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Item Anxiety Associated With Increased Risk for Emergency Department Recidivism in Patients With Low-Risk Chest Pain(Elsevier, 2018) Musey, Paul I., Jr.; Patel, Roma; Fry, Colin; Jimenez, Guadalupe; Koene, Rachael; Kline, Jeffrey A.; Emergency Medicine, School of MedicineAnxiety contributes to the chest pain symptom complex in 30% to 40% of patients with low-risk chest pain seen in the emergency department (ED). The validated Hospital Anxiety Depression Scale-Anxiety subscale (HADS-A) has been used as an anxiety screening tool in this population. The objective was to determine the prevalence of abnormal HADS-A scores in a cohort of low-risk chest pain patients and test the association of HADS-A score with subsequent healthcare utilization and symptom recurrence. In a single-center, prospective, observational cohort study of adult ED subjects with low-risk chest pain, the HADS-A was used to stratify participants into 2 groups: low anxiety (score <8) and high anxiety (score ≥8). At 45-day follow-up, chest pain recurrence was assessed by patient report, whereas ED utilization was assessed through chart review. Of the 167 subjects enrolled, 78 (47%) were stratified to high anxiety. The relative risk for high anxiety being associated with at least one 30-day ED return visit was 2.6 (95% confidence interval 1.4 to 4.7) and this relative risk increased to 9.1 (95% confidence interval 2.18 to 38.6) for 2 or more ED return visits. Occasional chest pain recurrence was reported by more subjects in the high anxiety group, 68% vs 47% (p = 0.029). In conclusion, 47% of low-risk chest pain cohort had abnormal levels of anxiety. These patients were more likely to have occasional recurrence of their chest pain and had an increased risk multiple ED return visits.Item Association between microbiome and the development of adverse posttraumatic neuropsychiatric sequelae after traumatic stress exposure(Springer Nature, 2023-11-18) Zeamer, Abigail L.; Salive, Marie-Claire; An, Xinming; Beaudoin, Francesca L.; House, Stacey L.; Stevens, Jennifer S.; Zeng, Donglin; Neylan, Thomas C.; Clifford, Gari D.; Linnstaedt, Sarah D.; Rauch, Scott L.; Storrow, Alan B.; Lewandowski, Christopher; Musey, Paul I., Jr.; Hendry, Phyllis L.; Sheikh, Sophia; Jones, Christopher W.; Punches, Brittany E.; Swor, Robert A.; Hudak, Lauren A.; Pascual, Jose L.; Seamon, Mark J.; Harris, Erica; Pearson, Claire; Peak, David A.; Merchant, Roland C.; Domeier, Robert M.; Rathlev, Niels K.; O’Neil, Brian J.; Sergot, Paulina; Sanchez, Leon D.; Bruce, Steven E.; Kessler, Ronald C.; Koenen, Karestan C.; McLean, Samuel A.; Bucci, Vanni; Haran, John P.; Emergency Medicine, School of MedicinePatients exposed to trauma often experience high rates of adverse post-traumatic neuropsychiatric sequelae (APNS). The biological mechanisms promoting APNS are currently unknown, but the microbiota-gut-brain axis offers an avenue to understanding mechanisms as well as possibilities for intervention. Microbiome composition after trauma exposure has been poorly examined regarding neuropsychiatric outcomes. We aimed to determine whether the gut microbiomes of trauma-exposed emergency department patients who develop APNS have dysfunctional gut microbiome profiles and discover potential associated mechanisms. We performed metagenomic analysis on stool samples (n = 51) from a subset of adults enrolled in the Advancing Understanding of RecOvery afteR traumA (AURORA) study. Two-, eight- and twelve-week post-trauma outcomes for post-traumatic stress disorder (PTSD) (PTSD checklist for DSM-5), normalized depression scores (PROMIS Depression Short Form 8b) and somatic symptom counts were collected. Generalized linear models were created for each outcome using microbial abundances and relevant demographics. Mixed-effect random forest machine learning models were used to identify associations between APNS outcomes and microbial features and encoded metabolic pathways from stool metagenomics. Microbial species, including Flavonifractor plautii, Ruminococcus gnavus and, Bifidobacterium species, which are prevalent commensal gut microbes, were found to be important in predicting worse APNS outcomes from microbial abundance data. Notably, through APNS outcome modeling using microbial metabolic pathways, worse APNS outcomes were highly predicted by decreased L-arginine related pathway genes and increased citrulline and ornithine pathways. Common commensal microbial species are enriched in individuals who develop APNS. More notably, we identified a biological mechanism through which the gut microbiome reduces global arginine bioavailability, a metabolic change that has also been demonstrated in the plasma of patients with PTSD.Item Brain-Based Biotypes of Psychiatric Vulnerability in the Acute Aftermath of Trauma(American Psychiatric Association, 2021) Stevens, Jennifer S.; Harnett, Nathaniel G.; Lebois, Lauren A.M.; van Rooij, Sanne J.H.; Ely, Timothy D.; Roeckner, Alyssa; Vincent, Nico; Beaudoin, Francesca L.; An, Xinming; Zeng, Donglin; Neylan, Thomas C.; Clifford, Gari D.; Linnstaedt, Sarah D.; Germine, Laura T.; Rauch, Scott L.; Lewandowski, Christopher; Storrow, Alan B.; Hendry, Phyllis L.; Sheikh, Sophia; Musey, Paul I., Jr.; Haran, John P.; Jones, Christopher W.; Punches, Brittany E.; Lyons, Michael S.; Kurz, Michael C.; McGrath, Meghan E.; Pascual, Jose L.; Datner, Elizabeth M.; Chang, Anna M.; Pearson, Claire; Peak, David A.; Domeier, Robert M.; O'Neil, Brian J.; Rathlev, Niels K.; Sanchez, Leon D.; Pietrzak, Robert H.; Joormann, Jutta; Barch, Deanna M.; Pizzagalli, Diego A.; Sheridan, John F.; Luna, Beatriz; Harte, Steven E.; Elliott, James M.; Murty, Vishnu P.; Jovanovic, Tanja; Bruce, Steven E.; House, Stacey L.; Kessler, Ronald C.; Koenen, Karestan C.; McLean, Samuel A.; Ressler, Kerry J.; Emergency Medicine, School of MedicineObjective: Major negative life events, such as trauma exposure, can play a key role in igniting or exacerbating psychopathology. However, few disorders are diagnosed with respect to precipitating events, and the role of these events in the unfolding of new psychopathology is not well understood. The authors conducted a multisite transdiagnostic longitudinal study of trauma exposure and related mental health outcomes to identify neurobiological predictors of risk, resilience, and different symptom presentations. Methods: A total of 146 participants (discovery cohort: N=69; internal replication cohort: N=77) were recruited from emergency departments within 72 hours of a trauma and followed for the next 6 months with a survey, MRI, and physiological assessments. Results: Task-based functional MRI 2 weeks after a motor vehicle collision identified four clusters of individuals based on profiles of neural activity reflecting threat reactivity, reward reactivity, and inhibitory engagement. Three clusters were replicated in an independent sample with a variety of trauma types. The clusters showed different longitudinal patterns of posttrauma symptoms. Conclusions: These findings provide a novel characterization of heterogeneous stress responses shortly after trauma exposure, identifying potential neuroimaging-based biotypes of trauma resilience and psychopathology.Item Characteristics of COVID-19 Patients with Bacterial Co-infection Admitted to the Hospital from the Emergency Department in a Large Regional Healthcare System(Wiley, 2021) Lardaro, Thomas; Wang, Alfred Z.; Bucca, Antonino; Croft, Alexander; Glober, Nancy; Holt, Daniel B.; Musey, Paul I., Jr.; Peterson, Kelli D.; Trigonis, Russell A.; Hunter, Benton R.; Emergency Medicine, School of MedicineIntroduction The rate of bacterial coinfection with SARS‐CoV‐2 is poorly defined. The decision to administer antibiotics early in the course of SARS‐CoV‐2 infection depends on the likelihood of bacterial coinfection. Methods We performed a retrospective chart review of all patients admitted through the emergency department with confirmed SARS‐CoV‐2 infection over a 6‐week period in a large healthcare system in the United States. Blood and respiratory culture results were abstracted and adjudicated by multiple authors. The primary outcome was the rate of bacteremia. We secondarily looked to define clinical or laboratory features associated with bacteremia. Results There were 542 patients admitted with confirmed SARS‐CoV‐2 infection, with an average age of 62.8 years. Of these, 395 had blood cultures performed upon admission, with six true positive results (1.1% of the total population). An additional 14 patients had positive respiratory cultures treated as true pathogens in the first 72 h. Low blood pressure and elevated white blood cell count, neutrophil count, blood urea nitrogen, and lactate were statistically significantly associated with bacteremia. Clinical outcomes were not statistically significantly different between patients with and without bacteremia. Conclusions We found a low rate of bacteremia in patients admitted with confirmed SARS‐CoV‐2 infection. In hemodynamically stable patients, routine antibiotics may not be warranted in this population.Item Classification and Prediction of Post-Trauma Outcomes Related to PTSD Using Circadian Rhythm Changes Measured via Wrist-Worn Research Watch in a Large Longitudinal Cohort(IEEE, 2021) Cakmak, Ayse S.; Perez Alday, Erick A.; Da Poian, Giulia; Rad, Ali Bahrami; Metzler, Thomas J.; Neylan, Thomas C.; House, Stacey L.; Beaudoin, Francesca L.; An, Xinming; Stevens, Jennifer S.; Zeng, Donglin; Linnstaedt, Sarah D.; Jovanovic, Tanja; Germine, Laura T.; Bollen, Kenneth A.; Rauch, Scott L.; Lewandowski, Christopher A.; Hendry, Phyllis L.; Sheikh, Sophia; Storrow, Alan B.; Musey, Paul I., Jr.; Haran, John P.; Jones, Christopher W.; Punches, Brittany E.; Swor, Robert A.; Gentile, Nina T.; McGrath, Meghan E.; Seamon, Mark J.; Mohiuddin, Kamran; Chang, Anna M.; Pearson, Claire; Domeier, Robert M.; Bruce, Steven E.; O’Neil, Brian J.; Rathlev, Niels K.; Sanchez, Leon D.; Pietrzak, Robert H.; Joormann, Jutta; Barch, Deanna M.; Pizzagalli, Diego A.; Harte, Steven E.; Elliott, James M.; Kessler, Ronald C.; Koenen, Karestan C.; Ressler, Kerry J.; Mclean, Samuel A.; Li, Qiao; Clifford, Gari D.; Emergency Medicine, School of MedicinePost-Traumatic Stress Disorder (PTSD) is a psychiatric condition resulting from threatening or horrifying events. We hypothesized that circadian rhythm changes, measured by a wrist-worn research watch are predictive of post-trauma outcomes. Approach: 1618 post-trauma patients were enrolled after admission to emergency departments (ED). Three standardized questionnaires were administered at week eight to measure post-trauma outcomes related to PTSD, sleep disturbance, and pain interference with daily life. Pulse activity and movement data were captured from a research watch for eight weeks. Standard and novel movement and cardiovascular metrics that reflect circadian rhythms were derived using this data. These features were used to train different classifiers to predict the three outcomes derived from week-eight surveys. Clinical surveys administered at ED were also used as features in the baseline models. Results: The highest cross-validated performance of research watch-based features was achieved for classifying participants with pain interference by a logistic regression model, with an area under the receiver operating characteristic curve (AUC) of 0.70. The ED survey-based model achieved an AUC of 0.77, and the fusion of research watch and ED survey metrics improved the AUC to 0.79. Significance: This work represents the first attempt to predict and classify post-trauma symptoms from passive wearable data using machine learning approaches that leverage the circadian desynchrony in a potential PTSD population.Item Derivation and Validation of a Brief Emergency Department-Based Prediction Tool for Posttraumatic Stress After Motor Vehicle Collision(Elsevier, 2023) Jones, Christopher W.; An, Xinming; Ji, Yinyao; Liu, Mochuan; Zeng, Donglin; House, Stacey L.; Beaudoin, Francesca L.; Stevens, Jennifer S.; Neylan, Thomas C.; Clifford, Gari D.; Jovanovic, Tanja; Linnstaedt, Sarah D.; Germine, Laura T.; Bollen, Kenneth A.; Rauch, Scott L.; Haran, John P.; Storrow, Alan B.; Lewandowski, Christopher; Musey, Paul I., Jr.; Hendry, Phyllis L.; Sheikh, Sophia; Punches, Brittany E.; Lyons, Michael S.; Kurz, Michael C.; Swor, Robert A.; McGrath, Meghan E.; Hudak, Lauren A.; Pascual, Jose L.; Seamon, Mark J.; Datner, Elizabeth M.; Harris, Erica; Chang, Anna M.; Pearson, Claire; Peak, David A.; Merchant, Roland C.; Domeier, Robert M.; Rathlev, Niels K.; O'Neil, Brian J.; Sergot, Paulina; Sanchez, Leon D.; Bruce, Steven E.; Miller, Mark W.; Pietrzak, Robert H.; Joormann, Jutta; Barch, Deanna M.; Pizzagalli, Diego A.; Sheridan, John F.; Smoller, Jordan W.; Harte, Steven E.; Elliott, James M.; Koenen, Karestan C.; Ressler, Kerry J.; Kessler, Ronald C.; McLean, Samuel A.; Emergency Medicine, School of MedicineStudy objective: To derive and initially validate a brief bedside clinical decision support tool that identifies emergency department (ED) patients at high risk of substantial, persistent posttraumatic stress symptoms after a motor vehicle collision. Methods: Derivation (n=1,282, 19 ED sites) and validation (n=282, 11 separate ED sites) data were obtained from adults prospectively enrolled in the Advancing Understanding of RecOvery afteR traumA study who were discharged from the ED after motor vehicle collision-related trauma. The primary outcome was substantial posttraumatic stress symptoms at 3 months (Posttraumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders-5 ≥38). Logistic regression derivation models were evaluated for discriminative ability using the area under the curve and the accuracy of predicted risk probabilities (Brier score). Candidate posttraumatic stress predictors assessed in these models (n=265) spanned a range of sociodemographic, baseline health, peritraumatic, and mechanistic domains. The final model selection was based on performance and ease of administration. Results: Significant 3-month posttraumatic stress symptoms were common in the derivation (27%) and validation (26%) cohort. The area under the curve and Brier score of the final 8-question tool were 0.82 and 0.14 in the derivation cohort and 0.76 and 0.17 in the validation cohort. Conclusion: This simple 8-question tool demonstrates promise to risk-stratify individuals with substantial posttraumatic stress symptoms who are discharged to home after a motor vehicle collision. Both external validation of this instrument, and work to further develop more accurate tools, are needed. Such tools might benefit public health by enabling the conduct of preventive intervention trials and assisting the growing number of EDs that provide services to trauma survivors aimed at promoting psychological recovery.Item Development and Validation of a Model to Predict Posttraumatic Stress Disorder and Major Depression After a Motor Vehicle Collision(American Medical Association, 2021) Ziobrowski, Hannah N.; Kennedy, Chris J.; Ustun, Berk; House, Stacey L.; Beaudoin, Francesca L.; An, Xinming; Zeng, Donglin; Bollen, Kenneth A.; Petukhova, Maria; Sampson, Nancy A.; Puac-Polanco, Victor; Lee, Sue; Koenen, Karestan C.; Ressler, Kerry J.; McLean, Samuel A.; Kessler, Ronald C.; AURORA Consortium; Stevens, Jennifer S.; Neylan, Thomas C.; Clifford, Gari D.; Jovanovic, Tanja; Linnstaedt, Sarah D.; Germine, Laura T.; Rauch, Scott L.; Haran, John P.; Storrow, Alan B.; Lewandowski, Christopher; Musey, Paul I., Jr.; Hendry, Phyllis L.; Sheikh, Sophia; Jones, Christopher W.; Punches, Brittany E.; Lyons, Michael S.; Murty, Vishnu P.; McGrath, Meghan E.; Pascual, Jose L.; Seamon, Mark J.; Datner, Elizabeth M.; Chang, Anna M.; Pearson, Claire; Peak, David A.; Jambaulikar, Guruprasad; Merchant, Roland C.; Domeier, Robert M.; Rathlev, Niels K.; O'Neil, Brian J.; Sergot, Paulina; Sanchez, Leon D.; Bruce, Steven E.; Pietrzak, Robert H.; Joormann, Jutta; Barch, Deanna M.; Pizzagalli, Diego A.; Sheridan, John F.; Harte, Steven E.; Elliott, James M.; van Rooij, Sanne J.H.; Emergency Medicine, School of MedicineImportance: A substantial proportion of the 40 million people in the US who present to emergency departments (EDs) each year after traumatic events develop posttraumatic stress disorder (PTSD) or major depressive episode (MDE). Accurately identifying patients at high risk in the ED would facilitate the targeting of preventive interventions. Objectives: To develop and validate a prediction tool based on ED reports after a motor vehicle collision to predict PTSD or MDE 3 months later. Design, setting, and participants: The Advancing Understanding of Recovery After Trauma (AURORA) study is a longitudinal study that examined adverse posttraumatic neuropsychiatric sequalae among patients who presented to 28 US urban EDs in the immediate aftermath of a traumatic experience. Enrollment began on September 25, 2017. The 1003 patients considered in this diagnostic/prognostic report completed 3-month assessments by January 31, 2020. Each patient received a baseline ED assessment along with follow-up self-report surveys 2 weeks, 8 weeks, and 3 months later. An ensemble machine learning method was used to predict 3-month PTSD or MDE from baseline information. Data analysis was performed from November 1, 2020, to May 31, 2021. Main outcomes and measures: The PTSD Checklist for DSM-5 was used to assess PTSD and the Patient Reported Outcomes Measurement Information System Depression Short-Form 8b to assess MDE. Results: A total of 1003 patients (median [interquartile range] age, 34.5 [24-43] years; 715 [weighted 67.9%] female; 100 [weighted 10.7%] Hispanic, 537 [weighted 52.7%] non-Hispanic Black, 324 [weighted 32.2%] non-Hispanic White, and 42 [weighted 4.4%] of non-Hispanic other race or ethnicity were included in this study. A total of 274 patients (weighted 26.6%) met criteria for 3-month PTSD or MDE. An ensemble machine learning model restricted to 30 predictors estimated in a training sample (patients from the Northeast or Midwest) had good prediction accuracy (mean [SE] area under the curve [AUC], 0.815 [0.031]) and calibration (mean [SE] integrated calibration index, 0.040 [0.002]; mean [SE] expected calibration error, 0.039 [0.002]) in an independent test sample (patients from the South). Patients in the top 30% of predicted risk accounted for 65% of all 3-month PTSD or MDE, with a mean (SE) positive predictive value of 58.2% (6.4%) among these patients at high risk. The model had good consistency across regions of the country in terms of both AUC (mean [SE], 0.789 [0.025] using the Northeast as the test sample and 0.809 [0.023] using the Midwest as the test sample) and calibration (mean [SE] integrated calibration index, 0.048 [0.003] using the Northeast as the test sample and 0.024 [0.001] using the Midwest as the test sample; mean [SE] expected calibration error, 0.034 [0.003] using the Northeast as the test sample and 0.025 [0.001] using the Midwest as the test sample). The most important predictors in terms of Shapley Additive Explanations values were symptoms of anxiety sensitivity and depressive disposition, psychological distress in the 30 days before motor vehicle collision, and peritraumatic psychosomatic symptoms. Conclusions and relevance: The results of this study suggest that a short set of questions feasible to administer in an ED can predict 3-month PTSD or MDE with good AUC, calibration, and geographic consistency. Patients at high risk can be identified in the ED for targeting if cost-effective preventive interventions are developed.Item Editorial: A Closer Examination of the Racial Discrepancies in ED Cardiac Care(Wiley, 2023-10) Anokwute, Chiamara C.; Musey, Paul I., Jr.; Emergency Medicine, School of MedicineItem Efficacy of Benzodiazepines or Antihistamines for Patients With Acute Vertigo: A Systematic Review and Meta-analysis(American Medical Association, 2022) Hunter, Benton R.; Wang, Alfred Z.; Bucca, Antonino W.; Musey, Paul I., Jr.; Strachan, Christian C.; Roumpf, Steven K.; Propst, Steven L.; Croft, Alexander; Menard, Laura M.; Kirschner, Jonathan M.; Emergency Medicine, School of MedicineImportance: Acute vertigo can be disabling. Antihistamines and benzodiazepines are frequently prescribed as "vestibular suppressants," but their efficacy is unclear. Objective: To assess the efficacy of antihistamines and benzodiazepines in the treatment of acute vertigo from any underlying cause. Data sources: We searched the PubMed, CENTRAL, EMBASE, CINAHL, Scopus, and ClinicalTrials.gov databases from inception to January 14, 2019, without language restrictions. Bibliographies of the included studies and relevant reviews were also screened. Study selection: We included randomized clinical trials (RCTs) comparing antihistamine or benzodiazepine use with another comparator, placebo, or no intervention for patients with a duration of acute vertigo for 2 weeks or less. Studies of healthy volunteers, prophylactic treatment, or induced vertigo were excluded, as were studies that compared 2 medications from the same class. Data extraction and synthesis: Following Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, data were extracted and risk of bias was assessed by 2 authors independently for each study. Data were pooled using a random-effects model. Main outcomes and measures: The predefined primary outcome was change in 10- or 100-point vertigo or dizziness visual analog scale (VAS) scores at 2 hours after treatment. Secondary outcomes included change in nausea VAS scores at 2 hours, use of rescue medication at 2 hours, and improvement or resolution of vertigo at 1 week or 1 month. Results: Of the 27 trials identified in the systematic review, 17 contributed to the quantitative meta-analysis and involved a total of 1586 participants. Seven trials with a total of 802 participants evaluated the primary outcome of interest: single-dose antihistamines resulted in significantly more improvement on 100-point VAS scores compared with benzodiazepines (difference, 16.1 [95% CI, 7.2 to 25.0]) but not compared with other active comparators (difference, 2.7 [95% CI, -6.1 to 11.5]). At 1 week and 1 month, neither daily benzodiazepines nor antihistamines were reported to be superior to placebo. RCTs comparing the immediate effects of medications (at 2 hours) after a single dose generally had a low risk of bias, but those evaluating 1-week and 1-month outcomes had a high risk of bias. Conclusions and relevance: Moderately strong evidence suggests that single-dose antihistamines provide greater vertigo relief at 2 hours than single-dose benzodiazepines. Furthermore, the available evidence did not support an association of benzodiazepine use with improvement in any outcomes for acute vertigo. Other evidence suggested that daily antihistamine use may not benefit patients with acute vertigo. Larger randomized trials comparing both antihistamines and benzodiazepines with placebo could better clarify the relative efficacy of these medications.Item Emergency Department Cardiopulmonary Evaluation of Low-Risk Chest Pain Patients with Self-Reported Stress and Anxiety(Elsevier, 2017-03) Musey, Paul I., Jr.; Kline, Jeffrey A.; Department of Emergency Medicine, School of MedicineBackground Chest pain is a high-risk emergency department (ED) chief complaint; the majority of clinical resources are directed toward detecting and treating cardiopulmonary emergencies. However, at follow-up, 80%–95% of these patients have only a symptom-based diagnosis; a large number have undiagnosed anxiety disorders. Objective Our aim was to measure the frequency of self-identified stress or anxiety among chest pain patients, and compare their pretest probabilities, care processes, and outcomes. Methods Patients were divided into two groups: explicitly self-reported anxiety and stress or not at 90-day follow-up, then compared on several variables: ultralow (<2.5%) pretest probability, outcome rates for acute coronary syndrome (ACS) and pulmonary embolism (PE), radiation exposure, total costs at 30 days, and 90-day recidivism. Results Eight hundred and forty-five patients were studied. Sixty-seven (8%) explicitly attributed their chest pain to “stress” or “anxiety”; their mean ACS pretest probability was 4% (95% confidence interval 2.9%–5.7%) and 49% (33/67) had ultralow pretest probability (0/33 with ACS or PE). None (0/67) were diagnosed with anxiety. Seven hundred and seventy-eight did not report stress or anxiety and, of these, 52% (403/778) had ultralow ACS pretest probability. Only one patient (0.2%; 1/403) was diagnosed with ACS and one patient (0.4%; 1/268) was diagnosed with PE. Patients with self-reported anxiety had similar radiation exposure, associated costs, and nearly identical (25.4% vs. 25.7%) ED recidivism to patients without reported anxiety. Conclusions Without prompting, 8% of patients self-identified “stress” or “anxiety” as the etiology for their chest pain. Most had low pretest probability, were over-investigated for ACS and PE, and not investigated for anxiety syndromes.
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