Volumetric analysis of acute uncomplicated type B aortic dissection using an automated deep learning aortic zone segmentation model.

BACKGROUND: Machine learning techniques have shown excellent performance in three-dimensional medical image analysis, but have not been applied to acute uncomplicated type B aortic dissection (auTBAD) using Society for Vascular Surgery (SVS) and Society of Thoracic Surgeons (STS)-defined aortic zones. The purpose of this study was to establish a trained, automatic machine learning aortic zone segmentation model to facilitate performance of an aortic zone volumetric comparison between patients with auTBAD based on the rate of aortic growth. METHODS: Patients with auTBAD and serial imaging were identified. For each patient, imaging characteristics from two computed tomography (CT) scans were analyzed: (1) the baseline CT angiography (CTA) at the index admission and (2) either the most recent surveillance CTA or the most recent CTA before an aortic intervention. Patients were stratified into two comparative groups based on aortic growth: rapid growth (diameter increase of ≥5 mm/year) and no or slow growth (diameter increase of <5 mm/year). Deidentified images were imported into an open source software package for medical image analysis and images were annotated based on SVS/STS criteria for aortic zones. Our model was trained using four-fold cross-validation. The segmentation output was used to calculate aortic zone volumes from each imaging study. RESULTS: Of 59 patients identified for inclusion, rapid growth was observed in 33 patients (56%) and no or slow growth was observed in 26 patients (44%). There were no differences in baseline demographics, comorbidities, admission mean arterial pressure, number of discharge antihypertensives, or high-risk imaging characteristics between groups (P > .05 for all). Median duration between baseline and interval CT was 1.07 years (interquartile range [IQR], 0.38-2.57). Postdischarge aortic intervention was performed in 13 patients (22%) at a mean of 1.5 ± 1.2 years, with no difference between the groups (P > .05). Among all patients, the largest relative percent increases in zone volumes over time were found in zone 4 (13.9%; IQR, -6.82 to 35.1) and zone 5 (13.4%; IQR, -7.78 to 37.9). There were no differences in baseline zone volumes between groups (P > .05 for all). The average Dice coefficient, a performance measure of the model output, was 0.73. Performance was best in zone 5 (0.84) and zone 9 (0.91). CONCLUSIONS: We describe an automatic deep learning segmentation model incorporating SVS-defined aortic zones. The open source, trained model demonstrates concordance to the manually segmented aortas with the strongest performance in zones 5 and 9, providing a framework for further clinical applications. In our limited sample, there were no differences in baseline aortic zone volumes between patients with rapid growth and patients with no or slow growth.

Outcomes of Patients with Acute Type B Aortic Dissection and High-Risk Features.

BACKGROUND: Recently the Society for Vascular Surgery (SVS) and Society for Thoracic Surgeons (STS) published contemporary guidelines clearly defining complicated versus uncomplicated acute type B aortic dissections (TBADs) with an additional high-risk grouping. Few studies have evaluated outcomes associated with "high-risk" TBADs. The objective of this study was to assess differences in demographics, clinical presentation, symptom onset, and outcomes in high-risk patients that underwent either thoracic endovascular aortic repair (TEVAR) or best medical management for acute TBAD compared to those with complicated and uncomplicated acute TBAD. METHODS: Patients admitted with acute TBADs from a single academic medical center from October 2011 to March 2020 were analyzed. Per the STS/SVS 2020 guidelines, high risk was defined as refractory pain/hypertension, bloody pleural effusion, aortic diameter >4 cm, false lumen diameter >22 mm, radiographic malperfusion, and early readmission, and complicated was defined as ruptured/malperfusion presentation. Uncomplicated patients were those without malperfusion/rupture and without high-risk features. The primary end-point was inpatient mortality. Secondary end-points included complications, reintervention, and survival. RESULTS: Of the 159 patients identified with acute TBAD, 63 (40%) met the high-risk criteria. In the high-risk cohort, 38 (60%) underwent TEVAR (HR-TEVAR), with refractory pain as the most common indication, while 25 (40%) were managed medically (HR-medical). Malperfusion or rupture was present in 63 (40%) patients (complicated TBAD (C-TBAD)), all of whom underwent TEVAR. An additional 33 patients had no high-risk features and were all managed medically (uncomplicated TBAD). There were no differences in age, body mass index, and race between groups. Among the 4 groups, there were variable distributions in sex, insurance status, and incidence of several baseline comorbidities including congestive heart failure, chronic obstructive pulmonary disease, and renal dysfunction (P < 0.05 for all). C-TBAD had increased length of stay (12, interquartile range [IQR] 9-22) compared to HR-TEVAR (11.5, IQR 7-15), HR-medical (6, IQR 5-8), and uncomplicated TBAD (7, IQR 5-10) (P < 0.01). C-TBAD had decreased days from admission to repair (0, IQR 0-2) compared to HR-TEVAR (3.5, IQR 1-8) (P < 0.01). C-TBAD patients had worse 3-year survival compared to other groups (log-rank P < 0.01), although when in-hospital mortality was excluded, survival was similar among groups (P = 0.37). Of patients initially managed medically, outpatient TEVAR was performed in 6 (24%) HR-medical and 4 (12%) uncomplicated patients, with no difference between rate of intervention between groups (P = 0.22). CONCLUSIONS: High-risk features, as defined in updated SVS/STS guidelines, are common in patients presenting with acute TBAD. High-risk patients had acceptable outcomes when managed either surgically or medically. High-risk patients that underwent TEVAR had improved perioperative outcomes and mortality compared to those undergoing TEVAR for C-TBAD, a finding which may help guide preoperative risk stratification and patient counseling.

Perioperative Cerebrospinal Fluid Drain Placement Does Not Increase Venous Thromboembolism Risk After Thoracic and Fenestrated Endovascular Aortic Repair.

BACKGROUND: Venous thromboembolism (VTE) incidence after thoracic and fenestrated endovascular aortic repair (TEVAR/FEVAR) is high (up to 6-7%) relative to other vascular procedures; however, the etiology for this discrepancy remains unknown. Notably, patients undergoing TEVAR/FEVAR commonly receive cerebrospinal fluid drains (CSFDs) for neuroprotection, requiring interruption of perioperative anticoagulation and prolonged immobility. We hypothesized that CSFDs are a risk factor for VTE after TEVAR/FEVAR. METHODS: Consecutive TEVAR/FEVAR patients at a single center were reviewed (2011-2020). Cerebrospinal fluid drains (CSFDs) were placed based on surgeon preference preoperatively or for spinal cord ischemia (SCI) rescue therapy postoperatively. The primary end-point was VTE occurrence, defined as any new deep venous thrombosis (DVT) or pulmonary embolism (PE) confirmed on imaging within 30 days postoperatively. Routine postoperative VTE screening was not performed. Patients with and without VTE, and subjects with and without CSFDs were compared. Logistic regression was used to explore associations between VTE incidence and CSFD exposure. RESULTS: Eight hundred ninety-seven patients underwent TEVAR/FEVAR and 43% (n = 387) received a CSFD at some point during their care (preoperative: 94% [n = 365/387]; postoperative SCI rescue therapy: 6% [n = 22/387]). CSFD patients were more likely to have previous aortic surgery (44% vs. 37%; P = 0.028) and received more postoperative blood products (780 vs. 405 mL; P = 0.005). The overall VTE incidence was 2.2% (n = 20). 70% (14) patients with VTE had DVT, 50% (10) had PE, and 20% (4) had DVT and PE. Among TEVAR/FEVAR patients with VTE, 65% (n = 13) were symptomatic. Most VTEs (90%, n = 18) were identified inhospital and the median time to diagnosis was 12.5 (interquartile range 7.5-18) days postoperatively. Patients with VTE were more likely to have nonelective surgery (95% vs. 41%; P < 0.001), had higher American Society of Anesthesiologists classification (4.1 vs. 3.7; P < 0.001), required longer intensive care unit admission (24 vs. 12 days; P < 0.001), and received more blood products (1,386 vs. 559 mL; P < 0.001). Venous thromboembolism (VTE) incidence was 1.8% in CSFD patients compared to 3.5% in non-CSFD patients (odds ratio 0.70 [95% confidence interval 0.28-1.78, P = 0.300). However, patients receiving CSFDs postoperatively for SCI rescue therapy had significantly greater VTE incidence (9.1% vs. 1.1%; P = 0.044). CONCLUSIONS: CSFD placement was not associated with an increased risk of VTE in patients undergoing TEVAR/FEVAR. Venous thromboembolism (VTE) risk was greater in patients undergoing nonelective surgery and those with complicated perioperative courses. Venous thromboembolism (VTE) risk was greater in patients receiving therapeutic CSFDs compared to prophylactic CSFDs, highlighting the importance of careful patient selection for prophylactic CSFD placement.

Presentation and Outcomes of Elective and Nonelective Complex Endovascular Repair for Thoracoabdominal and Juxtarenal Aortic Aneurysms.

BACKGROUND: Endovascular repair of thoracoabdominal aortic aneurysms (TAAA) and juxtarenal aortic aneurysms (JAA) with fenestrated and/or branched endografts (B/FEVAR) has become common. Physician modified endografts for patients presenting with symptomatic or contained ruptures has made B/FEVAR a feasible option in nonelective settings. The purpose of this study was to describe our 10-year institutional experience with endovascular interventions for TAAA in elective and nonelective cases to evaluate differences in outcomes and the clinical risk factors associated with nonelective presentation. METHODS: A prospectively maintained database was retrospectively queried for patients undergoing B/FEVAR for TAAA and JAA at a single tertiary care academic institution between 1/2011 and 12/2020. Data collected included demographics, comorbidities, presenting symptoms, aneurysm characteristics, and clinical outcomes. Nonelective repair was defined as any patient that presented through the Emergency Department, as a hospital transfer, or as a direct admission from clinic and had aortic repair performed during the same admission. Univariate analyses were used to compare patients. The primary outcomes were 30-day and 1-year mortality. Secondary outcomes included perioperative complications and nonhome discharge. RESULTS: Between 1/201 and 12/2020, a total of 208 patients underwent B/FEVAR for TAAA (173) and JAA (35). Nonelective repair was performed in 44 (21%) patients with 39 for TAAA (23%) and 5 for JAA (14%). Nonelective patients were younger (71 ± 11 vs. 74 ± 7 years, P = 0.03), more likely to be self-pay or have Medicaid (11% vs. 2%, P = 0.02) and had a different race distribution compared to the elective cohort (P < 0.01). Thirty-day mortality was 4% (n = 6) in elective repairs and 7% (n = 3) in nonelective repairs. One-year mortality was 13% (n = 22) in elective repairs and 18% (n = 8) in nonelective repairs. There were no differences between patients receiving elective versus nonelective repair in 30-day (P = 0.40) or 1-year mortality (P = 0.47). Nonelective patients had longer median duration of stay (11 interquartile range (IQR) 6-15 vs. 5 IQR 4-8, P < 0.01), postoperative length of stay (7 IQR 5-12 vs. 4 IQR 3-7, P < 0.01), and more intensive care unit days (6 IQR 3-8 vs. 3 IQR 2-5, P < 0.01). There were no differences in other secondary outcomes between elective and nonelective patients including inpatient and access-related complications, re-interventions, and nonhome discharge (P > 0.05 for all comparisons). A composite "any complication" occurred more frequently in patients with nonelective repair (50% vs. 35%, P = 0.03). CONCLUSIONS: Endovascular repair for TAAA or JAA is a good option in patients undergoing nonelective surgical intervention, with comparable 30-day mortality, 1-year mortality, and perioperative morbidity to that of patients undergoing elective B/FEVAR.

Prevalence of chronic opioid use in patients with peripheral arterial disease undergoing revascularization.

OBJECTIVE: Opiate use, dependence, and the associated morbidity and mortality are major current public health problems in the United States. Little is known about patterns of opioid use in patients with peripheral arterial disease (PAD). The purpose of this study was to identify the prevalence of chronic preoperative and postoperative prescription opioid use in patients with PAD. A secondary aim was to determine the demographic, comorbid conditions, and operative characteristics associated with chronic opioid use. METHODS: Using a single-institution database of patients with PAD undergoing open or endovascular lower extremity intervention from 2013 to 2014, data regarding opiate use and associated conditions were abstracted for analysis. Patients were excluded if they did not live in North Carolina or surgery was not for PAD. Preoperative (PreCOU) and postoperative chronic opioid use (PostCOU) were defined as consistent opioid prescription filling in the 3 months before and after the index procedure, respectively. Opioid prescription filling was assessed using the North Carolina Controlled Substance Reporting System. Demographics, comorbid conditions, other adjunct pain medication data, and operative characteristics were abstracted from our institutional electronic medical record. Associations with PreCOU were evaluated using the t test, Wilcoxon test, or two-sample median test (continuous), or the χ2 or Fisher exact tests (categorical). RESULTS: A total of 202 patients undergoing open (108; 53.5%) or endovascular (94; 46.5%) revascularization for claudication or critical limb ischemia were identified for analysis. The mean age was 64.6 years, and 36% were female. Claudication was the indication for revascularization in 26.7% of patients, and critical limb ischemia was the indication in 73.3% of patients. The median preoperative ankle-brachial index (ABI) was 0.50. Sixty-eight patients (34%) met the definition for PreCOU. PreCOU was associated with female gender, history of chronic musculoskeletal pain, benzodiazepine use, and self-reported illicit drug use. Less than 50% of patients reported use of non-opiate adjunct pain medications. No association was observed between PreCOU and pre- or postoperative ABI, or number of prior lower extremity interventions. Following revascularization, the median ABI was 0.88. PreCOU was not associated with significant differences in postoperative complications, length of stay, or mortality. Overall, 71 patients (35%) met the definition for PostCOU, 14 of whom had no history of preoperative chronic opiate use. Ten patients with PreCOU did not demonstrate PostCOU. CONCLUSIONS: Chronic opiate use was common in patients with PAD with a prevalence of approximately 35%, both prior to and following revascularization. Revascularization was associated with a termination of chronic opiate use in less than 15% of patients with PreCOU. Additionally, 10% of patients who did not use opiates chronically before their revascularization did so afterwards. Patients with PAD requiring intervention represent a high-risk group with regards to chronic opiate use. Increased diligence in identifying opioid use among patients with PAD and optimizing the use of non-narcotic adjunct pain medications may result in a lower prevalence of chronic opiate use and its attendant adverse effects.

Replicating medication trend studies using ad hoc information extraction in a clinical data warehouse.

BACKGROUND: Medication trend studies show the changes of medication over the years and may be replicated using a clinical Data Warehouse (CDW). Even nowadays, a lot of the patient information, like medication data, in the EHR is stored in the format of free text. As the conventional approach of information extraction (IE) demands a high developmental effort, we used ad hoc IE instead. This technique queries information and extracts it on the fly from texts contained in the CDW. METHODS: We present a generalizable approach of ad hoc IE for pharmacotherapy (medications and their daily dosage) presented in hospital discharge letters. We added import and query features to the CDW system, like error tolerant queries to deal with misspellings and proximity search for the extraction of the daily dosage. During the data integration process in the CDW, negated, historical and non-patient context data are filtered. For the replication studies, we used a drug list grouped by ATC (Anatomical Therapeutic Chemical Classification System) codes as input for queries to the CDW. RESULTS: We achieve an F1 score of 0.983 (precision 0.997, recall 0.970) for extracting medication from discharge letters and an F1 score of 0.974 (precision 0.977, recall 0.972) for extracting the dosage. We replicated three published medical trend studies for hypertension, atrial fibrillation and chronic kidney disease. Overall, 93% of the main findings could be replicated, 68% of sub-findings, and 75% of all findings. One study could be completely replicated with all main and sub-findings. CONCLUSION: A novel approach for ad hoc IE is presented. It is very suitable for basic medical texts like discharge letters and finding reports. Ad hoc IE is by definition more limited than conventional IE and does not claim to replace it, but it substantially exceeds the search capabilities of many CDWs and it is convenient to conduct replication studies fast and with high quality.

Sarcopenia is a Poor Predictor of Outcomes in Elective Colectomy for Diverticulitis.

BACKGROUND: Sarcopenia is associated with adverse perioperative outcomes in patients undergoing operations for malignancy, but its influence on patients undergoing elective colectomy for diverticulitis is unknown. We hypothesized that sarcopenia is associated with adverse perioperative events in patients undergoing elective colectomy for diverticulitis. METHODS: Comorbidities, operative characteristics, and postoperative complications were extrapolated from our institutional EMR in patients undergoing elective colectomy for diverticulitis from 2016 to 2020. Sarcopenia was calculated using perioperative imaging and defined by standard skeletal muscle index (SMI) and psoas muscle index (PMI) thresholds. Univariate analysis was used to compare sarcopenic and non-sarcopenic patients. RESULTS: 148 patients met inclusion criteria. Using SMI thresholds, 95 patients (64%) were sarcopenic. With SMI criteria, sarcopenic patients were older (67 vs 52 years old; P < .01) and had lower BMIs (26.2 vs 34.0, respectively; P < .001) than non-sarcopenic patients. There were no differences in baseline characteristics, postoperative complications, and non-home discharge between groups (P > .05 for all). Postoperative length of stay was greater in sarcopenic patients (3 IQR 2-5 vs 2 IQR 2-3 days; P < .01). Using PMI thresholds, 68 (46%) met criteria for sarcopenia. Using PMI thresholds, sarcopenic patients were older (68 vs 57.5 years old; P < .01) and had lower BMIs (25.8 vs 32.8; P < .01). There were no differences in comorbidities or measured operative outcomes between groups (P > .05 for all), other than postoperative length of stay which was longer in the sarcopenic group (3.5 IQR 3-5 vs 2 IQR 2-3; P < .01). CONCLUSIONS: Incidence of sarcopenia was high in patients undergoing elective colectomy for diverticulitis in our practice, but sarcopenia was not associated with adverse perioperative outcomes. In select patients, elective colectomy for diverticulitis can be safely performed in the presence of sarcopenia.

Resolvin D2/GPR18 signaling enhances monocytic myeloid-derived suppressor cell function to mitigate abdominal aortic aneurysm formation.

Abdominal aortic aneurysm (AAA) formation is a chronic vascular pathology characterized by inflammation, leukocyte infiltration and vascular remodeling. The aim of this study was to delineate the protective role of Resolvin D2 (RvD2), a bioactive isoform of specialized proresolving lipid mediators, via G-protein coupled receptor 18 (GPR18) receptor signaling in attenuating AAAs. Importantly, RvD2 and GPR18 levels were significantly decreased in aortic tissue of AAA patients compared with controls. Furthermore, using an established murine model of AAA in C57BL/6 (WT) mice, we observed that treatment with RvD2 significantly attenuated aortic diameter, pro-inflammatory cytokine production, immune cell infiltration (neutrophils and macrophages), elastic fiber disruption and increased smooth muscle cell α-actin expression as well as increased TGF-ß2 and IL-10 expressions compared to untreated mice. Moreover, the RvD2-mediated protection from vascular remodeling and AAA formation was blocked when mice were previously treated with siRNA for GPR18 signifying the importance of RvD2/GPR18 signaling in vascular inflammation. Mechanistically, RvD2-mediated protection significantly enhanced infiltration and activation of monocytic myeloid-derived suppressor cells (M-MDSCs) by increasing TGF-ß2 and IL-10 secretions that mitigated smooth muscle cell activation in a GPR18-dependent manner to attenuate aortic inflammation and vascular remodeling via this intercellular crosstalk. Collectively, this study demonstrates RvD2 treatment induces an expansion of myeloid-lineage committed progenitors, such as M-MDSCs, and activates GPR18-dependent signaling to enhance TGF-ß2 and IL-10 secretion that contributes to resolution of aortic inflammation and remodeling during AAA formation.

Using a Clinical Data Warehouse to Calculate and Present Key Metrics for the Radiology Department: Implementation and Performance Evaluation.

BACKGROUND: Due to the importance of radiologic examinations, such as X-rays or computed tomography scans, for many clinical diagnoses, the optimal use of the radiology department is 1 of the primary goals of many hospitals. OBJECTIVE: This study aims to calculate the key metrics of this use by creating a radiology data warehouse solution, where data from radiology information systems (RISs) can be imported and then queried using a query language as well as a graphical user interface (GUI). METHODS: Using a simple configuration file, the developed system allowed for the processing of radiology data exported from any kind of RIS into a Microsoft Excel, comma-separated value (CSV), or JavaScript Object Notation (JSON) file. These data were then imported into a clinical data warehouse. Additional values based on the radiology data were calculated during this import process by implementing 1 of several provided interfaces. Afterward, the query language and GUI of the data warehouse were used to configure and calculate reports on these data. For the most common types of requested reports, a web interface was created to view their numbers as graphics. RESULTS: The tool was successfully tested with the data of 4 different German hospitals from 2018 to 2021, with a total of 1,436,111 examinations. The user feedback was good, since all their queries could be answered if the available data were sufficient. The initial processing of the radiology data for using them with the clinical data warehouse took (depending on the amount of data provided by each hospital) between 7 minutes and 1 hour 11 minutes. Calculating 3 reports of different complexities on the data of each hospital was possible in 1-3 seconds for reports with up to 200 individual calculations and in up to 1.5 minutes for reports with up to 8200 individual calculations. CONCLUSIONS: A system was developed with the main advantage of being generic concerning the export of different RISs as well as concerning the configuration of queries for various reports. The queries could be configured easily using the GUI of the data warehouse, and their results could be exported into the standard formats Excel and CSV for further processing.

Sex differences in outcomes of exercise therapy for patients with intermittent claudication: A scoping review.

Exercise therapy is first-line treatment for intermittent claudication due to peripheral artery disease. We sought to synthesize the literature on sex differences in response to exercise therapy for the treatment of intermittent claudication due to peripheral artery disease. A scoping review was performed (1997 to 2023) using Ovid MEDLINE, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Embase, SPORTDiscus, and Web of Science. Articles were included if they were a scientific report of any measures of health-related quality of life or walking performance after an intervention that included a structured walking program. Of the 13 studies, 11 included measures of walking distance; 7 included measures of walking time, 5 included measures of walking speed, and 4 included quality of life measures. Overall, exercise therapy resulted in significant improvements across most measures of walking performance for both men and females. When comparing magnitudes of outcome improvement by sex, results of walking-based measures were contradictory; some studies noted no difference and others found superior outcomes for men. Results of quality of life-based measures were also contradictory, with some finding no difference and others reporting substantially more improvement for females. Both men and females experienced considerable improvement in walking performance and quality of life with exercise therapy. Evidence regarding the differential effect of exercise therapy on outcomes by sex for intermittent claudication is limited and contradictory. Further efforts should be directed at using standardized interventions and metrics for measuring the outcomes that match the indications for intervention in these patients to better understand the expected benefits and any variance according to sex.

Methods and evaluation metrics for reducing material waste in the operating room: a scoping review.

BACKGROUND: Operating rooms contribute up to 70% of total hospital waste. Although multiple studies have demonstrated reduced waste through targeted interventions, few examine processes. This scoping review highlights methods of study design, outcome assessment, and sustainability practices of operating room waste reduction strategies employed by surgeons. METHODS: Embase, PubMed, and Web of Science were screened for operating room-specific waste-reduction interventions. Waste was defined as hazardous and non-hazardous disposable material and energy consumption. Study-specific elements were tabulated by study design, evaluation metrics, strengths, limitations, and barriers to implementation in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines. RESULTS: A total of 38 articles were analyzed. Among them, 74% of studies had pre- versus postintervention designs, and 21% used quality improvement instruments. No studies used an implementation framework. The vast majority (92%) of studies measured cost as an outcome, whereas others included disposable waste by weight, hospital energy consumption, and stakeholder perspectives. The most common intervention was instrument tray optimization. Common barriers to implementation included lack of stakeholder buy-in, knowledge gaps, data capture, additional staff time, need for hospital or federal policies, and funding. Intervention sustainability was discussed in few studies (23%) and included regular waste audits, hospital policy change, and educational initiatives. Common methodologic limitations included limited outcome evaluation, narrow scope of intervention, and inability to capture indirect costs. CONCLUSION: Appraisal of quality improvement and implementation methods are critical for developing sustainable interventions for reducing operating room waste. Universal evaluation metrics and methodologies may aid in both quantifying the impact of waste reduction initiatives and understanding their implementation in clinical practice.

Self-pay insurance status is associated with failure of medical therapy in patients with acute uncomplicated type B aortic dissection.

BACKGROUND: Traditionally, acute uncomplicated type B aortic dissections are managed medically, and acute complicated dissections are managed surgically. Self-pay patients with medically managed acute uncomplicated type B aortic dissections may fare worse than their insured counterparts. METHODS: In this single-center, retrospective cohort study, demographics, follow-up, and outcomes of patients with acute type B aortic dissections from 2011 to 2020 were analyzed. RESULTS: In total, 159 patients presented with acute type B aortic dissections; 102 were complicated and managed with thoracic endovascular aortic repair, and 57 were uncomplicated and managed medically. A total of 32% (n = 51) were self-pay. Self-pay patients were from areas with worse area deprivation indices (71% vs 63%, P = .024). They more often reported alcohol abuse (28% vs 7%, P < .001), cocaine/methamphetamine use (16% vs 5%, P = .028), and nonadherence to home antihypertensives (35% vs 11%, P < .001). Self-pay patients less often had a primary care physician (65% vs 7%, P < .001) or took antihypertensives before admission (31% vs 58%, P = .003). Self-pay patients frequently required financial assistance at discharge (63%), most often using charity funds (46%). Few patients (7%) qualified for our hospital's financial assistance program, and most (78%) remained uninsured at the first follow-up. Self-pay acute uncomplicated type B aortic dissections patients had the lowest rate of follow-up (31% vs 66%, P < .001) and were more likely to represent emergently (75% vs 0%, P = .033) compared to insured acute uncomplicated type B aortic dissections patients. Self-pay patients were more likely to follow up after thoracic endovascular aortic repair for acute complicated type B aortic dissections (82% vs 31%, P < .001). CONCLUSION: Self-pay patients have multiple, interconnected, complex socioeconomic factors that likely influence preadmission risk for dissection and post-discharge adherence to optimal medical management. Further research is needed to clarify treatment strategies in this high-risk group.

Calculating Key Figures for Radiology Departments Using a Clinical Data Warehouse - A Technical Case Report.

Optimizing the utilization of radiology departments is one of the primary objectives for many hospitals. To support this, a solution has been developed, which at first transforms the export of different Radiological Information Systems (RIS) into the data format of a clinical data warehouse (CDW). Additional features, like for example the time between the creation of a radiologic request and the finalization of the diagnosis for the created images, can then be defined using a simple interface and are calculated and saved in the CDW as well. Finally, the query language of the CDW can be used to create custom reports with all the RIS data including the calculated features and export them into the standard formats Excel and CSV. The solution has been successfully tested with data from two German hospitals.

Implementation of a HL7-CQL Engine Using the Graph Database Neo4J.

The Clinical Quality Language (CQL) is a useful tool for defining search requests for data stores containing FHIR data. Unfortunately, there are only few execution engines that are able to evaluate CQL queries. As FHIR data represents a graph structure, the authors pursue the approach of storing all data contained in a FHIR server in the graph database Neo4J and to translate CQL queries into Neo4J's query language Cypher. The query results returned by the graph database are retranslated into their FHIR representation and returned to the querying user. The approach has been positively tested on publicly available FHIR servers with a handcrafted set of example CQL queries.

Query Translation Between AQL and CQL.

Secondary use of electronic health records using data aggregation systems (DAS) with standardized access interfaces (e.g. openEHR, i2b2, FHIR) have become an attractive approach to support clinical research. In order to increase the volume of underlying patient data, multiple DASs at different institutions can be connected to research networks. Two obstacles to connect a DAS to such a network are the syntactical differences between the involved DAS query interfaces and differences in the data models the DASs operate on. The current work presents an approach to tackle both problems by translating queries from a DAS using openEHR's query language AQL (Archetype Query Language) into queries using the query language CQL (Clinical Quality Language) and vice versa. For the subset of queries which are expressible in both query languages the presented approach is well feasible.

Query Translation Between openEHR and i2b2.

Secondary use of electronic health records using data warehouses (DW) has become an attractive approach to support clinical research. In order to increase the volume of underlying patient data DWs at different institutions can be connected to research networks. Two obstacles to connect a DW to such a network are the syntactical differences between the involved DW technologies and differences in the data models of the connected DWs. The current work presents an approach to tackle both problems by translating queries from the DW system openEHR into queries from the DW system i2b2 and vice versa. For the subset of queries expressible in the query languages of both systems, the presented approach is well feasible.

Exploration of Artificial Intelligence Use with ARIES in Multiple Myeloma Research.

BACKGROUND: Natural language processing (NLP) is a powerful tool supporting the generation of Real-World Evidence (RWE). There is no NLP system that enables the extensive querying of parameters specific to multiple myeloma (MM) out of unstructured medical reports. We therefore created a MM-specific ontology to accelerate the information extraction (IE) out of unstructured text. METHODS: Our MM ontology consists of extensive MM-specific and hierarchically structured attributes and values. We implemented "A Rule-based Information Extraction System" (ARIES) that uses this ontology. We evaluated ARIES on 200 randomly selected medical reports of patients diagnosed with MM. RESULTS: Our system achieved a high F1-Score of 0.92 on the evaluation dataset with a precision of 0.87 and recall of 0.98. CONCLUSIONS: Our rule-based IE system enables the comprehensive querying of medical reports. The IE accelerates the extraction of data and enables clinicians to faster generate RWE on hematological issues. RWE helps clinicians to make decisions in an evidence-based manner. Our tool easily accelerates the integration of research evidence into everyday clinical practice.

Information Extraction from Echocardiography Reports for a Clinical Follow-up Study-Comparison of Extracted Variables Intended for General Use in a Data Warehouse with Those Intended Specifically for the Study.

BACKGROUND: The interest in information extraction from clinical reports for secondary data use is increasing. But experience with the productive use of information extraction processes over time is scarce. A clinical data warehouse has been in use at our university hospital for several years, which also provides an information extraction of echocardiography reports developed for general use. OBJECTIVES: This study aims to illustrate the difficulties encountered, while using data from a preexisting information extraction process for a large clinical study. To compare the data from the preexisting process with the data obtained from a specially developed process designed to improve the quality and completeness of the study data. METHODS: We extracted the echocardiography variables for 440 patients from the general-use information extraction of the data warehouse (678 reports). Then we developed an information extraction process for the same variables but specifically for this study, with the aim to extract as much information as possible from the text. The extracted data of both processes were compared with a newly created gold standard defined by a cardiologist with long-standing experience in heart failure. RESULTS: Among 57 echocardiography variables considered relevant for the study, 50 were documented in the routine text reports and could be extracted. Twenty of the required variables were not provided by the general-use extraction process, some others were not provided correctly. The median macro F1-score (precision, recall) across the 30 variables for which values were extracted was 0.81 (0.94, 0.77). Across all 50 variables, as relevant for the study, median macro F1-score was only 0.49 (0.56, 0.46). Employing the study-specific approach considerably improved the quality and completeness of the variables, resulting in F1-scores of 0.97 (0.98, 0.96) across all variables. CONCLUSION: Data from information extractions can be used for large clinical studies. However, preexisting information extraction processes should be treated with caution, as the time and effort spent defining each variable in the information extraction process may not be clear.

Exporting Data from a Clinical Data Warehouse.

Data Warehouses (DW) are useful tools to support clinical studies as they can provide exports of routine care data for scientific reuse. Exported DW data is usually post-processed and integrated into study databases by study staff that is reasonably trained in specific tools like SPSS and Excel but which are no programmers or computer scientists. DW systems should therefore be configurable to satisfy export format desiderata as much as possible so that exports contain no unnecessary post-processing obstacles. In the presented work the authors analyze various existing DW systems in respect to a list of potential export formats.

Ad Hoc Information Extraction for Clinical Data Warehouses.

BACKGROUND: Clinical Data Warehouses (CDW) reuse Electronic health records (EHR) to make their data retrievable for research purposes or patient recruitment for clinical trials. However, much information are hidden in unstructured data like discharge letters. They can be preprocessed and converted to structured data via information extraction (IE), which is unfortunately a laborious task and therefore usually not available for most of the text data in CDW. OBJECTIVES: The goal of our work is to provide an ad hoc IE service that allows users to query text data ad hoc in a manner similar to querying structured data in a CDW. While search engines just return text snippets, our systems also returns frequencies (e.g. how many patients exist with "heart failure" including textual synonyms or how many patients have an LVEF < 45) based on the content of discharge letters or textual reports for special investigations like heart echo. Three subtasks are addressed: (1) To recognize and to exclude negations and their scopes, (2) to extract concepts, i.e. Boolean values and (3) to extract numerical values. METHODS: We implemented an extended version of the NegEx-algorithm for German texts that detects negations and determines their scope. Furthermore, our document oriented CDW PaDaWaN was extended with query functions, e.g. context sensitive queries and regex queries, and an extraction mode for computing the frequencies for Boolean and numerical values. RESULTS: Evaluations in chest X-ray reports and in discharge letters showed high F1-scores for the three subtasks: Detection of negated concepts in chest X-ray reports with an F1-score of 0.99 and in discharge letters with 0.97; of Boolean values in chest X-ray reports about 0.99, and of numerical values in chest X-ray reports and discharge letters also around 0.99 with the exception of the concept age. DISCUSSION: The advantages of an ad hoc IE over a standard IE are the low development effort (just entering the concept with its variants), the promptness of the results and the adaptability by the user to his or her particular question. Disadvantage are usually lower accuracy and confidence.This ad hoc information extraction approach is novel and exceeds existing systems: Roogle [1] extracts predefined concepts from texts at preprocessing and makes them retrievable at runtime. Dr. Warehouse [2] applies negation detection and indexes the produced subtexts which include affirmed findings. Our approach combines negation detection and the extraction of concepts. But the extraction does not take place during preprocessing, but at runtime. That provides an ad hoc, dynamic, interactive and adjustable information extraction of random concepts and even their values on the fly at runtime. CONCLUSIONS: We developed an ad hoc information extraction query feature for Boolean and numerical values within a CDW with high recall and precision based on a pipeline that detects and removes negations and their scope in clinical texts.