Respiratory Symptoms, Pulmonary Function and Lung CT Findings in Patients with Post-COVID-19 Syndrome: A Systematic Review and Meta-Analysis

The global COVID-19 pandemic has had an unprecedented deleterious impact. According to the WHO, the novel SARS-CoV-2 virus is responsible for 6.97 million deaths worldwide, with more than 771 million cumulative cases reported so far [1]. Since the beginning of the pandemic at the end of 2019, “It has become increasingly clear that patients recovering from acute COVID-19 are developing persistent symptoms that are not explained by any other underlying conditions.” A growing body of evidence has shown that survivors of the acute illness of COVID-19 are experiencing symptoms and signs that cannot be explained by an alternative etiology or a previous illness. As early as 2020, many studies that supported this conclusion began to emerge [2,3]. The time of onset of these manifestations varied greatly, from 2 weeks after PCR-confirmed infection with COVID-19, to more than a year [4, 5]. Consequences included signs and symptoms following acute COVID-19 (or newly developed), usually long-term respiratory (dyspnea, cough, excessive sputum production), as well as various new non-respiratory complaints, most often neuropsychiatric, dermatological, and other less common manifestations [6,7,8]. Many healthcare regulatory authorities worldwide have attempted to classify these signs and symptoms by time of onset and duration, as well as other attributes. Despite this, there is no internationally agreed clinical definition or clear treatment pathway, and the evidence base on this topic is a living and evolving matter. The UK’s National Institute for Health and Care Excellence (NICE), in collaboration with the Scottish Intercollegiate Guidelines Network (SIGN) and the Royal College of General Practitioners (RCGP), recognizes three separate entities associated with SARS-CoV-2 infection, formulated as clinical case definitions: acute COVID-19, ongoing symptomatic COVID-19 and post-COVID-19 syndrome [9]. According to previous guidelines, post-COVID-19 syndrome is recognized as “Signs and symptoms that develop during or after an infection consistent with COVID-19, persist for more than 12 weeks, and cannot be explained by an alternative diagnosis”. Post-COVID-19 syndrome continues to be a challenge in determining the best practice standards of care due to evolving evidence, while it can have significant impact on quality of life. Therefore, a summary of available evidence in the literature at a given time could be useful in further clarifying its nature and creating a strategy for management. In this context, we conducted a systematic review and meta-analysis to determine, with regard to the NICE clinical case definition, the respiratory profile of patients who experienced post-COVID-19 syndrome and had a previously laboratory-confirmed SARS-CoV-2 infection. The respiratory profile consisted of the prevalence of respiratory symptoms, the prevalence of abnormal Pulmonary Function Tests (PFTs) and Chest Computed Tomography (CT) findings, as well as the mean values of PFTs parameters.

We systematically searched across four databases: PubMed, Google Scholar, Research Gate and Elsevier, to identify the studies that were conducted in the period January 2020 - June 2022. The search terms used as keywords in the databases search engines were: post-COVID-19 syndrome (and synonyms such as post-COVID syndrome, long-COVID-19 syndrome, long-COVID-19, Post-COVID, Long-COVID, Post SARS-CoV-2, Long SARS-CoV-2), respiratory symptoms (or respiratory sequelae, respiratory complications), dyspnea (or dyspnoea), cough, sputum (or sputum production), CT scan (or lung CT scan, chest CT scan, CT scan findings), ground glass opacifications, bronchiectasis, parenchymal bands, COPD, asthma, lung fibrosis (or pulmonary fibrosis), spirometry findings (or spirometry results), FEV1, FVC, FEV1/FVC ratio (or Tiffeneau index), RV, TLC, 6-minute walking distance test, DLCO (or lung diffusion capacity), mMRC (or mMRC score). The terms referring to the post-COVID-19 entity were combined with the rest of the search terms using the Boolean Logical Operator (AND).

The individual references were screened by three investigators (I.R., N.G. and N.M). All duplicate references were removed from the reference pool and the remaining references were first screened based on their abstract and title. If they were excluded by merit of the exclusion criteria of this systematic review and meta-analysis, they were subjected to a full text screening by the same three investigators. (I.R., N.G. and N.M). All disagreements and problems in the selection process were resolved through consultation and under the guidance of the fourth author (Z.N.). If all inclusion criteria were met, an individual study was included in the final draft of this systematic review and meta-analysis. For all the studies included quality assessment by one author (I.R.) was performed. Data extraction was performed by three authors. (I.R., N.G. and N.M). The data were then compared, and the extraction process was assessed by the three authors in consultation with and under the guidance of the fourth author (Z.N.). From the included studies we extracted outcome data and study characteristics in a standardized data collection form. The collection form for the statistical analysis of pooled prevalence for each separate outcome contained the total number of events (patients with the target outcome), the total number of participants and the percentage of outcomes among the study’s participants. Studies without data on total events (outcomes) and/or total participants were excluded from the analysis for that particular outcome. If a study contained data on the total number of events (outcomes) and the total participants but not on the percentage of target outcomes among the study participants, the study was not excluded, and the percentage was calculated by dividing the total number of events (outcomes) by the total number of participants. If a study contained data on the total participants and the exact percentage of people with the target outcome, but not on the number of participants with the target event, the number of events was calculated by using the above data.

One review author (I.R.) conducted an independent risk of bias assessment for each study included in the review and meta-analysis using the “Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Studies Reporting Prevalence Data.” Each study’s full text and supplementary materials were submitted to analysis to answer the nine questions included in the questionnaire. Whenever needed, the review author consulted the three remaining authors to discuss the correct definitions and resolve issues. Each study’s overall risk of bias was classified as low, medium, or high, based on the summation of the risk of bias for each individual category for that study. In addition, for each of the studies used for the synthesis of an outcome the results for each question of the checklist were pooled together and presented in the form of a graph to evaluate the risk of bias for each category of that particular outcome.

We report the prevalence of all primary outcomes: respiratory symptoms (dyspnea, cough, increased and/or new sputum production), mMRC scores (≥ 1, and ≥ 2), PFTs results that deviate from normal range of values (DLCO/VA(KCO), DLCO, TLC, RV, FEV1 and FVC below 80% of predicted value, FEV1/FVC ratio below 70% of predicted value), chest CT-scan findings (ground-glass opacities, consolidation, bronchiectasis and/or bronchial dilation, interlobular septal thickening, reticular pattern, fibrosis and/or fibrotic lung changes, atelectasis, pulmonary nodules, emphysema, honeycombing, mixed ground-glass opacities, sub-pleural lines, line-like and/or band-like opacities), as well as overall prevalence of abnormal chest CT findings. Pertaining to the secondary outcomes we report the mean values of PFTs [6-minute walking distance (6MWD) score value (in meters), DLCO as % of predicted value, FEV1 value (in liters), and FVC value (in liters)], as well as FEV1, FVC, FEV1/FVC ratio, RV, and TLC as % of predicted value.

Statistical analysis and the creation of plots were carried out by one author (I.R.). For each of the primary and secondary outcomes a forest plot was constructed. We pooled the prevalence of each of the primary outcomes using the Freeman-Tukey double arcsine transformation method. We calculated the single means of each secondary outcome using a Restricted Maximum Likelihood Model (REML). The combined measurements of effect for each primary and secondary outcome were obtained under a random-effects model due to the expected heterogeneity between studies in prognostic reviews. Statistical heterogeneity was measured through the I² statistic and expressed as either low (I² <25%), moderate (I² =25–50%) or high (I² >50%). All statistical analyses were carried out with a confidence interval (CI) of 95%. To assess the risk of publication bias, funnel plots were constructed and visually analyzed. The certainty of evidence for each of the reported outcomes was assessed using the Grading of Recommendations, Assessment, Development, And Evaluations (GRADE) system. All the statistical analysis and the creation of plots were performed using the software program R Studio.

We conducted meta-analyses based on the available data on each outcome of each study. We tried to retrieve missing data where there was any. However, where missing data was not retrieved, it was not imputed either.

There were no patients involved in the development of this protocol.

This review does not require ethics approval as this is a systematic review of other published studies and does not directly involve patients. The results of this review will be submitted to a peer-reviewed journal for publication and will be available on publicly accessible institutional websites.

The initial search identified 13,675 potential studies from four databases: PubMed (n=6225), Google Scholar (n=3308), Research Gate (n=2605) and Scopus (n=1537). Out of these, 5812 publications were left after removing the duplicates (n=7003) and removing publications not written in English (n=860). The remaining 5812 abstracts were screened, and 4989 abstracts were excluded. Out of the remaining 823 abstracts, only two full texts could not be retrieved, so 821 studies’ full texts were assessed for eligibility. Out of them, 378 studies were excluded for having a follow-up period less than 12 weeks after an acute COVID-19 infection, 185 for not having a PCR or laboratory-confirmed acute COVID-19 infection for all study participants, 121 studies for having less than 30 participants, 51 studies for including patients with an ongoing acute COVID-19 infection in the follow-up, 36 studies for not being adequate (e.g., letters to the editor and reviews), 8 studies for having an insufficient gender ratio, and one study was retracted. Overall, 780 studies were excluded, and the remaining 41 studies were included in this systematic review and meta-analysis.

The studies included in this systematic review and meta-analysis were conducted in 13 different countries: China (n=11), Spain (n=8), Italy (n=4), France (n=3), India (n=3), United Kingdom (n=2), Iran (n=2), Switzerland (n=2), Germany (n=1), Finland (n=1), Chile (n=1), Australia (n=1), Turkey (n=1), and Brazil (n=1). The final selection included 32 prospective studies, 6 retrospective studies, 1 cross-sectional study, 1 ambidirectional study, and 1 retrospective case-series.

A total of 17,565 participants were enrolled. The smallest sample size was 39 and the largest was 4682. Participants included 50.9% males (8,938/17,565) and 49.1% females (8,655/17,565), with a maximum male predominance of 78.8% and maximum female predominance of 72.4%. Mean age ranged from 41.2 ± 12.8 years to 71 ± 5.56 years.

According to the “Joanna Briggs Institute (JBI) Critical Appraisal Checklist,” 7 studies were rated low quality (high risk of bias), 33 studies moderate quality (moderate risk), and 1 study high quality (low risk). Details are available in Supplementary file S5.

All outcomes were rated as having very low certainty of evidence, mainly due to observational design and serious risk of bias (Supplementary file S7).

The sensitivity and subgroup analysis results, along with forest plots, are included in the Mendeley Data Repository [56].

This review included the most common respiratory symptoms: dyspnea, cough, and increased/new sputum production, along with mMRC scores (≥ 1 and ≥ 2) for comparison. Dyspnea was most common at 0.25 (CI 0.19–0.31, p<0.01, I²=98%), followed by cough at 0.11 (CI 0.07–0.16, p<0.01, I²=96%) and sputum production at 0.07 (CI 0.02–0.16, p<0.01, I²=95%). mMRC scores were 0.47 (CI 0.31–0.63, p<0.01, I²=96%) for ≥1 and 0.10 (CI 0.05–0.16, p<0.01, I²=90%) for ≥2.

CT findings typical of pneumonia and COVID-19 were common. Overall prevalence of abnormal lung findings was 0.62 (CI 0.49–0.75, p<0.01, I²=96%). The most common findings were:

DLCO <80% had the highest prevalence at 0.37 (CI 0.29–0.46, p<0.01, I²=90%). Other abnormal PFT results:

Mean values were calculated for various PFT parameters. The lowest was DLCO at 85.77 (CI 80.02–91.51, I²=95%) and FEV1/FVC at 81.78 (CI 76.49–87.06, I²=99%). Highest values included FVC at 100.72 (CI 95.86–105.58), RV at 100.90 (CI 70.79–131.02), and VC at 106.00 (CI 104.43–107.58). FEV1 was 98.50, FVC was 101.82, and FEV1/FVC in liters was 2.85 and 3.62 respectively. 6MWD averaged 531.04 meters (CI 510.90–551.18).

In our systematic review and meta-analysis, a significant proportion of patients experienced dyspnea as a manifestation of post-COVID-19 syndrome. Dyspnea as part of the post-COVID-19 syndrome has been reported not only in patients with severe forms of acute COVID-19 but also in those with mild COVID-19 [57]. Mechanisms of dyspnea are very complex and include reflex stimulation of chemoreceptors, afferent signals through C-fibers of the vagal nerve and activation in the limbic system of the brain [58]. Afferent information from reflex stimulation of peripheral sensors in the form of chemoreceptors and/or vagal C-fibers is processed centrally in the limbic system and the sensorimotor cortex, resulting in increased neural output to the respiratory muscles. Dysfunction in the ventilatory response caused by paralysis, muscle weakness, as well as increased mechanical load in the muscle, generates an afferent impulse from the lungs vagal receptors (and possibly mechanoreceptors in the respiratory muscles) to the sensorimotor cortex, which then results in the sensation of dyspnea [58]. In the case of a COVID-19 infection, this dysfunction of the ventilatory response could be caused by vascular damage to the respiratory chest muscles, as SARS-CoV-2 has been shown to cause vascular and endothelial damage and thereby compromise tissue perfusion in the body [59]. Potential hypoxia of the respiratory muscles could reduce the number of respirations per minute, which would lead to the accumulation of carbon dioxide, which could then stimulate the C-fibers of the vagal nerve and, through the action of the previously mentioned cascade, lead to a feeling of dyspnea. However, a primary origin in the central nervous system cannot be ruled out, as it has been proven that SARS-CoV-2 disrupts the blood-brain barrier and thereby allows entry into the central nervous system [60]. Cough had the second highest prevalence of all the respiratory symptoms in our systematic review and meta-analysis, ranging from 2% [37] to 61.3% [32]. The hypothesized mechanisms of cough in the post-COVID-19 syndrome are similar to those of post-COVID-19 dyspnea, and include viral neuro-tropism, neuro-inflammation, and neuro-immune responses [61]. Interactions between the vagal nerve and the airway vagus, precipitated by neuro-inflammation, may play a key role in the initiation and maintenance of cough [62]. Newly detected and/or increased sputum production had the lowest prevalence among respiratory symptoms in our analysis. An interesting finding in patients with severe COVID-19 infections requiring intubation is the production of sputum with thicker consistency due to greater solid and protein contents, a finding that bears more similarity with sputum in patients with cystic fibrosis than it does with sputum in healthy control subjects [63]. A hypothetical explanation of the thicker respiratory secretions in severe acute forms of COVID-19 is the dysregulation of neutrophil extracellular traps and neutrophil elastase that occurs during the hyper-inflammatory immune response [64]. Spirometry is a very useful diagnostic and prognostic tool in the evaluation of a number of respiratory diseases. By quantifying the respiratory volumes, capacities and flows, such as Forced Vital Capacity (FVC) and Forced Expiratory Volume at First and Sixth second (FEV1 and FEV6, respectfully), and the relationship between some of these parameters (FEV1/FVC ratio), the obstructive ventilatory defect can be detected with high sensitivity and specificity, and it is possible to classify the severity in response to inhaled bronchodilator [65]. The reference values of the parameters measured with spirometry (and body-plethysmography, accordingly), when expressed in percentages of predicted values, are in the range of 80–120% for FEV1, FVC, and TLC, 75%–120% for RV, and 75%–120% for FRC [66]. The single mean values for each of the spirometry parameters in our systematic review and meta-analysis fell well within the normal expected range, while the results of pooled prevalence varied from approximately 9% for some of the parameters (FEV1, FVC) to one third for some of the other parameters (RV). Our finding is in accordance with previous studies of spirometry in patients during and after viral pneumonia. Reversible airflow limitation has been demonstrated in patients with acute respiratory infections, with a strong association between symptoms, such as cough and dyspnea, and low FEV1 in patients without previous asthma and COPD [67]. The Six-Minute Walking Distance (6MWD) is a sub-maximal exercise test to assess aerobic capacity and endurance in individuals. The distance walked is affected by the function of many organ systems, thus the 6MWD cannot be exclusively classified as a PFT. Nevertheless, it has a wide range of applicability in the assessment of lung function. In our meta-analysis the average value for walking distance was within the range predicted for healthy individuals (400 to 700 meters) [68]. The recommended reference values for DLCO, a measurement that quantifies the ability of the lungs to transfer carbon monoxide from inspired air into the bloodstream, are in the range of 75–140% of predicted values [69, 70]. In the studies included in our systematic review and meta-analysis, the prevalence of DLCO values varied across studies from 25% [29] to 58.1% [47]. This difference may be due to different follow-up periods between the studies, the characteristics of the patient populations, and/or the presence of previous undiagnosed respiratory illnesses that decrease DLCO. It is well known that DLCO can be decreased in interstitial lung diseases and pulmonary fibrosis due to the thickening of alveolar-capillary membrane or destruction of the alveoli [71]. Both mechanisms may be implicated for the decreased DLCO values in patients with post-COVID-19 syndrome, especially in patients with radiological lung changes at follow-up. The three most common changes in lung CT scans at ≥ 12 months after the initial PCR-confirmed COVID-19 infection were ground-glass opacities, fibrosis, and/or fibrotic-like changes, and pulmonary nodules. When the lungs were involved during acute COVID-19 infection, the most common CT findings within the first five days of diagnosis were ground-glass opacities or mixed findings of ground-glass opacities and consolidation with peripheral and sub-pleural distribution [72]. A parallel could be drawn between the similarity of lung CT scan changes found in acute COVID-19 infection and those found in the post-COVID-19 period, implying that the post-COVID-19 lung CT changes could be a continuum of the changes during an acute COVID-19 infection. This continuation has already been demonstrated in studies examining follow-up CT scans after other types of viral pneumonia, with some persistence of acute radiologic findings during the resolution/improvement or worsening of the initial lesions [73, 74]. In our systematic review, the major limitations in some of the studies were: the lack of baseline lung CT scan to be compared with the follow-up CT scans, and the lack of evidence if the patients experienced any other viral pneumonia in the window between acute COVID-19 and the follow-up period, or have had alternative pre-existing lung disease to which the lung CT scan changes could be attributed to. Regarding comparison with other systematic review and/or meta-analyses, several parallels can be drawn. To the best of our knowledge, this is the first systematic review and meta-analysis that combines the prevalence of most common respiratory symptoms experienced in post-COVID-19 syndrome with the most common lung CT findings and PFTs results. In similar systematic reviews and/or meta-analyses, the pooled prevalence of dyspnea among post-COVID-19 patients was, in ascending order, 18% [75], 24% [76], 26% [77], and 32% [78]. Cough, the second most common symptom in our meta-analysis, had a prevalence in other systematic reviews of 13% [78], 19% [76], and 25% [79]. In terms of residual lung changes on CT-scans in post-COVID-19 patients, the two most common findings in other meta-analyses were ground-glass opacities and fibrotic-like changes [80, 81], which is similar to findings in our systematic review and meta-analysis. Systematic reviews and/or meta-analyses examining PFTs revealed that 39% of post-COVID-19 patients experienced an altered DLCO, while 15% and 7% had a restrictive or obstructive ventilatory pattern, respectively [82].

The main limitations of this systematic review and meta-analysis arose mainly from different follow-up times, uneven sample sizes, and variations in the definition and criteria for some of the outcomes in different studies, as well as the unavailability of patients’ baseline chest CT scans. As for the first two issues, there is very little space left for correction, because they are influenced by factors that are not even related to the disease (e.g. the impossibility of conducting the same time monitoring for all participants due to patient unavailability and/or uncooperativeness, scarce resources and financing, lack of logistics, etc.). The same could be said about the different definitions and measurements of each outcome in the included studies. The symptom reporting is subjective; however, we attempted to correct the dyspnea outcome by including mMRC scores for comparison.

The lack of available information on whether the patients had previous lung changes on lung CT scans and history of previous respiratory diseases (including those that can cause lung changes visible on CT scan) is another limitation of this systematic review, as it is uncertain what percentage of the recorded CT scan outcomes can be attributed to COVID-19 and post-COVID-19 syndrome versus other viral illnesses and other pre-existing conditions.

Patients with post-COVID-19 syndrome show persistent or newly developed respiratory symptoms, altered pulmonary function test findings and abnormal lung CT scan patterns. The most common respiratory symptom is dyspnea, the most prevalent abnormal PFT parameter is RV, and the most common abnormal lung CT scan finding are ground glass opacities. The results of this systematic review must be analyzed with caution as they may be influenced by previous respiratory comorbidities, alternative viral illnesses during the follow-up period and the severity of the acute COVID-19 infection. Future research on post-COVID-19 syndrome should be focused on the early recognition and adequate treatment of post-COVID-19 syndrome and other associated comorbidities. The data collected in this systematic review could serve as a good starting point for that purpose. We believe that the insight and understanding of the health status and respiratory profile in post-COVID-19 syndrome could aid for its timely recognition and accurate diagnosis, as well as further research in terms of prevention and early mitigation of these sequelae, and improvement of quality of life.

This systematic review did not receive any funding.

The datasets, as well as forest plots and funnel plots of this systematic review and meta-analysis are available on Datasets and supplementary files for Respiratory symptoms, pulmonary function and lung CT findings in patients with post-COVID-19 syndrome: a systematic review and meta-analysis - Mendeley Data.

The authors declare no conflict of interest.

All authors contributed equally in all aspects of the creation of this systematic review, unless stated otherwise in the full text. All writers approved the final manuscript.

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