Comorbidity Data Research Articles

Abstract 4136721: Reducing the Use of Transesophageal Echocardiogram Prior to Cardioversion Using Machine Learning

Introduction/Background: Direct current cardioversion (DCC) is used to terminate atrial fibrillation and atrial flutter. Due to increased stroke risk post DCC, a transesophageal echocardiogram (TEE) is performed in selected patients to rule out left atrial appendage thrombus (LAAT) prior to DCC. The prevalence of LAAT is around 2.5% in the era of direct oral anticoagulants. This is a large proportion of patients with no LAAT on TEE and calls for strategies to improve patient selections for TEE before DCC. Research Questions/Hypothesis: In this study we aimed to determine if the use of machine learning could accurately predict the presence of LAAT among patients with nonvalvular atrial fibrillation and atrial flutter. Methods/Approach: We collected demographic, comorbid, and transthoracic echocardiographic data on 795 patients who underwent TEE prior to DCC for nonvalvular atrial fibrillation and atrial flutter. We developed and validated an explainable machine learning model using the eXtreme Gradient Boosting algorithm with 5x5 nested cross-validation. The algorithm used 37 variables to predict the probability of LAAT. Results/Data: The prevalence of LAAT in our cohort was 11.3%. Our model achieved an area under the curve (AUC) of 0.79 in predicting LAAT, figure 1A. In comparison, CHA2DS2-VASc score performed poorly in our cohort with an AUC of 0.48, figure 1B. The ranking of variables most strongly predictive of LAAT is shown in figure 1C, with left ventricle ejection fraction as the most instrumental. Patients were categorized into 10 groups based on the percentile of their predicted probability of having a thrombus. A lower percentile (e.g., 10%) indicates a lower probability of having a thrombus. By utilizing a cutoff point of 0.16, which includes 10.0% of the patients, we can exclude the presence of thrombus with 100% certainty. Conclusion: Machine learning, compared to traditional risk scores, offers enhanced predictive model for identifying LAAT and provides better guidance for TEE and anticoagulation therapy before DCC.

Cohort profile: the Nanjing Diabetes Cohort database – a population-based surveillance cohort

PurposeTo study epidemiology, complications, risk factors, clinical course and treatment patterns of diabetes, the Nanjing Diabetes Cohort (NDC) was established using anonymised electronic health records from 650 hospitals and primary...

Cardiopulmonary exercise test findings are not the same in distinct types of cardiac amyloidosis

Abstract Background Cardiopulmonary exercise testing (CPET) is a widely used tool for risk stratification and prognosis in patients with chronic heart failure. In amyloid patients, cardiac amyloid deposits are associated with poor prognosis, increased risk for arrhythmias, sudden death, and subsequent exercise limitation due to restrictive cardiomyopathy. The type of amyloidosis and its affectation of the heart are different, and little is known about the CPET parameters according to the type of cardiac amyloidosis. Purpose In this study, we aim to compare CPET data in different types of amyloidosis to determine if CPET variables evaluated could have a significant difference that could impact the follow-up or prognosis of the patients based on the type of amyloidosis. Methods We conducted a retrospective cohort study of 194 patients with a diagnosis of cardiac amyloidosis referred for CPET from February 2010 to February 2024. Patients with at least one CPET data were included in our analysis. The type of amyloidosis, comorbidities, and echocardiogram data were retrieved from medical records. Patients were divided into 3 different groups according to the type of amyloidosis: AL Amyloidosis(AL), Variant TTR Amyloidosis (vTRR), and Wild Type TTR Amyloidosis (wtTTR). Individuals with CPET studies after heart transplant were excluded from the analysis. Fisher’s exact test or chi-square was used to compare categorical variables. ANOVA and Tukey-Kramer (TK) were used to compare continuous variables. Adjustment using General Linear Models (GLM) procedure was used to identify any confounder that could affect the results. A p-value <0.05 was considered significant. Results Out of the 194 patients, 66 had AL Amyloidosis, 40 had vTTR Amyloidosis, and 88 had wtTTR Amyloidosis. Most of the patients were male, and the male predominance was higher in the wtTRR group. There were 41 (62.1%) males in the AL group, 35 (87.5%) in the vTRR group, and 83 (94.3%) in the wtTTR group (p<0.0001). Comorbidities were balanced among the groups. Additional demographic and comorbidities data are shown in Table 1. From the evaluated CPET variables, VE/VCO2 nadir and slope were significantly higher in the wtTTR group when compared to the other groups, as well as Peak VE and Peak TV(Figure A). However, after adjusting for sex, BMI, and age, VE/VCO2 nadir was still significantly higher in the wtTRR group (p=0.003) compared to the other groups, as well as Peak VE, which was higher again in vTTR patients (p=0.001), and Peak TV (Table 2). Conclusion Ventilation variables evaluated in CPET showed alterations in the wtTTR group. These findings suggest that wtTRR amyloid patients could have a severe problem in ventilation that could be of significant relevance in future prognosis.

Cardio Policy Optimiser: an integrated public health approach to enhancing cardiovascular health

Abstract Background Cardiovascular diseases (CVDs) remain a leading cause of mortality in Europe, with atherosclerotic-related conditions accounting for 80% of CVD deaths - a third of them premature. Despite extensive efforts over the past five decades, the decline in these deaths over the last 20-25 years has plateaued, highlighting the need for innovative approaches. Additionally, the co-occurrence of CVDs with other chronic conditions such as diabetes, hypertension, and renal and hepatic diseases, adds complexity to their management and prevention. Methods In Portugal, the pilot phase implemented a novel integrated approach combining a Bayesian epidemiological model - which incorporates genetic, sociodemographic, comorbidity, and lifestyle data - with an adaptive conjoint analysis model focusing on atherosclerosis policy intervention. These models are part of a comprehensive response framework that incorporates health outcomes and associated costs resulting from better prevention and diagnosis. Results Currently in the development and calibration stage, the model is expected to yield initial results by early September. Conclusions This modeling approach offers new opportunities for public health to intervene at early stages in the natural history of CVDs. It emphasizes enhancing prevention and early diagnosis to potentially reduce the incidence of acute episodes and associated mortalities. Moreover, the model facilitates rapid evaluation of the economic benefits derived from preventive policies, thereby supporting more informed public health decision-making. Key messages • The CPO model combines epidemiological and policy models to address cardiovascular morbidity and mortality. • It boosts early diagnosis and prevention, and assesses economic benefits from policies.

Hemoglobin-to-RDW ratio, hemoglobin-to-monocyte ratio, and hemoglobin-to-leukocyte ratio are predictive of 14-day readmission after primary total knee arthroplasty

BackgroundTotal knee arthroplasty (TKA) is an effective treatment for knee osteoarthritis; however, early readmissions due to complications are common. This study assessed the ability of the hemoglobin-to-red cell distribution width ratio (HRR), hemoglobin-to-monocyte ratio (HMR), and hemoglobin-to-leukocyte ratio (HLR) to predict readmission within 14 days after TKA.MethodsData from the Chang Gung Medical Research Database (CGRD) from 2014 to 2022 were retrospectively analyzed. Patients ≥ 20 years old who underwent primary TKA were eligible for inclusion. Patients with incomplete data on the indices of interest or follow-up < 14 days were excluded. Patient demographic, clinical, and comorbidity data were collected. Logistic regression was utilized to determine the associations between HRR, HMR, and HLR and 14-day readmission.ResultsData from 1,137 patients were analyzed. Multivariable analysis revealed that a higher HMR was significantly associated with lower 14-day readmission risk (adjusted OR [aOR] = 0.72, 95% confidence interval [CI]: 0.51–0.997), an HMR ≥ 2.18 (optimal cutoff value) was predictive of a significantly lower 14-day readmission risk (aOR = 0.61, 95% CI: 0.39–0.96). The composite indicator, HRR-HMR-HLR score, derived from the 3 indices assessed, was significantly associated with a lower 14-day readmission risk (score 2 vs. score 0: aOR = 0.51, 95% CI: 0.27–0.98; score 3 vs. score 0: aOR = 0.37, 95% CI: 0.17–0.82).ConclusionsHigh HMR and the HRR-HMR-HLR score are independently associated with a lower 14-day readmission risk after TKA. Implementing these indices into clinical practice may enhance postoperative management.

Integrated multiomic analyses: An approach to improve understanding of diabetic kidney disease.

Diabetes is increasing in prevalence worldwide, with a 20% rise in prevalence predicted between 2021 and 2030, bringing an increased burden of complications, such as diabetic kidney disease (DKD). DKD is a leading cause of end-stage kidney disease, with significant impacts on patients, families and healthcare providers. DKD often goes undetected until later stages, due to asymptomatic disease, non-standard presentation or progression, and sub-optimal screening tools and/or provision. Deeper insights are needed to improve DKD diagnosis, facilitating the identification of higher-risk patients. Improved tools to stratify patients based on disease prognosis would facilitate the optimisation of resources and the individualisation of care. This review aimed to identify how multiomic approaches provide an opportunity to understand the complex underlying biology of DKD. This review explores how multiomic analyses of DKD are improving our understanding of DKD pathology, and aiding in the identification of novel biomarkers to detect disease earlier or predict trajectories. Effective multiomic data integration allows novel interactions to be uncovered and empathises the need for harmonised studies and the incorporation of additional data types, such as co-morbidity, environmental and demographic data to understand DKD complexity. This will facilitate a better understanding of kidney health inequalities, such as social-, ethnicity- and sex-related differences in DKD risk, onset and progression. Multiomics provides opportunities to uncover how lifetime exposures become molecularly embodied to impact kidney health. Such insights would advance DKD diagnosis and treatment, inform preventative strategies and reduce the global impact of this disease.

The influence of non-cancer-related risk factors on the development of cancer-related lymphedema: a rapid review.

Extensive research supports an evidence-base for cancer treatment-related risk factors, including extent of lymph node dissection and use of radiotherapy, as contributing to secondary lymphedema. Additionally, comorbidities, such as higher body mass index, and vascular-related conditions are identified to further augment risk. While social determinants of health (SDOH) and socioeconomic factors are widely regarded as influencing an individual's healthcare outcomes, including cancer risk and survival, these factors have not been explored as risk factors for developing secondary lymphedema. A rapid literature review explored the current evidence for SDOH as risk factors for lymphedema. Studies that were published over the last 10years and that specifically analyzed social factors as variables associated with lymphedema were included. Studies that only characterized the social determinants of the study population were not included. Forty-nine studies were identified through a rapid literature review, and 13 studies that expressly analyzed social determinants as risk factors for secondary lymphedema were reviewed and extracted. All studies were conducted in patients with breast cancer-related lymphedema. Social risk factors included race, educational level, insurance type, and income level. These are consistent with the socioeconomic inequalities related to cancer survival. SDOH may influence the risk of developing cancer treatment-related health conditions like secondary lymphedema. Research trials studying cancer treatment-related conditions should collect consistent and robust data across social, behavioral, environmental, and economic domains and should analyze these variables to understand their contribution to study endpoints. Risk prediction modeling could be a future pathway to better incorporate social determinants, along with medical and co-morbidity data, to holistically understand lymphedema risk.

6809 Natural History Of Classic Congenital Adrenal Hyperplasia: Results From Pediatric And Adult Patients In The CAHtalog Registry

Abstract Disclosure: P.C. White: Consulting Fee; Self; Neurocrine Biosciences, Inc.. Research Investigator; Self; Neurocrine Biosciences, Inc. G.P. Sen: Employee; Self; Neurocrine Biosciences, Inc. F. Tang: Employee; Self; Cytel. J. Chen: Employee; Self; PicnicHealth. K. Lin-Su: Advisory Board Member; Self; CARES Foundation. D. Matos: Employee; Self; CARES Foundation. H. Cheng: Employee; Self; Neurocrine Biosciences, Inc. E. Roberts: Employee; Self; Neurocrine Biosciences, Inc. J.L. Chan: Employee; Self; Neurocrine Biosciences, Inc. G.S. Jeha: Employee; Self; Neurocrine Biosciences, Inc.. Introduction: Patients with congenital adrenal hyperplasia (CAH) are exposed to excess androgens and glucocorticoids (GC), which can affect growth and lead to obesity and other metabolic complications. CAHtalog is an active US-based CAH registry developed in partnership with CARES Foundation on the PicnicHealth platform to abstract retrospective and prospective medical record data. This study reports auxological and comorbidity data for pediatric and adult patients in the CAHtalog registry. Methods: All available medical records for consented adult and pediatric patients were collected. Data were abstracted and structured into a de-identified dataset. CAHtalog data available as of October 2023 were included for analysis. Auxological data were compared to the 2000 CDC growth data. Changes in body mass index (BMI) since the first documented measurements were evaluated. Comorbidities were defined based on diagnosis codes (ICD-9/10), laboratory measurements, vital signs, and/or clinical notes. Results: Data from 32 adult (mean age: 35.8±12.7 years; 72% female) and 35 pediatric patients (mean age: 12.7±5.5 years; 51% female) were available. From the first through last medical record with relevant ages (≥18 or &amp;lt;18 years), median follow-up durations were 13 years (adult) and 11 years (pediatric). Pediatric patients had early growth acceleration (that was more pronounced in females) with 95% confidence intervals for height-for-age of 66-99th percentile for females (2-10 years) and 42-87th percentile for males (2-13 years), followed by blunted pubertal growth. The mean peak bone age to chronological age ratio was 1.2±0.2 at age 7 years. The mean BMI-for-age consistently exceeded the 90th percentile in children aged ≥6 years, particularly for females. In adults, obesity (BMI ≥30) was highly prevalent in both females (74%) and males (33%) at all ages (61% overall), exceeding NHANES 2017-2018 general population prevalence (42%). Hypertension (53%), fatigue (47%), acne (36%), hyperlipidemia (33%), and insomnia/sleep disturbances (28%) were common comorbidities. Conclusion: Our CAH data reveal a persistent abnormal growth pattern, characterized by accelerated growth in early childhood and a deceleration in adolescents; early obesity was noted and sustained into adulthood. The anomalous growth trajectory and high rate of comorbidities reiterate the importance of early intervention and targeted disease management in this population. Presentation: 6/2/2024

Revisiting Fournier Gangrene: A Contemporary Epidemiological Perspective vs Perineal Cellulitis.

We conducted a population-based analysis of Fournier gangrene (FG) to compare risk factors and mortality with those of perineal cellulitis. We analyzed National Inpatient Sample data (2016-2020) to identify FG and perineal cellulitis cases. Demographic, comorbidity, and procedural data were extracted. Logistic models assessed risk factors of FG diagnosis and mortality. A total of 73,472 cellulitis and 9326 FG cases were identified corresponding to 74,905 (range, 63,050-79,165) and 9115 (range, 7925-11,080) median yearly weighted cases, respectively. FG diagnosis vs cellulitis was positively associated with Native American race (odds ratio [OR], 1.46; 95% CI, 1.19-1.79), weekend (OR, 1.12; 95% CI, 1.06-1.18) or December (OR, 1.33, 95% CI, 1.22-1.44) admissions, diabetes mellitus (OR, 2.51; 95% CI, 2.38-2.64), and malignancy (OR, 2.29; 95% CI, 2.07-2.54). Conversely, Hispanic (OR, 0.79; 95% CI, 0.74-0.85) and Asian/Pacific Islander races (OR, 0.83; 95% CI, 0.69-0.99) and the highest household income quartile (OR, 0.84; 95% CI, 0.78-0.90) were linked to a reduced likelihood of FG diagnosis. Elevated mortality risks were observed with female sex (OR, 1.33; 95% CI, 1.08-1.63), Native American ethnicity (OR, 2.29; 95% CI, 1.14-4.57), and procedural frequency (OR, 1.27; 95% CI, 1.24-1.3) among FG cases. Various patient and clinical factors are linked to the development and mortality of FG compared with perineal cellulitis. Improved access to care and understanding of FG can enhance patient outcomes.

Effect of Race and Socioeconomic Status on the Attainment of Substantial Clinical Benefit on Patient-Reported Outcome Measures Following Total Joint Arthroplasty

Utilization of and access to total joint arthroplasty (TJA) are disproportionately skewed in patients who have low socioeconomic status (SES) and in minority populations. Patient-reported outcome measures (PROMs) are critical markers of post-surgical outcomes following TJA. This study aimed to 1) evaluate differences in race, SES, and demographic factors between TJA patients who achieved substantial clinical benefit (SCB) and those who did not; 2) assess differences between preoperative PROMs in these patients; and 3) identify whether race and SES are associated with SCB achievement at 1-year post-TJA. This retrospective cohort study included 1,154 total hip arthroplasty (THA) and 1,879 total knee arthroplasty (TKA) patients who underwent surgery at a single academic medical center from May 2019 to February 2023. Preoperative and postoperative PROMs were collected using the Knee Injury and Osteoarthritis Outcome Score (KOOS JR) and Hip Disability and Osteoarthritis Outcome Score (HOOS JR) surveys. Demographic and comorbidity data were collected from charts. Multivariable logistic regression analyzed the association between predictive variables and SCB achievement. No differences in race were found between patients who achieved SCB and those who did not for both TKA and THA (P > 0.05). However, preoperative KOOS JR scores were lower in Black (P = 0.004) and Hispanic (P < 0.001) patients and preoperative HOOS JR scores were lower in Black patients (P < 0.001) compared to White patients. A higher proportion of patients in the lowest income category achieved SCB for both THA and TKA compared to those in other income categories (P = 0.04, P = 0.03, respectively). However, race was not associated with SCB likelihood at one year. For TKA patients, men were negative, and bilateral simultaneous TKA was positively associated with SCB achievement when controlling for race, income, and BMI (P < 0.001, P = 0.01, respectively). Race and income category were not significantly associated with achieving SCB at one year among TJA patients. However, non-White patients had a similar likelihood of achieving SCB as White patients, even with lower preoperative PROMs, indicating that these patients may benefit greatly from TJA despite delays in care. Men were negatively associated with TKA SCB achievement, while bilateral simultaneous TKA was positively associated with SCB.

Identifiable Historic and Observable Factors May Predict Progression to Exfoliation Glaucoma in Newly Diagnosed Exfoliation Patients

To identify clinical factors associated with conversion to exfoliation glaucoma (XFG) in exfoliation syndrome (XFS) patients most at risk of progression to XFG within 3 years for increased surveillance and early preventive interventions. A retrospective patient cohort study design was employed. A source population of XFS patients 50 years and older was identified from electronic medical records in the Utah Population Database. From this, 487 study patients with one or more dilated eye exams prior to chart-confirmed XFS onset in 2011 or later, and three or more years of subsequent eye exams, were selected for study. We implemented a binomial linear mixed models with L1-penalized estimation to select variables associated with conversion. Models included a random intercept to account for within-patient correlation for eye-level data. Candidate demographic, lifestyle, systemic and ocular comorbidities data were obtained and diagnoses categorized as binary (history or no history). These potential factors between conversion and non-conversion patients were used in model selection of variables jointly predictive of conversion. Odds ratios and confidence intervals were calculated using the link logit. To determine the main outcome of conversion to XFG following an index diagnosis of XFS compared with nonconversion within 3 years, clinical records of each subject's left and right eyes were assessed to confirm XFS and date of onset and date of XFG onset, if conversion occurred. Clinical measurements, e.g. intraocular pressure (IOP), cup to disc ratio, provider notes and IOP-lowering procedures and medications were used to corroborate conversion status. Eighteen variables jointly predicted XFG conversion within 3 years correctly in 71% of patient eyes. Odds of conversion was highest for exudative age-related macular degeneration (AMD), 2.3-fold (P=0.004). Other predictive variables included nonexudative AMD (P=0.05), primary open angle glaucoma (P<0.001), obstructive sleep apnea (P=0.03), and ocular hypertension (P=0.003) diagnosed prior to XFS onset. We determined a set of clinically relevant factors that predicted which newly-diagnosed XFS patients progressed to XFG within 3 years. A planned validation will independently confirm if these prognostic indicators hold promise in other settings.

Calcium channel blockers and beta blockers in pediatric supraventricular tachycardia.

Supraventricular tachycardia (SVT) is a common pediatric arrhythmia. Beta blockers (BBs) and calcium channel blockers (CCBs) are used for treatment despite little data examining their use. We describe the prescriptive tendencies, efficacy, and tolerability of BBs and CCBs used in the treatment of pediatric SVT. This is a multicenter retrospective cohort study from three academic children's hospitals. Individuals aged 1-21 years at time of SVT diagnosis initiated on a BB or a CCB between 01/01/2010 and 12/31/2020 were included. Exclusion criteria were pre-excitation, ectopic atrial tachycardia, and hemodynamically significant heart disease. Demographic, comorbidity, symptomatology, and medication data were collected. Treatment success was defined using a composite data abstraction tool. Of 164 patients, 151 received a BB and 13 received a CCB. The success rate on the initial dosage was 46% for both BB and CCB; the success rate following dosage adjustments was also comparable for BBs (98/151, 65%) and CCBs (9/13, 69%). While 27 (18%) BB patients experienced intolerable side effects, no CCB patient did. Treatment with a BB or CCB was successful in half of patients. BBs were prescribed more frequently than CCBs but were associated with more side effects.

Abstract C044: Social vulnerability is an important predictor of cardiovascular disease risk after allogeneic hematopoietic cell transplantation

Abstract Introduction: Allogeneic hematopoietic cell transplantation (HCT) is a curative treatment for malignant and non-malignant hematologic diseases. However, long-term HCT survivors have a &amp;gt;4-fold risk of developing cardiovascular disease (CVD) compared to the general population, and CVD is a leading cause of excess mortality after HCT. Comorbidities that emerge after HCT such as hypertension (HTN), diabetes mellitus (DM), and dyslipidemia (DL) are important modifiers of CVD risk, but the impact of social determinants of health (SDOH) on the development of these risk factors and resultant CVD has not been well-characterized. Methods: This retrospective cohort study included 889 patients who underwent an allogenic HCT between 2013 and 2019 at City of Hope and survived ≥1y after HCT. Demographic, disease, treatment, comorbidity, and health outcomes data were abstracted from medical records. The social vulnerability index (SVI), obtained from the Center for Disease Control, represented overall social vulnerability and included 4 themes: socioeconomic status, household composition &amp; disability, minority status &amp; language, and housing &amp; transportation. SVI scores were derived using patients’ addresses at time of HCT. SVI scores ranged from 0 (least vulnerable) to 100 (most vulnerable). Fine-Gray regression analysis evaluated the association between SVI and risk of HTN, DM, and DL, adjusted for age at HCT and treating death as competing risk. We also evaluated the association between having 0, 1, ≥2 cardiovascular risk factors on incidence of clinically significant CVD (heart failure, coronary artery disease, pericarditis, stroke, intracranial hemorrhage, arrhythmia, and/or valvular disease) after HCT. Results: Mean age at HCT was 44.2y (standard deviation 19.8y); 56.7% were male, 43.8% were non-Hispanic White, 35.4% were Hispanic, and 12.9% were Asian. The most common diagnosis was acute myeloid leukemia (39.6%); 48.6% received reduced intensity conditioning. Higher overall SVI was associated with increased risk of HTN (adjusted Hazard Ratio per 10 unit increase in SVI [aHR] 1.10, 95%CI 1.02-1.19) and DM (aHR 1.13, 95%CI 1.03-1.25). There was also an increased risk for DL for the highest SVI tertile for the housing &amp; transportation theme (aHR 1.61, 95%CI 1.10-2.37). Accumulation of de novo risk factors after HCT was associated with an incremental 5y incidence of CVD (None: 6.1%, 95% CI 3.4%-9.9%; 1 risk factor: 15.7%, 95% CI 7.1%-27.3%; &amp;gt;2 risk factors: 31.6%, 95%CI 12.8%-52.4%; p&amp;lt;0.001). In the adjusted multivariable model, survivors with &amp;gt;2 risk factors had 7.0-fold (aHR 6.99, 95%CI 2.86-17.05) risk of CVD compared to those without (ref). Conclusion: Among allogeneic HCT recipients, higher SVI was associated with increased risk of HTN, DM, and DL after HCT, which in turn were associated with incrementally higher 5y incidence of CVD. These findings underscore the importance of SDOH on clinically important outcomes after allogeneic HCT, and may ultimately inform tailored approaches for risk-based screening and resource allocation in long-term survivors. Citation Format: Osariemen V Ogiamien, Sitong Chen, Lizel Atencio, Alysia Bosworth, Meagan Echevarria, Caitlyn Estrada, Mareen Kassabian, Lanie Lindenfeld, F. Lennie Wong, Saro H Armenian, Rusha Bhandari. Social vulnerability is an important predictor of cardiovascular disease risk after allogeneic hematopoietic cell transplantation [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C044.

Perioperative outcomes using computer navigation in primary total shoulder arthroplasty

IntroductionThe utilization of computer navigation to improve glenoid component placement in primary total shoulder arthroplasty (TSA) is becoming increasingly prevalent. However, there is a paucity of literature examining the perioperative outcomes and cost of this technology compared to standard instrumentation. The purpose of this study was to compare the perioperative complications and healthcare utilization between computer navigation and standard instrumentation in primary TSA. MethodsThe Nationwide Readmissions Database was queried from 2016 to 2020 to identify patients who underwent elective primary TSA. Patients who underwent TSA with computer navigation (n = 752) were propensity score matched in a 1:3 proportion to patients who underwent TSA with standard instrumentation (n = 2256) for age, sex, smoking status, alcohol abuse, hypertension, diabetes mellitus, congestive heart failure, obesity, peripheral vascular disease, chronic kidney disease, chronic liver disease, and chronic lung disease. Bivariate statistical analyses were performed to compare preoperative demographic and comorbidity data, postoperative complications, and hospital utilization metrics between the 2 groups. Chi-square and student t-tests identified differences in categorical and continuous variables, respectively. ResultsPatients undergoing TSA with computer navigation exhibited lower rates of revision within 180 days (P < .001) and lower rates of certain postoperative medical and surgical complications, including acute renal failure (P = .006), urinary tract infection (P = .015), acute respiratory distress syndrome (P = .045), surgical site infection (P = .022), dislocation (P = .012), and prosthetic loosening (P = .032). Computer navigation patients had a higher cost of initial admission (P < .001) but were less likely to have extended hospital stays (P = .047), less likely to be discharged with home healthcare (P < .001), and more likely to be discharged routinely (P < .001). ConclusionTSA with computer navigation was associated with lower revision rates and reduced postoperative complications. Although greater initial costs were observed, decreased extended hospital stays and more routine discharges show promise for long-term cost efficiency. These findings underscore the advantages of computer navigation in TSA and should be considered by orthopedic surgeons when evaluating choice of instrumentation.

Comorbidity-based framework for Alzheimer’s disease classification using graph neural networks

Alzheimer’s disease (AD), the most prevalent form of dementia, requires early prediction for timely intervention. Current deep learning approaches, particularly those using traditional neural networks, face challenges such as handling high-dimensional data, interpreting complex relationships, and managing data bias. To address these limitations, we propose a framework utilizing graph neural networks (GNNs), which excel in modeling relationships within graph-structured data. Our study employs GNNs on data from the Alzheimer’s Disease Neuroimaging Initiative for binary and multi-class classification across the three stages of AD: cognitively normal (CN), mild cognitive impairment (MCI), and Alzheimer’s disease (AD). By incorporating comorbidity data derived from electronic health records, we achieved the most effective multi-classification results. Notably, the GNN model (Chebyshev Convolutional Neural Networks) demonstrated superior performance with a 0.98 accuracy in multi-class classification and 0.99, 0.93, and 0.94 in the AD/CN, AD/MCI, and CN/MCI binary tasks, respectively. The model’s robustness was further validated using the Australian Imaging, Biomarker & Lifestyle dataset as an external validation set. This work contributes to the field by offering a robust, accurate, and cost-effective method for early AD prediction (CN vs. MCI), addressing key challenges in existing deep learning approaches.

Risk factors for extended hospital stay following minimally invasive transforaminal lumbar interbody fusion

BackgroundPrior literature has examined predictors of length of stay (LOS) for lumbar fusion broadly, grouping multiple surgical approaches into one sample. Evaluating minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) specifically can reduce variability introduced by other approaches to effectively identify predictors of LOS. The purpose of this study is to evaluate preoperative predictors of extended LOS in patients undergoing MIS-TLIF. MethodsMIS-TLIF patients were identified from a spine surgeon’s database. Preoperative predictors of LOS, including demographics, comorbidity data, spinal pathology, patient-reported back pain, leg pain, physical function, disability, general physical health, mental health, and depressive burden scores were analyzed. Univariate analysis was performed to identify predictors of LOS ≥ 48 and LOS ≥ 72 h, a multivariate analysis confirmed significance. Eight-hundred-one patients were included. ResultsAfrican-American patients were 4.3 times more likely to have a LOS≥48 h compared to Caucasians (p ≤ 0.001). Diagnosis of herniated nucleus pulposus and foraminal stenosis were negative predictors of an LOS ≥ 72 h (p ≤ 0.014, both). Self-identified African American patients were approximately twice as likely to have a LOS ≥ 72 h compared to Caucasians. Preoperative Oswestry Disability Index (ODI) was positively correlated with LOS ≥ 48 h (p = 0.008). Other baseline patient-reported outcomes (PROs) were not predictive of LOS ≥ 48 or 72 h (p > 0.050, all). ConclusionsFurther research should explore why different demographic characteristics may be associated with extended postoperative LOS to target interventions toward potential health disparities. Understanding preoperative risk factors can help target increased healthcare costs and improve patient care through tailored interventions and future research.

Drug Repurposing for COVID-19 by Constructing a Comorbidity Network with Central Nervous System Disorders.

In the post-COVID-19 era, treatment options for potential SARS-CoV-2 outbreaks remain limited. An increased incidence of central nervous system (CNS) disorders has been observed in long-term COVID-19 patients. Understanding the shared molecular mechanisms between these conditions may provide new insights for developing effective therapies. This study developed an integrative drug-repurposing framework for COVID-19, leveraging comorbidity data with CNS disorders, network-based modular analysis, and dynamic perturbation analysis to identify potential drug targets and candidates against SARS-CoV-2. We constructed a comorbidity network based on the literature and data collection, including COVID-19-related proteins and genes associated with Alzheimer's disease, Parkinson's disease, multiple sclerosis, and autism spectrum disorder. Functional module detection and annotation identified a module primarily involved in protein synthesis as a key target module, utilizing connectivity map drug perturbation data. Through the construction of a weighted drug-target network and dynamic network-based drug-repurposing analysis, ubiquitin-carboxy-terminal hydrolase L1 emerged as a potential drug target. Molecular dynamics simulations suggested pregnenolone and BRD-K87426499 as two drug candidates for COVID-19. This study introduces a dynamic-perturbation-network-based drug-repurposing approach to identify COVID-19 drug targets and candidates by incorporating the comorbidity conditions of CNS disorders.

The spectrum of co-existing disease in children with established kidney failure using registry and linked electronic health record data

BackgroundChildren with established kidney failure may have additional medical conditions influencing kidney care and outcomes. This cross-sectional study aimed to examine the prevalence of co-existing diseases captured in the electronic hospital record compared to UK Renal Registry (UKRR) data and differences in coding.MethodsThe study population comprised children aged < 18 years receiving kidney replacement therapy (KRT) in England and Wales on 31/12/2016. Comorbidity data at KRT start was examined in the hospital record and compared to UKRR data. Agreement was assessed by the kappa statistic. Associations between patient and clinical factors and likelihood of coding were examined using multivariable logistic regression.ResultsA total of 869 children (62.5% male) had data linkage for inclusion. UKRR records generally reported a higher prevalence of co-existing disease than electronic health records; congenital, non-kidney disease was most commonly reported across both datasets. The highest sensitivity in the hospital record was seen for congenital heart disease (odds ratio (OR) 0.65, 95% confidence interval (CI) 0.51, 0.78) and malignancy (OR 0.63, 95% CI 0.41, 0.85). At best, moderate agreement (kappa ≥ 0.41) was seen between the datasets. Factors associated with higher odds of coding in hospital records included age, while kidney disease and a higher number of comorbidities were associated with lower odds of coding.ConclusionsHealth records generally under-reported co-existing disease compared to registry data with fair-moderate agreement between datasets. Electronic health records offer a non-selective overview of co-existing disease facilitating audit and research, but registry processes are still required to capture paediatric-specific variables pertinent to kidney disease.Graphical A higher resolution version of the Graphical abstract is available as Supplementary information

Fibromyalgia syndrome is an independent predictor of increased complications, revision, and cost of admission within 180 days of total shoulder arthroplasty

BackgroundFibromyalgia syndrome (FMS) frequently afflicts patients undergoing total shoulder arthroplasty (TSA), yet research investigating the effects of FMS on postoperative outcomes following TSA is lacking. The purpose of this study is to determine if patients with FMS are at increased risk for complications, readmission, revision, and mortality following primary elective TSA compared to a matched cohort of patients without FMS. MethodsThe Nationwide Readmissions Database was queried from 2016 to 2020 to identify patients who underwent elective primary TSA. Patients were stratified into two groups based on the presence of preoperative FMS. Patients with FMS were matched 1:1 based on age, sex, and Charlson-Deyo Comorbidity Index using an optimized matching algorithm to patients without FMS to generate an equal sized control group for statistical comparison. 5506 matched pairs of patients with and without FMS were identified and used for statistical analysis. Preoperative demographic and comorbidity data, postoperative outcomes, and economic and hospital metrics were compared between the two groups. Multivariate analysis was conducted to control for the influence of independent risk factors other than FMS on postoperative outcomes. ResultsPatients with FMS were more likely to be active smokers (P < .001) and have chronic kidney disease (P < .001) prior to surgery. Patients with FMS exhibited increased rates of complications, including requiring a transfusion (P = .002), acute respiratory distress syndrome (P < .001), surgical site infection (P < .001), dislocation (P < .001), prosthetic loosening (P < .001), and fracture (P < .001) compared to patients without FMS. Patients with FMS also exhibited higher rates of all-cause complications (P < .001) and revision TSA (P < .001) and decreased rates of readmission (P = .002) within 180 days of surgery. Mean cost of admission was found to be $1639 higher in patients with FMS (P < .001), despite no difference in total hospital length of stay or discharge disposition. ConclusionPatients with FMS are more likely to develop medical and surgical complications following primary TSA. Though associated with multiple comorbidities, FMS is an independent predictor of several adverse events. Orthopedic surgeons should be aware of the increased risk of FMS on TSA when determining treatment plans.

Prevalence and characterization of pain in radiation oncology: the PREDORT multicenter cross-sectional study.

Pain in cancer patients has enormous impact on their quality-of-life. Radiation therapy (RT) is a cornerstone in cancer treatment. The objective of the PREDORT study is to estimate the prevalence of pain in patients attending at Radiation Oncology (RO) Services. A prospective, multicenter study was designed for patients treated at the RO Services of reference hospitals. Patients were seen in their initial Nursing consultation, during which key data was collected, including demographic and comorbidities data, medical history, and oncological and pain characteristics. The study has received approval from the Ethics Committee of Navarra, and all patients signed the Informed Consent. Of the 860 participating patients, 306 reported some type of pain, which implies a prevalence of 35.6%. Of them, 213 identified a cause of oncological origin. The proportion of pain was similar among sexes, but the proportion of non-cancer pain was higher among women (p < 0.05). Regarding pain intensity, the magnitude of breakthrough pain in patients with oncological pain is nearly 1 point greater than in patients with non-oncological pain (7.53 vs 6.81; p = 0.064). Cancer pain is more likely to be limiting of normal life than non-cancer pain (59% versus 38%, p < 0.001). Regarding analgesic treatment, only 60/306 patients (19.6%) were receiving strong opioids. There were 68 patients with pain without any treatment (22.2%). The prevalence of pain in cancer patients referred to RO services is 35.6%, with the prevalence of exclusively oncological pain being 24.8%. Understanding and addressing oncological pain is essential to provide comprehensive care to patients.