.

Flash glucose monitoring system help reduce the frequency of hypoglycemia and hypoglycemic fear behavior in type 1 diabetes patients

ObjectiveHypoglycemia represents a serious acute complication in individuals with type 1 diabetes mellitus (T1DM). In order to more effectively identify and discriminate the occurrence of hypoglycemic events in patients with T1DM, this study aims to evaluate the impact of two distinct glucose monitoring systems—Flash Glucose Monitoring (FGM) and Continuous Glucose Monitoring (CGM)—on the management of blood glucose levels and the emotional responses associated with hypoglycemic episodes in individuals with T1DM.MethodIn this study, a total of 113 patients with type 1 diabetes mellitus were enrolled and allocated to two groups for the implementation of Glucose Monitoring Systems (GMS). The groups consisted of the FreeStyle Libre group (FGM, n=56) and the ipro2 group (CGM, n=57). Participants in both groups utilized GMS at least biannually and completed a set of three questionnaires: the Diabetes Monitoring and Treatment Satisfaction Questionnaire (DMTSQ), the Diabetes Specific Quality of Life (DQOL), and the Chinese Version of the Hypoglycemia Fear Survey II (CFHSII). Clinical data, CGM metrics, and questionnaire scores were collected at the initial visit and after a one-year follow-up period.ResultsThe glucose coefficient of variation (GCV) and the standard deviation of blood glucose (SDBG) were independently associated with Time Below Range (TBR). Specifically, GCV could predict TBR ≥12%, with a cut-off point of 40.55. This yielded a specificity of 88.10% and a sensitivity of 68.18% in the overall patient population. For the FreeStyle Libre group and the iPro2 group, the cut-off points were 38.69 and 40.55, respectively, with specificities of 0.74 and 0.92, and sensitivities of 0.73 and 0.86, respectively. In the FreeStyle Libre group, where the frequency of use was greater than or equal to five times per year, the hypoglycemic episodes (time/month) and CHFSII-B scores were significantly reduced at follow-up compared to baseline (7.80 ± 10.25 vs 13.95 ± 14.87; 27.37 ± 11.05 vs 38.90 ± 21.61, respectively, all P <0.05).ConclusionThe utilization of multiple Flash Glucose Monitoring (FGM) implementations proved to be valuable in discriminating the occurrence of hypoglycemia and mitigating the fear of hypoglycemic episodes in patients with type 1 diabetes. Within the parameters of Glucose Monitoring Systems (GMS), the glucose glycemic variability (GCV) was identified as a predictive factor for the risk of severe hypoglycemia (TBR > 12%). The optimal cut-off point for GCV was determined to be 40.55.

Clinical Tools to Assess Functional Capacity During Risk Assessment Before Elective Noncardiac Surgery : A Scoping Review.

Functional capacity is critical to preoperative risk assessment, yet guidance on its measurement in clinical practice remains lacking. To identify functional capacity assessment tools studied before surgery and characterize the extent of evidence regarding performance, including in populations where assessment is confounded by noncardiopulmonary reasons. MEDLINE, EMBASE, and EBM Reviews (until July 2024). Studies evaluating performance of functional capacity assessment tools administered before elective noncardiac surgery to stratify risk for postoperative outcomes. Study details, measurement properties, pragmatic qualities, and/or clinical utility metrics. 6 categories of performance-based tests and 5 approaches using patient-reported exercise tolerance were identified. Cardiopulmonary exercise testing (CPET) was the most studied tool (132 studies, 32 662 patients) followed by field walking tests (58 studies, 9393 patients) among performance-based tests. Among patient-reported assessments, the Duke Activity Status Index (14 studies, 3303 patients) and unstructured assessments (19 studies, 28 520 patients) were most researched. Most evidence focused on predictive validity (92% of studies), specifically accuracy in predicting cardiorespiratory complications. Several tools lacked evidence on reliability (test consistency across similar measurements), pragmatic qualities (feasibility of implementation), or concurrent criterion validity (correlation to gold standard). Only CPET had evidence on clinical utility (whether administration improved postoperative outcomes). Older adults (≥65 years) were well represented across studies, whereas there were minimal data in patients with obesity, lower-limb arthritis, and disability. Synthesis focused on reported data without requesting missing information. Though several tools for preoperative functional capacity assessment have been studied, research has overwhelmingly focused on CPET and only 1 aspect of validity (predictive validity). Important evidence gaps remain among vulnerable populations with obesity, arthritis, and physical disability. None. (Open Science Framework: https://osf.io/ah7u5).

NIMG-59. COMPARATIVE ANALYSIS OF LONG-TERM GLIOBLASTOMA SURVIVORS USING MACHINE LEARNING GENERATED RADIO-PATHOMIC METRICS

Abstract BACKGROUND Glioblastoma (GBM) remains the most devastating central nervous system malignancy with poor overall survival (OS), even with gross total resection (GTR) and chemoradiation. Identifying factors associated with long-term survival (LTS) in GBM patients is challenging but crucial for improving prognostic models. This study compares an internal dataset of the top 10% long-term survivors of GBM (n=14) against a combined external cohort of 528 GBM patients who underwent GTR. METHODS We used a previously published machine learning-generated radio-pathomic model based on autopsy tissue as ground-truth to generate whole-brain maps of cell density and tumor probability maps (TPM) using conventional preoperative MRI sequences in both our internal dataset and a combined external cohort of GBM patients who underwent GTR from the UCSF-PDGM-v2 and UPenn-GBM databases. We then analyzed clinical and radio-pathomic metrics, including cell density and TPM values within contrast-enhancing (CE) and FLAIR hyperintense regions. Statistical comparisons were performed using t-tests. RESULTS Cell density metrics showed significant differences, with lower cell density in contrast-enhancing regions (t-value: 4.709, p<0.001; median: 1559 vs. 1959) and in FLAIR hyperintense regions (t-value: 3.585, p<0.001; median: 1356 vs. 1568) within the LTS group. TPM metrics also showed significant differences, with lower TPM values in contrast-enhancing regions (t-value: 3.312, p<0.001; median: 0.71 vs. 0.72) and in non-enhancing regions (t-value: 2.606, p<0.01; median: 0.68 vs. 0.69) in the LTS group. CONCLUSION Our comparative analysis reveals distinct radio-pathomic characteristics associated with long-term survival in GBM patients. Reduced cell density and lower TPM values in both contrast-enhancing and FLAIR hyperintense regions are significantly correlated with long-term survival. These findings suggest that integrating radio-pathomic data may enhance prognostic models and warrants further studies evaluating the relationship of these markers and OS.

The clinical application value of mixed reality in robotic laparoscopic partial nephrectomy

PurposeRobot-assisted laparoscopic partial nephrectomy (RAPN) has become a key technology in the treatment of renal tumors. Effective preoperative planning and precise intraoperative navigation are critical to a successful surgical outcome. This study aimed to evaluate the clinical application value of mixed reality (MR) in robotic nephron-sparing partial nephrectomy for patients with renal tumors of different complexity based on the R.E.N.A.L. score.Patients and methodsA retrospective analysis was conducted on 68 eligible patients with renal cancer who underwent RAPN at The Second Affiliated Hospital of Nanchang University from January 2021 to December 2023, with postoperative pathology confirmation. Patients were divided into two groups: the MR group, with 28 cases, and the traditional imaging (control) group, with 40 cases. All patients underwent mid-abdominal CT plain scans and enhancements. The MR group utilized three-dimensional reconstruction of CT data and employed 3D tablets and HoloLens glasses for preoperative discussions, surgical planning, and intraoperative guidance. Collect clinical data and metrics to assess surgical outcomes, as well as evaluate performance in areas such as preoperative discussions, doctor-patient communication, surgical planning, and intraoperative navigation.ResultsCompared to robot-assisted partial nephrectomy in the control group, the MR group experienced a reduction in operation time by approximately 30 min [(135.89 ± 23.494) min vs. (165.00 ± 34.320) min, P< 0.001)] and a decrease in ischemia time by around 2.5 min [(20.36 ± 3.956) min vs. (23.80± 6.889) min, P = 0.02)]. Within the subgroup with a R.E.N.A.L. score of less than 7 points, the MR group only showed a significant reduction in operation time [(134.55 ± 150.190) min vs. (150.19 ± 28.638) min, P = 0.045], with no notable differences in other parameters. For the subgroup with a R.E.N.A.L. score of 7 points or higher, the MR group exhibited shorter operation time [(140.83 ± 25.183) min vs. (195.77 ± 23.080) min, P< 0.001] and reduced warm ischemia time [(21.17 ± 2.714) min vs. (28.85 ± 7.570) min, P = 0.029]. Additionally, there was less estimated blood loss [(53.33 ± 5.164) min vs. (114.62 ± 80.376) min, P = 0.018]. All patients had negative resection margins, indicating equivalent therapeutic outcomes between the two groups.ConclusionIn comparison to traditional RAPN, MR technology demonstrates the ability to decrease operation time and warm ischemia time all the while maintaining equivalent curative outcomes. Additionally, it enhances preoperative discussions, doctor-patient interactions, preoperative strategizing, and intraoperative navigation, particularly excelling in complex renal tumor cases of RAPN, where its benefits are most pronounced.

Categorizing Care Delays and Their Impact on Hospital Length of Stay.

Unnecessary care delays of hospitalized patients increase the risk of hospital-related complications and drive up health care costs. While health systems focus on reducing the length of stay of hospitalized patients, not many studies looked at specific causes of the care delays that prolong length of stay. In this study, we sought to systematically identify and categorize the various care delays that contribute to prolonged length of stay on a hospital medicine service. We conducted a retrospective observational study looking at all inpatient encounters to the hospitalist service (N=6633) for the fiscal year 2021. Observation status, COVID-19 positive, and other services' discharged patients were excluded (N=2849) leaving 3784 eligible encounters. The resulting 5% stratified random sample accounted for 190 encounters accounting for a total of 1152 patient-days. Using a standardized data extraction tool, a day-by-day review of the sample encounters was performed for all care delays. These care delays were categorized into specific groups (System, Discharge, Provider, Patient/Family, or Consultant related) and subgroups based on predetermined criteria. The stratified sample was found to be comparable to the total patient population, with no statistically significant differences in key demographic and clinical metrics. About 30% of all patient-days had a care delay; 33% of these delays were attributable to system delays internal to the hospital such as waiting for imaging/procedures; 28% of delays were due to discharge barriers, driven overwhelmingly by a lack of available post-acute care beds, and about 20% of delays were attributable to the provider. Our study systematically looked at care delays that led to prolonged hospital length of stay. Most of these care delays were caused by either wait times for procedures and imaging studies or by a lack of post-acute care bed availability. Hospitals and health systems can use this approach to better determine which systemic changes are likely to be the most effective at reducing length of stay.

Longitudinal analysis of ARDS variability and biomarker predictive power in burn patients

Acute Respiratory Distress Syndrome (ARDS) is a severe complication in burn patients, characterized by rapid lung inflammation and hypoxemia. Managing ARDS is challenging due to its high mortality rates and the complex interplay of various pathophysiological factors. This study aims to investigate the heterogeneity of ARDS in burn patients admitted to the Intensive Care Unit (ICU) and evaluate the predictive efficacy of biomarkers in comparison to the PaO2/FiO2 (PF) ratio. A retrospective cohort study was conducted at the Burn Intensive Care Unit of Hangang Sacred Heart Hospital in Seoul, Korea, from July 2010 to December 2022, involving 2,318 patients. Longitudinal k-means clustering was employed to identify patient subgroups based on PF ratio trajectories. Biomarkers, including albumin, white blood cell (WBC) count, and lactate, were assessed for their predictive accuracy using multivariable logistic regression, area under the curve (AUC) analysis, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Four distinct patient clusters were identified. Cluster A exhibited the highest mortality rate at 54.9%, while Cluster D showed the lowest at 7.9%. Albumin demonstrated significantly higher predictive accuracy in Cluster A (AUC: 0.905, NRI: 0.421) and Cluster C (AUC: 0.915, NRI: 0.845), outperforming the PF ratio in both groups. However, in Clusters B and D, biomarkers did not significantly improve upon the predictive power of the PF ratio. Across all clusters, the integration of biomarkers with the PF ratio led to modest improvements but did not consistently outperform the PF ratio as a standalone predictor. This study reveals substantial heterogeneity in ARDS progression among burn patients, with varying mortality rates and biomarker efficacy across clusters. While biomarkers such as albumin showed potential in specific subgroups, their overall contribution to predictive accuracy was limited. Further multicenter, prospective studies are required to validate these findings and develop more refined predictive models. Personalized treatment strategies, based on biomarker profiles and traditional clinical metrics, could enhance ARDS management in burn patients.

Establishing Clinical Significance for Patients Undergoing Arthroscopic Repair of Type II SLAP Lesions.

Type II superior labrum anterior to posterior (SLAP) lesions may be treated with either arthroscopic repair or biceps tenodesis. There are no previous reports of measures of clinically significant improvement after arthroscopic repair of SLAP lesions. To establish the minimal clinically important difference (MCID), Patient Acceptable Symptom State (PASS), and substantial clinical benefit (SCB) for patients undergoing arthroscopic repair for type II SLAP lesions. Case series; Level of evidence, 4. A total of 69 arthroscopic repair procedures for isolated type II SLAP lesions were performed in a military population. The mean age was 28.1 ± 4.7 years, 97.1% were male, and the mean follow-up was 99.5 ± 19.7 months. The MCID, PASS, and SCB were calculated for each patient-reported outcome measure, consisting of the American Shoulder and Elbow Surgeons (ASES) score, Single Assessment Numeric Evaluation (SANE), and visual analog scale (VAS) for pain, using anchor- and distribution-based models. Factors associated with achieving a clinically relevant improvement were also determined. The MCID, PASS, and SCB for each measure were as follows: 7.7, 70, and 34 for the ASES score, respectively; 10.4, 80, and 45 for the SANE, respectively; and 1.0, 4, and 6 for the VAS pain, respectively. At least 85% of patients achieved the MCID for each measure; however, PASS rates were lower, with 50.7% for the SANE and 69.6% for both the ASES score and VAS pain. The ASES score had the highest percentage of patients achieving the SCB at 44.9%, followed by the SANE (26.1%) and VAS pain (10.1%). Greater forward flexion at final follow-up was associated with achieving the MCID and PASS for both the ASES score and SANE. Internal rotation stiffness at final follow-up was negatively associated with achieving the PASS for the VAS pain. Combat arms military occupational specialty was associated with a lesser likelihood of achieving the SCB for the ASES score. Clinical metrics of improvement were defined for the ASES score, SANE, and VAS pain using the MCID, PASS, and SCB for patients undergoing arthroscopic repair of type II SLAP lesions. Better final range of motion was positively associated with achieving improvement, while high-intensity military duty was negatively associated.

Clinical diagnostic reference levels and image quality metrics for CT in oncology patients

Background: In CT, the volumetric CT dose index (CTDIvol), dose-length product (DLP) and patient’s size-specific dose estimates (SSDE) are used as diagnostic reference level (DRL) metrics.Objectives: To develop clinical local DRL values for CT chest-abdomen-pelvis (CAP) examinations using the CTDIvol, DLP and SSDE, and to determine the image quality achieved.Method: In total, 201 cancer patients were included in the study. The scanning parameters, dose metrics from the CT unit and participants’ body mass index (BMI) were documented. The local CT DRL values for CAP examinations were defined as the median and 75th percentiles of the dose distribution.Results: The local DRL values given in terms of median CTDIvol ranged between 8.4 mGy and 12.7 mGy for the different types of cancers. The median DLPs ranged from 848 to 1173.4 mGy.cm for the various cancers. Generally, the radiation dose was directly proportional to the BMI and number of scan phases. Significant differences were observed between the DRLs for the various size-related parameters, number of scan phases and BMI classifications. The image quality was clinically satisfactory.Conclusion: No baseline data for clinical DRL values were available for this medical oncology department. The achieved DRLs were similar to published size-specific DRLs. The image quality was maintained during CT imaging. Dose optimisation and image quality assessment should be implemented to ensure optimal scanning parameters for different cancers in CT CAP examinations.Contribution: The first size-specific local DRL values for CT CAP investigations carried out on oncology patients in South Africa have been established.

Assessment of Artificial Intelligence Chatbot Responses to Common Patient Questions on Bone Sarcoma.

The potential impacts of artificial intelligence (AI) chatbots on care for patients with bone sarcoma is poorly understood. Elucidating potential risks and benefits would allow surgeons to define appropriate roles for these tools in clinical care. Eleven questions on bone sarcoma diagnosis, treatment, and recovery were inputted into three AI chatbots. Answers were assessed on a 5-point Likert scale for five clinical accuracy metrics: relevance to the question, balance and lack of bias, basis on established data, factual accuracy, and completeness in scope. Responses were quantitatively assessed for empathy and readability. The Patient Education Materials Assessment Tool (PEMAT) was assessed for understandability and actionability. Chatbots scored highly on relevance (4.24) and balance/lack of bias (4.09) but lower on basing responses on established data (3.77), completeness (3.68), and factual accuracy (3.66). Responses generally scored well on understandability (84.30%), while actionability scores were low for questions on treatment (64.58%) and recovery (60.64%). GPT-4 exhibited the highest empathy (4.12). Readability scores averaged between 10.28 for diagnosis questions to 11.65 for recovery questions. While AI chatbots are promising tools, current limitations in factual accuracy and completeness, as well as concerns of inaccessibility to populations with lower health literacy, may significantly limit their clinical utility.

Multi-centre post-mortem study on the use of coronary inflammation in CCTA to improve the diagnosis of the coronary related cause of death with histopathology validation

Abstract Background/Introduction A limitation of post-mortem computed tomography (PMCT) is the diagnostic accuracy of coronary related death, which constitute majority of investigations. Measurements using coronary inflammation with fat attenuation index (FAI) Score, clinical risk factors and coronary plaque metrics from CCTA to predict fatal cardiac events (AI-Risk) in living patients has not been used in post-mortem setting. Purpose This study investigates two new techniques to aid the diagnosis of coronary related death in the post-mortem setting: (1) minimally invasive interventional technique to perform PMCT; (2) diagnostic accuracy of FAI-assisted PMCT with histopathology validation. Method Adults with sudden death of unknown cause <48 hours from death were included. Ultrasound guided femoral access to deliver guidewire to the aortic root (Figure 1A), followed by inflation of aortic occlusion balloon and injection of contrast for angiogram. A cardiac radiologist performed the coronary and FAI analysis (1B &C). Two experienced radiologists reported the cause of death without/with aid of FAI score results. The technique was introduced at a second PMCT centre. Results PMCT analysis of 37 participants (27 males, 10 females, age range 42-98) – 15 minimally invasive PMCT, and 22 PMCT from previous study showed FAI score (1D) and AI-Risk (1E) were significantly higher in participants who had coronary related death vs non-coronary related causes. In the receiver operating characteristic (ROC, 1F) analysis, thresholding at 42% for AI-Risk and 34 for Mean FAI score, was able to detect all 18 true positives, 2 false positives (1xpulmonary embolism, and 1xdual pathology of ruptured abdominal aneurysm with severe coronary artery disease; these cases showed high FAI score and AI-Risk), and all true negatives. Both radiologists identified 17/18 coronary related death. There were 5 cases of false positives for coronary related death in Radiologist 1 (3 years’ experience); 8 false positives in Radiologists 2 (10 years’ experience). In non-coronary related deaths, Radiologist 1 identified 14/19 true negative cases, and Radiologist 2 identified 11/19 true negative cases. In all the false positive and negative cases, the radiologists’ diagnostic confidence level was either possible, or unascertain. With the aid of FAI score results, all the true coronary related deaths were identified and no false negative case. This method was introduced at a second centre with 108 PMCTs analysed. There were 40 cases of non-coronary death, and 68 cases of coronary related death on PMCT (imaging diagnosis only). In the non-coronary group, FAI-score assisted results showed 100% concordance. In the coronary group, there was 10% dis-concordance (7/68). Conclusion Minimally invasive PMCT with FAI score-assisted diagnosis has the potential to increase the diagnostic confidence and accuracy of coronary-related cause of death.

RNA-seq validation of microRNA expression signatures for precision melanoma diagnosis and prognostic stratification

BackgroundNew diagnostic tools are needed to improve the diagnosis and risk stratification of cutaneous melanoma. Disease-specific microRNA signatures have been previously described via NanoString profiling of solid biopsy tissue and plasma. This study validated these signatures via next-generation sequencing technology and compared their performance against clinical metrics and other published melanoma signatures.MethodsRNA from 64 plasma and 60 FFPE biopsy samples from individuals with invasive melanoma or related benign/control phenotypes was extracted and enriched for microRNA. RNA sequencing was performed to compute MEL38/MEL12 signature scores. The results were evaluated with published NanoString and RNA sequencing datasets, comprising 548 solid tissue samples and 217 plasma samples, to predict disease status and patient outcome.ResultsThe MEL38 diagnostic signature classifies patients into discrete diagnostic groups via RNA sequencing in either solid tissue or plasma (P < 0.001). In solid tissue, the prognostic MEL12 signature stratifies patients into low-, intermediate- and high-risk groups, independent of clinical covariates. The hazard ratios for 10-year overall survival, based on observed survival intervals, were 2.2 (MEL12 high-risk vs low-risk, P < 0.001) and 1.8 (intermediate-risk vs low-risk, P < 0.001), outperforming other published prognostic models. MEL12 also exhibited prognostic significance in the plasma of 42 patients with invasive disease.ConclusionsThe MEL38 and MEL12 signatures can be assessed in either solid tissue or plasma using RNA-seq and are strong predictors of disease state and patient outcome. Compared with other genomic methods, MEL12 was shown to be the strongest predictor of poor prognosis. MicroRNA expression profiling offers objective, accurate genomic information about a patient’s likelihood of invasive melanoma and prognosis.

Clinician Staffing and Quality of Care in US Health Centers

Health centers are vital primary care safety nets for underserved populations, but optimal clinician staffing associated with quality care is unclear. Understanding the association of clinician staffing patterns with quality of care may inform care delivery, scope-of-practice policy, and resource allocation. To describe the association of clinician staffing models and ratios with quality-of-care metrics in health centers. This cross-sectional study of US health centers used data from the 2022 Health Resources and Services Administration Uniform Data System (UDS). Clinician staffing ratios, expressed as the fraction of full-time equivalents (FTEs) per 1000 visits of physicians, advanced practice registered nurses (APRNs), and physician associates (PAs) to total clinician FTEs at each health center. Percentage of eligible patients receiving the corresponding service or outcome for 14 individual clinical quality metrics collected by the UDS, including infant immunizations; screening for cancer, depression, tobacco use, hypertension, HIV, and glycated hemoglobin levels; weight and body mass index (BMI) assessment; and appropriate statin, aspirin, and/or antiplatelet therapy. This analysis of 791 health centers serving 16 114 842 patients (56.6% female) identified 5 clinician staffing models: balanced (similar FTEs of physicians, APRNs, and PAs; 152 [19.2%] of health centers), higher FTEs of APRNs than physicians (174 [22.0%]), higher FTEs of physicians than APRNs (160 [20.2%]), approximately equal FTEs of physicians and APRNs (263 [33.2%]), and large scale (42 [5.3%]). Adjusted linear models showed positive associations between physician FTEs per 1000 visits and cervical (β, 14.9; 95% CI, 3.1-26.7), breast (β, 15.7; 95% CI, 3.2-28.1), and colorectal (β, 18.3; 95% CI, 6.0-30.6) cancer screening. Generalized additive models showed nonlinear positive associations beginning at a physician FTE ratio of 0.45 (95% CI, 0.02-6.22) for infant vaccinations, 0.39 (95% CI, 0.05-2.21) for cervical cancer screening, 0.39 (95% CI, 0.02-1.67) for breast cancer screening, 0.47 (95% CI, 0.00-5.76) for HIV testing, and 0.70 (95% CI, 0.18-19.96) for depression in remission; APRN FTE ratio of 0.45 (95% CI, 0.17-7.46) for adult BMI assessment; and PA FTE ratio of 0.16 (95% CI, 0.11-3.88) for infant vaccinations. Staffing models were not associated with 7 of the 14 metrics analyzed. In this cross-sectional study of health centers, physician FTE ratio was associated with higher performance in cancer screening, infant vaccinations, and HIV testing; APRN FTE ratio was associated with higher performance in preventative health assessments; and PA FTE ratio was associated with higher performance in infant vaccination. These findings suggest that targeted staffing strategies may be associated with quality of care in certain domains and that tailored approaches to health center staffing based on community-specific needs are warranted.

Enhancing Cardiovascular Risk Prediction: Development of an Advanced Xgboost Model with Hospital-Level Random Effects.

Ensemble tree-based models such as Xgboost are highly prognostic in cardiovascular medicine, as measured by the Clinical Effectiveness Metric (CEM). However, their ability to handle correlated data, such as hospital-level effects, is limited. The aim of this work is to develop a binary-outcome mixed-effects Xgboost (BME) model that integrates random effects at the hospital level. To ascertain how well the model handles correlated data in cardiovascular outcomes, we aim to assess its performance and compare it to fixed-effects Xgboost and traditional logistic regression models. A total of 227,087 patients over 17 years of age, undergoing cardiac surgery from 42 UK hospitals between 1 January 2012 and 31 March 2019, were included. The dataset was split into two cohorts: training/validation (n = 157,196; 2012-2016) and holdout (n = 69,891; 2017-2019). The outcome variable was 30-day mortality with hospitals considered as the clustering variable. The logistic regression, mixed-effects logistic regression, Xgboost and binary-outcome mixed-effects Xgboost (BME) were fitted to both standardized and unstandardized datasets across a range of sample sizes and the estimated prediction power metrics were compared to identify the best approach. The exploratory study found high variability in hospital-related mortality across datasets, which supported the adoption of the mixed-effects models. Unstandardized Xgboost BME demonstrated marked improvements in prediction power over the Xgboost model at small sample size ranges, but performance differences decreased as dataset sizes increased. Generalized linear models (glms) and generalized linear mixed-effects models (glmers) followed similar results, with the Xgboost models also excelling at greater sample sizes. These findings suggest that integrating mixed effects into machine learning models can enhance their performance on datasets where the sample size is small.

Renal function and risk of dementia: a Mendelian randomization study

Background The burgeoning recognition of the nexus between renal functionality and the prevalence of dementia has precipitated a surge in research endeavors. This study aims to substantiate the causal relationship between kidney functionality and dementia. Methods We utilized clinical renal function metrics from the Chronic Kidney Disease Genetics (CKDGen) Consortium and diverse dementia types (Alzheimer’s disease [AD] and vascular dementia) from the FinnGen Biobank by using Mendelian randomization analysis. At the stratum of genetic susceptibility, we tested the causal relationship between variations index in renal function and the occurrence of dementia. Inverse-variance weighted (IVW) method was the main analysis, and several supplementary analyses and sensitivity analyses were performed to test the causal estimates. Results The findings indicate a significant correlation between each unit increase in cystatin C-based estimated glomerular filtration rate (eGFR-cys) levels was significantly associated with a reduction in the incidence of late-onset Alzheimer’s disease (LOAD) (IVW: OR = 0.35, 95% CI: 0.13–0.91, p = 0.031). After adjusting for creatinine-based eGFR (eGFR-cre) and urinary albumin-to-creatinine ratio (UACR), a causal relationship was still identified between elevated levels of eGFR-cys and decreased risk of LOAD (IVW: OR: 0.08; 95% CI: 0.01–0.97, p = 0.047). Sensitivity tests demonstrated the reliability of causal estimates. Conclusions The association between renal function based on cystatin C and the augmented risk of developing AD lends support to the perspective that regular monitoring of cystatin C may be a valuable investigative biomarker.

Treatment and Outcome Metrics for Speech-Language Pathology Treatment of Upper Airway Disorders: A Systematic Review.

Clinical treatment strategies and progress metrics for patients with inducible laryngeal obstruction (ILO) and exercise-induced laryngeal obstruction (EILO) have not been systematically applied across clinics. The goals of this review were to identify the intervention strategies used to treat upper airway disorders and determine the clinical metrics by which improvement or resolution of ILO/EILO is determined in clinical studies of speech-language pathology intervention. A systematic review was conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Systematic Reviews Checklist. English language, full-text publications were identified through MEDLINE (Ovid), APA PsycINFO, and Web of Science for publications that described clinical outcomes following behavioral treatment for ILO provided by a speech-language pathologist (SLP). A total of 238 sources were retrieved, of which 75 were duplicates. Titles and abstracts of 163 were screened, with 22 sources included for full-text review. Citation review yielded nine additional resources. Thirty-one sources were included for data extraction. Most sources described use of respiratory/laryngeal retraining. There was a lack of consistency for clinical and standardized metrics used to evaluate improvement or resolution of upper airway symptoms. Behavioral and standardized outcome metrics for evaluating therapy outcomes from SLP behavioral intervention of ILO/EILO are not consistently applied. Clinical metrics standards for clinicians are needed to provide a means to evaluate graded improvement in treatment and changes in health care utilization as well as for training less-experienced clinicians. https://doi.org/10.23641/asha.27172683.

Comparison of the efficacy of medial tarsal venous flaps and traditional venous/arterial free flaps in the reconstruction of hand soft tissue defects: A new type of physiological flap.

The treatment of hand soft tissue defects primarily relies on flap reconstruction. However, traditional venous/arterial free flaps have several disadvantages, including damage to the donor site, bruising, discoloration, blister formation, and even necrosis. These issues can significantly impact patient recovery and outcomes. Therefore, there is a need for alternative approaches that minimize these complications and improve overall patient care. To compare the efficacy of medial tarsal venous flaps and traditional venous/arterial free flaps in the reconstruction of hand soft tissue defects, evaluating various clinical outcomes and patient recovery metrics. We screened 30 suitable patients with hand soft tissue defects and randomly assigned them to three groups. Patients in each group were transplanted with either medial tarsal free venous flaps or traditional arterial/venous free flaps to achieve coverage and reconstruction of the soft tissue defects. The results were compared and analyzed using the following metrics: operation time, survival rate, complication rate, pain index, postoperative infection rate, and functional evaluations of both the donor and recipient areas. There was no significant difference in operation time between the medial tarsal free venous flaps and the traditional forearm free venous flaps. The operative time for both types of flaps was shorter than that of the traditional free fibular flap from the hallux. The survival rate of the medial tarsal free venous flaps was comparable to that of the fibular free arterial flaps from the great toes and significantly higher than that of the traditional forearm free venous flaps. The complication rate showed an inverse trend to the survival rate of the flaps. In terms of pain, the pain index for the medial tarsal free venous flaps was significantly lower than that of the fibular free arterial flaps from the hallux and comparable to that of the forearm free venous flaps. Regarding postoperative infection rates, the forearm free venous flap had the highest rate, while there was no significant difference between the medial tarsal free venous flaps and the fibular free arterial flaps from the great toes. The functional recovery of the medial tarsal free venous flaps was good in both the donor and recipient areas. There was no poor functional performance in the donor areas of the fibular free arterial flaps from the hallux or the recipient areas of the forearm free venous flaps. The medial tarsal free venous flaps effectively avoid the disadvantages of traditional venous and arterial free flaps, combining their advantages. These flaps offer shorter operative times, higher survival rates, and lower pain indices. They also provide excellent functional recovery in both donor and recipient areas. Thus, medial tarsal free venous flaps represent an ideal solution for reconstructing hand soft tissue defects.

Linking housing, socio-demographic, environmental and mental health data at scale

Mental disorders are a growing problem worldwide, putting pressure on healthcare systems and wider society. Anxiety and depression are estimated to cost the global economy US$1 trillion per year, yet only 2% of global median government healthcare expenditure goes towards mental health. There is growing evidence linking housing, socio-economic status and local environmental conditions with mental health inequalities. The aim of this paper is to link several open-access datasets at the local area level (N = 32,844) for England to clinical mental health metrics and describe initial statistical findings. Two mental health metrics were used: Small Area Mental Health Index (SAMHI) and diagnosed depression prevalence. To demonstrate the utility of the longitudinal mental health data, changes in depression prevalence were investigated over two study periods (2011–19, i.e. austerity; and 2019–22, i.e. COVID-19). These data were linked to housing data (energy efficiency, floor area, year built, type and tenure) from Energy Performance Certificates (EPCs); socio-demographic data (age, sex, income and education deprivation, household size) from administrative records; and local environment data (winter temperature, air pollution and access to green space). The linked dataset provides a useful resource with which to investigate the social and environmental determinants of mental health. Practice relevance Initial observations of the data revealed a non-linear relationship between home energy efficiency (EPC band) and the mental health metrics, with depression prevalence higher in local areas where the mode EPC bands were C and D, compared with B and E. Researchers can further investigate this relationship using the dataset through robust statistical analysis, adjusting for confounding variables. National and local governments may use the dataset to help allocate resources to prevent and treat mental health conditions. Practitioners can map and interrogate the data to describe their local areas and make preliminary conclusions about the relationships between the built environment and mental health. This preliminary analysis of the data demonstrated a gradient in SAMHI and depression prevalence with income and employment deprivation at the local area level.

Silent brain ischemia within the TAXINOMISIS framework: association with clinical and advanced ultrasound metrics.

IntroductionThe relationship between carotid artery stenosis (CAS) and ipsilateral silent brain ischemia (SBI) remains unclear, with uncertain therapeutic implications. The present study, part of the TAXINOMISIS project (nr. 755,320), aimed to investigate SBIs in patients with asymptomatic CAS, correlating them with clinical, carotid ultrasonographic data, and CFD analyses.MethodsThe TAXINOMISIS clinical trial study (nr. NCT03495830) involved six vascular surgery centers across Europe, enrolling patients with asymptomatic and symptomatic CAS ranging from 50 to 99%. Patients underwent carotid ultrasound and magnetic resonance imaging (MRI), including brain diffusion-weighted, T2-weighted/FLAIR, and T1-weighted sequences. Brain MRI scans were analyzed for the presence of SBI according to established definitions. Ultrasound assessments included Doppler and CFD analysis. Only asymptomatic patients were included in this substudy.ResultsAmong 195 asymptomatic patients, the mean stenosis (NASCET) was 64.1%. Of these, a total of 33 patients (16.9%) had at least one SBI detected on a brain MRI scan. Specifically, 19 out of 33 patients (57.6%) had cortical infarcts, 4 out of 33 patients (12.1%) had ipsilateral lacunar infarcts, 6 out of 33 patients had (18.2%) subcortical infarcts, 1 out of 33 patients (3.0%) had both cortical and lacunar infarcts, and 3 out of 33 patients (9.1%) both cortical and subcortical infarcts. Patients with SBIs exhibited significantly higher risk factors, including a higher body mass index (28.52 ± 9.38 vs. 26.39 ± 3.35, p = 0.02), diastolic blood pressure (80.87 ± 15.73 mmHg vs. 80.06 ± 8.49 mmHg, p = 0.02), creatinine levels (93.66 ± 34.61 μmol/L vs. 84.69 ± 23.67 μmol/L, p = 0.02), and blood triglycerides (1.8 ± 1.06 mmol/L vs. 1.48 ± 0.78 mmol/L, p = 0.03). They also had a higher prevalence of cardiovascular interventions (29.6% vs. 13.8%, p = 0.04), greater usage of third/fourth-line antihypertensive treatment (50%vs16%, p = 0.03), and anticoagulant medications (60% vs. 16%, p = 0.01). Additionally, the number of contralateral cerebral infarcts was higher in patients with SBIs (35.5% vs. 13.4%, p &amp;lt; 0.01). Moreover, carotid ultrasound revealed higher Saint Mary’s ratios (15.33 ± 12.45 vs. 12.96 ± 7.99, p = 0.02), and CFD analysis demonstrated larger areas of low wall shear stress (WSS) (0.0004 ± 0.0004 m2 vs. 0.0002 ± 0.0002 m2, p &amp;lt; 0.01).ConclusionThe TAXINOMISIS clinical trial provides valuable insights into the prevalence and risk factors associated with SBIs in patients with moderate asymptomatic carotid stenosis. The findings suggest that specific hemodynamic and arterial wall characteristics may contribute to the development of silent brain infarcts.