What this is
- This research investigates microcirculatory and endothelial function alterations in pediatric Long COVID patients.
- It compares 37 pediatric patients with Long COVID to 46 healthy controls.
- Findings reveal significant vascular impairments, particularly in patients with dyspnea.
Essence
- Pediatric Long COVID patients exhibit significant microvascular damage and increased compared to healthy controls, particularly among those with dyspnea.
Key takeaways
- Microcirculatory alterations are evident in pediatric Long COVID patients, with reduced microvascular flow index (MFI), total vessel density (TVD), and proportion of perfused vessels (PPV) compared to controls.
- Increased is observed in Long COVID patients, suggesting potential long-term cardiovascular risks.
- Patients with dyspnea show more pronounced microvascular impairment, indicating a distinct vascular phenotype associated with respiratory symptoms.
Caveats
- The small sample size limits the generalizability of findings, as pediatric Long COVID cases are rare.
- Using historical controls may introduce temporal confounding, although sensitivity analyses yielded consistent results.
- Assessment methods may not fully capture the nuances of endothelial function in younger children, potentially affecting validity.
Definitions
- Microcirculation: The circulation of blood in the smallest blood vessels, including capillaries, which is crucial for tissue perfusion.
- Arterial stiffness: The reduced ability of an artery to expand and contract in response to pressure changes, often associated with cardiovascular risk.
Simplified
Introduction
While most patients recover rapidly from acute COVID-19, a significant proportion of 6–13% report persisting symptoms beyond the initial acute phase, including children [1–3]. These symptoms occur regardless of the severity of the initial disease and encompass a broad spectrum, including respiratory dysfunction, cardiovascular symptoms, persistent fatigue, and neurocognitive impairments [4]. Although some symptoms may appear mild in terms of clinical importance, they result in a substantial impairment of quality of life [1–3].
The terminology “Long COVID” and “post-COVID syndrome” rapidly emerged, later defined by the National Institute for Health and Care Excellence (NICE) [5]. According to this, Long COVID is defined by signs and symptoms that persist or develop after acute COVID-19, including both ongoing symptomatic COVID-19 (from 4 to 12 weeks) and post-COVID-19 syndrome (12 weeks or more) [5].
Although SARS-CoV-2 infection primarily manifests as a respiratory disease, many pathophysiological mechanisms occur at the vascular level [6]. Vascular effects, particularly microcirculatory impairment and endothelial dysfunction, have been observed in various SARS-CoV-2-related diseases including multisystem inflammatory syndrome in children (MIS-C) [7–9]. Potential pathophysiological mechanisms include direct viral toxicity, endotheliitis, microthrombosis, and immune system dysregulation with cytokine storms [10–13]. Such mechanisms may persist and contribute to pulmonary, cardiovascular, and neurological symptoms observed in Long COVID. Prolonged inflammation, either due to persistent SARS-CoV-2 infection or immune dysregulation, could further drive these effects [14–17]. Alterations in the microcirculation with persistent capillary rarefication and endothelial dysfunction have already been identified in adult patients with Long COVID [18–20].
In this study, we investigate (i) the general impact of Long COVID on microcirculation and endothelial function in a pediatric patient cohort and (ii) whether disease-specific clinical symptoms are associated with these microvascular and endothelial alterations.
Methods
Study design
This comparative cohort study included children with Long COVID, treated at the Children’s University Hospital of the LMU Munich, Germany, between December 2021 and February 2023. According to the study protocol, Long COVID patients were examined on the day of their initial presentation at our specialized multidisciplinary outpatient clinic for pediatric Long COVID patients. Both Long COVID patients and healthy controls were examined using the same SDF imaging system and the same EndoPAT device under identical conditions. Patients were examined in a single room without the presence of other patients or external distractions. The ambient temperature was maintained between 20 and 24 °C. Prior to the examination, patients were instructed to rest quietly in a supine position for 10 min. This ensures internal consistency and allows for valid comparative analysis of relative differences between groups.
This study was approved by the ethics committee of the medical faculty of Ludwig-Maximilian-University (LMU), Munich, Germany (Approval No. 22–0057) and carried out in accordance with the Declaration of Helsinki. We followed the STROBE guideline. The study is registered at the German Clinical Trials Register with the study protocol available online: https://drks.de/search/de/trial/DRKS00029642↗
Participants
Children with serological evidence of a SARS-CoV-2 infection and a diagnosis of Long COVID according to NICE criteria, presenting with persisting symptoms for more than 4 weeks after confirmed infection, were eligible [5]. To exclude the potential influence of any undetected prior SARS-CoV-2 infection, we used a control group that had been evaluated prior to the pandemic between February 2018 and April 2019. The control group consisted of healthy children with a standardized clinical workup including uneventful clinical examination and no history of infectious diseases within the past 3 weeks. Exclusion criteria for both patients and controls included a history of hemato-oncologic, rheumatologic, or cardiac conditions as well as diabetes mellitus, hypercholesterolemia, and chronic inflammatory diseases (e.g., Crohn’s disease and ulcerative colitis). Controls showing any sign of inflammation, acute illness at the investigation time-point, medical conditions or requiring continuous medication were also excluded.
Written informed consent was obtained from all participants and from the parents or legal guardians prior to study participation.
Procedures
Assessment of patients’ characteristics
Clinical patient characteristics were collected using a standard questionnaire addressing specific symptoms, pre-existing illnesses, routine clinical examinations (imaging and laboratory), and treatments. Weight, height, blood pressure, heart rate, and oxygen saturation were measured within 10 min before study examinations.
Assessment of the microcirculation
The sublingual microcirculation was visualized using a handheld video microscope (MicroScan, MicroVision Medical, Holland) with sidestream dark field (SDF) imaging technology. This microscope camera has an outer ring of greenlight-emitting diodes in the absorption maximum of hemoglobin (wavelength 530 nm) resulting in dark appearing vessels. The light penetrates the tissue and is reflected from deeper layers, enabling the transillumination of superficial layers. A central optical unit with a fivefold magnification lens detects the reflected light and generates a real-time video sequence of the microcirculation which is projected on a computer screen for later off-line analysis [21]. Recordings lasted 10 seconds each, with 3–10 attempts per patient depending on cooperation. To facilitate engagement, children could watch a cartoon if needed, and parents were allowed to sit beside them and provide support. Videos affected by movement artifacts (e.g., tongue or respiratory motion) were excluded, the three highest-quality recordings per patient were analyzed, and special care was taken to guarantee sufficient image recording quality [22]. All measurements were performed using the same camera and protocol as for the control cohort and processed with the automated AVA software without manual correction. The inter- and intrarater reliability of the measurement of the microcirculatory measurements using this system has previously been demonstrated [23].
Using the Automated Vascular Analysis program (AVA 3.2, MicroVision Medical Amsterdam, The Netherlands), we assessed total vessel density (TVD; mm/mm2), microvascular flow index (MFI; 0 = no flow, 1 = intermittent, 2 = sluggish, 3 = continuous flow), proportion of perfused vessels (PPV; %), and vessel diameter distribution (%). For statistical analyses, the mean of these recordings was used. Small vessels were defined as vessels with a diameter < 10 μm, medium vessels from ≥ 10 to < 25 μm, and large vessels ≥ 25 μm.
Assessment of endothelial function and arterial stiffness
The plethysmography EndoPAT device (EndoPAT, Itamar Medical Ltd., Israel) was used to evaluate endothelial function and arterial stiffness by measurement of the reactive hyperemia index (RHI) and the augmentation index normalized to a heart rate of 75 beats per minute (AIx@75, %), respectively [24]. The feasibility and reproducibility of this method in adolescents have been demonstrated previously [25].
These peripheral arterial tonometry (PAT) measurements were performed under a constant ambient temperature of 20–24 °C [26]. The examination consisted of 5 min baseline measurement pre-occlusion, 5 min arterial occlusion, and 5 min post-occlusion. Arterial occlusion was induced by inflating a blood pressure cuff placed around the upper arm to 60 mmHg above systolic pressure (max. 200 mmHg). Deflating the cuff leads to reactive hyperemia by arterial vasodilatation, which reflects local bioavailability of endothelial NO and represents a surrogate for endothelial function. The contralateral arm served as control to account for non-specific changes in vascular tone. An automated software program calculated the RHI and AI. Due to a temporary technical malfunction of the EndoPAT device, valid EndoPAT measurements could not be performed for all participants, particularly in the control group.
Statistical analyses
Statistical analyses were performed with SPSS (IBM Corp. Released 2021. IBM SPSS Statistics for Windows, Version 29.0. Armonk, NY: IBM Corp), GraphPad Prism (Version 8.4.3.; GraphPad Software, LLC, San Diego, CA), and R (R Core Team. Released 2023. R for Windows, Version 4.3.3. Vienna, Austria: R Foundation for Statistical Computing).
As suitable microcirculatory data from children with COVID-19 were lacking, we based sample size calculation on preliminary control data from a previous study [26]. To detect a difference of 20% in means between patients and controls with a power of 0.8 at a significance level of 0.05 (dropout rate 0.1), we calculated required sample sizes ranging between 12 and 17 per group (see Suppl. Table 1).
Sex distribution of the groups was analyzed with the chi2-test. Normal distribution was tested using the Shapiro–Wilk test. For pairwise comparison, a T-Test or a Mann–Whitney U test was used as appropriate. When comparing three groups, a one-way ANOVA was employed with Tukey’s post hoc test for multiple comparisons. To confirm the results, we additionally conducted multivariate linear regression analysis adjusting for potential confounders, including age, BMI, blood pressure, and sex. A p-value < 0.05 was considered statistically significant.
Missing data in regression models were handled using complete case analysis (listwise deletion), as implemented by default in SPSS. Cases with missing values in any of the variables included in a given model were excluded from that specific analysis, and no imputation was applied. Assumptions of linear regression were assessed using standard diagnostic procedures in SPSS. Linearity and homoscedasticity were evaluated by visual inspection of residual plots, and normality of residuals was assessed using histograms and normal Q–Q plots, supplemented by the Shapiro–Wilk test. To assess the stability and robustness of the results, we performed bootstrap resampling of the control group with 5000 iterations, keeping the Long COVID group fixed. For each bootstrap sample, the same adjusted regression model was fitted, and the distribution of effect estimates was used to calculate mean beta estimates and 95% confidence intervals.
PCA was performed in R with the FactoMineR package. All data were standardized using the scale function to account for differing variable scales, and missing values were imputed using the imputePCA function from the missMDA package. The complete imputed dataset was used for subsequent analysis. Key outputs included eigenvalues, variance explained by each component, and variable contributions to the first two principal components (PC1 and PC2). Results were visualized using the factoextra package. Pairwise Spearman correlations were computed using the R cor function. The resulting correlation matrix was visualized with the corrplot package.
Results
Baseline clinical characteristics
At the time of assessment, anthropometric measurements and blood pressure were recorded for all participants.
All children with Long COVID reported at least one symptom related to their condition, with 33 (89%) experiencing multiple symptoms. The most frequently reported symptoms included headache (25 patients, 68%), reduced endurance (20 patients, 54%), fatigue (16 patients, 43%), and dyspnea (14 patients, 38%). Laboratory findings of the Long COVID cohort at the time of investigation are summarized in Suppl. Table. Overall, no significant abnormalities were detected, and in particular, inflammatory markers were not elevated. 2
Number of patients and controls for each study examination
| Long COVID (= 37)N | Controls (= 46)N | -value (-test, *chi-square test)pt | |
|---|---|---|---|
| Age, years | 13.5 ± 2.6 | 12.4 ± 4.8 | 0.19 |
| Female sex,N | 22 | 21 | *.214 |
| BMI, kg/m2 | 20.0 ± 4.7 | 18.6 ± 3.2 | 0.127 |
| SBP, mmHg | 112 ± 11 | 114 ± 14 | 0.438 |
| DBP, mmHg | 69 ± 6 | 68 ± 8 | 0.428 |
Microcirculation in Long COVID patients vs. controls
Regarding the EndoPAT measurements, we observed a significantly increased augmentation index (AIx@75) as a measure of arterial stiffness in Long COVID patients (Table 2).
To ensure that differences between the treatment group and the historic controls were not driven by time-related effects, we compared the historic control values with contemporary controls measured using the same protocol. The comparable results argue against temporal bias and support measurement reliability (Suppl. Table). 3
The pairwise comparisons of Long COVID patients versus controls gave nearly identical results between the original analysis and the bootstrap resampling. Likewise, bootstrap resampling yielded similar results to the multivariate regression (Suppl. Tables, and). 4 5
| Measure | Long COVID | Controls | Mann–WhitneytestU | Multivariate linear regression | ||
|---|---|---|---|---|---|---|
| -valuepa | ßb | 95% CI | -valuepb | |||
| SDF,N | 36 | 43 | NA | NA | NA | NA |
| MFIsmall vesselsc | 2.66 (2.40 to 2.87) | 2.92 (2.75 to 3.00) | <.001 | −0.395 | −0.122 to – 0.031 | 0.001 |
| MFIall vesselsc | 2.59 (2.38 to 2.75) | 2.83 (2.69 to 2.96) | <.001 | −0.374 | −0.121 to −0.027 | 0.003 |
| TVD small vessels, mm/mm2 | 4.61 (3.64 to 6.41) | 9.53 (7.53 to 11.02) | <.001 | − 0.683 | − 1.761 to − 1.079 | <.001 |
| TVD all vessels, mm/mm2 | 16.12 (15.24 to 17.86) | 19.38 (17.58 to 20.57) | <.001 | − 0.630 | − 1.285 to –0.697 | <.001 |
| PPV small vessels, % | 4.00 (3.19 to 5.07) | 9.21 (7.01 to 10.74) | <.001 | − 0.735 | − 1.791 to − 1.185 | <.001 |
| PPV all vessels, % | 13.58 (12.72 to 14.89) | 17.67 (16.60 to 19.32) | <.001 | − 0.699 | − 1.656 to –0.993 | <.001 |
| Small vessels, %d | 29.97 (24.35 to 37.93) | 49.08 (42.93 to 55.72) | <.001 | − 0.675 | − 7.217 to –4.390 | <.001 |
| Medium vessels, %d | 56.59 (50.99 to 60.80) | 45.81 (40.61 to 48.50) | <.001 | 0.455 | 1.617 to 4.090 | <.001 |
| Large vessels, %d | 12.10 (9.74 to 17.99) | 5.07 (3.50 to 7.68) | <.001 | 0.583 | 1.630 to 3.137 | <.001 |
| EndoPAT,N | 36 | 26 | NA | NA | NA | NA |
| RHI | 1.43 (1.07 to 1.84) | 1.20 (1.13 to 1.53) | 0.18 | 0.089 | − 0.044 to 0.100 | 0.439 |
| AIx75 | − 11.01 (− 18.15 to − 5.24) | − 21.29 (− 31.81 to − 11.91) | 0.001 | 0.329 | 0.747 to 4.709 | 0.008 |
Association of microcirculatory and clinical parameters
Microvascular flow patterns and arterial stiffness, however, showed no significant differences related to the presence of dyspnea. Similarly, other symptoms, including headache, reduced endurance, fatigue, and dizziness, did not exhibit a significant impact on these vascular parameters.
We performed PCA on the full dataset to investigate the extent to which microcirculatory data could differentiate between Long COVID patients and controls. The first two principal components (PC1 and PC2) accounted for 52.8% and 19.2% of the total variance, respectively, cumulatively explaining 72.0% of the variability.
Finally, when including only patients with dyspnea as a symptom in the PCA alongside controls, the Long COVID group now clustered more tightly along PC1 with only minimal overlap with the controls. This finding suggests that dyspnea is associated with a more distinct microcirculatory phenotype compared to other Long COVID manifestations, potentially reflecting consistent and specific pathophysiological changes within this subgroup (Fig. 3B).
Spearman correlation matrix of clinical and microcirculatory parameters from Long COVID patients. The Spearman correlation coefficient is color-coded, with values ranging from − 1 (indicated by blue) to + 1 (indicated by red).Vessel distribution across Long COVID patients with and without dyspnea and controls. Small vessels were defined as vessels with a diameter less than 10 μm; medium, from 10 μm to less than 25 μm; and large, 25 μm or larger.-values are derived from linear regression adjusted for age, BMI, blood pressure, and sex. One-way ANOVA with Tukey’s multiple comparison test: * = < 0.05; *** < 0.001; n.s. = non significant A B p
Principal component analysis of microcirculatory data from Long COVID patients and controls.Principal component analysis of microcirculatory data from Long COVID patients presenting with dyspnea and controls A B
| Measure | Dyspnea | No dyspnea | Controls | One-way ANOVA | Multivariate linear regression | ||
|---|---|---|---|---|---|---|---|
| -valuepa | ß | 95% CI | -valuepb | ||||
| Small vessels, % | 25.82 (21.07 to 30.34) | 32.79 (27.14 to 39.68) | 49.08 (42.93 to 55.72) | <.001 | − 0.638 | − 7.72 to − 4.35 | <.001 |
| Medium vessels, % | 59.97 (56.70 to 63.35) | 52.79 (48.92 to 57.18) | 45.81 (40.61 to 48.50) | <.001 | 0.398 | 1.29 to 4.19 | <.001 |
| Large vessels, % | 13.52 (10.79 to 18.36) | 11.24 (8.50 to 18.29) | 5.07 (3.50 to 7.68) | <.001 | 0.607 | 1.86 to 3.55 | <.001 |
Discussion
In this study, we observed significant microvascular damage, including perfusion deficits, capillary loss, and increased arterial stiffness in pediatric Long COVID patients compared to healthy controls. Multivariate linear regression analyses, adjusted for age, BMI, blood pressure, and sex, confirmed Long COVID as an independent predictor of microcirculatory variables and arterial stiffness. Within the Long COVID group, patients with dyspnea exhibited additional impairment with capillary rarefication.
The pathophysiology of Long COVID remains incompletely understood and is the subject of ongoing research. Several mechanisms implicated in acute SARS-CoV-2 infection, such as endothelial inflammation and microcirculatory damage, may explain microvascular alterations observed in our cohort [10, 27–31]. Key mechanisms of Long COVID include viral persistence, post-acute inflammation, autoimmunity, thrombotic events, endothelial dysfunction, and mitochondrial dysfunction [32, 33]. These factors contribute to systemic immune dysregulation, tissue inflammation, metabolic disruption, and end-organ damage [32]. While most evidence to date originates from adult populations, recent pediatric studies also point to subtle but relevant endothelial changes [34].
Microvascular perturbations during the acute phase of COVID-19 have been reported in adults and children, including reduced capillary density, enlarged capillaries, and impaired perfusion observed by nailfold and conjunctival capillaroscopy [8, 35–38]. Some impairments may persist beyond the acute phase, consistent with endothelial dysfunction. In line with adult Long COVID studies demonstrating persistent capillary rarefication, our pediatric data suggest that similar microvascular alterations may already occur early in life [18, 19]. In a multivariate analysis, Charfeddine et al. identified endothelial dysfunction - assessed by finger thermal monitoring - along with female sex and severe clinical status during acute COVID-19 infection requiring oxygen supplementation as independent risk factors for Long COVID [20].
Similar long-lasting microvascular alterations have been described in MIS-C, supporting the concept that SARS-CoV-2-related vascular injury may persist beyond the acute phase [7].
Our findings underscore the involvement of the microvascular system and provide evidence for variability in vascular changes based on clinical symptoms. Specifically, patients with dyspnea exhibit more pronounced microvascular impairment compared to those with other symptoms. This suggests that the mechanisms underlying different phenotypes may vary significantly. Implementing microvascular monitoring in this heterogeneous patient population could offer valuable insights into the pathophysiology, aiding in the identification of Long COVID patients who may require intensified medical support and helping to mitigate the risk of severe complications in high-risk individuals.
The observed microcirculation damage and increased arterial stiffness in our pediatric Long COVID population may predispose affected children to a higher risk of cardiovascular disease such as hypertension and atherosclerosis in the long term. Whether these impairments persist over time and might contribute to sequelae - such as increased afterload leading to ventricular hypertrophy and heart failure, or insufficient tissue perfusion resulting in ischemia and organ dysfunction - remains speculative and requires more research. Nevertheless, our findings underscore the importance of understanding the cardiovascular implications of Long COVID.
This study has several limitations. First, the major limitation is the small study population caused by the rarity of diagnosed Long COVID cases in pediatric patients.
Second, the control group consists of historical controls recruited prior to the COVID-19 pandemic. This choice was a deliberate methodological decision to ensure that control participants had not been exposed to SARS-CoV-2. However, the use of historical controls may introduce temporal confounding and secular trends related to changes in environmental factors, health behaviors, or examination conditions over time. Sensitivity analyses including bootstrap resampling, as well as comparison with a small subgroup of contemporaneously examined controls, yielded consistent results. Nonetheless, residual temporal bias cannot be entirely excluded.
Third, the study may be subject to survivor bias and referral bias, as participants were recruited from our specialized Long COVID clinic. Individuals presenting to such clinics may differ systematically from the broader population of children and adolescents with post-acute sequelae of SARS-CoV-2 infection, and patients with milder or fully resolved symptoms may be underrepresented. In addition, the study population consisted predominantly of adolescents, reflecting the patient spectrum of our specialized pediatric Long COVID clinic and limiting the generalizability of the findings to younger children.
Furthermore, we assessed endothelial function and arterial stiffness using the EndoPAT device, which is designed for measurements in adults. Existing pediatric EndoPAT studies have generally included children > 10 years and adolescents, while the youngest child in our study was 6 years old [39]. This may potentially cause problems by a lack of cooperation during measurements as arterial occlusion for 5 min may be uncomfortable, and the fingertip probes may not fit properly. As raw post-occlusive data were not available, peak-based analyses of maximal dilation could not be performed, representing a further methodological limitation. Together with the small number of control patients with valid EndoPAT data, this may have reduced the validity and statistical power of our analyses.
Physical activity levels and cardiorespiratory fitness were not quantitatively assessed and therefore could not be included in baseline characteristics or statistical analyses. Reduced physical activity and exercise intolerance are common in pediatric Long COVID and may independently impair endothelial function and increase arterial stiffness, which should be considered when interpreting the findings. Prolonged reductions in physical activity can independently affect endothelial function and vascular stiffness [40].
Follow-up measurements were not feasible due to considerable travel distances and symptom resolution in a relevant portion of patients.
Lastly, it would be of great interest to compare microvascular function and arterial stiffness in children with Long COVID to those who were infected with SARS-CoV-2 but did not develop persistent symptoms to isolate the specific effects of Long COVID more precisely. However, recruiting such asymptomatic post-COVID patients is challenging, as they typically do not present to the hospital. Therefore, it remains unclear whether the observed microvascular alterations are specifically associated with Long COVID or represent a general consequence of SARS-CoV-2 infection.
Conclusion
Our findings collectively reveal substantial microvascular impairments and increased arterial stiffness in pediatric Long COVID patients, particularly among those presenting with dyspnea. These results are concerning and point to the potential involvement of disease-specific pathophysiological mechanisms. However, further longitudinal studies involving larger patient cohorts and extended follow-up periods are essential to comprehensively characterize the trajectory of these abnormalities and to uncover the underlying mechanisms. Monitoring microcirculatory function and endothelial health in these patients could provide valuable biomarkers, critical not only for optimizing the clinical management but also for informing the development of targeted therapeutic strategies and novel interventions for Long COVID.
Supplementary Information
Below is the link to the electronic supplementary material. ESM 1 (DOCX 29.9 KB) ESM 2 (DOCX 17.6 KB) ESM 3 (DOCX 17.8 KB) ESM 4 (DOCX 16.7 KB) ESM 5 (DOCX 15.4 KB)
Long Covid