Hand grip strength in hospital workers with post-COVID syndrome compared to those without infection

Following an infection with severe acute respiratory syndrome coronavirus (SARS-CoV-2), 5–10% of individuals develop long-lasting symptomatology with high individual health burdens^1,2. The term long COVID refers to persistent or newly emerging symptoms following acute SARS-CoV-2 infection beyond four weeks³. Within this spectrum, the World Health Organization (WHO) defines post COVID-19 condition or post-COVID syndrome (PCS) as symptoms occurring three months after probable or confirmed SARS-CoV-2 infection, lasting for at least two months, and not explained by alternative diagnoses⁴. Symptom clusters include persistent fatigue, neurocognitive impairment, chest pain and shortness of breath⁵. PCS is a multisystemic condition with several pathomechanisms that are not yet well understood⁶.

A subset of PCS patients fullfill diagnostic criteria for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)^7,8. ME/CFS is a complex and debilitating neurological disease limiting daily activities and quality of life^8–10. In most cases, patients report preceding infections or infection-like symptomatology; however, other triggers such as surgical procedures have also been described, and in some cases no clear initiating event can be identified^8,11,12. The worldwide prevalence was estimated to be 0.3–0.9% before the pandemic, with a significant increase expected during the COVID-19 pandemic, and at least two thirds of cases occuring in females^8,13. The most prominent symptom is post-exertional malaise (PEM), an exceeding muscular and cognitive fatigability after cognitive, emotional or light physical activity, lasting days to weeks^9,14. Due to the absence of specific biomarkers, diagnosis relies on clinical evaluation using the Canadian Consensus Criteria (CCC), and no curative treatment has been established to date; management remains symptomatic^8,15. Dysregulated involvement of autonomic and central nervous, immune and cardiovascular system, viral replication, dysfunction of cellular energy metabolism and endothelium are probable causes^9,15,16.

Both conditions rely on subjective reports and clinical criteria for diagnosis as well as classification of impairment. Assessment of hand grip strength (HGS) with dynamometers has been used as a reliable tool, to quantify muscular strength and fatigue as an objective marker with high test-retest reliability (intraclass correlation coefficient 0.92–0.96)¹⁷. It has been used in musculoskelatal, neurological conditions or general assessment of physical performance^17,18. Different studies demonstrated impaired HGS in ME/CFS patients^19,20. Additionally, lower HGS was correlated with higher levels of PEM, fatigue and pain^19,20. HGS determination enables more insides in the underlying pathophysiology as studies show impaired recovery in ME/CFS patients^19–21. More recently HGS has been applied to PCS patients^7,22. A European expert consensus recommends HGS determination as an assessment tool in ME/CFS patients¹⁶, however clinical protocols for its use are not established.

In this study, we aimed to compare HGS in hospital employees (HE) with PCS and fatigue as a leading symptom to healthy controls (HC) with no documented SARS-CoV-2 infection in order to identify characteristic differences in force performance and fatigability. To this end, HGS trajectories across repeated measurements and sessions were analyzed using a linear mixed model to assess group differences while accounting for relevant covariates and within-subject variability. In addition, an exploratory set of established and newly derived HGS parameters was evaluated to identify those most suitable for distinguishing between PCS and control participants. The predictive value of these parameters for group classification was assessed using logistic and mixed-effects logistic regression models with bootstrap-based validation.

In total, 42 individuals were recruited for the HGS measurement, including 19 HEs with PCS (hereafter referred to as the PCS group) and 23 HCs with no known history of SARS-CoV-2 infection based on testing history and symptom assessment. Females were overrepresented in both groups (PCS 89.5% and HC 69.6%). The PCS group was slightly older on average (47.8 years) compared to the HC group (43.7 years). In both groups, the proportion of nursing staff was highest, followed by other professions (physiotherapists, support staff) and medical staff. The CCC for the diagnosis of ME/CFS were fulfilled in 7 participants in the PCS group and in none of the HC group. Functional status, assessed by the Bell Score, was lower in the PCS group compared to HC (mean 65.3 vs. 93.9 points). Further characteristics are presented in Table 1. The assessment of the PCS group took place between July and December 2022, at a median of 629 days (467 − 1008 days) after the first SARS-CoV-2 infection. According to WHO criteria, all PCS participants had experienced mild to moderate COVID-19, and none required hospitalization during the acute phase²³. All participants in the PCS group were unvaccinated at the time of their initial infection, as vaccines were not yet available. At the time of assessment, participants had received COVID-19 vaccinations; the number of doses is summarized in Table 1. Based on epidemiological data on circulating SARS-CoV-2 variants in Germany and the federal state of North Rhine-Westphalia during the respective infection period, the PCS group was most likely infected with wild-type SARS-CoV-2 or the Alpha variant (B.1.1.7)²⁴. Following the initial infection, 42% of participants of the PCS group reported at least one SARS-CoV-2 reinfection, with a total of one to five infections per individual until the time of assessment.

HGS has been proposed as a diagnostic tool in ME/CFS^16,19 and has more recently been applied to patients with PCS who fulfill these criteria^7,22,25. A standardized measurement procedure has been proposed but is not yet established. Consequently, the interpretation of HGS values remains uncertain, particularly in individuals with mild to moderate PCS. In this exploratory study, HGS was assessed in HEs with PCS and HCs across repeated measurements and two sessions to investigate potential differences in force performance and fatigability. The applied linear mixed model suggests that HGS trajectories may differ between groups, although no consistent overall group effect was observed. Taken together, these findings may indicate that HGS reflects aspects of impaired muscle function in PCS; however, they should be interpreted with caution.

As demonstrated in Fig. 1, visual differences in the force of HGS in PCS and HC groups are detectable. The linear mixed model revealed significant main effects of session, measurement number, age, and sex, whereas the overall main effect of the study group was not significant. This indicates that HGS is primarily influenced by repeated testing, demographic factors, and potential practice or fatigue effects rather than PCS alone. Post-hoc analyses, however, identified specific differences between PCS and HC participants: predicted HGS was lower in PCS at the beginning and end of each session, particularly at higher measurement numbers and in older participants. Within the HC group, expected age-and sex-related differences were observed, while these effects were attenuated or absent in PCS. This context-dependent pattern may explain the absence of a global group effect and suggests that potential impairments in PCS may become apparent under repeated testing conditions rather than as a uniform reduction in strength. Sensitivity analyses confirmed that the direction of group differences remained consistent after adjustment for age and sex, whereas statistical significance was lost in the fully adjusted model. This suggests that part of the observed differences may be influenced by demographic confounding. Overall, the results indicate that PCS does not affect HGS uniformly, but rather in a context- and situation-specific manner rather than of a generalized reduction in strength.

Lower HGS values in PCS have been reported previously in studies comparing ME/CFS¹⁹ and PCS²⁶ patients with controls. In the present analysis, HGS appeared to be lower in PCS at specific measurement points, although no consistent overall group effect was observed. Reduced functional status (Bell Score) and higher symptom burden based on CCC items in the PCS group may be in line with these observations and could reflect underlying physical impairment and fatigue. This interpretation is supported by prior studies reporting associations between lower HGS and reduced functional status, higher scores in the DePaul Symptom Questionnaire for PEM and higher fatigue scores^19,22.

Exploratory correlation analysis using parameters derived from minimum, maximum, and mean force values across both sessions showed moderate associations between HGS parameters and clinical measures, with positive correlations for functional status (the Bell Score) and negative correlations for symptom burden based on fulfilled CCC items. These findings may suggest a relationship between reduced grip strength and clinical severity; however, given the exploratory nature of these analyses and the reliance on self-reported CCC data, they should be considered hypothesis-generating. This limitation is particularly relevant, as variability in self-reported symptom burden may influence the observed association. Nevertheless, previous studies have also reported associations between maximum and minimum HGS and clinical measures of disease severity and pain analogue scales²⁰, and have suggested that maximum HGS values may relate to physical capacity²⁷.

Reduced HGS has also been reported in a range of other conditions, including advanced cancer²⁸, cancer-related fatigue¹⁹, and multiple sclerosis²⁰. In the present analysis, HGS appeared to be lower in PCS at specific measurement points; however, no consistent overall group effect was observed. With regard to repeated measurements, HGS was significantly lower in the second session compared to the first in the PCS group, whereas no significant session-related differences were observed in controls. This pattern may indicate altered or delayed recovery in PCS, as previously described in ME/CFS¹⁹, although this interpretation should be made with caution. At the same time, both groups showed a general decline in force across measurements within each session, and no clear difference in the slopes of decline was observed. This suggests that both groups showed a similar decline in force during repeated measurements, while differences between groups may rather be related to overall performance levels or recovery between sessions. In line with this, similar HGS impairments have been reported in PCS patients with and without ME/CFS, although functional status was lower in those fulfilling ME/CFS criteria²².

Previous studies have assessed HGS using a limited number of repetitions, often based on three measurements^20,27, whereas more recent studies in PCS and ME/CFS have adopted extended protocols with repeated measurements across sessions^7,22,25. In line with these studies, we applied the protocol proposed by Jäkel et al.¹⁹, consisting of two familiarization attempts followed by ten consecutive measurements in two sessions. While a standardized protocol has not yet been established and evidence comparing different measurement approaches remains limited, the use of repeated measurements may provide a more comprehensive assessment of force development and fatigability, particularly in conditions characterized by variability and fluctuating symptoms. Compared to single or few measurements, this approach allows for the analysis of performance trajectories within and between sessions. Adopting a protocol consistent with recent studies was intended to facilitate comparability and to contribute to a more consistent methodological framework for future investigations of HGS in PCS and related conditions. The hand dynamometer used in this study has been previously been evaluated and shown to provide reliable measurements of HGS, and appears to correspond to the same device platform (EH101) used by Jäkel et al.¹⁹.

The HGS measurements showed substantial intra- and inter-individual variability, including occasional fluctuations despite a standardized protocol. To account for this variability in a relatively small dataset, a linear mixed model was applied, allowing the simultaneous consideration of fixed effects (age, sex, study group, session, and measurement number) and subject-specific random effects. The inclusion of random intercepts and slopes enabled the modeling of individual performance trajectories and contributed substantially to the explained variance, indicating that a considerable proportion of variability was attributed to between-subject differences. These differences may reflect factors not explicitly captured in the model, such as physical activity level, body composition, or individual physiological characteristics. While the inclusion of additional covariates (e.g. body mass index, as suggested by Nacul et al.²⁰) might further reduce unexplained variance, the applied modeling approach allows a robust representation of overall HGS trajectories while accounting for within-subject correlations and measurement variability. In contrast to analyses based solely on absolute values, the use of model-based predictions enables the assessment of dynamic changes in HGS across repeated measurements and sessions.

In the further exploratory analysis, several HGS parameters showed a moderate ability to discriminate between PCS and control participants. Parameters derived from maximum, minimum and mean force values yielded the highest predictive performance, with Fmax1 and Fmin2 showing the most consistent results across bootstrap validation. The highest accuracy was observed for parameters reflecting maximum, minimum, and mean force values rather than the ratio-based measures describing the decline of force over time, as proposed by Jäkel et al.¹⁹ and subsequent studies^7,22,29. While the linear mixed model indicated a decline in force over time, this pattern was observed in both groups, suggesting that ratio-based parameters may have limited discriminatory value due to insufficient between-group differences. These findings may suggest that reduced force capacity, particularly at the beginning (Fmax1) and later stages (Fmin2) of a measurement sequence, is potentially associated with PCS-related fatigue. The logistic regression models for Fmax1 and Fmin2 indicated a significant negative association with the probability of belonging to the PCS group, implying that higher force values were associated with a lower likelihood of PCS. However, these findings should be interpreted with caution. A relatively large number of candidate parameters (n = 30) were evaluated, increasing the risk of overfitting and selection bias, particularly given the limited sample size. Although bootstrap validation was applied, predictive performance remained moderate. Nevertheless, several parameters may represent promising candidates for further investigation and warrant validation in larger, independent cohorts to assess their potential diagnostic utility.

Notably, specificity was consistently higher than sensitivity across models, suggesting that HGS may be more suitable as a rule-in indicator rather than a screening tool. If confirmed beyond this exploratory analysis, HGS could therefore serve as a supportive adjunct to clinical assessment, with clinical presentation remaining the primary basis for diagnosis rather than HGS functioning as an independent diagnostic test.

It should further be noted that parameters based on minimum or maximum force values may be particularly sensitive to variability, as they reflect extreme values within a sequence of measurements and are therefore more susceptible to the influence of outliers. In contrast, parameters derived from multiple observations (e.g. mean values or variability-based metrics) may provide more stable estimates, although they are not entirely robust to extreme values. More generally, models relying on absolute force values may have limited generalizability to other populations, as they reduce dynamic performance patterns to single summary measures and may be influenced by differences in age distribution, physical condition, or fatigue levels, even under standardized testing conditions. Overall, the present findings suggest that certain HGS-derived parameters may carry potential for characterizing PCS-related functional impairment. However, their clinical utility for individual-level prediction remains uncertain and requires confirmation in larger, independent cohorts.

Vaccination status and viral variants may have influenced the observed findings and should be considered when interpreting the results. The control group showed a higher vaccination rate, and vaccination has been associated with a reduced risk of developing PCS and potentially milder symptom courses³⁰. In addition, the PCS cohort was infected during the early phase of the pandemic, when wild-type SARS-CoV-2 and the Alpha variant predominated, which have been linked to a higher risk of long COVID compared to later variants³. Furthermore, 42% of the PCS group reported at least one reinfection, which has been associated with a lower likelihood of recovery³. However, it remains unclear to what extent these factors directly influence muscle strength or fatigability. Additionally, the long interval between infection and assessment may have contributed to heterogeneous disease trajectories and increased the likelihood of additional confounding factors that could not be fully controlled for.

The control group was classified based on routine occupational testing and symptom monitoring during the pandemic; however, prior asymptomatic SARS-CoV-2 infections cannot be fully excluded in the absence of serological testing. Participants were further characterized using the CCC to assess symptoms consistent with ME/CFS, although a clinical diagnosis cannot be fully excluded despite being unlikely in this group. The PCS group comprised participants with and without ME/CFS, reflecting the heterogeneity of the condition. Comorbidities were present mostly only in the PCS group but were reported to be clinically stable under ongoing treatment at the time of assessment. While their overall frequency was limited, a potential influence on HGS cannot be entirely excluded. Potential pathomechanisms within this cohort, including autoantibodies against G-protein coupled receptors, Epstein-Barr virus reactivations, and chronic inflammatory processes, have been described previously¹⁰. The heterogeneity may have attenuated subgroup-specific effects; however, it is consistent with the current understanding of PCS as a multisystemic condition with incompletely understood mechanisms^3,31. Participants were recruited from a previously characterized cohort of HEs reporting persistent fatigue, without further selection or exclusion within this subgroup. This approach was intended to reflect a broad spectrum of PCS presentations. The predominance of female participants is in line with previous observations suggesting a higher risk of PCS in women³². In addition, all PCS participants were unvaccinated at the time of initial infection and were likely infected with early SARS-CoV-2 variants, which may have influenced disease manifestation¹. The cohort represents a moderately affected PCS population (mean Bell Score 65), in contrast to more severely affected cohorts (median Bell Scores of 40 and 50) reported elsewhere, where lower functional status has been associated with more pronounced HGS impairment^22,25. These differences should be interpreted in light of the respective study populations, as previous studies were conducted in specialized centers with potentially more severely affected patients, whereas the present study is based on a predefined occupational cohort.

Pathophysiological explanations for lower HGS in PCS might include hypoperfusion of skeletal muscles, as demonstrated in a study using MRIs showing higher sodium content in muscles of ME/CFS patients compared to HCs. The correlation of HGS with higher sodium content suggests impaired function of ion transport in ME/CFS caused by hypoperfusion³³. Current knowledge on the pathophysiology of skeletal muscle in ME/CFS and post-COVID ME/CFS, respectively, suggests skeletal muscle damage and mitochondrial dysfunction caused by increased intracellular sodium concentration, leading to calcium overload. If sustained mitochondrial dysfunction induces an ongoing vicious cycle, this might explain PEM. Infection-triggered mechanisms such as endothelial dysfunction, inflammation, and autoantibodies also cause circulatory disturbances and hypoperfusion of muscles³⁴. In the context of PEM in PCS diminished exercise capacity of skeletal muscles was observed, alongside severe exercise-induced myopathy³⁵.

The utility of HGS as a diagnostic marker for a specific disease appears to be limited, particularly when HGS values are compared to heterogeneous samples rather than well-defined HC groups. However, HGS has been shown to be associated with clinical scores^19,20,22, laboratory values^19,36, as well as maximum work rate²⁷. Nevertheless, these correlations offer a valuable opportunity to objectively quantify and track clinical changes over time, whether in response to a specific intervention or during routine longitudinal monitoring, anchored by an initial baseline measurement of HGS. This approach was illustrated in a small-scale study involving patients with ME/CFS, in which creatine supplementation led to a significant increase in HGS³⁷.

HGS represents a simple, inexpensive and reproducible measure that may provide insights into functional impairment in PCS. In this exploratory study, HGS tended to be lower in PCS compared to HCs at specific measurement points, while no consistent overall group effect was observed. In addition, HGS was reduced in the second session in PCS but not in controls, which may indicate altered or delayed recovery following repeated exertion. Exploratory analyses identified certain HGS-derived parameters, particularly those based on maximum, minimum, and mean force values, as potentially informative for characterizing PCS-related differences; however, their predictive performance was moderate and should be interpreted with caution. Overall, HGS may serve as a supportive adjunct in the clinical assessment of PCS, particularly as a rule-in indicator, but its utility as a screening or standalone diagnostic tool appears limited. Further validation in larger, standardized cohorts is required before clinical use.

Below is the link to the electronic supplementary material.

MT, RG and FM contributed to the study conception and design. Data was collected and interpreted by MT, RG, GS and FM. Formal analysis and visualization was performed by LB and SH. The first draft of the manuscript was written by MT and FM and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Open Access funding enabled and organized by Projekt DEAL.

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.