Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 5 de 5
Filter
Add filters

Language
Document Type
Year range
1.
Open Forum Infectious Diseases ; 9(Supplement 2):S451, 2022.
Article in English | EMBASE | ID: covidwho-2189721

ABSTRACT

Background. Characterizing, diagnosing, and caring for 'long COVID' patients has proven to be challenging due to heterogenous symptoms and broad definitions of these post-acute sequelae. Here, we take a machine learning approach to identify discrete clusters of long COVID symptoms which may define specific long COVID phenotypes. Figure 1: (A) Principal component analysis followed by K-means clustering identified three groups of participants. (B) Heatmap depicting three distinct clusters (high values are in red and low value are in blue);Cluster 1 exhibits sensory symptoms (e.g., loss of smell and/or taste), Cluster 2 exhibits fatigue and difficulty thinking (e.g., changes in ability to think) symptoms, and Cluster 3 exhibits difficulty breathing and exercise intolerance symptoms. (C) Clinical and demographic characteristics of 97 military health system beneficiaries by identified clusters Methods. The Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases with Pandemic Potential (EPICC) study is a longitudinal COVID-19 cohort study with data and biospecimens collected from 10 military treatment facilities and online recruitment. Demographic and clinical characteristics were collected using case report forms and surveys completed at enrollment and at 1, 3, 6, 9, and 12 months. For this analysis, we identified those who reported any moderate to severe persistent symptoms on surveys collected 6-months post-COVID-19 symptom onset. Using the survey responses, we applied principal component analysis (PCA) followed by unsupervised machine learning clustering algorithm K-means to identify groups with distinct clusters of symptoms. Results. Of 1299 subjects with 6-month survey responses, 97 (7.47%) reported moderate to severe persistent symptoms. Among these subjects, three clusters were identified using PCA (Figure 1A). Cluster 1 is characterized by sensory symptoms (loss of taste and/or smell), Cluster 2 by fatigue and difficulty thinking, and Cluster 3 by difficulty breathing and exercise intolerance (Figure 1B). More than half of these subjects (57%) were female, 64% were 18-44 years old, and 64% had no comorbidities at enrollment (Figure 1C). Those in the sensory symptom cluster were all outpatients at the time of initial COVID-19 presentation (p < 0.01). The difficulty breathing and exercise intolerance symptom-clusters had a higher proportion of older participants (Age group >= 45-64) with more comorbidities (CCI >= 1-2). Conclusion. We identified three distinct 'long COVID' phenotypes among those with moderate to severe COVID-19 symptoms at 6-months post-symptom onset. With further validation and characterization, this framework may allow more precise classification of long COVID cases, and potentially improve the diagnosis, prognosis, and treatment of post- infectious sequelae.

2.
Open Forum Infectious Diseases ; 9(Supplement 2):S4-S5, 2022.
Article in English | EMBASE | ID: covidwho-2189493

ABSTRACT

Background. COVID-19 may have deleterious effects on the fitness of active duty US military service members. We seek to understand the long-term functional consequences of SARS-CoV-2 infection in this critical population, and in other military healthcare beneficiaries. Methods. The Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases with Pandemic Potential (EPICC) study is a longitudinal cohort study to describe the outcomes of SARS-CoV-2 infection in US Military Health System beneficiaries. Subjects provided information about difficulties experienced with daily activities, exercise, and physical fitness performance via electronic surveys. Subjects completed surveys at enrollment and at 1, 3, 6, 9, and 12 months. Results. 5,910 subjects completed survey fitness questions, 3,244 (55%) of whom tested SARS-CoV-2 positive at least once during the period of observation. Over 75% of subjects were young adults and over half were male (Table 1). 1,093 (34.3%) of SARS-CoV-2-positive subjects reported new or increased difficulty exercising compared to 393 (14.8%) SARS-CoV-2 negative subjects (p < 0.01) (Table 2). The most commonly reported symptoms related to problems with exercise and activities were dyspnea and fatigue.Among the active-duty members who answered the question about their service-mandated physical fitness test scores, 43.2% of SARS-CoV-2-positive participants reported that their scores had worsened in the study period, compared with 24.3%of SARS-CoV-2 negative participants.Among SARS-CoV-2-positive subjects, reports of difficulty exercising and performing daily activities were highest within one month of the first positive test, decreasing in prevalence among the cohort only slightly to 24% and 18%, respectively, at 12 months (Figure 1). Conclusion. A substantial proportion of military service-members in this cohort have reported impairment of their service-mandated physical fitness scores after COVID-19;this proportion is significantly higher than those who are SARS-CoV-2 negative and persists to 12 months in many;similar complaints were reported among non-active duty. Further objective evaluation of post-COVID fitness impairment in this population is warranted. (Figure Presented).

3.
Sleep Medicine ; 100:S196-S197, 2022.
Article in English | ScienceDirect | ID: covidwho-1937192
4.
Open Forum Infectious Diseases ; 8(SUPPL 1):S273, 2021.
Article in English | EMBASE | ID: covidwho-1746657

ABSTRACT

Background. The risk factors of venous thromboembolism (VTE) in COVID-19 warrant further study. We leveraged a cohort in the Military Health System (MHS) to identify clinical and virological predictors of incident deep venous thrombosis (DVT), pulmonary embolism (PE), and other VTE within 90-days after COVID-19 onset. Methods. PCR or serologically-confirmed SARS-CoV-2 infected MHS beneficiaries were enrolled via nine military treatment facilities (MTF) through April 2021. Case characteristics were derived from interview and review of the electronic medical record (EMR) through one-year follow-up in outpatients and inpatients. qPCR was performed on upper respiratory swab specimens collected post-enrollment to estimate SARS-CoV-2 viral load. The frequency of incident DVT, PE, or other VTE by 90-days post-COVID-19 onset were ascertained by ICD-10 code. Correlates of 90-day VTE were determined through multivariate logistic regression, including age and sampling-time-adjusted log10-SARS-CoV-2 GE/reaction as a priori predictors in addition to other demographic and clinical covariates which were selected through stepwise regression. Results. 1473 participants with SARS-CoV-2 infection were enrolled through April 2021. 21% of study participants were inpatients;the mean age was 41 years (SD = 17.0 years). The median Charlson Comorbidity Index score was 0 (IQR = 0 -1, range = 0 - 13). 27 (1.8%) had a prior history of VTE. Mean maximum viral load observed was 1.65 x 107 genome equivalents/reaction. 36 (2.4%) of all SARS-CoV-2 cases (including inpatients and outpatients), 29 (9.5%) of COVID-19 inpatients, and 7 (0.6%) of outpatients received an ICD-10 diagnosis of any VTE within 90 days after COVID-19 onset. Logistic regression identified hospitalization (aOR = 11.1, p = 0.003) and prior VTE (aOR = 6.2 , p = 0.009) as independent predictors of VTE within 90 days of symptom onset. Neither age (aOR = 1.0, p = 0.50), other demographic covariates, other comorbidities, nor SARS-CoV-2 viral load (aOR = 1.1, p = 0.60) were associated with 90-day VTE. Conclusion. VTE was relatively frequent in this MHS cohort. SARS-CoV-2 viral load did not increase the odds of 90-day VTE. Rather, being hospitalized for SARS-CoV-2 and prior VTE history remained the strongest predictors of this complication.

5.
Dance Magazine ; 94(10):32-35, 2020.
Article in English | Scopus | ID: covidwho-934860
SELECTION OF CITATIONS
SEARCH DETAIL