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1.
Sci Rep ; 14(1): 19049, 2024 08 17.
Artigo em Inglês | MEDLINE | ID: mdl-39152190

RESUMO

Patients recovering from COVID-19 commonly exhibit cognitive and brain alterations, yet the specific neuropathological mechanisms and risk factors underlying these alterations remain elusive. Given the significant global incidence of COVID-19, identifying factors that can distinguish individuals at risk of developing brain alterations is crucial for prioritizing follow-up care. Here, we report findings from a sample of patients consisting of 73 adults with a mild to moderate SARS-CoV-2 infection without signs of respiratory failure and 27 with infections attributed to other agents and no history of COVID-19. The participants underwent cognitive screening, a decision-making task, and MRI evaluations. We assessed for the presence of anosmia and the requirement for hospitalization. Groups did not differ in age or cognitive performance. Patients who presented with anosmia exhibited more impulsive alternative changes after a shift in probabilities (r = - 0.26, p = 0.001), while patients who required hospitalization showed more perseverative choices (r = 0.25, p = 0.003). Anosmia correlated with brain measures, including decreased functional activity during the decision-making task, thinning of cortical thickness in parietal regions, and loss of white matter integrity. Hence, anosmia could be a factor to be considered when identifying at-risk populations for follow-up.


Assuntos
Anosmia , Encéfalo , COVID-19 , Imageamento por Ressonância Magnética , SARS-CoV-2 , Humanos , COVID-19/complicações , COVID-19/psicologia , COVID-19/fisiopatologia , COVID-19/diagnóstico por imagem , COVID-19/patologia , Anosmia/etiologia , Anosmia/fisiopatologia , Masculino , Feminino , Pessoa de Meia-Idade , Adulto , Encéfalo/diagnóstico por imagem , Encéfalo/patologia , Encéfalo/fisiopatologia , SARS-CoV-2/isolamento & purificação , Idoso , Tomada de Decisões , Cognição/fisiologia
2.
medRxiv ; 2024 Aug 26.
Artigo em Inglês | MEDLINE | ID: mdl-38826460

RESUMO

Objective: Long COVID, marked by persistent, recurring, or new symptoms post-COVID-19 infection, impacts children's well-being yet lacks a unified clinical definition. This study evaluates the performance of an empirically derived Long COVID case identification algorithm, or computable phenotype, with manual chart review in a pediatric sample. This approach aims to facilitate large-scale research efforts to understand this condition better. Methods: The algorithm, composed of diagnostic codes empirically associated with Long COVID, was applied to a cohort of pediatric patients with SARS-CoV-2 infection in the RECOVER PCORnet EHR database. The algorithm classified 31,781 patients with conclusive, probable, or possible Long COVID and 307,686 patients without evidence of Long COVID. A chart review was performed on a subset of patients (n=651) to determine the overlap between the two methods. Instances of discordance were reviewed to understand the reasons for differences. Results: The sample comprised 651 pediatric patients (339 females, M age = 10.10 years) across 16 hospital systems. Results showed moderate overlap between phenotype and chart review Long COVID identification (accuracy = 0.62, PPV = 0.49, NPV = 0.75); however, there were also numerous cases of disagreement. No notable differences were found when the analyses were stratified by age at infection or era of infection. Further examination of the discordant cases revealed that the most common cause of disagreement was the clinician reviewers' tendency to attribute Long COVID-like symptoms to prior medical conditions. The performance of the phenotype improved when prior medical conditions were considered (accuracy = 0.71, PPV = 0.65, NPV = 0.74). Conclusions: Although there was moderate overlap between the two methods, the discrepancies between the two sources are likely attributed to the lack of consensus on a Long COVID clinical definition. It is essential to consider the strengths and limitations of each method when developing Long COVID classification algorithms.

3.
J Pediatr ; 257: 113358, 2023 06.
Artigo em Inglês | MEDLINE | ID: mdl-36822507

RESUMO

Using an electronic health record-based algorithm, we identified children with Coronavirus disease 2019 (COVID-19) based exclusively on serologic testing between March 2020 and April 2022. Compared with the 131 537 polymerase chain reaction-positive children, the 2714 serology-positive children were more likely to be inpatients (24% vs 2%), to have a chronic condition (37% vs 24%), and to have a diagnosis of multisystem inflammatory syndrome in children (23% vs <1%). Identification of children who could have been asymptomatic or paucisymptomatic and not tested is critical to define the burden of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 infection in children.


Assuntos
COVID-19 , Humanos , Criança , COVID-19/complicações , COVID-19/diagnóstico , Síndrome de COVID-19 Pós-Aguda , SARS-CoV-2 , Estudos de Coortes , Registros Eletrônicos de Saúde , Anticorpos Antivirais , Progressão da Doença , Teste para COVID-19
4.
J Clin Med ; 12(1)2022 Dec 22.
Artigo em Inglês | MEDLINE | ID: mdl-36614901

RESUMO

BACKGROUND: Heart rate variability is a non-invasive, measurable, and established autonomic nervous system test. Long-term COVID-19 sequelae are unclear; however, acute symptoms have been studied. OBJECTIVES: To determine autonomic cardiac differences between long COVID-19 patients and healthy controls and evaluate associations among symptoms, comorbidities, and laboratory findings. METHODS: This single-center study included long COVID-19 patients and healthy controls. The heart rate variability (HRV), a quantitative marker of autonomic activity, was monitored for 24 h using an ambulatory electrocardiogram system. HRV indices were compared between case and control groups. Symptom frequency and inflammatory markers were evaluated. A significant statistical level of 5% (p-value 0.05) was adopted. RESULTS: A total of 47 long COVID-19 patients were compared to 42 healthy controls. Patients averaged 43.8 (SD14.8) years old, and 60.3% were female. In total, 52.5% of patients had moderate illness. Post-exercise dyspnea was most common (71.6%), and 53.2% lacked comorbidities. CNP, D-dimer, and CRP levels were elevated (p-values of 0.0098, 0.0023, and 0.0015, respectively). The control group had greater SDNN24 and SDANNI (OR = 0.98 (0.97 to 0.99; p = 0.01)). Increased low-frequency (LF) indices in COVID-19 patients (OR = 1.002 (1.0001 to 1.004; p = 0.030)) and high-frequency (HF) indices in the control group (OR = 0.987 (0.98 to 0.995; p = 0.001)) were also associated. CONCLUSIONS: Patients with long COVID-19 had lower HF values than healthy individuals. These variations are associated with increased parasympathetic activity, which may be related to long COVID-19 symptoms and inflammatory laboratory findings.

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