Factors influencing patient’s perception during COVID-19 recovery

In a recent study posted to medRxiv*, a team of researchers characterized individual-level illness perception, both cognitive and emotional, following coronavirus disease 2019 (COVID-19).

Study: Persistent somatic symptoms are key to individual illness perception at one year after COVID-19. Image Credit: fizkes/Shutterstock
Study: Persistent somatic symptoms are key to individual illness perception at one year after COVID-19. Image Credit: fizkes/Shutterstock

Background

Studies have shown that the individual illness perception following acute COVID-19 influences how one copes later, adjusts to chronic persistent symptoms and health conditions, and complies with the prevention, treatment, and rehabilitation practices. Likewise, as for the general population, COVID-19 patients have all severe illness perceptions, including anxiety, depression, and stress.

The post-COVID-19 syndrome has a broad range of patient-reported manifestations. A sizable fraction of COVID-19 patients report having somatic symptoms, cardiopulmonary pathology, and mental health disorders. Although these characteristics are not always consistent; yet, it is crucial to characterize them because they pose significant healthcare costs and socioeconomic burdens.

About the study

In the present study, researchers examined a cross-sectional COVID-19 convalescent collective to investigate the severity of overall illness perception and the illness perception components. All the participating individuals had unresolved somatic symptoms or COVID-19-related lung and heart pathology up to one year after disease onset. The cognitive aspect of illness perception covered self-perceived disease symptoms, consequences, expected duration and effect of COVID-19 treatment, personal control, and understanding of the disease. The emotional components encompassed COVID-19-related fear, anger, or distress.

The team recruited the study participants between April and June 2020. All the eligible participants were 18 years or older and had symptomatic reverse transcription-polymerase chain reaction (RT-PCR)-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The team scheduled follow-up visits for all the participants at two, three, six months, and one year after COVID-19 diagnosis.

In particular, the study analyzed the following COVID-19-related persistent somatic symptoms - physical performance, dyspnea, self-reported cough, night sweating, sleep disorders, anosmia, fatigue, hair loss, and dermatological and gastrointestinal symptoms. Further, the researchers analyzed lung function test (LFT) abnormalities, chest computed tomography (CT), and trans-thoracic echocardiography (TTE) severity scores. The primary and secondary analysis endpoints of the study were illness perception score values and (Brief Illness Perception Questionnaire (BIPQ) component scores, respectively. The team used penalized multi-parameter regression and unsupervised clustering to identify factors influencing these endpoints.

Study findings

A total of 145 individuals enrolled for the study; however, the final study population comprised 74 individuals due to the high patient dropout rate. The majority of participants (65%) were male, with a median age of 56. The researchers classified them based on COVID-19 severity as ambulatory, moderate, and severe COVID-19 survivors, with the first subset comprising 20% of participants having the lowest median age, least smokers, and lowest comorbidity frequency.

The researchers discerned four factors, including fatigue scoring, reduced physical performance, hair loss, and pre-existing respiratory comorbidity, explaining 47% of overall illness perception variance one year after COVID-19. The effect of age, gender, COVID-19 severity, or residual lung lesions was negligible in CT and LFT findings. Likewise, the authors noted negligible to no heart abnormality in TTE. Notably, all participants with multiple residual somatic symptoms and moderate-to-severe acute COVID-19 had high levels of COVID-19-related emotional concerns.

The authors used the Likert and bimodal Chalder’s Fatigue Scales (CFS) to rate fatigue at a one-year follow-up visit. They identified fatigue as a strong covariate of overall illness perception scoring in COVID-19 survivors. Studies have established similar effects of chronic fatigue in arthritis and hematological malignancy. Further, clustering analysis identified three subsets of participants differing in key illness perception components at the one-year follow-up. Nearly 50% of this subset displayed low severity of overall illness perception, 27% of participants showed a similarly low level of persistent fatigue, and the remaining minor cluster suffered from multiple somatic issues.

The last subset of study participants had residual lung lesions in CT, severe COVID-19 course, significant fatigue, sleep problems, and hair loss, all of which pointed to intense emotional representation. These people could benefit most from psychological and psychiatric interventions for the post-COVID-19 syndrome.

Conclusions

Previous literature has linked illness perception to other chronic conditions, such as chronic obstructive pulmonary disease. However, according to the authors, this is the first study evaluating the severity and components of illness perception in COVID-19 convalescents. It demonstrated that negative illness perceptions could perpetuate symptoms in somatoform disorders resulting in higher future healthcare expenditure.

Furthermore, the study highlighted the need for combining persistent somatic symptoms and clinical assessment results to showcase a complete picture of the post-COVID-19 syndrome. Most importantly, it emphasized that proper rehabilitation and psychiatric resource allocation for managing this condition requires an in-depth understanding of the interplay between persistent somatic symptoms and individual illness perceptions.

*Important notice

medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

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