Introduction

The acute impacts of COVID-19 are now more elucidated in our 4^th year post pandemic. The long-term impacts in the form of sustained symptoms, exacerbation of comorbidities, and increased risk of subsequent disease development are still emerging. Certain populations who are more vulnerable to contracting COVID-19, or experiencing worse outcomes, are also more at risk of developing frailty or experiencing poorer frailty-related outcomes. These include older adults and individuals with chronic comorbid conditions [1]. While we are still without uniform consensus on the broader definition of frailty, it can be described as a “biologic syndrome of decreased reserve and resistance to stressors, resulting from cumulative declines across multiple physiologic systems, and causing vulnerability to adverse outcomes” [2]. Despite the lack of a uniform definition, any relationship between COVID-19 and frailty outcomes is important to assess considering the growing aging population and projected increases in the number of people with chronic conditions [3]. Naturally, the COVID-19 pandemic has increased attention toward frailty throughout clinical research. Sciacchitano et al [1] point out a dramatically increased number of publications that incorporate the term frailty in recent post-pandemic years. The interest in the relationship between COVID-19 and frailty, however, may be falling short in the sense that most research attends to only one direction of the bidirectional relationship between these two conditions.

The relationship between viral infection and frailty is often described concerning the influence that frailty has on health outcomes after viral infection. Pott et al [4] investigated combined cases of RSV and influenza and reported that frailty, among several other risk factors, was associated with a heightened risk of poor health outcomes [4]. In their systematic review of the literature, Yang et al [5] report that frailty has a significant positive association with exacerbated adverse health outcomes among those with COVID-19. What is lesser reported is the impact of viral infection on the incidence and severity of frailty in at-risk populations. This systematic review is designed to address this gap in our understanding of the relationship between viral infection and frailty. Due to the prevalence and persistence of COVID-19 as well as its long-term impacts, we are specifically addressing the research question, “Does an episode of COVID-19 affect the risk and trajectory of frailty in community-dwelling or institution-dwelling individuals?”

Materials and methods

The protocol for this systematic review and meta-analysis has been registered on the International Prospective Register of Systematic Reviews (CRD42023468297). This protocol is consistent with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [6]. To ensure a high-quality research design, this methodology consists of a comprehensive literature search, clearly defined eligibility criteria to select relevant studies, appraising the quality of studies using a standardized tool, extracting data showing associations of COVID-19 on the trajectory of frailty using pre-designed data form, and analyzing data quantitatively with meta-analysis. The quality of the studies included in the review will be appraised using the Quality In Prognosis Studies (QUIPS) tool [7,8].

Eligibility criteria and identification of studies for the review

The eligibility of the studies retrieved from the literature search will be reviewed using pre-defined inclusion and exclusion criteria shown in Table 1.

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Table 1. Eligibility criteria for the studies to be included in this review.

https://doi.org/10.1371/journal.pone.0312163.t001

These criteria encompass categories of type of patient population recruited, exposure, outcomes, types of studies to be included, and timeline for the outcome to emerge after exposure. In addition, the studies published in languages other than English will be excluded from this review. All citations found from the literature search will be exported to the Covidence platform. Two reviewers will independently review all the citations to determine their eligibility, first by reviewing titles/abstracts and then by reviewing full-text copies of the articles. A third reviewer will arbitrate disagreements when the primary reviewers cannot reach a consensus on determining the eligibility of citations. Agreement between two raters in determining the eligibility of articles will be assessed using kappa statistic (κ), where κ values between 0.60–0.79 will suggest moderate agreement, values between 0.80–0.90 will suggest strong agreement and those >0.90 will suggest almost perfect agreement [12].

Data extraction

The data from each study will be extracted for categories of participants, study design, exposure, outcomes assessed, statistical analyses, and results. Specifically, we will collect data for the design and objective of the study, description of the study population, exposure assessment, follow-up period, outcome assessed, covariates analyzed, statistical analyses conducted, and results. Table 2 outlines specific attributes for which the data will be extracted for each of these categories.

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Table 2. Details of attributes to be collected during data extraction.

https://doi.org/10.1371/journal.pone.0312163.t002

Assessment of methodological quality and risk of bias of studies, and certainty of evidence

The risk of bias (RoB) and quality of methodology for the studies included in the will be examined using the QUIPS tool [7,8]. Six domains included in the QUIPS tool to assess the quality of studies are study participation (selection bias), attrition (attrition bias), prognostic factor assessment (measurement bias), outcome assessment (measurement bias), confounding (confounder bias), and statistical analysis and reporting (bias in statistical analysis). The overall RoB for each study will be determined based on RoB in each of the six domains. Studies will be deemed to have low RoB if all six domains have low RoB, or only one domain has moderate RoB. The overall RoB for a study will be high if one or more domains have high RoB or ≥3 domains have moderate RoB. All other studies will be considered to have moderate RoB [7,8]. We will use Grading of Recommendations Assessment, Development and Evaluation (GRADE) [13] to assess the quality and certainty of the body of evidence. The GRADE approach considers five factors (limitations in study design or execution (risk of bias); inconsistency of results; indirectness of evidence; imprecision; and publication bias), resulting in one of four grades along a continuum [14] (Table 3).

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Table 3. Quality and certainty of evidence grades.

https://doi.org/10.1371/journal.pone.0312163.t003

Discussion

The long-term health [17–19] and economic [20,21] consequences following an episode of COVID-19 are well documented. Especially in older adults, the COVID-19 episode can have severe effects including higher odds of institutionalization as well as mortality [22,23]. Frailty is a clinical syndrome characterized by decreased reserve across multiple physiological systems [24]. The relationship between COVID-19 episodes and frailty has been explored in literature [5,25]. Using systematic review and meta-analysis design, this review will examine the prevalent literature to determine whether having an episode of COVID-19 is associated with the development of frailty within 12 months after the episode. The review will provide crucial information regarding the profile of people who have a greater likelihood of developing frailty after COVID-19, which will facilitate timely management to decrease the risk of frailty. The results of this study will be important for healthcare providers, patients, and their families of patients in understanding individual risk for developing frailty after COVID-19 and preparing healthcare as well as social support systems to manage frailty.

Undertaking systematic review and meta-analysis requires that the researchers follow a robust methodology to improve internal validity as well as generalization of results. This review will follow recommendations from the Cochrane Collaboration for conducting systematic reviews of prognostic studies [26]. These recommendations offer guidelines for each step of the review from locating the evidence using comprehensive search methods, to appraising the evidence using standardized appraisal tools and using high-quality statistical approaches to synthesize the data for understanding the phenomenon under the investigation. The literature search strategy shown in S1 Appendix was developed in consultation with a medical librarian and will locate relevant literature from six different databases. The QUIPS tool that will be used for assessing the quality of studies provides a detailed assessment of the methodological quality of the prognostic study [8]. This tool is one of the recommended instruments by the Cochrane Prognosis Methods Group [27]. The other strength of this review is that the author team is a group of multidisciplinary scholars who collectively have considerable expertise in conducting similar reviews in the past.

While we feel confident about our methodological approach, we foresee some challenges that we will encounter throughout the different phases of this review. One of the eligibility criteria for inclusion of studies in this review is to ensure that the study sample did not have frailty before the episode of COVID-19, since pre-existing diagnosis of frailty may render the assessment of associations between COVID-19 and frailty meaningless. It is anticipated that some studies may not have considered the prevalence of frailty before the COVID-19 episode in the study sample, which would misclassify people and increase false positive cases in that study. To our end, we will locate and separately analyze studies where the sample was recruited from institutionalized settings such as long-term care or skilled nursing facilities since it is logical to assume that the prevalence of frailty before COVID-19 episode might be higher in such individuals. Secondly, we anticipate significant diversity in the timing and measurement tools used for determining frailty. Especially, a wide range of assessment tools has been identified in the literature [11] due to the broad interpretation of what frailty is [24]. Our approach to only include studies that have used the most commonly utilized tool will lead to some clarity and increased generalizability of this review. Lastly, multiple indices are used to demonstrate associations between two variables [28]. There is a possibility that the use of different indices across different studies included in this review will render meta-analysis very challenging. We, however, do hope that the binary nature of both the exposure (i.e. episode of COVID-19 or not) and the outcome variable (occurrence of frailty or not) will bring some level of homogeneity in the statistical index used across the studies to demonstrate an association.

Conclusion

While COVID-19 infections may have peaked worldwide, the disabling aftereffects of the infections continue to prevail in many individuals. Understanding the risk profile for developing adverse health outcomes such as frailty after a COVID-19 episode can improve care for COVID-19 survivors. The results of this systematic review will have important clinical implications for understanding the profile of patients at higher risk of developing frailty after an episode of COVID-19. Moreover, the study results will also identify prevalent gaps in knowledge to understand better the risk of developing frailty after an episode of COVID-19.

Supporting information