Publications by authors named "Christopher A Aakre"

14 Publications

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Central Sensitization Phenotypes in Post Acute Sequelae of SARS-CoV-2 Infection (PASC): Defining the Post COVID Syndrome.

J Prim Care Community Health 2021 Jan-Dec;12:21501327211030826

Mayo Clinic, Rochester, MN, USA.

Objective: To develop and implement criteria for description of post COVID syndrome based on analysis of patients presenting for evaluation at Mayo Clinic Rochester between November 2019 and August 2020.

Methods: A total of 465 patients with a history of testing positive for COVID-19 were identified and their medical records reviewed. After a thorough review, utilizing the DELPHI methods by an expert panel, 42 (9%) cases were identified with persistent central sensitization (CS) symptoms persisting after the resolution of acute COVID-19, herein referred to as Post COVID syndrome (PoCoS). In this report we describe the baseline characteristics of these PoCoS patients.

Results: Among these 42 PoCoS patients, the mean age was 46.2 years (median age was 46.5 years). Pain (90%), fatigue (74%), dyspnea (43%), and orthostatic intolerance (38%) were the most common symptoms. The characteristics of an initial 14 patients were utilized for the development of clinical criteria via a modified Delphi Method by a panel of experts in central sensitization disorders. These criteria were subsequently applied in the identification of 28 additional cases of suspected PoCoS. A 2-reviewer system was used to analyze agreement with using the criteria, with all 28 cases determined to be either probable or possible cases by the reviewers. Inter-reviewer agreement using these proposed defining criteria was high with a Cohen's alpha of .88.

Conclusions: Here we present what we believe to be the first definitional criteria for Post COVID syndrome. These may be useful in clinical phenotyping of these patients for targeted treatment and future research.
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http://dx.doi.org/10.1177/21501327211030826DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8267019PMC
July 2021

Fibromyalgia screening in patients with unexplained chronic fatigue.

Menopause 2020 11 2;28(1):93-95. Epub 2020 Nov 2.

Mayo Clinic, Rochester, Minnesota.

Abstract: Women often complain of symptoms of fatigue and generalized aches and pains around menopause. Even though fibromyalgia is more prevalent in midlife women, not all women presenting with aches and pain and disrupted sleep meet diagnostic criteria for fibromyalgia. This Practice Pearl addresses the distinction between chronic fatigue syndrome and fibromyalgia and the management of fibromyalgia in perimenopausal and postmenopausal women.
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http://dx.doi.org/10.1097/GME.0000000000001656DOI Listing
November 2020

Impact of Clinicians' Use of Electronic Knowledge Resources on Clinical and Learning Outcomes: Systematic Review and Meta-Analysis.

J Med Internet Res 2019 07 25;21(7):e13315. Epub 2019 Jul 25.

Division of General Internal Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, United States.

Background: Clinicians use electronic knowledge resources, such as Micromedex, UpToDate, and Wikipedia, to deliver evidence-based care and engage in point-of-care learning. Despite this use in clinical practice, their impact on patient care and learning outcomes is incompletely understood. A comprehensive synthesis of available evidence regarding the effectiveness of electronic knowledge resources would guide clinicians, health care system administrators, medical educators, and informaticians in making evidence-based decisions about their purchase, implementation, and use.

Objective: The aim of this review is to quantify the impact of electronic knowledge resources on clinical and learning outcomes.

Methods: We searched MEDLINE, Embase, PsycINFO, and the Cochrane Library for articles published from 1991 to 2017. Two authors independently screened studies for inclusion and extracted outcomes related to knowledge, skills, attitudes, behaviors, patient effects, and cost. We used random-effects meta-analysis to pool standardized mean differences (SMDs) across studies.

Results: Of 10,811 studies screened, we identified 25 eligible studies published between 2003 and 2016. A total of 5 studies were randomized trials, 22 involved physicians in practice or training, and 10 reported potential conflicts of interest. A total of 15 studies compared electronic knowledge resources with no intervention. Of these, 7 reported clinician behaviors, with a pooled SMD of 0.47 (95% CI 0.27 to 0.67; P<.001), and 8 reported objective patient effects with a pooled SMD of 0.19 (95% CI 0.07 to 0.32; P=.003). Heterogeneity was large (I>50%) across studies. When compared with other resources-7 studies, not amenable to meta-analytic pooling-the use of electronic knowledge resources was associated with increased frequency of answering questions and perceived benefits on patient care, with variable impact on time to find an answer. A total of 2 studies compared different implementations of the same electronic knowledge resource.

Conclusions: Use of electronic knowledge resources is associated with a positive impact on clinician behaviors and patient effects. We found statistically significant associations between the use of electronic knowledge resources and improved clinician behaviors and patient effects. When compared with other resources, the use of electronic knowledge resources was associated with increased success in answering clinical questions, with variable impact on speed. Comparisons of different implementation strategies of the same electronic knowledge resource suggest that there are benefits from allowing clinicians to choose to access the resource, versus automated display of resource information, and from integrating patient-specific information. A total of 4 studies compared different commercial electronic knowledge resources, with variable results. Resource implementation strategies can significantly influence outcomes but few studies have examined such factors.
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http://dx.doi.org/10.2196/13315DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6690166PMC
July 2019

Barriers and facilitators to clinical information seeking: a systematic review.

J Am Med Inform Assoc 2019 10;26(10):1129-1140

Division of General Internal Medicine, Mayo Clinic, Rochester, Minnesota, USA.

Objective: The study sought to identify barriers to and facilitators of point-of-care information seeking and use of knowledge resources.

Materials And Methods: We searched MEDLINE, Embase, PsycINFO, and Cochrane Library from 1991 to February 2017. We included qualitative studies in any language exploring barriers to and facilitators of point-of-care information seeking or use of electronic knowledge resources. Two authors independently extracted data on users, study design, and study quality. We inductively identified specific barriers or facilitators and from these synthesized a model of key determinants of information-seeking behaviors.

Results: Forty-five qualitative studies were included, reporting data derived from interviews (n = 26), focus groups (n = 21), ethnographies (n = 6), logs (n = 4), and usability studies (n = 2). Most studies were performed within the context of general medicine (n = 28) or medical specialties (n = 13). We inductively identified 58 specific barriers and facilitators and then created a model reflecting 5 key determinants of information-seeking behaviors: time includes subthemes of time availability, efficiency of information seeking, and urgency of information need; accessibility includes subthemes of hardware access, hardware speed, hardware portability, information restriction, and cost of resources; personal skills and attitudes includes subthemes of computer literacy, information-seeking skills, and contextual attitudes about information seeking; institutional attitudes, cultures, and policies includes subthemes describing external individual and institutional information-seeking influences; and knowledge resource features includes subthemes describing information-seeking efficiency, information content, information organization, resource familiarity, information credibility, information currency, workflow integration, compatibility of recommendations with local processes, and patient educational support.

Conclusions: Addressing these determinants of information-seeking behaviors may facilitate clinicians' question answering to improve patient care.
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http://dx.doi.org/10.1093/jamia/ocz065DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7647205PMC
October 2019

Electronic Knowledge Resources and Point-of-Care Learning: A Scoping Review.

Acad Med 2018 11;93(11S Association of American Medical Colleges Learn Serve Lead: Proceedings of the 57th Annual Research in Medical Education Sessions):S60-S67

C.A. Aakre is assistant professor of medicine and senior associate consultant, Division of General Internal Medicine, Mayo Clinic College of Medicine and Science, Rochester, Minnesota. L.J. Pencille is program coordinator, Knowledge and Delivery Center, Center for Translational Informatics and Knowledge Management, Mayo Clinic, Rochester, Minnesota. K.J. Sorensen is assistant professor of medical education and unit head, Knowledge Management Technologies, Center for Translational Informatics and Knowledge Management, Mayo Clinic, Rochester, Minnesota. J.L. Shellum is section head, Knowledge and Delivery Center, Center for Translational Informatics and Knowledge Management, Mayo Clinic, Rochester, Minnesota. G. Del Fiol is assistant professor of biomedical informatics, University of Utah School of Medicine, Salt Lake City, Utah, and co-chair, Clinical Decision Support Work Group at Health Level Seven (HL7). L.A. Maggio is associate professor of medicine and associate director of technology and distributed learning, Department of Medicine, Uniformed Services University, Bethesda, Maryland. L.J. Prokop is reference librarian, Plummer Library, Mayo Clinic, Rochester, Minnesota. D.A. Cook is professor of medicine and medical education; researcher, Center for Translational Informatics and Knowledge Management; associate director, Office of Applied Scholarship and Education Science; and consultant, Division of General Internal Medicine, Mayo Clinic College of Medicine and Science, Rochester, Minnesota.

Purpose: The authors sought to summarize quantitative and qualitative research addressing electronic knowledge resources and point-of-care learning in a scoping review.

Method: The authors searched MEDLINE, Embase, PsycINFO, and the Cochrane Database for studies addressing electronic knowledge resources and point-of-care learning. They iteratively revised inclusion criteria and operational definitions of study features and research themes of interest. Two reviewers independently performed each phase of study selection and data extraction.

Results: Of 10,811 studies identified, 305 were included and reviewed. Most studies (225; 74%) included physicians or medical students. The most frequently mentioned electronic resources were UpToDate (88; 29%), Micromedex (59; 19%), Epocrates (50; 16%), WebMD (46; 15%), MD Consult (32; 10%), and LexiComp (31; 10%). Eight studies (3%) evaluated electronic resources or point-of-care learning using outcomes of patient effects, and 36 studies (12%) reported objectively measured clinician behaviors. Twenty-five studies (8%) examined the clinical or educational impact of electronic knowledge resource use on patient care or clinician knowledge, 124 (41%) compared use rates of various knowledge resources, 69 (23%) examined the quality of knowledge resource content, and 115 (38%) explored the process of point-of-care learning. Two conceptual clarifications were identified, distinguishing the impact on clinical or educational outcomes versus the impact on test setting decision support, and the quality of information content versus the correctness of information obtained by a clinician-user.

Conclusions: Research on electronic knowledge resources is dominated by studies involving physicians and evaluating use rates. Studies involving nonphysician users, and evaluating resource impact and implementation, are needed.
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http://dx.doi.org/10.1097/ACM.0000000000002375DOI Listing
November 2018

Towards automated calculation of evidence-based clinical scores.

World J Methodol 2017 Mar 26;7(1):16-24. Epub 2017 Mar 26.

Christopher A Aakre, Division of General Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN 55905, United States.

Aim: To determine clinical scores important for automated calculation in the inpatient setting.

Methods: A modified Delphi methodology was used to create consensus of important clinical scores for inpatient practice. A list of 176 externally validated clinical scores were identified from freely available internet-based services frequently used by clinicians. Scores were categorized based on pertinent specialty and a customized survey was created for each clinician specialty group. Clinicians were asked to rank each score based on importance of automated calculation to their clinical practice in three categories - "not important", "nice to have", or "very important". Surveys were solicited specialty-group listserv over a 3-mo interval. Respondents must have been practicing physicians with more than 20% clinical time spent in the inpatient setting. Within each specialty, consensus was established for any clinical score with greater than 70% of responses in a single category and a minimum of 10 responses. Logistic regression was performed to determine predictors of automation importance.

Results: Seventy-nine divided by one hundred and forty-four (54.9%) surveys were completed and 72/144 (50%) surveys were completed by eligible respondents. Only the critical care and internal medicine specialties surpassed the 10-respondent threshold (14 respondents each). For internists, 2/110 (1.8%) of scores were "very important" and 73/110 (66.4%) were "nice to have". For intensivists, no scores were "very important" and 26/76 (34.2%) were "nice to have". Only the number of medical history (OR = 2.34; 95%CI: 1.26-4.67; < 0.05) and vital sign (OR = 1.88; 95%CI: 1.03-3.68; < 0.05) variables for clinical scores used by internists was predictive of desire for automation.

Conclusion: Few clinical scores were deemed "very important" for automated calculation. Future efforts towards score calculator automation should focus on technically feasible "nice to have" scores.
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http://dx.doi.org/10.5662/wjm.v7.i1.16DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5366935PMC
March 2017

Comparison of methods of alert acknowledgement by critical care clinicians in the ICU setting.

PeerJ 2017 14;5:e3083. Epub 2017 Mar 14.

Department of Anesthesiology, Mayo Clinic , Rochester , MN , United States of America.

Background: Electronic Health Record (EHR)-based sepsis alert systems have failed to demonstrate improvements in clinically meaningful endpoints. However, the effect of implementation barriers on the success of new sepsis alert systems is rarely explored.

Objective: To test the hypothesis time to severe sepsis alert acknowledgement by critical care clinicians in the ICU setting would be reduced using an EHR-based alert acknowledgement system compared to a text paging-based system.

Study Design: In one arm of this simulation study, real alerts for patients in the medical ICU were delivered to critical care clinicians through the EHR. In the other arm, simulated alerts were delivered through text paging. The primary outcome was time to alert acknowledgement. The secondary outcomes were a structured, mixed quantitative/qualitative survey and informal group interview.

Results: The alert acknowledgement rate from the severe sepsis alert system was 3% ( = 148) and 51% ( = 156) from simulated severe sepsis alerts through traditional text paging. Time to alert acknowledgement from the severe sepsis alert system was median 274 min ( = 5) and median 2 min ( = 80) from text paging. The response rate from the EHR-based alert system was insufficient to compare primary measures. However, secondary measures revealed important barriers.

Conclusion: Alert fatigue, interruption, human error, and information overload are barriers to alert and simulation studies in the ICU setting.
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http://dx.doi.org/10.7717/peerj.3083DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5354075PMC
March 2017

Information Needs Assessment for a Medicine Ward-Focused Rounding Dashboard.

J Med Syst 2016 Aug 15;40(8):183. Epub 2016 Jun 15.

Department of Anesthesiology, Mayo Clinic, Rochester, MN, USA.

To identify the routine information needs of inpatient clinicians on the general wards for the development of an electronic dashboard. Survey of internal medicine and subspecialty clinicians from March 2014-July 2014 at Saint Marys Hospital in Rochester, Minnesota. An information needs assessment was generated from all unique data elements extracted from all handoff and rounding tools used by clinicians in our ICUs and general wards. An electronic survey was distributed to 104 inpatient medical providers. 89 unique data elements were identified from currently utilized handoff and rounding instruments. All data elements were present in our multipurpose ICU-based dashboard. 42 of 104 (40 %) surveys were returned. Data elements important (50/89, 56 %) and unimportant (24/89, 27 %) for routine use were identified. No significant differences in data element ranking were observed between supervisory and nonsupervisory roles. The routine information needs of general ward clinicians are a subset of data elements used routinely by ICU clinicians. Our findings suggest an electronic dashboard could be adapted from the critical care setting to the general wards with minimal modification.
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http://dx.doi.org/10.1007/s10916-016-0542-1DOI Listing
August 2016

Early Computerization of Patient Care at Mayo Clinic.

Mayo Clin Proc 2016 07 26;91(7):e93-e101. Epub 2016 May 26.

Department of Anesthesiology, Mayo Clinic, Rochester, MN; Multidisciplinary Epidemiology and Translation Research in Intensive Care (METRIC), Mayo Clinic, Rochester, MN.

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http://dx.doi.org/10.1016/j.mayocp.2016.04.001DOI Listing
July 2016

Pulmonary embolism in patients with transvenous cardiac implantable electronic device leads.

Europace 2016 Feb 12;18(2):246-52. Epub 2015 Mar 12.

Division of Cardiovascular Diseases, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA Department of Pediatrics and Adolescent Medicine, Mayo Clinic, Rochester, MN, USA

Background: Cardiac implantable electronic devices (CIEDs) are commonly associated with transvenous lead-related thrombi that can cause pulmonary embolism (PE).

Methods And Results: We retrospectively evaluated all patients with transvenous CIED leads implanted at Mayo Clinic Rochester between 1 January 2000, and 25 October 2010. Pulmonary embolism outcomes during follow-up were screened using diagnosis codes and confirmed with imaging study reports. Of 5646 CIED patients (age 67.3 ± 16.3 years, 64% men, mean follow-up 4.69 years) 88 developed PE (1.6%), incidence 3.32 [95% confidence interval (CI) 2.68-4.07] per 1000 person-years [men: 3.04 (95% CI 2.29-3.96) per 1000 person-years; women: 3.81 (95% CI 2.72-5.20) per 1000 person-years]. Other than transvenous CIED lead(s), 84% had another established risk factor for PE such as deep vein thrombosis (28%), recent surgery (27%), malignancy (25%), or prior history of venous thromboembolism (15%). At the time of PE, 22% had been hospitalized for ≥ 48 h, and 59% had been hospitalized in the preceding 30 days. Pulmonary embolism occurred in 22% despite being on systemic anticoagulation therapy. Out of 88 patients with PE, 45 subsequently died, mortality rate 93 (95% CI 67-123) per 1000 person-years (hazard ratio 2.0, 95% CI 1.5-2.7, P < 0.0001).

Conclusions: Though lead-related thrombus is commonly seen in patients with transvenous CIED leads, clinical PE occurs with a low incidence. It is possible that embolism of lead thrombus is uncommon or emboli are too small to cause consequential pulmonary infarction.
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http://dx.doi.org/10.1093/europace/euv038DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4767120PMC
February 2016

73-year-old man with dyspnea on exertion.

Mayo Clin Proc 2015 Mar;90(3):404-7

Advisor to resident and Consultant in Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN. Electronic address:

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http://dx.doi.org/10.1016/j.mayocp.2014.06.024DOI Listing
March 2015

Comparison of clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation.

Stroke 2014 Feb 5;45(2):426-31. Epub 2013 Dec 5.

From the Department of Internal Medicine (C.A.A.), Division of Cardiovascular Diseases (C.J.M., B.J.G.), and Section of Biostatistics (S.S.C.), Mayo Clinic, Rochester, MN; Division of Cardiology, Department of Medicine, The University British Columbia, Vancouver, British Columbia, Canada (T.S.M.T.); and University Department of Medicine, University of Birmingham Centre for Cardiovascular Sciences, City Hospital, Birmingham, United Kingdom (G.Y.H.L.).

Background And Purpose: Several accepted algorithms exist to characterize the risk of thromboembolism in atrial fibrillation. We performed a comparative analysis to assess the predictive value of 9 such schemes.

Methods: In a longitudinal community-based cohort study from Olmsted County, Minnesota, 2720 residents with atrial fibrillation were followed up for 4.4±3.6 years±SD from 1990 to 2004. Risk factors were identified using a diagnostic index integrated with the electronic medical record. Thromboembolism and cardiovascular event data were collected and analyzed.

Results: We identified 350 validated thromboembolic events in our cohort. Multivariable analysis identified age >75 years (odds ratio, 2.08; P<0.0001), female sex (odds ratio, 1.45; P=0.0015), history of hypertension (odds ratio, 3.07; P<0.0001), diabetes mellitus (odds ratio, 1.58; P=0.0003), and history of heart failure (odds ratio, 1.50; P=0.0102) as significant predictors of clinical thromboembolism. The Stroke Prevention in Atrial Fibrillation (SPAF; hazard ratio, 2.75; c=0.659), CHADS2-revised (hazard ratio, 3.48; c=0.654), and CHADS2-classical (hazard ratio, 2.90; c=0.653) risk schemes were most accurate in risk stratification. The low-risk cohort within the CHA2DS2-VASc scheme had the lowest event rate among all low-risk cohorts (0.11 per 100 person-years).

Conclusions: A direct comparison of 9 risk schemes reveals no profound differences in risk stratification accuracy for high-risk patients. Accurate prediction of low-risk patients is perhaps more valuable in determining those unlikely to benefit from oral anticoagulation therapy. Among our cohort, CHA2DS2-VASc performed best in this purpose.
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http://dx.doi.org/10.1161/STROKEAHA.113.002585DOI Listing
February 2014

Stroke or transient ischemic attack in patients with transvenous pacemaker or defibrillator and echocardiographically detected patent foramen ovale.

Circulation 2013 Sep 14;128(13):1433-41. Epub 2013 Aug 14.

Department of Internal Medicine, Mayo Clinic, Rochester, MN (C.V.D, D.C.D, C.A.A, V.R.V.); Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN (C.V.D, P.A.F., M.J.A, S.J.A.); Division of Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.N.); Mayo Medical School, Rochester, MN (N.A.P.); Mayo Graduate School of Medicine Visiting Scholars Program, Mayo Clinic, Rochester, MN (S.B.); Department of Statistics, Mayo Clinic, Rochester, MN (J.P.S., D.O.H.); Department of Pediatrics and Adolescent Medicine Mayo Clinic, Rochester, MN (M.J.A., S.J.A.); and Department of Neurology, Mayo Clinic, Rochester, MN (A.A.R.).

Background: A patent foramen ovale (PFO) may permit arterial embolization of thrombi that accumulate on the leads of cardiac implantable electronic devices in the right-sided cardiac chambers. We sought to determine whether a PFO increases the risk of stroke/transient ischemic attack (TIA) in patients with endocardial leads.

Methods And Results: We retrospectively evaluated all patients who had endocardial leads implanted between January 1, 2000, and October 25, 2010, at Mayo Clinic Rochester. Echocardiography was used to establish definite PFO and non-PFO cohorts. The primary end point of stroke/TIA consistent with a cardioembolic etiology and the secondary end point of mortality during postimplantation follow-up were compared in PFO versus non-PFO patients with the use of Cox proportional hazards models. We analyzed 6075 patients (364 with PFO) followed for a mean 4.7 ± 3.1 years. The primary end point of stroke/TIA was met in 30/364 (8.2%) PFO versus 117/5711 (2.0%) non-PFO patients (hazard ratio, 3.49; 95% confidence interval, 2.33-5.25; P<0.0001). The association of PFO with stroke/TIA remained significant after multivariable adjustment for age, sex, history of stroke/TIA, atrial fibrillation, and baseline aspirin/warfarin use (hazard ratio, 3.30; 95% confidence interval, 2.19-4.96; P<0.0001). There was no significant difference in all-cause mortality between PFO and non-PFO patients (hazard ratio, 0.91; 95% confidence interval, 0.77-1.07; P=0.25).

Conclusions: In patients with endocardial leads, the presence of a PFO on routine echocardiography is associated with a substantially increased risk of embolic stroke/TIA. This finding suggests a role of screening for PFOs in patients who require cardiac implantable electronic devices; if a PFO is detected, PFO closure, anticoagulation, or nonvascular lead placement may be considered.
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http://dx.doi.org/10.1161/CIRCULATIONAHA.113.003540DOI Listing
September 2013
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