Persisting Symptoms After COVID-19
Prevalence and Risk Factors in a Population-Based Cohort
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Background: After recovering from coronavirus disease 2019 (COVID-19), a considerable number of patients report long-term sequelae. The epidemiologic data vary widely in the studies published to date, depending on the study design and the patient cohorts analyzed. Using a population-based approach, we report symptoms and clinical characteristics following COVID-19 (long COVID), focusing on symptoms ≥ 12 weeks (post-COVID-19).
Methods: In three German administrative districts, all adult patients with a diagnosis of COVID-19 confirmed by polymerase chain reaction (PCR) between March and September 2020 (n = 4632) were invited to complete a questionnaire. Predictors for post-COVID-19 were identified by multiple ordinal regression analysis. Study registration: DRKS00023069.
Results: A total of 1459 patients were included in the study, 175 (12%) of whom had been hospitalized for treatment of the acute phase of COVID-19. The prevalence of post-COVID-19 was 72.6% (n = 127) and 46.2% (n = 588) for hospitalized and non-hospitalized patients, respectively. The most frequently occurring long-term symptoms were fatigue (41.5% of all symptoms ≥ 12 weeks, n = 297), physical exhaustion (40.8%, n = 292), difficulty in concentrating (30.6%, n = 219), and loss of the senses of taste (25.9%, n = 185) and smell (25.5%, n = 182). Quality of life was significantly impaired in patients with post-COVID-19. The strongest risk factors for post-COVID-19 were female sex, overall severity of comorbidities, and severity of acute COVID-19.
Conclusion: Patients who are not hospitalized also frequently experience continued symptoms following COVID-19. The heterogeneity of symptoms calls for a multidisciplinary stepped-care approach, for which identification of patients at risk is crucial. A limitation of the study is the lack of a control group.
A considerable proportion of patients infected with the novel coronavirus-2 (SARS-CoV-2) continue to experience symptoms after recovery from the acute phase of coronavirus disease 2019 (COVID-19). These long-term conditions manifest in a wide range of symptoms, such as fatigue, dyspnea, and cognitive dysfunction (1, 2, 3, 4). There is ongoing discussion on the definition and terminology of sequelae after COVID-19 (long COVID). In the present study, the term post-COVID-19 refers to all symptoms persisting at least 12 weeks after COVID-19, irrespective of the etiology. The 12-week duration was defined by the National Institute for Health and Care Excellence (NICE) and a consensus conference of the World Health Organization (WHO), and has been adopted in the the German clinical practice guideline (5, 6, 7).
The reported prevalences differ by study design, the definition of post-COVID-19 applied, and the sample analyzed (8). The literature and systematic reviews report a prevalence of 33–87% in cohorts hospitalized for treatment of acute COVID-19, whereas studies with non-hospitalized patients report lower prevalences of between 2% and 53% (1, 9, 10). However, most studies have investigated small (11, 12) or non-representative samples (13, 14) or included participants without positive SARS-CoV-2 test results (15). Due to the heterogeneity in the existing evidence, the Long-COVID Forum and other groups recently defined as a research priority the identification of clinical characteristics, comorbidities, and potential risk factors of post-COVID-19, particularly in non-hospitalized or population-based cohorts (3, 16, 17).
The aims of this study were:
- To report the prevalence of symptoms following COVID-19
- To describe the clinical characteristics
- To identify potential predictive factors in a population-based retrospective cohort in Germany
The study was conducted as a total population survey in three German administrative districts (Reutlingen, Tübingen, Enzkreis) with a total of 715 268 inhabitants. In Germany, every person who tests positive for infection with SARS-CoV-2 is registered by the local health office. These offices sent out a questionnaire to all adult patients with a positive polymerase chain reaction (PCR) test between 1 March and 30 September 2020 (n = 4632).
We asked participants retrospectively to recall the symptoms they experienced due to COVID-19 and to specify symptom duration. Based on the NICE guideline, patients were divided into the following groups:
- Acute COVID-19 (symptoms for 0–4 weeks)
- Ongoing COVID-19 (4–12 weeks)
- Post-COVID-19 (≥ 12 weeks)
For reasons of clarity, patients without symptoms and symptoms < 12 weeks are presented in the same column of the relevant Tables. For the multiple ordinal logistic regression, we combined participants with acute and ongoing COVID-19 into one category, resulting in an outcome variable with three categories (no symptoms, symptom duration < 12 weeks, symptom duration ≥ 12 weeks). Goodness of fit was assessed by means of a likelihood ratio test comparing the fitted model to a model with varying location parameters. We conducted multiple imputation to replace missing values. Backward selection was used to select variables, taking account of p-values between 0.05 and 0.10. Age and sex were included in all models. More detail can be found in the eMethods.
By 31 January 2021, a total of 1907 questionnaires (41%) had been returned. Of those, 448 were excluded (eMethods), so the final study population comprised 1459 participants.
The median age of the participants was 53 years (interquartile range [IQR] 37–62); n = 824 (56.5%) of the participants were women. This is in line with the total 4632 confirmed COVID-19 cases in the districts (median age 48 years, 52.7% women; eTable 1). The mean duration of follow-up was 219 days (standard deviation [SD] 32.6). A total of 175 (12%) participants received hospital treatment for COVID-19. Further details are shown in Table 1.
Prevalence of symptoms following COVID-19
No symptoms during or after COVID-19 were reported by 8.3% (n = 121), while 33.0% (n = 481) had at least one COVID-19-related symptom for < 4 weeks (acute COVID-19), 9.4% (n = 137) had at least one symptom that lasted for 4 to < 12 weeks (ongoing COVID-19), and 49.3% (n = 720) had at least one symptom ≥ 12 weeks after the infection (post-COVID-19). Among hospitalized and non-hospitalized participants, the prevalence of post-COVID-19 was 72.6% (n = 127) and 46.2% (n = 588), respectively.
The most frequently occurring symptoms among patients with post-COVID-19 were:
- Fatigue or lethargy (41.5%, n = 297)
- Physical exhaustion (40.8%, n = 292)
- Difficulty concentrating (30.6%, n = 219)
- Loss of sense of taste (25.9%, n = 185)
- Loss of sense of smell (25.5%, n = 182)
Figure 1 displays the percentage occurrence of all symptoms reported for a duration of < 12 weeks or ≥ 12 weeks.
Table 2 shows the post-COVID-19 symptoms with immediate onset (within the first 2 weeks of the infection) versus delayed onset (at least 2 weeks after infection). Most symptoms were present from the beginning of the infection. The only symptoms that often had delayed onset were skin lesions and hair loss.
Characteristics of patients with post-COVID-19
Patients with post-COVID-19 were older, more often female, had a significantly lower health-related quality of life (HrQoL), and had more days of sick leave (Table 1). The overall burden of comorbidity correlated with a higher risk of post-COVID-19, as did most of the specific chronic conditions such as hypertension, heart and lung disease, and depression (Table 3, eTable 2). Polypharmacy and intake of most of the long-term medications also correlated with a higher risk of post-COVID-19 (eTable 3).
Patients with post-COVID-19 more often took medication such as antibiotics, anticoagulants, or analgesics during the acute phase of acute COVID-19 (eTable 4).
Predictors of post-COVID-19
Univariate ordinal logistic regression identified only a small number of variables that proved to be potential predictors for long-term sequelae (Table 4). The strongest predictors for post-COVID-19 identified here were:
- Female sex (odds ratio [OR] 1.81, 95% confidence interval [1.45; 2.24])
- The overall burden of comorbidity with an OR of 1.10 per point in the Self-Administered Comorbidity Questionnaire (SCQ-D; maximum 45 points) [1.06; 1.14)
- Hospitalization for acute COVID-19 (OR 2.01 [1.54; 2.64)
- The need for analgesics during acute COVID-19 (OR 1.70 [1.19; 2.45)
The last two points are surrogates for a severe course of the acute infection.
Nursing home residents had a lower risk of post-COVID-19 (OR 0.09 [0.05; 0.17]). No positive or negative association was found for smoking, specific comorbidities, regular medication, other specific medication for COVID-19, polypharmacy, or age.
Prevalence and symptoms
The present study is one of the largest so far to investigate the prevalence of symptoms following COVID-19 in a population-based cohort. A total of 1273 (87.3%) participants were not hospitalized for treatment of their acute COVID-19.
While previous studies mostly described mixed cohorts with varying proportions of non-hospitalized and hospitalized participants, we present data for non-hospitalized and hospitalized patients separately. At least one post-COVID-19 symptom was reported by 46.2% (n = 588) of the non-hospitalized and 72.6% (n = 127) of the hospitalized patients. Compared with previous smaller studies that were also based on the NICE and WHO definition of post-COVID-19, there is good agreement (e1, e2, e3, e4).
The most frequently mentioned symptoms in the post-COVID-19 group were fatigue or lethargy (n = 297, 41.5%) and rapid physical exhaustion (n = 292, 40.8%), followed by difficulty concentrating (n = 219, 30.6%). Although the reported frequency of these symptoms varies very widely between studies, recent reviews confirm that fatigue is a predominant symptom (2, 3). Considering the heterogeneity of symptoms, however, it should be discussed whether these conditions represent phenotypes of one and the same entity or whether they result from different pathophysiology. In contrast, loss of the sense of taste and/or smell is thought to be a rather specific symptoms of COVID-19 and was reported to persist ≥ 12 weeks by n = 185 (25.9%) and n = 182 (25.5%), respectively. In the general population, the self-reported frequency of problems with taste and smell is 0.4% and 1.6%, respectively (e5).
Considerations on pathophysiology
Most participants in our study reported that their long-term symptoms had been present since the beginning of the infection. However, skin lesions and hair loss were mostly reported with a delay in symptom onset. Whether these differences in time of onset are due to different pathophysiological causes is currently a matter for discussion. Persistence of symptoms from the onset could support the hypothesis of residual viral particles to which the organism reacts as in the acute phase (18, 19), while delayed symptom onset could indicate immunological dysregulation (20). Moreover, direct viral toxicity the severity of the acute illness might also influence the underlying pathophysiology, the latter potentially causing hair loss and skin lesions (21).
On the other hand, some symptoms following COVID-19 may not be specific for SARS-CoV-2 but could be caused by another etiology and/or triggered by social effects of the pandemic; this is particularly likely for fatigue and mental health problems (22, 23). Some conditions reported by hospitalized patients could also be caused by post-intensive care syndrome (PICS) or post-traumatic stress disorder (PTSD) following an ICU stay (e6, e7). The lack of a control group in this study means it is not possible to differentiate between post-COVID-19 and symptoms with other causes.
Implications for health care
The quality of life was lower in the post-COVID-19 group, particularly in hospitalized participants. This is consistent with previous reports (e1, e2). Periods of sick leave were longer in patients with post-COVID-19, presumably reflecting the disabling character of the symptoms. Studies from the USA and other countries report that 40% of patients had not returned to regular work by 60 days after discharge and that 22.3% were still not back to work after a median of 7 months (15, 24). Considering the still growing number of infections, this could have a major economic impact.
The heterogeneity of symptoms calls for multidisciplinary management, coordinated by primary care specialists (5, 25). Referrals to specialists should be limited to patients with specific needs (stepped-care approach). Local cross-specialty networks with multidisciplinary boards, supplemented by specialty units from the inpatient sector, could improve the care of these patients (26, 27, 28). In addition, the identification of patients at risk for developing post-COVID-19 will help to set the course of treatment and develop structured management strategies.
Predictors of post-COVID-19
The regression analysis revealed that hospitalization for COVID-19 and the need for analgesics during the acute phase of COVID-19 were risk factors for post-COVID-19. This suggests an association of acute infection severity with the risk of developing post-COVID-19, as previously reported by other study groups (29, 30). It is therefore plausible that convalescence is prolonged in patients who were immobilized during the acute infection or had severe pulmonary pathology resulting in post-critical illness, persisting dyspnea, PTSD, or PICS (31, 32, 33).
Another strong predictor for post-COVID-19 was the overall burden of comorbidity. Patients with post-COVID-19 were more likely to have chronic concomitant diseases, were more often on regular medication, and had a higher rate of polypharmacy. This is in line with other studies that also show an association between preexisting comorbidity and the risk of developing post-COVID-19 (13, 34).
Consistent with previous studies, we found that female sex was associated with an increased risk of developing post-COVID-19 (4, 14, 35, 36). Other studies also reported more advanced age as an independent risk factor for post-COVID-19 (35), which was not confirmed by our multiple regression analysis.
Interestingly, we found that higher educational qualifications were also a predictor for post-COVID-19. This could not attributed to age differences and may therefore be in line with a study showing that persons with higher education levels develop depressive symptoms and a greater decline in life satisfaction during the pandemic more often than others (37). However, this could indicate that these symptoms are not specific for COVID-19.
Living in a nursing home seemed to protect against developing post-COVID-19. This may be due to a healthy patient effect, since those nursing home residents who survive COVID-19 presumably possess greater resilience (38).
Strengths and limitations
A major limitation of this study is the lack of a control group. This means that it is not possible to distinguish between symptoms specific for COVID-19 and symptoms arising from other causes.
Reports of prevalence vary substantially among previous studies owing to differences in study design. In the present study, we therefore chose a population-based approach and found an overall post-COVID-19 prevalence of 49.3% in hospitalized and non-hospitalized patients. After standardization for age, gender, and district with the data known for all of the 4632 patients contacted (eTable 1), this sensitivity analysis yielded only a slight reduction in prevalence to 47.4%. Nonetheless, sampling bias is very likely and could have led to an overestimation of the prevalence of post-COVID-19, since patients with long-term sequelae would be more likely to participate than those without. The most conservative estimation would count all of the non-responders as not having post-COVID-19, resulting in a post-COVID-19 prevalence of 14.6% for non-hospitalized and 22.9% for hospitalized patients, given that 31.5% of the questionnaires distributed were included for statistical analysis.
Growing media attention to post-COVID-19 may influence both patients and medical staff and could also have led to overestimation of symptoms (39). All data derived from patients’ self-reports and may have been biased by patients having to recall their symptoms and duration of illness retrospectively. Another possible bias is the number of persons with higher educational status.
The data from a large population-based cohort indicate that long-term health consequences are a frequent burden even after a moderate acute course of COVID-19. Health care professionals can take advantage of these findings to improve their understanding of these patients’ symptoms and care needs and to identify patients at risk. Within the spectrum of post-COVID-19 symptoms, further studies are needed with a focus on the most disabling sequelae and should include a control group in order to distinguish between post-COVID-19 and symptoms from other causes.
Major medical and socio-economic challenges are posed when some patients are unable to attain their previous state of health or return to work owing to functional impairment and reduced quality of life (40). Interdisciplinary local networks based on a stepped-care approach will be key to the treatment strategy for this complex disease.
This work was supported by the Ministry of Science, Research, and Art of Baden-Württemberg through the special funding program for COVID-19 research, a component of the medical research package to combat the SARS-CoV-2 pandemic.
We thank the health authorities in Reutlingen, Tuebingen and Enzkreis for supporting this study. We thank Dr. Hannah Fuhr for critical reading of the manuscript and Jasmin Mangold, Raphaela Samrock, and Lena Gassner for their assistance with data acquisition.
Conflict of interest statement
All authors declare that no conflict of interest exists.
Manuscript submitted on 10 December 2021, revised version accepted on 10 February 2022
Dr. med. Christian Förster
Institut für Allgemeinmedizin und interprofessionelle Versorgung
Osianderstr. 5, 72076 Tübingen, Germany
Cite this as:
Förster C, Colombo MG, Wetzel AJ, Martus P, Joos S:
Persisting symptoms after COVID-19—prevalence and risk factors
in a population-based cohort. Dtsch Arztebl Int 2022; 119: 167–74. DOI: 10.3238/arztebl.m2022.0147
eReferences, eMethods, eTables:
Institute for Clinical Epidemiology and Applied Biometrics, University Hospital Tübingen: Prof. Dr. rer. nat. Peter Martus
Center for Public Health and Healthcare Research, University Hospital Tübingen: Prof. Dr. med. Stefanie Joos
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