Tag: long covid diagnosis

High Prevalence of Alternative Diagnoses in Children and Adolescents with Suspected Long COVID-A Single Center Cohort Study

Abstract:

Background: Long COVID (LC) is a diagnosis that requires exclusion of alternative somatic and mental diseases. The aim of this study was to examine the prevalence of differential diagnoses in suspected pediatric LC patients and assess whether adult LC symptom clusters are applicable to pediatric patients.

Materials and methods: Pediatric presentations at the Pediatric Infectious Diseases Department of the University Hospital Essen (Germany) were assessed retrospectively. The correlation of initial symptoms and final diagnoses (LC versus other diseases or unclarified) was assessed. The sensitivity, specificity, negative and positive predictive values of adult LC symptom clusters were calculated.

Results: Of 110 patients, 32 (29%) suffered from LC, 52 (47%) were diagnosed with alternative somatic/mental diseases, and 26 (23%) remained unclarified. Combined neurological and respiratory clusters displayed a sensitivity of 0.97 (95% CI 0.91-1.00) and a negative predictive value of 0.97 (0.92-1.00) for LC.

Discussion/conclusions: The prevalence of alternative somatic and mental diseases in pediatric patients with suspected LC is high. The range of underlying diseases is wide, including chronic and potentially life-threatening conditions. Neurological and respiratory symptom clusters may help to identify patients that are unlikely to be suffering from LC.

Source: Goretzki SC, Brasseler M, Dogan B, Hühne T, Bernard D, Schönecker A, Steindor M, Gangfuß A, Della Marina A, Felderhoff-Müser U, Dohna-Schwake C, Bruns N. High Prevalence of Alternative Diagnoses in Children and Adolescents with Suspected Long COVID-A Single Center Cohort Study. Viruses. 2023 Feb 20;15(2):579. doi: 10.3390/v15020579. PMID: 36851793; PMCID: PMC9961131. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9961131/ (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)

Long COVID could become a widespread post-pandemic disease? A debate on the organs most affected

Abstract:

Long COVID is an emerging problem in the current health care scenario. It is a syndrome with common symptoms of shortness of breath, fatigue, cognitive dysfunction, and other conditions that have a high impact on daily life. They are fluctuating or relapsing states that occur in patients with a history of SARS-CoV-2 infection for at least 2 months. They are usually conditions that at 3 months after onset cannot be explained by an alternative diagnosis. Currently very little is known about this syndrome.

A thorough review of the literature highlights that the cause is attributable to deposits of tau protein. Massive phosphorylation of tau protein in response to SARS-CoV-2 infection occurred in brain samples from autopsies of people previously affected with COVID-19. The neurological disorders resulting from this clinical condition are termed tauopathies and can give different pathological symptoms depending on the involved anatomical region of the brain.

Peripheral small-fiber neuropathies are also evident among patients with Long COVID leading to fatigue, which is the main symptom of this syndrome. Certainly more research studies could confirm the association between tau protein and Long COVID by defining the main role of tau protein as a biomarker for the diagnosis of this syndrome that is widespread in the post-pandemic period.

Source: Ferrara, F., Zovi, A., Masi, M. et al. Long COVID could become a widespread post-pandemic disease? A debate on the organs most affected. Naunyn-Schmiedeberg’s Arch Pharmacol (2023). https://doi.org/10.1007/s00210-023-02417-5 https://link.springer.com/article/10.1007/s00210-023-02417-5 (Full text)

ME/CFS and Post-Exertional Malaise among Patients with Long COVID

Abstract:

This study sought to ascertain the prevalence of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) among a sample of 465 patients with Long COVID. The participants completed three questionnaires: (1) a new questionnaire measuring both the frequency and severity of 38 common symptoms of COVID and Long COVID, (2) a validated short form questionnaire assessing ME/CFS, and (3) a validated questionnaire measuring post-exertional malaise.
The population was predominantly white, female, and living in North America. The mean duration since the onset of COVID-19 symptoms was 70.5 weeks. Among the 465 participants, 58% met a ME/CFS case definition. Of respondents who reported that they had ME/CFS only 70.57% met criteria for ME/CFS and of those who did not report they had ME/CFS, 29.43% nevertheless did meet criteria for the disease: both over-diagnosis and under-diagnosis were evident on self-report. This study supports prior findings that ME/CFS occurs with high prevalence among those who have persistent COVID-19 symptoms.
Source: Jason LA, Dorri JA. ME/CFS and Post-Exertional Malaise among Patients with Long COVID. Neurology International. 2023; 15(1):1-11. https://doi.org/10.3390/neurolint15010001 https://www.mdpi.com/2035-8377/15/1/1 (Full text)

Elevated vascular transformation blood biomarkers in Long-COVID indicate angiogenesis as a key pathophysiological mechanism

Abstract:

Background: Long-COVID is characterized by prolonged, diffuse symptoms months after acute COVID-19. Accurate diagnosis and targeted therapies for Long-COVID are lacking. We investigated vascular transformation biomarkers in Long-COVID patients.

Methods: A case–control study utilizing Long-COVID patients, one to six months (median 98.5 days) post-infection, with multiplex immunoassay measurement of sixteen blood biomarkers of vascular transformation, including ANG-1, P-SEL, MMP-1, VE-Cad, Syn-1, Endoglin, PECAM-1, VEGF-A, ICAM-1, VLA-4, E-SEL, thrombomodulin, VEGF-R2, VEGF-R3, VCAM-1 and VEGF-D.

Results: Fourteen vasculature transformation blood biomarkers were significantly elevated in Long-COVID outpatients, versus acutely ill COVID-19 inpatients and healthy controls subjects (P < 0.05). A unique two biomarker profile consisting of ANG-1/P-SEL was developed with machine learning, providing a classification accuracy for Long-COVID status of 96%. Individually, ANG-1 and P-SEL had excellent sensitivity and specificity for Long-COVID status (AUC = 1.00, P < 0.0001; validated in a secondary cohort). Specific to Long-COVID, ANG-1 levels were associated with female sex and a lack of disease interventions at follow-up (P < 0.05).

Conclusions: Long-COVID patients suffer prolonged, diffuse symptoms and poorer health. Vascular transformation blood biomarkers were significantly elevated in Long-COVID, with angiogenesis markers (ANG-1/P-SEL) providing classification accuracy of 96%. Vascular transformation blood biomarkers hold potential for diagnostics, and modulators of angiogenesis may have therapeutic efficacy.

Source: Patel, M.A., Knauer, M.J., Nicholson, M. et al. Elevated vascular transformation blood biomarkers in Long-COVID indicate angiogenesis as a key pathophysiological mechanism. Mol Med 28, 122 (2022). https://doi.org/10.1186/s10020-022-00548-8 https://molmed.biomedcentral.com/articles/10.1186/s10020-022-00548-8 (Full text)

Inflammation and autoreactivity define a discrete subset of patients with post-acute sequelae of COVID-19, or long-COVID

Abstract:

While significant attention has been paid to the immunologic determinants of disease states associated with COVID-19, their contributions to post-acute sequelae of COVID-19 (PASC) remain less clear. Due to the wide array of PASC presentations, it is critical to understand if specific features of the disease are associated with discrete immune processes, and whether those processes may be therapeutically targeted. To this end, we performed wide immunologic and serological characterization of patients in the early recovery phase of COVID-19 across a breadth of symptomatic presentations.

Using high-parameter proteomics screening and applied machine learning (ML), we identify clear signatures of immunologic activity between PASC patients and uncomplicated recovery, dominated by inflammatory cytokine signaling, neutrophil activity, and markers of cell death. Consistent with disease complexity, heterogeneity in plasma profiling reveals distinct PASC subsets with striking divergence in these ongoing inflammatory processes, here termed plasma quiescent (plaq) and inflammatory (infl) PASC.

In addition to elevated inflammatory blood proteomics, inflPASC patients display positive clinical tests of acute inflammation including C-reactive protein and fibrinogen, increased B cell activity with extrafollicular involvement coupled with elevated targeting of viral nucleocapsid protein and clinical autoreactivity. Further, the unique plasma signatures of PASC patients allowed for the creation of refined models with high sensitivity and specificity for the positive identification of inflPASC with a streamlined assessment of 12 blood markers. Additionally, refined ML modeling highlights the unexpected significance of several markers of potential diagnostic or therapeutic use for PASC in general, including the peptide hormone, epiregulin.

In all, this work identifies clear biological signatures of PASC with potential diagnostic and therapeutic potential and establishes clear disease subtypes that are both easily identifiable and highly relevant to ongoing efforts in both therapeutic targeting and epidemiological investigation of this highly complex disease.

Source: Matthew Woodruff, Kevin S Bonham, Fabliha A Anam, Tiffany Walker, Yusho Ishii, Candice Y Kaminski, Martin Runnstrom, Alexander Truong, Adviteeya Dixit, Jenny Han, Richard Ramonell, Natalie S. Haddad, Mark Rudoloph, Arezou Khosroshahi, Scott A Jenks, F. Eun-Hyung Lee, Ignacio Sanz. Inflammation and autoreactivity define a discrete subset of patients with post-acute sequelae of COVID-19, or long-COVID. medRxiv 2021.09.21.21263845; doi: https://doi.org/10.1101/2021.09.21.21263845.  (Full text available as PDF file)

Differential diagnosis and pathogenesis of the neurological signs and symptoms in COVID-19 and long-COVID syndrome

Abstract:

Neurological features have now been reported very frequently in the ongoing COVID-19 pandemic caused by SARS-CoV-2. The neurological deficits associated features are observed in both acute and chronic stages of COVID-19 and they appear to overlap with wide-ranging symptoms that can be attributed to being of non-neural origins, thus obscuring the definitive diagnosis of neuro-COVID.

The pathogenetic factors acting in concert to cause neuronal injury are now emerging, with SARS-CoV-2 directly affecting the brain coupled with the neuroinflammatory factors have been implicated in the causation of disabilities in acute COVID-19 and patients with Long-COVID syndrome. As the differentiation between a neural origin and other organ-based causation of a particular neurological feature is of prognostic significance, it implores a course of action to this covert, yet important neurological challenge.

Source: Baig AM. Differential diagnosis and pathogenesis of the neurological signs and symptoms in COVID-19 and long-COVID syndrome. CNS Neurosci Ther. 2022 Sep 19. doi: 10.1111/cns.13957. Epub ahead of print. PMID: 36117492. https://onlinelibrary.wiley.com/doi/10.1111/cns.13957 (Full text)

Post-acute COVID syndrome (long COVID): What should radiographers know and the potential impact for imaging services

Abstract:

Objectives: The COVID-19 pandemic caused an unprecedented health crisis resulting in over 6 million deaths worldwide, a figure, which continues to grow. In addition to the excess mortality, there are individuals who recovered from the acute stages, but suffered long-term changes in their health post COVID-19, commonly referred to as long COVID. It is estimated there are currently 1.8 million long COVID sufferers by May 2022 in the UK alone. The aim of this narrative literature review is to explore the signs, symptoms and diagnosis of long COVID and the potential impact on imaging services.

Key findings: Long COVID is estimated to occur in 9.5% of those with two doses of vaccination and 14.6% if those with a single dose or no vaccination. Long COVID is defined by ongoing symptoms lasting for 12 or more weeks post acute infection. Symptoms are associated with reductions in the quality of daily life and may involve multisystem manifestations or present as a single symptom.

Conclusion: The full impact of long COVID on imaging services is yet to be realised, but there is likely to be significant increased demand for imaging, particularly in CT for the assessment of lung disease. Educators will need to include aspects related to long COVID pathophysiology and imaging presentations in curricula, underpinned by the rapidly evolving evidence base.

Implications for practice: Symptoms relating to long COVID are likely to become a common reason for imaging, with a particular burden on Computed Tomography services. Planning, education and updating protocols in line with a rapidly emerging evidence base is going to be essential.

Source: Alghamdi F, Owen R, Ashton REM, Obotiba AD, Meertens RM, Hyde E, Faghy MA, Knapp KM, Rogers P, Strain WD. Post-acute COVID syndrome (long COVID): What should radiographers know and the potential impact for imaging services. Radiography (Lond). 2022 Sep 12:S1078-8174(22)00119-5. doi: 10.1016/j.radi.2022.08.009. Epub ahead of print. PMID: 36109264; PMCID: PMC9468096. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9468096/ (Full text)

Disorders of gut-brain interaction in post-acute COVID-19 syndrome

Abstract:

The novel coronavirus SARS-CoV-2 is responsible for the devastating pandemic which has caused more than 5 million deaths across the world until today. Apart from causing acute respiratory illness and multiorgan dysfunction, there can be long-term multiorgan sequalae after recovery, which is termed ‘long COVID-19’ or ‘post-acute COVID-19 syndrome’. Little is known about long-term gastrointestinal (GI) consequences, occurrence of post-infection functional gastrointestinal disorders and impact the virus may have on overall intestinal health.

In this review, we put forth the various mechanisms which may lead to this entity and possible ways to diagnose and manage this disorder. Hence, making physicians aware of this spectrum of disease is of utmost importance in the present pandemic and this review will help clinicians understand and suspect the occurrence of functional GI disease post recovery from COVID-19 and manage it accordingly, avoiding unnecessary misconceptions and delay in treatment.

Source: Golla R, Vuyyuru SK, Kante B, Kedia S, Ahuja V. Disorders of gut-brain interaction in post-acute COVID-19 syndrome. Postgrad Med J. 2022 Jul 1:postgradmedj-2022-141749. doi: 10.1136/pmj-2022-141749. Epub ahead of print. PMID: 35777934. https://pmj.bmj.com/content/early/2022/07/01/pmj-2022-141749 (Full text)

Long-COVID diagnosis: From diagnostic to advanced AI-driven models

Abstract:

SARS-COV 2 is recognized to be responsible for a multi-organ syndrome. In most patients, symptoms are mild. However, in certain subjects, COVID-19 tends to progress more severely. Most of the patients infected with SARS-COV2 fully recovered within some weeks. In a considerable number of patients, like many other viral infections, various long-lasting symptoms have been described, now defined as “long COVID-19 syndrome”. Given the high number of contagious over the world, it is necessary to understand and comprehend this emerging pathology to enable early diagnosis and improve patents outcomes.

In this scenario, AI-based models can be applied in long-COVID-19 patients to assist clinicians and at the same time, to reduce the considerable impact on the care and rehabilitation unit. The purpose of this manuscript is to review different aspects of long-COVID-19 syndrome from clinical presentation to diagnosis, highlighting the considerable impact that AI can have.

Source: Cau R, Faa G, Nardi V, Balestrieri A, Puig J, Suri JS, SanFilippo R, Saba L. Long-COVID diagnosis: From diagnostic to advanced AI-driven models. Eur J Radiol. 2022 Jan 19;148:110164. doi: 10.1016/j.ejrad.2022.110164. Epub ahead of print. PMID: 35114535; PMCID: PMC8791239. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8791239/ (Full text)