United States

Background: Accurately predicting the healing time of wounds is a critical aspect of wound care. Developing models that can predict when a wound will heal based on different parameters can provide the healthcare provider and the patient with valuable information. This knowledge can help tailor personalized treatment plans, and optimize resource allocation, thus enhancing patient outcomes. The current project aims to create a predictive model capable of providing precise estimates of wound healing time. 

Methods: A retrospective analysis of 1061 healed wounds was performed using Tissue Analytics (TA). The wounds were stratified into one of six wound etiologies: diabetic, arterial, venous, pressure, traumatic and idiopathic. Different metrics such as total area, length, width and perimeter of the wound, red tissue, black tissue, yellow tissue, other tissue and pink tissue percentages were extrapolated. The number of days in treatment was calculated by subtracting the first presenting day by the day the wound healed. The above information was compiled into a CSV file and Google Colaboratory was employed to generate different regression models using Pycaret. Pycaret automatically tests different machine learning regression models and their efficacy in predicting wound heal time in days.

Results: 20 different machine learning regression models were used and compared to analyze the data and make predictions. Of the 20 different machine learning models, the Random Forest Regressor (RF) had the lowest mean squared error of 1109.46 and root mean squared error of 33.25 days. Extra Trees Regressor (ET) model had the lowest mean absolute error of 26.81 days and mean absolute percentage of 35.51%. The RF model also had the best R-squared of 0.12. A feature importance plot was also generated, which showed that red tissue percentage and etiology were the greatest predictors of wound heal time.

Conclusion: The results showed a high rate of error and low accuracy as indicated by the relatively high MSE and RMSE as well as a low R-sqared for almost all models. Extra metrics generated by Pycaret showed the presence of overfitting, meaning that the models memorized the different numbers to make predictions instead of evaluating the different features. Prior research has shown that wound perimeter and wound area are more likely to predict heal time; however, the data structure could force the the model to determine that etiology and red tissue is best predictor of wound heal time. The current study is limited by the number of wounds as well as other variables that can affect wound heal time such as compliance; however, it can be improved by increasing the number of wounds to train the model.

2023 AMA Research Challenge

Leveraging Machine Learning Algorithms to Predict Wound Heal Time

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Background: In the United States, hemodialysis is the most common treatment for kidney failure despite the significant health advantages of kidney transplantation. This represents a significant health disparity. The hemodialysis clinic is unique because patients receive therapy in a group setting allowing the patients to form social networks. Patient social networks within hemodialysis facilities may spread kidney transplant (KT) attitudes and behaviors. For the first step in a KT network intervention, we mapped two geographically and demographically different hemodialysis facilities’ social networks to identify the most influential patients as measured by in-degree centrality.  

Methods: We surveyed hemodialysis patients’ social networks in two geographically and demographically different hemodialysis facilities. Statistical and social network analysis were performed in R. We first compared demographic and structural network differences between the two facilities. A multivariable exponential random graph model estimated the associations between in-degree centrality and demographic variables and transplant attitudes/knowledge while controlling for network structure and homophily (in which people form relationships with similar people).  

Results: Participants differed between Facility 1 (N=71) and Facility 2 (N=40) by race (91% Black vs 40%, p<0.001), positive KT attitude (70% vs 45%, p=0.02), and knowing more successful KT recipients (2.5±4.4 vs 0.8±1.1, p=0.002). In-degree centrality was higher at Facility 1 (1.5±1.7) compared to Facility 2 (0.9±1.2, p<0.001). At Facility 1, predictors of in-degree centrality were younger age (β -0.03, 95% Confidence Interval (CI) [-0.05 to -0.014]; p=0.004), female sex (β 0.51, 95% CI [0.00 to 1.02]; p=0.04), and knowing more successful KT recipients (β 0.13, 95% CI [0.03 to 0.23]; p=0.01). Conversely at Facility 2, those who knew fewer successful KT recipients had higher in-degree centrality (β -0.92, 95% CI [-1.84 to 0.00]; p=0.048).  

Conclusion: Observed differences in social network structure could explain facility-level differences in KT attitudes. At Facility 1, the most influential patients (in-degree centrality) knew many successful KT recipients and may disseminate positive attitudes towards KT throughout the network. On the contrary, influential patients at Facility 2 knew fewer KT recipients and may disseminate negative attitudes towards KT. These findings help guide future network interventions targeting patients with high in-degree centrality and understanding how their attitudes towards KT influence the overall network.

A Social Network Analysis of Hemodialysis Clinics: Attitudes Towards Living Donor Kidney Transplant Among Influential Patients

Background:
In September 2021, a task force of kidney experts recommended a new eGFR formula without a race term to replace the previous race-based CKD-EPI formula. Existing studies have not assessed the effect of the new formula on the timeliness of chronic kidney disease (CKD) patients’ first nephrology clinic visit, a factor which has been shown to be associated with slowed progression and reduced costs of CKD. In this study we aimed to examine changes in the racial disparity between Black and non-Black patients in the timeliness of CKD patients’ first nephrology clinic visit before and after the implementation of the new race-free eGFR formula.
Methods:
We included adults seen at any of Indiana University Health’s 17 nephrology clinics between April 1st, 2021, and March 15th, 2023 for CKD or low GFR, excluding inpatient referrals and those who had previously seen an IU Health nephrologist. We conducted a multivariate linear regression with covariates including sex, self-reported race, age, timeframe, BMI, and an interaction term between race and timeframe, with timeframe defined as before or after implementation of the new formula on April 1st, 2022. Timeliness of care was defined as receiving care earlier in CKD progression (i.e., higher eGFR). All eGFR values shown are ml/min/1.73m2.
Results:
On average, throughout the entire study period, eGFR was 13.0 (95%CI: 10.3, 15.7) higher for female than male patients, 6.7 (95%CI: 2.4, 10.9) higher for non-Black than Black patients, and 5.9 (95%CI: 0.3, 11.4) higher for patients seen after the formula change than patients seen before the change. Each additional year of life reduced eGFR at time of first visit by -0.3 (95%CI: -0.4, -0.2). Our analysis found no evidence that the gap in eGFR at time of first visit between Black and non-Black patients changed significantly after the formula change (-3.7, 95%CI: -10.1, 2.7).
Conclusion:
The removal of the race term from the eGFR formula aimed to address systemic racial disparities in the diagnosis and treatment of CKD. Our results indicate that it instead led to earlier consultation with a nephrologist for all patients, as evidenced by a higher mean eGFR at the time of first clinic visit after the formula change. Despite this general trend, Black patients continued to have a lower mean eGFR at the time of first clinic visit than non-Black patients after the formula change, indicating a persistent delay in the involvement of outpatient nephrology for Black CKD patients.


Impact of race-free estimated Glomerular Filtration Rate (eGFR) on racial disparity in receiving timely outpatient nephrology care

Background:
Acute kidney injury is associated with significant morbidity and mortality. Estimation of volume status plays a major role in the differentiation of acute kidney injury. Invasive right heart catheterization has been traditionally used to guide management. We examined whether a simple bedside ultrasound assessment of intra-abdominal organ congestion can address this question and help differentiate acute kidney injury.
Methods:
A prospective single-center study included patients with cardiorenal, hepatorenal, acute tubular necrosis (ATN), and volume depletion acute kidney injury (AKI). Arrhythmias and body mass index (BMI)>30 were exclusions. Clinical data were obtained via chart review and urine microscopy was performed on all the patients. Inferior vena cava diameter (IVC); hepatic vein, portal vein and renal vein patterns; and Renal Resistive Indices (RRI) were obtained on three consecutive days via Logic e BT-12 ultrasound. Sonographers underwent training for eight hours and completed five ultrasound assessments prior to the study. Sonographers were also blinded from clinical diagnoses. We used analysis of variance (ANOVA) for continuous variables and chi-square tests for categorical variables.
Results:
A total of 81 AKI subjects were included, 34% with volume depletion, 19% cardiorenal, 35% ATN, 6% hepatorenal, and 3% other. The IVC diameters on the day of diagnosis in ATN, volume depletion, and cardiorenal were 2, 1.87, and 2.34 cm respectively (p=0.05). Diminished or reversed systolic hepatic duplex was seen in only 2 patients with volume depletion(p=0.002), and both these patients had moderate tricuspid regurgitation and elevated pulmonary arterial pressures on echocardiogram explaining the deviation. Similar hepatic duplex findings were noted on day 2 and day 3. The portal vein was continuous in 62.1% ATN, 60.7% volume depletion, and 31.3% cardiorenal patients (p=0.09). In comparison to patients in the cardiorenal group, portal pulsatility in the volume depletion arm was almost always less than 50% (p=0.49). Renal venous flow was continuous in 18.8% of the cardiorenal patients(p=0.18). Quality assessment was performed and estimated concordance with the expert review was 96.6, 94.4, 95.5, and 75.6 percent in IVC, hepatic vein, portal vein, and renal vein interpretations respectively.
Conclusion:
Based on our results, we propose that the Hepatic vein, IVC, and marked portal pulsatility(>50%) can help differentiate volume depletion from cardiorenal syndrome. This noninvasive bedside tool in addition to urine sediment can help differentiate acute kidney injury and future trials will examine management.

A pragmatic study utilizing bedside ultrasound to replace invasive interventions.

**Scoring is only possible in the semifinals hall**

**Abstract:**



Bilateral Pulvinar Responsive Stimulation for Broad Onset Drug Resistant Epilepsy

Objective:
Chordomas are rare primary tumors of the skull base, sacrum and vertebral column, derived from remnants of the embryonic notochord. Treatment options consist of surgical resection, and radiotherapy, with few chemotherapy options available. This study reviews clinical trials focused on radiotherapy modalities, such as photon therapy and particle therapy, as well as the concomitant use of radiation sensitizers.

Methods:
Literature review on all published clinical trials studying the usage of photon, proton, and carbon ion radiotherapy for chordoma in adults, as well as all published literature on radiation sensitizers used for treatment of chordoma from 2000 to 2023. Reviewed all of the current clinical trials on radiotherapy for chordoma in adults. 

Results:
We found 8 clinical trials, which include data from 1 observational study, 1 pilot study, 2 Phase I studies, 2 Phase I-II studies, and 7 Phase II studies. Of the completed clinical trials, 2 focused on protons alone, 2 focused on combined proton-photon radiotherapy, and 4 focused on carbon ion radiotherapy. The lowest radiation dosage was 48.0 GyE for carbon ion radiotherapy and highest was 79.2 GyE using protons only. All clinical trials reported an overall survival rate above 50% at 3-year follow-up. Nine publications were found on the use of radiation sensitizers for chordomas, 6 of which included in vitro studies and 5 included in vivo studies, using both patient and xenograft models. 

Conclusion:
The completed clinical trials focus on evaluating the effectiveness of proton, photon, and carbon ion radiotherapy for treatment of skull-base, spine, and sacral chordoma. Current trials continue to focus on effectiveness of treatments as well as comparing the different forms of radiotherapy and determining appropriate doses. Research on radiation sensitizers for chordomas shows various therapies, ranging from hyperthermia to pharmaceutical options, that require further study. Altogether, research on radiotherapy and radiation sensitizers have been used alongside radiation with positive and promising results for chordoma.

Use of Ion Radiotherapy and Radiation Sensitizers for Treatment of Chordoma: A Narrative Review

**Scoring is only possible in the semifinals hall**

**Abstract:**



The Relationship of Pelvic Ganglia and Anterior Vesical Branches of the Pelvic Nerve in Human Cadavers

Evaluation of Flow-Diversion Procedures Using Microangioscopy: Correlation with Histology and Digital Subtraction Angiography

Background
Parkinson’s Disease (PD) is a progressive neurodegenerative movement disorder that encompasses neuropsychological symptoms. Symptoms of both motor and cognitive deficits are secondary to the depletion of dopaminergic neurons in the brain. Therefore, analyzing variables of neuroanatomical morphology, such as cortical gray matter volume and deep nuclei volume, can be used to characterize PD more completely. Such variables can also be compared with neurocognitive test performance and clinical movement assessment scores to elucidate a correlation with results of neuroimaging. Therefore, we hypothesize that neuroanatomical abnormalities will have corresponding changes in neurocognitive test performance and movement disorder assessment scores.

Methods
Using electronic medical records of PD patients, we retrospectively collected demographic and neurocognitive data from Robert Wood Johnson Medical School Neurosurgery department and Robert Wood Johnson Barnabas Health hospital systems. Neuroimaging records were segmented, normalized, and smoothed using Statistical Parametric Mapping (SPM12) software. Group level analysis of gray matter densities was compared between 45 controls subjects with no history of a movement disorder and 45 PD subjects using Voxel-Based Morphometry (VBM) to generate statistical maps brain regions with statistically significant differences in tissue volume. Significance was determined by p< 0.001 and a threshold of 50 voxels.

Results
SPM results were based on two contrasts: CN-PD (decreased gray matter volume in the PD group compared to controls) and PD-CN (increased gray matter volume in the PD group compared to controls). Peak regions of difference in the CN-PD group were observed in the putamen, globus pallidus, entorhinal area, parahippocampal gyrus, middle frontal gyrus, and cerebellar cortex. Conversely, in the PD-CN group, increased gray matter volumes were observed in the brain stem, thalamus proper, supplementary motor cortex, and middle cingulate gyrus.

Conclusion
Based on the results, we concluded that PD and related movement disorders are associated with significant reductions in gray matter in regions of the BG, hippocampal formation, cerebellar cortex, and primary motor cortex, which are regions involved with motor initiation, regulation, and learning. Also, Significant increases in gray matter of PD subjects were found in the thalamus, temporal gyrus, cingulate gyrus, and supplementary motor cortex, involved in movement and processing of auditory information and emotions.

MRI Correlates of Neurocognitive Functioning in Movement Disorders

Opioids are a leading cause of overdose-related deaths in the US, accounting for 70.6% of fatalities in 2019 due primarily to respiratory depression. Epidural electrical stimulation (EES) has emerged as a novel approach for facilitating rhythmic movement such as respiration in humans and rodent models. To reveal the mechanism underpinning modulation of respiratory neural circuits, we compared the effects of dorsal and ventral cervical epidural electrical stimulation (D-CEES, V-CEES) on respiration after opioid-induced respiratory suppression or depression (OIRD) via administration of remifentanil in anesthetized patients undergoing medically necessary spinal cord surgery. We hypothesized that V-CEES activates ventral horn motoneurons while D-CEES recruits local spinal circuits and tracts to supraspinal structures. We enrolled 43 patients receiving opioids during ventral (n = 25) and dorsal (n = 18) cervical spinal surgery. EES was delivered to the spinal cord (C2-C7) for <90 seconds at an optimal intensity (0.5-5mA) at 5Hz or 30Hz. The subjects’ vital signs were recorded intraoperatively. Electromyograms (EMG) were used to monitor respiratory and upper extremity muscles such as the diaphragm, laryngeal, intercostal, genioglossal, and deltoid muscles bilaterally. The anesthesia stage was measured via electroencephalogram (EEG). A pneumotach recorded each patient’s airway pressure. An independent anesthesiologist, tasked with ensuring patient safety, maintained a stable surgical plane of anesthesia via propofol in conjunction with minimal remifentanil prior to EES. We divided the responses into 2 states: ON- and OFF-State. The ON-State condition was defined as suppressed, but still present, respiration compared to baseline through an additional dose of remifentanil (0.001-.05mcg/kg/min). OFF-State condition was produced by dosing the subject with the lowest sufficient concentration of remifentanil (0.05-0.1mcg/kg/min) necessary to induce apnea. We observed four main differences between D- and V-CEES in regulating respiration in the presence of remifentanil: 1) D-CEES alone induced inspiratory phase resetting; 2) D-CEES induced longer lasting respiratory modulation after EES cessation; 3) D-CEES induced both frequency and tidal volume changes of respiration while V-CEES modulated the tidal volume more significantly; and 4) D-CEES respiratory modulation was inhibited more significantly during the OFF-state, while the most responsive spinal level to V-CEES, C6/7, maintained its respiratory modulation in both ON- and OFF-States. These observations suggest D- and V-CEES facilitate respiration via different neural circuits.

Dorsal and Ventral Cervical Epidural Electrical Stimulation Opposes Opioid-Induced Respiratory Depression via Different Respiratory Neural Circuits

Introduction: Increasing frailty is a significant determinant of perioperative morbidity and mortality within neurosurgical literature. This study investigates the predictive value of the modified frailty index 5 (mFI-5) for postoperative morbidity and mortality following surgical drainage of chronic subdural hematoma (cSDH).

METHODS: A retrospective cohort study was performed on patients who underwent surgical evacuation of a cSDH. The mFI-5 score was calculated for each patient and used to stratify patients: prefrail (mFI-5<2), frail (mFI-5 [ 2), and
severely frail (mFI-5>2). Multivariate Cox proportional hazards (CPH) regression analysis were used to identify factors associated with our primary outcomes: overall
survival and 30-day readmission. Secondary outcomes included nonhome discharge, length of stay, hematoma accumulation, development of new postoperative neurologic deficits, resolution of preoperative neurologic deficits, and a modified Rankin score >2 at discharge.

RESULTS: 118 patients with a mean age of 74.4 +/- 11.9 years were analyzed. All baseline demographics were similar across the 3 groups. On multivariate analysis,
severely frail patients (N [ 24, 20.3%) had increased rates of 30-day readmission (hazard ratio [HR] 4.3, CPH regression P value<0.001) and postoperative mortality (HR 3.1, CPH regression P value<0.01) compared to the prefrail cohort. Severely frail patients had increased rates of nonhome disposition (HR 9.6, CPH regression P value<0.001), development of new postoperative neurologic deficits (HR 2.75, CPH regression P value [ 0.03), and hematoma reaccumulation (HR 4.07, CPH regression
P value [ 0.004). A novel scoring system accounting for patient age and frailty was predictive of 90-day mortality (area under the curve 0.77).

CONCLUSIONS: Frailty, measured by the mFI-5, and our novel scoring system holds a predictive value regarding outcomes for patients undergoing surgical drainage of a
cSDH.

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A Social Network Analysis of Hemodialysis Clinics: Attitudes Towards Living Donor Kidney Transplant Among Influential Patients