Publications by authors named "Rickey E Carter"

273 Publications

A Pilot Study to Estimate the Impact of High Matrix Image Reconstruction on Chest Computed Tomography.

J Clin Imaging Sci 2021 30;11:52. Epub 2021 Sep 30.

Department of Radiology, Mayo Clinic, Rochester, Minnesota, United States.

Objectives: The objectives of the study were to estimate the impact of high matrix image reconstruction on chest computed tomography (CT) compared to standard image reconstruction.

Material And Methods: This retrospective study included patients with interstitial or parenchymal lung disease, airway disease, and pulmonary nodules who underwent chest CT. Chest CT images were reconstructed using high matrix (1024 × 1024) or standard matrix (512 × 512), with all other parameters matched. Two radiologists, blinded to reconstruction technique, independently examined each lung, viewing image sets side by side and rating the conspicuity of imaging findings using a 5-point relative conspicuity scale. The presence of pulmonary nodules and confidence in classification of internal attenuation was also graded. Overall image quality and subjective noise/artifacts were assessed.

Results: Thirty-four patients with 68 lungs were evaluated. Relative conspicuity scores were significantly higher using high matrix image reconstruction for all imaging findings indicative of idiopathic lung fibrosis (peripheral airway visualization, interlobular septal thickening, intralobular reticular opacity, and end-stage fibrotic change; ≤ 0.001) along with emphysema, mosaic attenuation, and fourth order bronchi for both readers ( ≤ 0.001). High matrix reconstruction did not improve confidence in the presence or classification of internal nodule attenuation for either reader. Overall image quality was increased but not subjective noise/artifacts with high matrix image reconstruction for both readers ( < 0.001).

Conclusion: High matrix image reconstruction significantly improves the conspicuity of imaging findings reflecting interstitial lung disease and may be useful for diagnosis or treatment response assessment.
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http://dx.doi.org/10.25259/JCIS_143_2021DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8492437PMC
September 2021

Mortality in individuals treated with COVID-19 convalescent plasma varies with the geographic provenance of donors.

Nat Commun 2021 08 11;12(1):4864. Epub 2021 Aug 11.

Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA.

Successful therapeutics and vaccines for coronavirus disease 2019 (COVID-19) have harnessed the immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Evidence that SARS-CoV-2 exists as locally evolving variants suggests that immunological differences may impact the effectiveness of antibody-based treatments such as convalescent plasma and vaccines. Considering that near-sourced convalescent plasma likely reflects the antigenic composition of local viral strains, we hypothesize that convalescent plasma has a higher efficacy, as defined by death within 30 days of transfusion, when the convalescent plasma donor and treated patient were in close geographic proximity. Results of a series of modeling techniques applied to approximately 28,000 patients from the Expanded Access to Convalescent Plasma program (ClinicalTrials.gov number: NCT04338360) support this hypothesis. This work has implications for the interpretation of clinical studies, the ability to develop effective COVID-19 treatments, and, potentially, for the effectiveness of COVID-19 vaccines as additional locally-evolving variants continue to emerge.
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http://dx.doi.org/10.1038/s41467-021-25113-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8357797PMC
August 2021

In Reply-How Safe Is COVID-19 Convalescent Plasma?

Mayo Clin Proc 2021 08 25;96(8):2281-2282. Epub 2021 Jun 25.

Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL.

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http://dx.doi.org/10.1016/j.mayocp.2021.06.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8226061PMC
August 2021

Rapid Exclusion of COVID Infection With the Artificial Intelligence Electrocardiogram.

Mayo Clin Proc 2021 08;96(8):2081-2094

Department of Cardiovascular Medicine, The University of Kansas Health System, Kansas City, KS.

Objective: To rapidly exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using artificial intelligence applied to the electrocardiogram (ECG).

Methods: A global, volunteer consortium from 4 continents identified patients with ECGs obtained around the time of polymerase chain reaction-confirmed COVID-19 diagnosis and age- and sex-matched controls from the same sites. Clinical characteristics, polymerase chain reaction results, and raw electrocardiographic data were collected. A convolutional neural network was trained using 26,153 ECGs (33.2% COVID positive), validated with 3826 ECGs (33.3% positive), and tested on 7870 ECGs not included in other sets (32.7% positive). Performance under different prevalence values was tested by adding control ECGs from a single high-volume site.

Results: The area under the curve for detection of acute COVID-19 infection in the test group was 0.767 (95% CI, 0.756 to 0.778; sensitivity, 98%; specificity, 10%; positive predictive value, 37%; negative predictive value, 91%). To more accurately reflect a real-world population, 50,905 normal controls were added to adjust the COVID prevalence to approximately 5% (2657/58,555), resulting in an area under the curve of 0.780 (95% CI, 0.771 to 0.790) with a specificity of 12.1% and a negative predictive value of 99.2%.

Conclusion: Infection with SARS-CoV-2 results in electrocardiographic changes that permit the artificial intelligence-enhanced ECG to be used as a rapid screening test with a high negative predictive value (99.2%). This may permit the development of electrocardiography-based tools to rapidly screen individuals for pandemic control.
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http://dx.doi.org/10.1016/j.mayocp.2021.05.027DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8327278PMC
August 2021

Directed stimulation of the dentato-rubro-thalamic tract for deep brain stimulation in essential tremor: a blinded clinical trial.

Neuroradiol J 2021 Aug 2:19714009211036689. Epub 2021 Aug 2.

Department of Neurosurgery, Mayo Clinic, USA.

Objective: Observational studies utilising diffusion tractography have suggested a common mechanism for tremor alleviation in deep brain stimulation for essential tremor: the decussating portion of the dentato-rubro-thalamic tract. We hypothesised that directional stimulation of the dentato-rubro-thalamic tract would result in greater tremor improvement compared to sham programming, as well as comparable improvement as more tedious standard-of-care programming.

Methods: A prospective, blinded crossover trial was performed to assess the feasibility, safety and outcomes of programming based solely on dentato-rubro-thalamic tract anatomy. Using magnetic resonance imaging diffusion-tractography, the dentato-rubro-thalamic tract was identified and a connectivity-based treatment setting was derived by modelling a volume of tissue activated using directional current steering oriented towards the dentato-rubro-thalamic tract centre. A sham setting was created at approximately 180° opposite the connectivity-based treatment. Standard-of-care programming at 3 months was compared to connectivity-based treatment and sham settings that were blinded to the programmer. The primary outcome measure was percentage improvement in the Fahn-Tolosa-Marín tremor rating score compared to the preoperative baseline.

Results: Among the six patients, tremor rating scores differed significantly among the three experimental conditions (=0.030). The mean tremor rating score improvement was greater with the connectivity-based treatment settings (64.6% ± 14.3%) than with sham (44.8% ± 18.6%; =0.031) and standard-of-care programming (50.7% ± 19.2%; =0.062). The distance between the centre of the dentato-rubro-thalamic tract and the volume of tissue activated inversely correlated with the percentage improvement in the tremor rating score (R=0.24; =0.04). No significant adverse events were encountered.

Conclusions: Using a blinded, crossover trial design, we have shown the technical feasibility, safety and potential efficacy of connectivity-based stimulation settings in deep brain stimulation for treatment of essential tremor.
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http://dx.doi.org/10.1177/19714009211036689DOI Listing
August 2021

European Heart Journal quality standards.

Eur Heart J 2021 07;42(28):2729-2736

Department of Cardiovascular Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.

The aim of the European Heart Journal (EHJ) is to attract innovative, methodologically sound, and clinically relevant research manuscripts able to change clinical practice and/or substantially advance knowledge on cardiovascular diseases. As the reference journal in cardiovascular medicine, the EHJ is committed to publishing only the best cardiovascular science adhering to the highest ethical principles. EHJ uses highly rigorous peer-review, critical statistical review and the highest quality editorial process, to ensure the novelty, accuracy, quality, and relevance of all accepted manuscripts with the aim of inspiring the clinical practice of EHJ readers and reducing the global burden of cardiovascular diseases. This review article summarizes the quality standards pursued by the EHJ to fulfill its mission.
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http://dx.doi.org/10.1093/eurheartj/ehab324DOI Listing
July 2021

NIH funding trends for neurosurgeon-scientists from 1993-2017: Biomedical workforce implications for neurooncology.

J Neurooncol 2021 Aug 7;154(1):51-62. Epub 2021 Jul 7.

Department of Neurosurgery, Mayo Clinic, Jacksonville, FL, USA.

Introduction: Neurosurgeons represent 0.5% of all physicians and currently face a high burden of disease. Physician-scientists are essential to advance the mission of National Academies of Science (NAS) and National Institutes of Health (NIH) through discovery and bench to bedside translation. We investigated trends in NIH neurosurgeon-scientist funding over time as an indicator of physician-scientist workforce training.

Methods: We used NIH Research Portfolio Online Reporting Tools (RePORTER) to extract grants to neurosurgery departments and neurosurgeons from 1993 to 2017. Manual extraction of each individual grant awardee was conducted.

Results: After adjusting for U.S. inflation (base year: 1993), NIH funding to neurosurgery departments increased yearly (P < 0.00001). However, neurosurgeon-scientists received significantly less NIH funding compared to scientists (including basic scientists and research only neurosurgeons) (P = 0.09). The ratio of neurosurgeon-scientists to scientists receiving grants was significantly reduced (P = 0.002). Interestingly, the percentage of oncology-related neurosurgery grants significantly increased throughout the study period (P = 0.002). The average number of grants per neurosurgeon-scientists showed an upward trend (P < 0.001); however, the average number of grants for early-career neurosurgeon-scientists, showed a significant downward trend (P = 0.05).

Conclusion: Over the past 23 years, despite the overall increasing trends in the number of NIH grants awarded to neurosurgery departments overall, the proportion of neurosurgeon-scientists that were awarded NIH grants compared to scientists demonstrates a declining trend. This observed shift is disproportionate in the number of NIH grants awarded to senior level compared to early-career neurosurgeon-scientists, with more funding allocated towards neurosurgical-oncology-related grants.
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http://dx.doi.org/10.1007/s11060-021-03797-5DOI Listing
August 2021

Quantifying the Importance of COVID-19 Vaccination to Our Future Outlook.

Mayo Clin Proc 2021 07 27;96(7):1890-1895. Epub 2021 Apr 27.

Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN.

Predictive models have played a critical role in local, national, and international response to the COVID-19 pandemic. In the United States, health care systems and governmental agencies have relied on several models, such as the Institute for Health Metrics and Evaluation, Youyang Gu (YYG), Massachusetts Institute of Technology, and Centers for Disease Control and Prevention ensemble, to predict short- and long-term trends in disease activity. The Mayo Clinic Bayesian SIR model, recently made publicly available, has informed Mayo Clinic practice leadership at all sites across the United States and has been shared with Minnesota governmental leadership to help inform critical decisions during the past year. One key to the accuracy of the Mayo Clinic model is its ability to adapt to the constantly changing dynamics of the pandemic and uncertainties of human behavior, such as changes in the rate of contact among the population over time and by geographic location and now new virus variants. The Mayo Clinic model can also be used to forecast COVID-19 trends in different hypothetical worlds in which no vaccine is available, vaccinations are no longer being accepted from this point forward, and 75% of the population is already vaccinated. Surveys indicate that half of American adults are hesitant to receive a COVID-19 vaccine, and lack of understanding of the benefits of vaccination is an important barrier to use. The focus of this paper is to illustrate the stark contrast between these 3 scenarios and to demonstrate, mathematically, the benefit of high vaccine uptake on the future course of the pandemic.
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http://dx.doi.org/10.1016/j.mayocp.2021.04.012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8075811PMC
July 2021

SARS-CoV-2 Serologic Assays Dependent on Dual-Antigen Binding Demonstrate Diverging Kinetics Relative to Other Antibody Detection Methods.

J Clin Microbiol 2021 08 18;59(9):e0123121. Epub 2021 Aug 18.

Department of Laboratory Medicine and Pathology, Mayo Clinicgrid.66875.3a, Rochester, Minnesota, USA.

Longitudinal studies assessing durability of the anti-severe acute respiratory syndrome coronavirus 2 (anti-SARS-CoV-2) humoral immune response have generated conflicting results. This has been proposed to be due to differences in patient populations, the lack of standardized methodologies, and the use of assays that measure distinct aspects of the humoral response. SARS-CoV-2 antibodies were serially measured in sera from a cohort of 44 well-characterized convalescent plasma donors over 120 days post-COVID-19 symptom onset, utilizing eight assays, which varied according to antigen source, the detected antibody isotype, and the activity measured (i.e., binding, blocking, or neutralizing). While the majority of assays demonstrated a gradual decline in antibody titers over the course of 120 days, the two electrochemiluminescence immunoassay Roche assays (Roche Diagnostics Elecsys anti-SARS-CoV-2 [qualitative, nucleocapsid based] and Roche Diagnostics Elecsys anti-SARS-CoV-2 S [semiquantitative, spike based]), which utilize dual-antigen binding for antibody detection, demonstrated stable and/or increasing antibody titers over the study period. This study is among the first to assess longitudinal, rather than cross-sectional, SARS-CoV-2 antibody profiles among convalescent COVID-19 patients, primarily using commercially available serologic assays with Food and Drug Administration emergency use authorization. We show that SARS-CoV-2 antibody detection is dependent on the serologic method used, which has implications for future assay utilization and clinical value.
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http://dx.doi.org/10.1128/JCM.01231-21DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8373029PMC
August 2021

Convalescent Plasma Therapy for COVID-19: A Graphical Mosaic of the Worldwide Evidence.

Front Med (Lausanne) 2021 7;8:684151. Epub 2021 Jun 7.

Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, United States.

Convalescent plasma has been used worldwide to treat patients hospitalized with coronavirus disease 2019 (COVID-19) and prevent disease progression. Despite global usage, uncertainty remains regarding plasma efficacy, as randomized controlled trials (RCTs) have provided divergent evidence regarding the survival benefit of convalescent plasma. Here, we argue that during a global health emergency, the mosaic of evidence originating from multiple levels of the epistemic hierarchy should inform contemporary policy and healthcare decisions. Indeed, worldwide matched-control studies have generally found convalescent plasma to improve COVID-19 patient survival, and RCTs have demonstrated a survival benefit when transfused early in the disease course but limited or no benefit later in the disease course when patients required greater supportive therapies. RCTs have also revealed that convalescent plasma transfusion contributes to improved symptomatology and viral clearance. To further investigate the effect of convalescent plasma on patient mortality, we performed a meta-analytical approach to pool daily survival data from all controlled studies that reported Kaplan-Meier survival plots. Qualitative inspection of all available Kaplan-Meier survival data and an aggregate Kaplan-Meier survival plot revealed a directionally consistent pattern among studies arising from multiple levels of the epistemic hierarchy, whereby convalescent plasma transfusion was generally associated with greater patient survival. Given that convalescent plasma has a similar safety profile as standard plasma, convalescent plasma should be implemented within weeks of the onset of future infectious disease outbreaks.
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http://dx.doi.org/10.3389/fmed.2021.684151DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8215127PMC
June 2021

Cost Effectiveness of an Electrocardiographic Deep Learning Algorithm to Detect Asymptomatic Left Ventricular Dysfunction.

Mayo Clin Proc 2021 07 9;96(7):1835-1844. Epub 2021 Jun 9.

Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.

Objective: To evaluate the cost-effectiveness of an artificial intelligence electrocardiogram (AI-ECG) algorithm under various clinical and cost scenarios when used for universal screening at age 65.

Patients And Methods: We used decision analytic modeling to perform a cost-effectiveness analysis of the use of AI-ECG to screen for asymptomatic left ventricular dysfunction (ALVD) once at age 65 compared with no screening. This screening consisted of an initial screening decision tree and subsequent construction of a Markov model. One-way sensitivity analysis on various disease and cost parameters to evaluate cost-effectiveness at both $50,000 per quality-adjusted life year (QALY) and $100,000 per QALY willingness-to-pay threshold.

Results: We found that for universal screening at age 65, the novel AI-ECG algorithm would cost $43,351 per QALY gained, test performance, disease characteristics, and testing cost parameters significantly affect cost-effectiveness, and screening at ages 55 and 75 would cost $48,649 and $52,072 per QALY gained, respectively. Overall, under most of the clinical scenarios modeled, coupled with its robust test performance in both testing and validation cohorts, screening with the novel AI-ECG algorithm appears to be cost-effective at a willingness-to-pay threshold of $50,000.

Conclusion: Universal screening for ALVD with the novel AI-ECG appears to be cost-effective under most clinical scenarios with a cost of <$50,000 per QALY. Cost-effectiveness is particularly sensitive to both the probability of disease progression and the cost of screening and downstream testing. To improve cost-effectiveness modeling, further study of the natural progression and treatment of ALVD and external validation of AI-ECG should be undertaken.
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http://dx.doi.org/10.1016/j.mayocp.2020.11.032DOI Listing
July 2021

Convalescent plasma use in the USA was inversely correlated with COVID-19 mortality.

Elife 2021 06 4;10. Epub 2021 Jun 4.

Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, United States.

Background: The US Food and Drug Administration authorized COVID-19 convalescent plasma (CCP) therapy for hospitalized COVID-19 patients via the Expanded Access Program (EAP) and the Emergency Use Authorization (EUA), leading to use in about 500,000 patients during the first year of the pandemic for the USA.

Methods: We tracked the number of CCP units dispensed to hospitals by blood banking organizations and correlated that usage with hospital admission and mortality data.

Results: CCP usage per admission peaked in Fall 2020, with more than 40% of inpatients estimated to have received CCP between late September and early November 2020. However, after randomized controlled trials failed to show a reduction in mortality, CCP usage per admission declined steadily to a nadir of less than 10% in March 2021. We found a strong inverse correlation (r = -0.52, p=0.002) between CCP usage per hospital admission and deaths occurring 2 weeks after admission, and this finding was robust to examination of deaths taking place 1, 2, or 3 weeks after admission. Changes in the number of hospital admissions, SARS-CoV-2 variants, and age of patients could not explain these findings. The retreat from CCP usage might have resulted in as many as 29,000 excess deaths from mid-November 2020 to February 2021.

Conclusions: A strong inverse correlation between CCP use and mortality per admission in the USA provides population-level evidence consistent with the notion that CCP reduces mortality in COVID-19 and suggests that the recent decline in usage could have resulted in excess deaths.

Funding: There was no specific funding for this study. AC was supported in part by RO1 HL059842 and R01 AI1520789; MJJ was supported in part by 5R35HL139854. This project has been funded in whole or in part with Federal funds from the Department of Health and Human Services; Office of the Assistant Secretary for Preparedness and Response; Biomedical Advanced Research and Development Authority under Contract No. 75A50120C00096.
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http://dx.doi.org/10.7554/eLife.69866DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8205484PMC
June 2021

Wearable electronic devices for chronic pain intensity assessment: A systematic review.

Pain Pract 2021 Jun 3. Epub 2021 Jun 3.

Division of Plastic Surgery, Mayo Clinic, Jacksonville, Florida, USA.

Wearable electronic devices are a convenient solution to pain intensity assessment as they can provide continuous monitoring for more precise medication adjustments. However, there is little evidence regarding the use of wearable electronic devices for chronic pain intensity assessment. Our primary objective was to examine the physiologic parameters used by wearable electronic devices for chronic pain intensity assessment. We initially inquired PubMed, CINAHL, and Embase for studies evaluating the use of wearable electronic devices for chronic pain intensity assessment. We updated our inquiry by searching on PubMed, Embase, Scopus, and Google Scholar. English peer-reviewed studies were included, with no exclusions based on time frame or publication status. Of 348 articles that were identified on the first inquiry, 8 fulfilled the eligibility criteria. Of 179 articles that were identified on the last inquiry, only 1 fulfilled the eligibility criteria. We found articles evaluating wristbands, smartwatches, and belts. Parameters evaluated were psychomotor and sleep patterns, space and time mobility, heart rate variability, and skeletal muscle electrical activity. Most of the studies found significant positive associations between physiological parameters measured by wearable electronic devices and self-reporting pain scales. Wearable electronic devices reliably reflect physiologic or biometric parameters, providing a physiological correlation for pain. Early stage investigation suggests that the degree of pain intensity can be discerned, which ideally will reduce the bias inherent to existing numeric/verbal scales. Further research on the use of these devices is vital.
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http://dx.doi.org/10.1111/papr.13047DOI Listing
June 2021

Use of convalescent plasma in COVID-19 patients with immunosuppression.

Transfusion 2021 08 1;61(8):2503-2511. Epub 2021 Jun 1.

Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, Minnesota, USA.

In the absence of effective countermeasures, human convalescent plasma has been widely used to treat severe acute respiratory syndrome coronavirus 2, the causative agent of novel coronavirus disease 19 (COVID-19), including among patients with innate or acquired immunosuppression. However, the association between COVID-19-associated mortality in patients with immunosuppression and therapeutic use of convalescent plasma is unknown. We review 75 reports, including one large matched-control registry study of 143 COVID-19 patients with hematological malignancies, and 51 case reports and 23 case series representing 238 COVID-19 patients with immunosuppression. We review clinical features and treatment protocols of COVID-19 patients with immunosuppression after treatment with human convalescent plasma. We also discuss the time course and clinical features of recovery. The available data from case reports and case series provide evidence suggesting a mortality benefit and rapid clinical improvement in patients with several forms of immunosuppression following COVID-19 convalescent plasma transfusion. The utility of convalescent plasma or other forms of antibody therapy in immune-deficient and immune-suppressed patients with COVID-19 warrants further investigation.
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http://dx.doi.org/10.1111/trf.16525DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8242637PMC
August 2021

Using Facial Recognition Tools for Health Assessment.

Plast Surg Nurs 2021 Apr-Jun 01;41(2):112-116

Daniel Boczar, MD, is a postdoctoral research fellow at the Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL.

The number of applications for facial recognition technology is increasing due to the improvement in image quality, artificial intelligence, and computer processing power that has occurred during the last decades. Algorithms can be used to convert facial anthropometric landmarks into a computer representation, which can be used to help identify nonverbal information about an individual's health status. This article discusses the potential ways a facial recognition tool can perform a health assessment. Because facial attributes may be considered biometric data, clinicians should be informed about the clinical, ethical, and legal issues associated with its use.
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http://dx.doi.org/10.1097/PSN.0000000000000357DOI Listing
September 2021

Accuracy of Wearable Sensor Technology in Hand Goniometry: A Systematic Review.

Hand (N Y) 2021 May 25:15589447211014606. Epub 2021 May 25.

Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA.

Background: Wearable devices and sensor technology provide objective, unbiased range of motion measurements that help health care professionals overcome the hindrances of protractor-based goniometry. This review aims to analyze the accuracy of existing wearable sensor technologies for hand range of motion measurement and identify the most accurate one.

Methods: We performed a systematic review by searching PubMed, CINAHL, and Embase for studies evaluating wearable sensor technology in hand range of motion assessment. Keywords used for the inquiry were related to wearable devices and hand goniometry.

Results: Of the 71 studies, 11 met the inclusion criteria. Ten studies evaluated gloves and 1 evaluated a wristband. The most common types of sensors used were bend sensors, followed by inertial sensors, Hall effect sensors, and magnetometers. Most studies compared wearable devices with manual goniometry, achieving optimal accuracy. Although most of the devices reached adequate levels of measurement error, accuracy evaluation in the reviewed studies might be subject to bias owing to the use of poorly reliable measurement techniques for comparison of the devices.

Conclusion: Gloves using inertial sensors were the most accurate. Future studies should use different comparison techniques, such as infrared camera-based goniometry or virtual motion tracking, to evaluate the performance of wearable devices.
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http://dx.doi.org/10.1177/15589447211014606DOI Listing
May 2021

Impact of ECG Characteristics on the Performance of an Artificial Intelligence Enabled ECG for Predicting Left Ventricular Dysfunction.

Circ Arrhythm Electrophysiol 2021 05 17;14(5):e009871. Epub 2021 May 17.

Department of Cardiovascular Diseases (J.P.-D., D.A., F.K.), Mayo Clinic, Jacksonville, FL.

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http://dx.doi.org/10.1161/CIRCEP.121.009871DOI Listing
May 2021

The Effect of Convalescent Plasma Therapy on Mortality Among Patients With COVID-19: Systematic Review and Meta-analysis.

Mayo Clin Proc 2021 05 17;96(5):1262-1275. Epub 2021 Feb 17.

Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN. Electronic address:

To determine the effect of COVID-19 convalescent plasma on mortality, we aggregated patient outcome data from 10 randomized clinical trials, 20 matched control studies, 2 dose-response studies, and 96 case reports or case series. Studies published between January 1, 2020, and January 16, 2021, were identified through a systematic search of online PubMed and MEDLINE databases. Random effects analyses of randomized clinical trials and matched control data demonstrated that patients with COVID-19 transfused with convalescent plasma exhibited a lower mortality rate compared with patients receiving standard treatments. Additional analyses showed that early transfusion (within 3 days of hospital admission) of higher titer plasma is associated with lower patient mortality. These data provide evidence favoring the efficacy of human convalescent plasma as a therapeutic agent in hospitalized patients with COVID-19.
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http://dx.doi.org/10.1016/j.mayocp.2021.02.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7888247PMC
May 2021

Prevalence of SARS-CoV-2 Antibodies in a Multistate Academic Medical Center.

Mayo Clin Proc 2021 05 26;96(5):1165-1174. Epub 2021 Mar 26.

Mayo Clinic, Phoenix, AZ.

Objective: To estimate the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in health care personnel.

Methods: The Mayo Clinic Serology Screening Program was created to provide a voluntary, two-stage testing program for SARS-CoV-2 antibodies to health care personnel. The first stage used a dried blood spot screening test initiated on June 15, 2020. Those participants identified as reactive were advised to have confirmatory testing via a venipuncture. Venipuncture results through August 8, 2020, were considered. Consent and authorization for testing was required to participate in the screening program. This report, which was conducted under an institutional review board-approved protocol, only includes employees who have further authorized their records for use in research.

Results: A total of 81,113 health care personnel were eligible for the program, and of these 29,606 participated in the screening program. A total of 4284 (14.5%) of the dried blood spot test results were "reactive" and warranted confirmatory testing. Confirmatory testing was completed on 4094 (95.6%) of the screen reactive with an overall seroprevalence rate of 0.60% (95% CI, 0.52% to 0.69%). Significant variation in seroprevalence was observed by region of the country and age group.

Conclusion: The seroprevalence for SARS-CoV-2 antibodies through August 8, 2020, was found to be lower than previously reported in other health care organizations. There was an observation that seroprevalence may be associated with community disease burden.
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http://dx.doi.org/10.1016/j.mayocp.2021.03.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997730PMC
May 2021

Transcriptomic analysis to identify genes associated with selective hippocampal vulnerability in Alzheimer's disease.

Nat Commun 2021 04 19;12(1):2311. Epub 2021 Apr 19.

Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA.

Selective vulnerability of different brain regions is seen in many neurodegenerative disorders. The hippocampus and cortex are selectively vulnerable in Alzheimer's disease (AD), however the degree of involvement of the different brain regions differs among patients. We classified corticolimbic patterns of neurofibrillary tangles in postmortem tissue to capture extreme and representative phenotypes. We combined bulk RNA sequencing with digital pathology to examine hippocampal vulnerability in AD. We identified hippocampal gene expression changes associated with hippocampal vulnerability and used machine learning to identify genes that were associated with AD neuropathology, including SERPINA5, RYBP, SLC38A2, FEM1B, and PYDC1. Further histologic and biochemical analyses suggested SERPINA5 expression is associated with tau expression in the brain. Our study highlights the importance of embracing heterogeneity of the human brain in disease to identify disease-relevant gene expression.
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http://dx.doi.org/10.1038/s41467-021-22399-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055900PMC
April 2021

Convalescent Plasma Use in the United States was inversely correlated with COVID-19 Mortality: Did Plasma Hesitancy cost lives?

medRxiv 2021 Apr 16. Epub 2021 Apr 16.

Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL.

Background: The US Food and Drug Administration authorized Convalescent Plasma (CCP) therapy for hospitalized COVID-19 patients via the Expanded Access Program (EAP) and the Emergency Use Authorization (EUA), leading to use in about 500,000 patients during the first year of the pandemic for the US.

Methods: We tracked the number of CCP units dispensed to hospitals by blood banking organizations and correlated that usage with hospital admission and mortality data.

Results: CCP usage per admission peaked in Fall 2020, with more than 40% of inpatients estimated to have received CCP between late September and early November 2020. However, after randomized controlled trials failed to show a reduction in mortality, CCP usage per admission declined steadily to a nadir of less than 10% in March 2021. We found a strong inverse correlation (r = -0.52, P = 0.002) between CCP usage per hospital admission and deaths occurring two weeks after admission, and this finding was robust to examination of deaths taking place one, two or three weeks after admission. Changes in the number of hospital admissions, SARS-CoV-2 variants, and age of patients could not explain these findings. The retreat from CCP usage might have resulted in as many as 29,000 excess deaths from mid-November 2020 to February 2021.

Conclusions: A strong inverse correlation between CCP use and mortality per admission in the USA provides population level evidence consistent with the notion that CCP reduces mortality in COVID-19 and suggests that the recent decline in usage could have resulted in excess deaths.
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http://dx.doi.org/10.1101/2021.04.07.21255089DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043483PMC
April 2021

Program and patient characteristics for the United States Expanded Access Program to COVID-19 convalescent plasma.

medRxiv 2021 Apr 10. Epub 2021 Apr 10.

Background: The United States (US) Expanded Access Program (EAP) to COVID-19 convalescent plasma was initiated in response to the rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease-2019 (COVID-19). While randomized clinical trials were in various stages of development and enrollment, there was an urgent need for widespread access to potential therapeutic agents particularly for vulnerable racial and ethnic minority populations who were disproportionately affected by the pandemic. The objective of this study is to report on the demographic, geographic, and chronological access to COVID-19 convalescent plasma in the US via the EAP.

Methods And Findings: Mayo Clinic served as the central IRB for all participating facilities and any US physician could participate as local physician-principal investigator. Registration occurred through the EAP central website. Blood banks rapidly developed logistics to provide convalescent plasma to hospitalized patients with COVID-19. Demographic and clinical characteristics of all enrolled patients in the EAP were summarized. Temporal trends in access to COVID-19 convalescent plasma were investigated by comparing daily and weekly changes in EAP enrollment in response to changes in infection rate on a state level. Geographical analyses on access to convalescent plasma included assessing EAP enrollment in all national hospital referral regions as well as assessing enrollment in metropolitan and less populated areas which did not have access to COVID-19 clinical trials.From April 3 to August 23, 2020, 105,717 hospitalized patients with severe or life-threatening COVID-19 were enrolled in the EAP. A majority of patients were older than 60 years of age (57.8%), male (58.4%), and overweight or obese (83.8%). There was substantial inclusion of minorities and underserved populations, including 46.4% of patients with a race other than White, and 37.2% of patients were of Hispanic ethnicity. Severe or life-threatening COVID-19 was present in 61.8% of patients and 18.9% of patients were mechanically ventilated at time of convalescent plasma infusion. Chronologically and geographically, increases in enrollment in the EAP closely followed confirmed infections across all 50 states. Nearly all national hospital referral regions enrolled patients in the EAP, including both in metropolitan and less populated areas.

Conclusions: The EAP successfully provided widespread access to COVID-19 convalescent plasma in all 50 states, including for underserved racial and ethnic minority populations. The efficient study design of the EAP may serve as an example framework for future efforts when broad access to a treatment is needed in response to a dynamic disease affecting demographic groups and areas historically underrepresented in clinical studies.
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http://dx.doi.org/10.1101/2021.04.08.21255115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043472PMC
April 2021

Electrocardiogram screening for aortic valve stenosis using artificial intelligence.

Eur Heart J 2021 08;42(30):2885-2896

Department of Cardiovascular Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.

Aims: Early detection of aortic stenosis (AS) is becoming increasingly important with a better outcome after aortic valve replacement in asymptomatic severe AS patients and a poor outcome in moderate AS. We aimed to develop artificial intelligence-enabled electrocardiogram (AI-ECG) using a convolutional neural network to identify patients with moderate to severe AS.

Methods And Results: Between 1989 and 2019, 258 607 adults [mean age 63 ± 16.3 years; women 122 790 (48%)] with an echocardiography and an ECG performed within 180 days were identified from the Mayo Clinic database. Moderate to severe AS by echocardiography was present in 9723 (3.7%) patients. Artificial intelligence training was performed in 129 788 (50%), validation in 25 893 (10%), and testing in 102 926 (40%) randomly selected subjects. In the test group, the AI-ECG labelled 3833 (3.7%) patients as positive with the area under the curve (AUC) of 0.85. The sensitivity, specificity, and accuracy were 78%, 74%, and 74%, respectively. The sensitivity increased and the specificity decreased as age increased. Women had lower sensitivity but higher specificity compared with men at any age groups. The model performance increased when age and sex were added to the model (AUC 0.87), which further increased to 0.90 in patients without hypertension. Patients with false-positive AI-ECGs had twice the risk for developing moderate or severe AS in 15 years compared with true negative AI-ECGs (hazard ratio 2.18, 95% confidence interval 1.90-2.50).

Conclusion: An AI-ECG can identify patients with moderate or severe AS and may serve as a powerful screening tool for AS in the community.
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http://dx.doi.org/10.1093/eurheartj/ehab153DOI Listing
August 2021

Deployment of an Interdisciplinary Predictive Analytics Task Force to Inform Hospital Operational Decision-Making During the COVID-19 Pandemic.

Mayo Clin Proc 2021 03 30;96(3):690-698. Epub 2020 Dec 30.

Department of Health Sciences Research and Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN; Department of Health Sciences Research, Mayo Clinic, Rochester, MN.

In March 2020, our institution developed an interdisciplinary predictive analytics task force to provide coronavirus disease 2019 (COVID-19) hospital census forecasting to help clinical leaders understand the potential impacts on hospital operations. As the situation unfolded into a pandemic, our task force provided predictive insights through a structured set of visualizations and key messages that have helped the practice to anticipate and react to changing operational needs and opportunities. The framework shared here for the deployment of a COVID-19 predictive analytics task force could be adapted for effective implementation at other institutions to provide evidence-based messaging for operational decision-making. For hospitals without such a structure, immediate consideration may be warranted in light of the devastating COVID-19 third-wave which has arrived for winter 2020-2021.
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http://dx.doi.org/10.1016/j.mayocp.2020.12.019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833949PMC
March 2021

Diagnostic scores predict morbidity and mortality in patients hospitalized for heart failure with preserved ejection fraction.

Eur J Heart Fail 2021 06 9;23(6):954-963. Epub 2021 Mar 9.

Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA.

Aims: To investigate the prognostic value of diagnostic scores for heart failure (HF) with preserved ejection fraction (HFpEF).

Methods And Results: Consecutive patients with HFpEF admitted for unequivocal decompensated HF treated with intravenous loop diuretics were evaluated (n = 443; mean age 78 ± 12 years; 60% women). The HFA-PEFF and H FPEF scores were calculated for all patients with echocardiography data available within 1 year and the population was stratified according to HFA-PEFF scores 2-4 (n = 79), 5 (n = 93), or 6 (n = 271) and H FPEF score probabilities <90% (n = 80), 90-95% (n = 61), and 96-100% (n = 293). HF readmission rates (95% confidence intervals) increased from 28.9 (22.7-35.0) per 100 patient-years in HFA-PEFF 2-4 to 46.0 (38.5-53.5) in HFA-PEFF 5 and 45.0 (40.1-49.8) in HFA-PEFF 6. Similarly, HF readmission rates increased with increasing H FPEF probability: <0.90 [31.8 (25.3-38.2) per 100 patient-years], 0.90-0.95 [41.5 (32.9-50.1)], and 0.96-1.00 [45.9 (41.2-50.6]. Median survival was 65 months (36-89 months) in HFA-PEFF score 2-4, 45 months (26-59 months) in HFA-PEFF score 5, and 28 months (22-42 months) in HFA-PEFF score 6 (P < 0.001), while the hazard ratio (95% confidence interval) for all-cause mortality was 1.16 (1.02-1.32) per 0.10 increase in H FPEF probability.

Conclusions: Among patients hospitalized with HFpEF, higher HFpEF probability according to diagnostic scores is associated with increased risk of subsequent HF readmissions and all-cause mortality.
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http://dx.doi.org/10.1002/ejhf.2142DOI Listing
June 2021

Convalescent Plasma Antibody Levels and the Risk of Death from Covid-19.

N Engl J Med 2021 03 13;384(11):1015-1027. Epub 2021 Jan 13.

From the Departments of Anesthesiology and Perioperative Medicine (M.J.J., J.W.S., S.A.K., C.C.W., A.M.K., M.A.S., J.C.D.S., S.E.B., J.R.A.S., V.H., A.J.C., J.G.R., K.J.A., M.N.P.V., J.J.D., R.J.R.), Laboratory Medicine and Pathology (J.R.M., E.S.T., C.M.B., J.L.W., J.R.S.), and Cardiovascular Medicine (R.F.R., K.F.L., R.S.W.), the Human Research Protection Program (R.S.W.), and the Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine (P.R.B.), Mayo Clinic, Rochester, MN; the Departments of Health Sciences Research (R.E.C., P.W.J., E.R.L., D.O.H.) and Cardiovascular Medicine (K.A.B., E.R.W., D.F.), Mayo Clinic, Jacksonville, FL; the Department of Health Sciences Research (K.L.K., M.R.B.) and the Department of Internal Medicine, Division of Infectious Diseases (J.E.B.), Mayo Clinic, Phoenix, AZ; the Department of Anesthesiology, Cooper Medical School of Rowan University, Cooper University Health Care, Camden, NJ (N.H.); the Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring (N.C.V., P.M.), and the Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore (A.C.) - both in Maryland; and the Departments of Epidemiology and Biostatistics and of Pediatrics and Human Development, College of Human Medicine, Michigan State University, East Lansing (N.S.P.).

Background: Convalescent plasma has been widely used to treat coronavirus disease 2019 (Covid-19) under the presumption that such plasma contains potentially therapeutic antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that can be passively transferred to the plasma recipient. Whether convalescent plasma with high antibody levels rather than low antibody levels is associated with a lower risk of death is unknown.

Methods: In a retrospective study based on a U.S. national registry, we determined the anti-SARS-CoV-2 IgG antibody levels in convalescent plasma used to treat hospitalized adults with Covid-19. The primary outcome was death within 30 days after plasma transfusion. Patients who were enrolled through July 4, 2020, and for whom data on anti-SARS-CoV-2 antibody levels in plasma transfusions and on 30-day mortality were available were included in the analysis.

Results: Of the 3082 patients included in this analysis, death within 30 days after plasma transfusion occurred in 115 of 515 patients (22.3%) in the high-titer group, 549 of 2006 patients (27.4%) in the medium-titer group, and 166 of 561 patients (29.6%) in the low-titer group. The association of anti-SARS-CoV-2 antibody levels with the risk of death from Covid-19 was moderated by mechanical ventilation status. A lower risk of death within 30 days in the high-titer group than in the low-titer group was observed among patients who had not received mechanical ventilation before transfusion (relative risk, 0.66; 95% confidence interval [CI], 0.48 to 0.91), and no effect on the risk of death was observed among patients who had received mechanical ventilation (relative risk, 1.02; 95% CI, 0.78 to 1.32).

Conclusions: Among patients hospitalized with Covid-19 who were not receiving mechanical ventilation, transfusion of plasma with higher anti-SARS-CoV-2 IgG antibody levels was associated with a lower risk of death than transfusion of plasma with lower antibody levels. (Funded by the Department of Health and Human Services and others; ClinicalTrials.gov number, NCT04338360.).
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http://dx.doi.org/10.1056/NEJMoa2031893DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7821984PMC
March 2021

Artificial Intelligence-Enabled Assessment of the Heart Rate Corrected QT Interval Using a Mobile Electrocardiogram Device.

Circulation 2021 03 1;143(13):1274-1286. Epub 2021 Feb 1.

Division of Heart Rhythm Services, Windland Smith Rice Genetic Heart Rhythm Clinic (L.W.D., Z.I.A., P.A.N., P.A.F., M.J.A.), Mayo Clinic, Rochester, MN.

Background: Heart rate-corrected QT interval (QTc) prolongation, whether secondary to drugs, genetics including congenital long QT syndrome, and/or systemic diseases including SARS-CoV-2-mediated coronavirus disease 2019 (COVID-19), can predispose to ventricular arrhythmias and sudden cardiac death. Currently, QTc assessment and monitoring relies largely on 12-lead electrocardiography. As such, we sought to train and validate an artificial intelligence (AI)-enabled 12-lead ECG algorithm to determine the QTc, and then prospectively test this algorithm on tracings acquired from a mobile ECG (mECG) device in a population enriched for repolarization abnormalities.

Methods: Using >1.6 million 12-lead ECGs from 538 200 patients, a deep neural network (DNN) was derived (patients for training, n = 250 767; patients for testing, n = 107 920) and validated (n = 179 513 patients) to predict the QTc using cardiologist-overread QTc values as the "gold standard". The ability of this DNN to detect clinically-relevant QTc prolongation (eg, QTc ≥500 ms) was then tested prospectively on 686 patients with genetic heart disease (50% with long QT syndrome) with QTc values obtained from both a 12-lead ECG and a prototype mECG device equivalent to the commercially-available AliveCor KardiaMobile 6L.

Results: In the validation sample, strong agreement was observed between human over-read and DNN-predicted QTc values (-1.76±23.14 ms). Similarly, within the prospective, genetic heart disease-enriched dataset, the difference between DNN-predicted QTc values derived from mECG tracings and those annotated from 12-lead ECGs by a QT expert (-0.45±24.73 ms) and a commercial core ECG laboratory [10.52±25.64 ms] was nominal. When applied to mECG tracings, the DNN's ability to detect a QTc value ≥500 ms yielded an area under the curve, sensitivity, and specificity of 0.97, 80.0%, and 94.4%, respectively.

Conclusions: Using smartphone-enabled electrodes, an AI DNN can predict accurately the QTc of a standard 12-lead ECG. QTc estimation from an AI-enabled mECG device may provide a cost-effective means of screening for both acquired and congenital long QT syndrome in a variety of clinical settings where standard 12-lead electrocardiography is not accessible or cost-effective.
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http://dx.doi.org/10.1161/CIRCULATIONAHA.120.050231DOI Listing
March 2021

The Role of Disease Severity and Demographics in the Clinical Course of COVID-19 Patients Treated with Convalescent Plasma.

medRxiv 2021 Jan 20. Epub 2021 Jan 20.

Treatment of patients with COVID-19 using convalescent plasma from recently recovered patients has been shown to be safe, but the time course of change in clinical status following plasma transfusion in relation to baseline disease severity has not yet been described. We analyzed short, descriptive daily reports of patient status in 7,180 hospitalized recipients of COVID-19 convalescent plasma in the Mayo Clinic Expanded Access Program. We assessed, from the day following transfusion, whether the patient was categorized by his or her physician as better, worse or unchanged compared to the day before, and whether, on the reporting day, the patient received mechanical ventilation, was in the ICU, had died or had been discharged. Most patients improved following transfusion, but clinical improvement was most notable in mild to moderately ill patients. Patients classified as severely ill upon enrollment improved, but not as rapidly, while patients classified as critically ill/end-stage and patients on ventilators showed worsening of disease status even after treatment with convalescent plasma. Patients age 80 and over showed little or no clinical improvement following transfusion. Clinical status at enrollment and age appear to be the primary factors in determining the therapeutic effectiveness of COVID-19 convalescent plasma among hospitalized patients.
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http://dx.doi.org/10.1101/2021.01.19.21249678DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836142PMC
January 2021

Prediction of short-term antidepressant response using probabilistic graphical models with replication across multiple drugs and treatment settings.

Neuropsychopharmacology 2021 06 15;46(7):1272-1282. Epub 2021 Jan 15.

Department of Psychiatry and Psychology, Mayo Clinic, Jacksonville, FL, USA.

Heterogeneity in the clinical presentation of major depressive disorder and response to antidepressants limits clinicians' ability to accurately predict a specific patient's eventual response to therapy. Validated depressive symptom profiles may be an important tool for identifying poor outcomes early in the course of treatment. To derive these symptom profiles, we first examined data from 947 depressed subjects treated with selective serotonin reuptake inhibitors (SSRIs) to delineate the heterogeneity of antidepressant response using probabilistic graphical models (PGMs). We then used unsupervised machine learning to identify specific depressive symptoms and thresholds of improvement that were predictive of antidepressant response by 4 weeks for a patient to achieve remission, response, or nonresponse by 8 weeks. Four depressive symptoms (depressed mood, guilt feelings and delusion, work and activities and psychic anxiety) and specific thresholds of change in each at 4 weeks predicted eventual outcome at 8 weeks to SSRI therapy with an average accuracy of 77% (p = 5.5E-08). The same four symptoms and prognostic thresholds derived from patients treated with SSRIs correctly predicted outcomes in 72% (p = 1.25E-05) of 1996 patients treated with other antidepressants in both inpatient and outpatient settings in independent publicly-available datasets. These predictive accuracies were higher than the accuracy of 53% for predicting SSRI response achieved using approaches that (i) incorporated only baseline clinical and sociodemographic factors, or (ii) used 4-week nonresponse status to predict likely outcomes at 8 weeks. The present findings suggest that PGMs providing interpretable predictions have the potential to enhance clinical treatment of depression and reduce the time burden associated with trials of ineffective antidepressants. Prospective trials examining this approach are forthcoming.
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http://dx.doi.org/10.1038/s41386-020-00943-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8134509PMC
June 2021
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