Tag: long covid assessment

Long COVID in Young Patients: Impact on Lung Volume Evaluated Using Multidetector CT

Abstract:

Purpose: To evaluate using quantitative analysis on chest CT images a possible lung volume reduction in Long COVID patients who complain mild respiratory symptoms, with chest CT negative for inflammatory findings.
Materials and Methods: CT images of patients from 18 to 40 years old who underwent chest CT scan at our institution were analyzed retrospectively, using AwServer Thoracic VCAR software for a quantitative study. Exclusion criteria were inflammatory findings at CT, previous lung surgery, lung cancer, and breath artifacts that invalidate the quality of images. Patients were divided into two groups: in the first one (“post-COVID”) were patients who had previous SARS-CoV-2 infection, confirmed by an RT-PCR, who underwent chest CT from 3 to 6 months after their negativization for long COVID symptoms; in the control group (“non-COVID”), were enrolled patients who underwent a chest CT scan from January 2018 to December 2019, before the spread of COVID in Italy.
Results: Our final population included 154 TC, 77 post-COVID patients (mean age 33 ± 6) and 77 non-COVID patients (mean age 33 ± 4.9). Non statistical significative differences were obtained between groups in terms of age, sex, and other characteristics that affect total lung capacity such as obesity, thoracic malformations, and smoking habit. Mean values of the total lung volume (TV), right-lung volume (RV), and left-lung volume (LV) in the post-COVID group compared with non-COVID group were, respectively: 5.25 ± 0.25 L vs. 5.72 ± 0.26 L (p = 0.01); 2.76 ± 0.14 L vs. 3 ± 0.14 L (p = 0.01); 2.48 ± 0.12 L vs. 2.72 ± 0.12 L (p = 0.01).
Conclusion: In patients with symptoms suggesting Long COVID and negative chest CT macroscopic findings, quantitative volume analysis demonstrated a mean value of reduction in lung volume of 10% compared to patients of the same age who never had COVID. A chest CT negative for inflammatory findings may induce clinicians to attribute Long COVID mild respiratory symptoms to anxiety, especially in young patients. Our study brings us beyond appearances and beyond the classic radiological signs, introducing a quantitative evaluation of lung volumes in these patients. It is hard to establish to what extent this finding may contribute to Long COVID symptoms, but this is another step to gain a wider knowledge of the potential long-term effects caused by this new virus.
Source: Bellini D, Capodiferro P, Vicini S, Rengo M, Carbone I. Long COVID in Young Patients: Impact on Lung Volume Evaluated Using Multidetector CT. Tomography. 2023; 9(4):1276-1285. https://doi.org/10.3390/tomography9040101 https://www.mdpi.com/2379-139X/9/4/101 (Full text)
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Use Of Total-Body Pet Imaging To Identify Deep-Tissue Sars-Cov-2 Viral Reservoirs And T Cell Responses In Patients With Long Covid

Project Summary:

This study is the first in the world to use advanced imaging technologies to identify deep tissue SARS-CoV-2 reservoirs and T cell activity in LongCovid study participants. Specifically the team will use longitudinal ImmunoPET-CT imaging of radiolabeled SARS-CoV-2-specific monoclonal antibodies (mAbs) to identify SARS-CoV-2 tissue reservoirs in individuals with Long COVID. The project team is also using ImmunoPET-CT imaging to identify the spatial and temporal dynamics of tissue-based T cell activity in Long COVID study participants.

Tissue biopsy samples from the lymph node and gut will also be collected from Long COVID study participants undergoing imaging. These tissue samples will be analyzed for SARS-CoV-2 RNA, spike, and nucleocapsid proteins, other chronic viruses (e.g., Epstein-Barr virus and cytomegalovirus), and cellular immune responses. Data collected on the tissue samples will be correlated with the imaging data, so that potential viral reservoirs and T cell activity in study participants can be validated by overlapping methods.

Read full article HERE.

Development and measurement properties of the PEM/PESE activity questionnaire (PAQ)

Abstract:

Background: Existing instruments often are inappropriate to measure the effects of post-exertional malaise (PEM) and post-exertional symptom exacerbation (PESE) on activities of daily living (ADLs). A validated questionnaire to measure self-reported ability with ADLs would advance research and clinical practice in conditions like myalgic encephalomyelitis and Long Covid.

Objective: Determine the measurement properties of the PEM/PESE Activity Questionnaire (PAQ).

Methods: The PAQ is adapted from the Patient Specific Functional Scale. Respondents rated three self-selected ADLs on two 0-100 scales, including current performance compared to (1) a ‘good day’ and (2) before illness. Respondents provided a Burden of Functioning rating on a 0-100 scale, anchored at 0 being the activity took “No time, effort, and resources at all” and 10 being “All of my time, effort, and resources.” Respondents took the PAQ twice, completing a demographic questionnaire after the first PAQ and before the second PAQ. Descriptive statistics and intraclass correlation coefficients were calculated for each scale to assess test-retest reliability. Minimum detectable change outside the 95% confidence interval (MDC95) was calculated. Ceiling and floor effects were determined when the MDC95 for average and function scores crossed 0 and 100, respectively.

Results: n = 981 responses were recorded, including n = 675 complete surveys. Test-retest reliability was generally fair to excellent, depending on function and scale. MDC95 values generally indicated scale responsiveness. Ceiling and floor effects were noted infrequently for specific functions.

Conclusion: The PAQ is valid, reliable, and sensitive. Additional research may explore measurement properties involving functions that were infrequently selected in this sample.

Source: Davenport TE, Stevens SR, Stevens J, Snell CR, Van Ness JM. Development and measurement properties of the PEM/PESE activity questionnaire (PAQ). Work. 2023 Mar 13. doi: 10.3233/WOR-220553. Epub ahead of print. PMID: 36938768. https://content.iospress.com/articles/work/wor220553 (Full text)

Understanding pediatric long COVID using a tree-based scan statistic approach: an EHR-based cohort study from the RECOVER Program

Abstract:

Objectives: Post-acute sequalae of SARS-CoV-2 infection (PASC) is not well defined in pediatrics given its heterogeneity of presentation and severity in this population. The aim of this study is to use novel methods that rely on data mining approaches rather than clinical experience to detect conditions and symptoms associated with pediatric PASC.

Materials and methods: We used a propensity-matched cohort design comparing children identified using the new PASC ICD10CM diagnosis code (U09.9) (N = 1309) to children with (N = 6545) and without (N = 6545) SARS-CoV-2 infection. We used a tree-based scan statistic to identify potential condition clusters co-occurring more frequently in cases than controls.

Results: We found significant enrichment among children with PASC in cardiac, respiratory, neurologic, psychological, endocrine, gastrointestinal, and musculoskeletal systems, the most significant related to circulatory and respiratory such as dyspnea, difficulty breathing, and fatigue and malaise.

Discussion: Our study addresses methodological limitations of prior studies that rely on prespecified clusters of potential PASC-associated diagnoses driven by clinician experience. Future studies are needed to identify patterns of diagnoses and their associations to derive clinical phenotypes.

Conclusion: We identified multiple conditions and body systems associated with pediatric PASC. Because we rely on a data-driven approach, several new or under-reported conditions and symptoms were detected that warrant further investigation.

Source: Lorman V, Rao S, Jhaveri R, Case A, Mejias A, Pajor NM, Patel P, Thacker D, Bose-Brill S, Block J, Hanley PC, Prahalad P, Chen Y, Forrest CB, Bailey LC, Lee GM, Razzaghi H. Understanding pediatric long COVID using a tree-based scan statistic approach: an EHR-based cohort study from the RECOVER Program. JAMIA Open. 2023 Mar 14;6(1):ooad016. doi: 10.1093/jamiaopen/ooad016. PMID: 36926600; PMCID: PMC10013630. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10013630/ (Full text)

Predictors of Long-COVID-19 and its Impact on Quality of Life: Longitudinal Analysis at 3, 6 and 9 Months after Discharge from a Portuguese Centre

Abstract:

Introduction: Long-COVID-19 impacts health-related quality of life (HR-QoL) but data is scarce. The aim of this study was to describe and prospectively assess the prevalence and risk factors for long-COVID-19 after hospital discharge, and to evaluate its impact on patient HR-QoL.

Material and methods: Single-centre longitudinal study including all COVID-19 patients discharged between December 2020 and February 2021. Patients were contacted remotely at three, six and nine months. Data were collected as follows: 1) Long-COVID-19 symptoms were self-reported; 2) HRQoL were assessed using the 3-level EuroQoL-5D (EQ-5D-3L) questionnaire. Pregnant women, demented, bedridden, and non-Portuguese-speaking patients were excluded.

Results: The three-, six- and nine-month assessments were completed by 152, 117 and 110 patients (median age: 61 years; male sex: 56.6%). Long-COVID-19 (≥ 1 symptom) was reported by 66.5%, 62.4% and 53.6% of patients and HR-QoL assessment showed impairment of at least some domain in 65.8%, 69.2% and 55.4% of patients at three, six and nine months, respectively. Fatigue was the most common long-COVID-19 symptom. Anxiety/depression domain was the most frequently affected in all three time-points, peaking at six months (39%), followed by pain/discomfort and mobility domains. Long-COVID-19 was associated with the impairment of all EQ-5D-3L domains except for self-care domain at each time-point. Neither intensive care unit admission nor disease severity were associated with long-COVID-19 nor with impairment of any EQ-5D-3L domain. After adjusting for sex, age, frailty status, and comorbid conditions, long-COVID-19 remained significantly associated with HR-QoL impairment at three (OR 4.27, 95% CI 1.92 – 9.52, p < 0.001), six (OR 3.46, 95% CI 1.40 – 8.57, p = 0.007) and nine months (OR 4.13, 95% CI 1.62 – 10.55, p = 0.003) after hospital discharge. In a longitudinal analysis, patients reporting long-COVID-19 at three months had an EQ-5D-3L index value decreased by 0.14 per visit (p < 0.001) compared to those without long-COVID-19 and both groups had a non-significant change in mean EQ-5D-3L index over the nine-month period (time-point assessment, Z = 0.91, p = 0.364).

Conclusion: Clinical sequelae associated with long-COVID-19 can persist for at least nine months after hospital discharge in most patients and can impair long-term HR-QoL in more than half of patients regardless of disease severity, and clinicodemographic characteristics.

Source: Gaspar P, Dias M, Parreira I, Gonçalves HD, Parlato F, Maione V, Atalaia Barbacena H, Carreiro C, Duarte L. Predictors of Long-COVID-19 and its Impact on Quality of Life: Longitudinal Analysis at 3, 6 and 9 Months after Discharge from a Portuguese Centre. Acta Med Port. 2023 Feb 24. doi: 10.20344/amp.19047. Epub ahead of print. PMID: 36827994. https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/19047 (Full text)

Organ and cell-specific biomarkers of Long-COVID identified with targeted proteomics and machine learning

Abstract:

Background: Survivors of acute COVID-19 often suffer prolonged, diffuse symptoms post-infection, referred to as “Long-COVID”. A lack of Long-COVID biomarkers and pathophysiological mechanisms limits effective diagnosis, treatment and disease surveillance. We performed targeted proteomics and machine learning analyses to identify novel blood biomarkers of Long-COVID.

Methods: A case-control study comparing the expression of 2925 unique blood proteins in Long-COVID outpatients versus COVID-19 inpatients and healthy control subjects. Targeted proteomics was accomplished with proximity extension assays, and machine learning was used to identify the most important proteins for identifying Long-COVID patients. Organ system and cell type expression patterns were identified with Natural Language Processing (NLP) of the UniProt Knowledgebase.

Results: Machine learning analysis identified 119 relevant proteins for differentiating Long-COVID outpatients (Bonferonni corrected P < 0.01). Protein combinations were narrowed down to two optimal models, with nine and five proteins each, and with both having excellent sensitivity and specificity for Long-COVID status (AUC = 1.00, F1 = 1.00). NLP expression analysis highlighted the diffuse organ system involvement in Long-COVID, as well as the involved cell types, including leukocytes and platelets, as key components associated with Long-COVID.

Conclusions: Proteomic analysis of plasma from Long-COVID patients identified 119 highly relevant proteins and two optimal models with nine and five proteins, respectively. The identified proteins reflected widespread organ and cell type expression. Optimal protein models, as well as individual proteins, hold the potential for accurate diagnosis of Long-COVID and targeted therapeutics.

Source: Patel MA, Knauer MJ, Nicholson M, Daley M, Van Nynatten LR, Cepinskas G, Fraser DD. Organ and cell-specific biomarkers of Long-COVID identified with targeted proteomics and machine learning. Mol Med. 2023 Feb 21;29(1):26. doi: 10.1186/s10020-023-00610-z. PMID: 36809921; PMCID: PMC9942653. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9942653/ (Full text)

An Exploratory Factor Analysis of Long Covid

Abstract:
An exploratory factor analysis (EFA) can provide a window into the latent dimensions of a disease, such as Long COVID.
Discovering the latent factors of Long COVID enables researchers and clinicians to better conceptualize, study and treat
this disease.
In this study, participants were recruited from social media sites dedicated to COVID and Long COVID. Among the 480 participants, those who completed at least 90% of the survey, reported symptoms for two or more months since COVID-19 symptom onset, and had not been hospitalized for COVID were used in the EFA. The mean duration since initial symptom onset was 74.0 (37.3) weeks.
A new questionnaire called The DePaul Symptom Questionnaire-COVID was used to assess self-reports of the frequency and severity of 38 Long COVID symptoms experienced over the most recent month. The most burdensome symptoms were “Symptoms that get worse after physical or mental activities (also known as Post-Exertional Malaise),” “Fatigue/extreme tiredness,” “Difficulty thinking and/or concentrating,” “Sleep problems,” and “Muscle aches.” The EFA resulted in a three-factor model with factors labeled General, PEM/Fatigue/Cognitive Dysfunction, and Psychological, consisting of 16, 6, and 3 items respectively (25 items in total).
The reliability of the items in the EFA was .90 using a split-half reliability test. Finally, participant self-reported level of
functional impairment was analyzed across the three EFA factors. Interpretations and applications to research and
practice are provided.
Source: Joseph A. Dorri1 and Leonard A. Jason. An exploratory factor analysis of long covid. Central Asian Journal of Medical Hypotheses and Ethics. 2/14/23 https://www.researchgate.net/publication/368502945_AN_EXPLORATORY_FACTOR_ANALYSIS_OF_LONG_COVID (Full text)

Assessment of short- and long-term functionality and quality of life in patients with post-acute COVID-19 syndrome

Abstract:

Background: Although the number of new cases of coronavirus 2019 (COVID-19) has been drastically reduced worldwide, patients who demonstrate long-term symptoms need more attention from health systems, as these symptoms can negatively affect functionality and quality of life.

Objective: To evaluate muscle function and quality of life at 3, 6, 9 and 12 months in patients with post-acute COVID-19 syndrome and to assess their associations with general fatigue and lung function.

Methods: This observational and longitudinal study evaluated patients with post-acute COVID-19 syndrome. Participants were subjected to the following evaluations: Short Form-36; handgrip strength; Functional Assessment of Chronic Illness Therapy-Fatigue scale; and spirometry.

Results: Among the 350 participants who were evaluated in the third month, 74.6%, 61.4% and 45.4% reported general fatigue, dyspnoea and cough, respectively. In the comparisons between the third month and the sixth month, there were significant increases in Functional Assessment of Chronic Illness Therapy-Fatigue scale, pulmonary function and several Short Form-36 domains. In the comparisons between the sixth month and the ninth month, there was a significant increase only in the social functioning domain of the Short Form-36. In the comparisons between the ninth month and the twelfth month, there was an increase only in some Short Form-36 domains. Significant correlations were observed between the Short Form-36 domains with Functional Assessment of Chronic Illness Therapy-Fatigue scale, handgrip strength and pulmonary function.

Conclusion: In patients with post-acute COVID-19 syndrome, there was a progressive improvement in quality of life, general fatigue and pulmonary function during the 12 months of follow-up, with this improvement being more pronounced in the first 6 months. There was a relationship between functionality and quality of life in these patients.

Source: de Azevedo Vieira JE, Mafort TT, Monnerat LB, da Cal MS, Ghetti ATA, Lopes AJ. Assessment of short- and long-term functionality and quality of life in patients with post-acute COVID-19 syndrome. J Back Musculoskelet Rehabil. 2023 Feb 2. doi: 10.3233/BMR-220308. Epub ahead of print. PMID: 36776041. https://content.iospress.com/articles/journal-of-back-and-musculoskeletal-rehabilitation/bmr220308 (Full text)

Compliance challenges in a longitudinal COVID-19 cohort using wearables for continuous monitoring

Abstract:

Background: Wearables to Investigate the Long Term Cardiovascular and Behavioral Impacts of COVID-19 (WEAICOR) study is a prospective observational study using continuous monitoring to detect and analyze biometrics. Compliance to wearables was a major challenge when conducting the study and was crucial for the results.

Objective: The aim of this study is to evaluate patients’ compliance to wearable wristbands and determinants of compliance in a prospective COVID-19 cohort.

Methods: Biostrap wearable device was used to monitor participants’ biometric data. Compliance was calculated by dividing the total number of days in which transmissions were sent by the total number of days in the study. Univariate correlation was performed between compliance, days in the study and age, BMI, sex, symptom severity, and number of complications/comorbidites as independent variables. Also, multivariate linear regression was then performed with days in the study as a dependent variable to assess the power of different parameters in determining days in the study.

Results: On hundred twenty-two patients were included in the study. Patients were on average 43 years old and 32% were female. Age was found to be correlated with compliance (r=0.23, P=0.01). In addition, age (r=0.30, P=0.001), BMI (r=0.19, P=0.03) and severity of symptoms (r=0.19, P=0.03) were found to be correlated with days spent in the study. On multivariate analysis with days spent in the study as a dependent variable, only increased age was a significant determinant of compliance with wearables (adjusted R2 = 0.1, β = 1.6, P= 0.01).

Conclusions: Compliance is a major obstacle in remote monitoring studies and the reasons for a lack thereof are multifactorial. Patient factors such as age, in addition to environmental factors can affect compliance to wearables.

Source: Mekhael M, Ho C, Noujaim C, Assaf A, Younes H, El Hajjar AH, Chaudhry HA, Lanier B, Chouman N, Makan N, Shan B, Zhang Y, Dagher L, Kreidieh O, Marrouche N, Donnellan E. Compliance challenges in a longitudinal COVID-19 cohort using wearables for continuous monitoring. J Med Internet Res. 2023 Jan 6. doi: 10.2196/43134. Epub ahead of print. PMID: 36763647. https://preprints.jmir.org/preprint/43134/accepted (Full text available as PDF file)

Improvement of Long COVID symptoms over one year

Abstract:

Importance: Early and accurate diagnosis and treatment of Long COVID, clinically known as post-acute sequelae of COVID-19 (PASC), may mitigate progression to chronic diseases such as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Our objective was to determine the utility of the DePaul Symptom Questionnaire (DSQ) to assess the frequency and severity of common symptoms of ME/CFS, to diagnose and monitor symptoms in patients with PASC.

Methods: This prospective, observational cohort study enrolled 185 people that included 34 patients with PASC that had positive COVID-19 test and persistent symptoms of >3 months and 151 patients diagnosed with ME/CFS. PASC patients were followed over 1 year and responded to the DSQ at baseline and 12 months. ME/CFS patients responded to the DSQ at baseline and 1 year later. Changes in symptoms over time were analyzed using a fixed-effects model to compute difference-in-differences estimates between baseline and 1-year follow-up assessments.

Participants: Patients were defined as having PASC if they had a previous positive COVID-19 test, were experiencing symptoms of fatigue, post-exertional malaise, or other unwellness for at least 3 months, were not hospitalized for COVID-19, had no documented major medical or psychiatric diseases prior to COVID-19, and had no other active and untreated disease processes that could explain their symptoms. PASC patients were recruited in 2021. ME/CFS patients were recruited in 2017.

Results: At baseline, patients with PASC had similar symptom severity and frequency as patients with ME/CFS and satisfied ME/CFS diagnostic criteria. ME/CFS patients experienced significantly more severe unrefreshing sleep and flu-like symptoms. Five symptoms improved significantly over the course of 1 year for PASC patients including fatigue, post-exertional malaise, brain fog, irritable bowel symptoms and feeling unsteady. In contrast, there were no significant symptom improvements for ME/CFS patients.

Conclusion and relevance: There were considerable similarities between patients with PASC and ME/CFS at baseline. However, symptoms improved for PASC patients over the course of a year but not for ME/CFS patients. PASC patients with significant symptom improvement no longer met ME/CFS clinical diagnostic criteria. These findings indicate that the DSQ can be used to reliably assess and monitor PASC symptoms.

Source: Oliveira CR, Jason LA, Unutmaz D, Bateman L, Vernon SD. Improvement of Long COVID symptoms over one year. Front Med (Lausanne). 2023 Jan 9;9:1065620. doi: 10.3389/fmed.2022.1065620. PMID: 36698810; PMCID: PMC9868805. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9868805/ (Full text)