Oral Health, Periodontal Status, and Cognitive Function in Middle-Aged and Older Adults: A Cross-Sectional Analytical Pilot Study

Abstract

Background: Cognitive aging is a physiological process that involves gradual and mild changes in mental functions. When these changes significantly affect cognitive performance, it is considered cognitive decline. Objective: This analytical cross-sectional pilot study examined the association between periodontal status, systemic conditions, and cognitive performance in middle-aged and older adults. Methods: Forty adults aged 35–59 years (n = 20) and ≥60 years (n = 20) from northeastern Mexico were evaluated. Oral assessments included the Modified Gingival Index and detection of Porphyromonas gingivalis and Fusobacterium nucleatum using qPCR. Cognitive function was evaluated with the Mini-Mental State Examination (MMSE), and frailty with the Clinical Frailty Scale (CFS) and Oral Frailty Checklist (OF-5). Systemic medical history and oral hygiene habits were determined using a questionnaire. Results: MMSE scores were lower in older adults compared with middle-aged adults, and the magnitude of the difference was small. The presence of P. gingivalis or F. nucleatum was similar between groups. Frailty indicators were more prevalent in older adults. Logistic regression identified age and frailty-related variables as the strongest predictors of lower cognitive performance, whereas microbiological findings were not significant predictors. Conclusions: Age and frailty indicators, rather than bacterial presence alone, were associated with reduced cognitive performance in this pilot sample. Although no microbiological differences were observed, the findings highlight the need for larger analytical studies incorporating quantitative bacterial load and additional confounders to better understand the oral–systemic–cognitive interactions.

1. Introduction

Aging involves progressive changes in the brain structure that affect the cognitive abilities of individuals, leading to age-related functional decline, which impacts various aspects of cognition such as memory, attention, processing speed, and executive function [1]. Different studies support the interaction between cognitive decline, systemic diseases, and periodontal disease (PD), suggesting that chronic inflammation present in both periodontal inflammation and cardiovascular disorders may represent a common pathophysiological mechanism capable of affecting cerebral blood flow and promoting neuroinflammatory processes, thus contributing to the progressive decline in cognitive function [2,3]. However, it is important to consider the multifactorial and multimodal etiology of these conditions [4].

The oral cavity plays a central role in systemic health through bacterial translocation, activation of inflammatory pathways, and disturbance of the host–microbiota balance. Contemporary models of periodontitis pathogenesis emphasize microbial dysbiosis, immune activation, and chronic low-grade inflammation (inflammaging), processes that may influence extraoral tissues, including the central nervous system. Key periodontal pathogens such as Porphyromonas gingivalis and Fusobacterium nucleatum have been associated with neuroinflammatory responses, amyloid deposition, and neurodegenerative changes, as reported in the recent literature from 2022 to 2024 [5,6,7].

Because common inflammatory pathways in periodontal inflammation and systemic diseases can disrupt vascular homeostasis and initiate mechanisms that alter cerebral blood flow and neuroinflammatory processes that accelerate cognitive decline [8,9], the systemic conditions evaluated in this study (hypertension, hypotension, diabetes mellitus, metabolic syndrome, thyroid disorders, and other inflammatory states) were selected due to their evidence-based association with chronic inflammation, impaired oral health, and increased cognitive vulnerability.

Beyond the oral–systemic connection, the current literature highlights the importance of the gut–brain–oral axis [10,11]. This bidirectional communication network integrates immune, microbiological, and neural pathways, suggesting that disturbances in the oral microbiome may influence brain function through systemic dissemination of inflammatory mediators or bacterial components. Understanding how these mechanisms interact across different stages of adulthood is essential for early identification of risk factors for cognitive decline [12,13,14].

Frailty, both systemic and oral, also contributes to vulnerability in aging adults. Oral frailty, including decreased chewing efficiency, swallowing difficulties, dry mouth and impaired pronunciation, has been associated with adverse health outcomes and may overlap with cognitive impairment. However, the extent to which periodontal status, frailty indicators, and cognitive function interact in middle-aged adults compared with older adults remains insufficiently understood [15,16,17].

Periodontal disease and root caries are highly prevalent among older adults [18]. In periodontal disease, pathogenic microorganisms in dental plaque accumulate within the gingival sulcus and initiate inflammatory responses [19,20]. Age-related decline in manual dexterity and oral hygiene capacity may further predispose older adults to oral disease [12].

Given the biological transitions that occur around the age of 60, including immunosenescence, increased susceptibility to chronic inflammation, and changes in oral physiology, comparing middle-aged adults (35–59 years) with older adults (≥60 years) offers an opportunity to explore early versus late manifestations of oral and cognitive health. Interdisciplinary research integrating dentistry, gerontology, microbiology, and cognitive science is needed to clarify these relationships.

The aim of this cross-sectional pilot study was to examine the association between periodontal status, systemic factors, frailty indicators, and cognitive performance in middle-aged and older adults. We hypothesized that older adults would present lower cognitive scores and higher frailty indicators, but that microbial presence alone would not fully explain differences in cognitive outcomes.

2. Materials and Methods

2.1. Study Design

This study was designed as an analytical cross-sectional pilot study. The primary aim was to obtain preliminary evidence on the relationship between cognitive function, frailty, periodontal health, and the presence of Porphyromonas gingivalis and Fusobacterium nucleatum, in two adult age groups: middle-aged adults (35–59 years) and older adults (≥60 years).

The pilot nature of this project aimed to evaluate feasibility and generate effect-size estimates to inform future adequately powered studies.

2.2. Ethical Considerations

The study was conducted in accordance with the Declaration of Helsinki, reviewed and approved by the Bioethics Committee of the Faculty of Dentistry, Universidad Autónoma de Nuevo León, protocol SPSI-010613700217 (1 December 2023). All participants provided written informed consent, and their participation was voluntary and anonymous.

2.3. Participants

A total of 40 individuals from northeastern Mexico were enrolled, 20 older adults (≥60 years) and 20 middle-aged adults (35–59 years). The sample consisted of 60% women (n = 24) and 40% men (n = 16). Most participants were married (55%), 30% were single, and the remainder were widowed, separated, or divorced.

The sample size corresponded to all eligible individuals who met inclusion criteria during the recruitment period and agreed to participate, consistent with the exploratory pilot design. No a priori sample size calculation was performed, as the intention was to obtain preliminary variability estimates for future research.

All participants had an educational level of at least upper-secondary education (high-school equivalent or higher) and were actively engaged in work or household responsibilities. This educational profile is considered adequate to minimize the well-known educational bias associated with the Mini-Mental State Examination (MMSE).

2.3.1. Inclusion Criteria

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Adults aged ≥35 years.

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Frailty status classified as CFS 1–3 (very fit to managing well).

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Without oral frailty, having no more than one of the OF-5 components.

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Ability to provide informed consent.

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At least 10 natural teeth, ensuring minimal masticatory function.

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Ability to undergo an oral examination and complete the questionnaires.

2.3.2. Exclusion Criteria

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Neurological or psychiatric conditions affecting cognition (e.g., stroke, Parkinson’s disease, schizophrenia).

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Severe functional dependence (CFS ≥ 6).

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Systemic infections, recent periodontal treatment (<6 months), or antibiotic use within the past 3 months.

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Edentulous patients without prosthetic rehabilitation.

2.4. Instruments

Cognitive Function: Cognitive status was assessed using the Mini-Mental State Examination (MMSE) [21], Spanish-adapted version [22,23]. The MMSE evaluates orientation, registration, attention-calculation, recall, and language.

Scores range from 0 to 30.

Clinical categories:

• 24–30: No cognitive impairment
• 18–23: Mild cognitive impairment

The original MMSE demonstrates excellent internal consistency (α = 0.96); the Spanish version shows α = 0.89.

Frailty Assessment: Frailty was assessed using the Clinical Frailty Scale (CFS) developed by Rockwood et al. and adapted to Spanish by the Geriatric Medicine Research group at Dalhousie University [24].

The scale ranges from 1 to 9, where:

• 1–3: Very fit to managing well (no frailty).
• 4: Vulnerable (pre-frailty).
• 5–6: Mild to moderate frailty.
• 7–9: Severe frailty to terminal condition.

The CFS has demonstrated adequate psychometric reliability and is validated for older adult populations.

Oral Frailty Assessment: Oral frailty was assessed using the Oral Frailty 5-item Checklist (OF-5) developed by Tanaka et al. [25,26]. The items evaluate: The instrument consists of five dichotomous items related to oral function:

(1)

Number of natural teeth.

(2)

Chewing difficulty.

(3)

Swallowing difficulty.

(4)

Dry mouth.

(5)

Low articulatory oral motor skill (difficulty with clear pronunciation).

Oral frailty is defined as ≥2 positive items. The OF-5 has demonstrated predictive validity for adverse outcomes in community-dwelling adults.

2.5. Periodontal Evaluation

Periodontal inflammation was assessed using the Modified.

Gingival Index (MGI) [27,28], a validated visual indicator of gingival health frequently used in population and community studies, including frail or older adults who may not tolerate more invasive periodontal probing. MGI categories:

• 0 = Normal gingiva
• 1 = Mild inflammation
• 2 = Moderate inflammation (erythema, edema)

As noted in the Discussion, MGI does not measure periodontal breakdown; however, it was selected due to its non-invasive nature and feasibility for this pilot design.

2.6. Microbiological Analysis (qPCR)

Subgingival samples were obtained from the deepest gingival sulcus of each participant. Bacterial DNA was analyzed for the presence of P. gingivalis and F. nucleatum using real-time quantitative PCR (qPCR) with species-specific primers.

Ct values were interpreted qualitatively:

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Ct ≤ 35 = Positive detection

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Ct > 35 = Negative

Due to the exploratory nature of the study and absence of a standard calibration curve, bacterial load was not quantified. Instead, microbial detection was treated as a binary variable (present vs. absent). Amplification curves were reviewed for signal quality and specificity.

2.7. Statistical Analysis

Data were analyzed using IBM SPSS Statistics version 27. Quantitative variables were first evaluated for normality using the Kolmogorov–Smirnov and Shapiro–Wilk tests. Given the non-normal distribution of MMSE scores and the categorical nature of the CFS and OF-5 indices, all cognitive and frailty variables were treated as categorical outcomes.

MMSE was dichotomized (no impairment = 24–30; mild impairment = 18–23), and group differences were assessed using the Fisher Exact Test. Effect sizes were expressed as Odds Ratios (OR) with 95% Confidence Intervals (95% CI).

Frailty status (CFS 1–3) was analyzed using the Chi-square test.

Detection of P. gingivalis and F. nucleatum (qPCR positive/negative) was analyzed using Fisher’s Exact Test, with OR (95% CI).

Due to the very low frequency of mild cognitive impairment (n = 4), multivariable regression could not be performed reliably (insufficient events per predictor for a stable model). This limitation is discussed in the manuscript.

Statistical significance was set at p < 0.05.

Potential confounding factors, including age, sex, educational level, comorbidities, and oral hygiene practices, were documented and considered in the interpretation of results. Due to the small number of cognitive impairment events, formal statistical adjustment was not possible, but these variables were controlled conceptually during data interpretation.

3. Results

The sample was divided into two groups based on age:

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Group 1 (G1) = 60 years and older (M = 67.9, SD = 8.0).

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Group 2 (G2) = 35 to 59 years (M = 48.9, SD = 6.9).

3.1. The Mini-Mental State Examination (MMSE)

The distribution of Mini-Mental State Examination (MMSE) categories differed between age groups (

Table 1. MMSE categories by age group.

MMSE Category	≥60 Years (n = 20)	35–59 Years (n = 20)
Mild impairment (18–23)	4	0
No impairment (24–30)	16	20

Mild impairment is the MMSE second category: mild cognitive decline. No impairment is the MMSE first category: no cognitive decline.

). Mild cognitive impairment was observed in 20% of older adults (n = 4) and in none of the middle-aged adults (0%), although this difference did not reach statistical significance (Fisher’s Exact Test, p = 0.106).

Despite the lack of statistical significance, the pattern suggests an age-related trend, consistent with early cognitive vulnerability. Due to the presence of a zero cell, odds ratios were not computed.

3.2. Frailty Status

All participants were classified within the non-frail range (CFS 1–3). However, the distribution of specific functional categories differed significantly between age groups (

Table 2. Clinical Frailty Scale categories by age group.

CFS Category	≥60 (n = 20)	35–59 (n = 20)	Total
1—Very Fit	4 (20.0%)	15 (75.0%)	19 (47.5%)
2—Well	1 (5.0%)	0 (0.0%)	1 (2.5%)
3—Managing Well	15 (75.0%)	5 (25.0%)	20 (50.0%)

Scores are within the non-frail functional range (Levels 1–3).

). Older adults were more frequently classified as “Managing Well,” while middle-aged adults were more often categorized as “Very Fit.”

This difference was statistically significant (Chi-square = 12.368, p = 0.002), indicating early functional differences associated with aging, despite all participants being non-frail.

3.3. Oral Frailty

No participant met the criteria for oral frailty (≥2 positive OF-5 components). Differences were found only in the number of natural teeth, with older adults showing fewer teeth than middle-aged adults (

Table 3. OF-5 components by age group.

Natura Teeth	≥60 (n = 20)	35–59 (n = 20)	Total
12	1	0	1
14	1	0	1
16	0	1	1
18	1	1	2
24	3	2	5
25	1	1	2
26	4	5	9
27	2	1	3
28	7	9	16

Due to sparse cell counts across categories, statistical significance testing was not reliable; results are presented descriptively.

).

However, the distribution across 12 tooth-count categories was sparse, making a valid significance test inappropriate. Therefore, these findings are presented descriptively only.

3.4. Systemic Diseases

Hypertension was significantly more frequent in older adults (p = 0.0033), and the odds ratio indicated a strong association with age (

Table 4. Systemic diseases by age group.

	≥60 (n = 20)	35–59 (n = 20)	OR	p
Hypothyroidism	1	1	1.0	1.0
Hyperthyroidism	1	0	∞	1.0
Hypotension	1	0	∞	1.0
Hypertension	8	0	∞	0.0033
Diabetes	4	3	1.42	1.0
Metabolic Syndrome	0	1	1.0	1.0

Adjusted significance level (Bonferroni): α = 0.0083; OR = ∞ indicates no cases in the control group.

). No significant differences were found for other systemic conditions after applying the Bonferroni correction (α = 0.0083).

3.5. Gingival Inflammation (Modified Gingival Index)

Gingival inflammation differed significantly between groups (

Table 5. Gingival inflammation categories by age group.

Inflammation Level	≥60 (n = 20)	35–59 (n = 20)	p
Mild	8	7	0.045
Moderate	7	1
Moderate with erythema	4	1
Total with inflammation	19	9	0.001

) when analyzed as a binary variable (presence vs. absence of inflammation), with older adults showing a higher frequency of inflammation (p = 0.001).

When evaluated across three MGI categories (normal, mild inflammation, moderate inflammation), the distribution also differed significantly between age groups using the Fisher–Freeman–Halton exact test (3 × 2 contingency table, p = 0.045).

These results indicate greater susceptibility to gingival inflammation among older adults.

3.6. Microbiological Findings (qPCR)

The presence of Porphyromonas gingivalis and Fusobacterium nucleatum was determined using real-time qPCR. Ct values were analyzed qualitatively (Ct ≤ 35 = positive). No quantitative calibration curve was used; thus, results are interpreted as presence vs. absence of each microorganism.

Both P. gingivalis and F. nucleatum were detected in participants from both age groups (

Table 6. qPCR detection of periodontal pathogens by age group.

	≥60 (n = 20)	35–59 (n = 20)	Total	p
P. gingivalis (+)	17	16	33	1.000
F. nucleatum (+)	12	15	27	0.508

). No statistically significant differences were found between groups for the presence of P. gingivalis (85% vs. 80%; Fisher’s Exact Test, p = 1.000) or F. nucleatum (75% vs. 60%; p = 0.508).

Odds ratios indicated no meaningful differences in microbial detection. As explained in the Methods, bacterial load could not be quantified due to the qualitative nature of the qPCR procedure.

4. Discussion

This analytical cross-sectional pilot study explored the relationship between cognitive function, frailty, oral health indicators, and the presence of Porphyromonas gingivalis and Fusobacterium nucleatum in middle-aged and older adults. The findings showed age-related differences in functional status and a non-significant trend toward lower cognitive performance in the older group; however, no statistically significant associations were found between age and oral bacterial detection or oral frailty indicators.

Age-related variation in cognitive scores was expected, and the distribution observed in this sample aligns with previous reports describing early cognitive decline as a multifactorial process influenced by education, comorbidities, inflammation, and environmental conditions.

Although all participants had at least an upper-secondary educational level, adults aged 35–59 years reported higher academic attainment than older participants, which may partially explain their higher MMSE scores. Nevertheless, the very small number of individuals with mild cognitive impairment (n = 4) limits interpretability and reinforces the exploratory nature of this study.

Regarding functional frailty, all participants fell within the non-frail range of the Clinical Frailty Scale. However, older adults were more frequently classified as “Managing Well,” a category that includes individuals with well-controlled medical conditions or normal functional aging. This pattern is consistent with early functional transitions that precede clinically evident frailty and supports the concept that frailty develops progressively over time.

For oral frailty, only the number of natural teeth differed meaningfully between groups. Although older adults exhibited greater tooth loss, most maintained adequate chewing and articulation through prosthetic rehabilitation. This functional compensation likely contributed to the absence of oral frailty (≥3 positive OF-5 items) in both age groups.

Gingival inflammation was more frequent among older adults, which is consistent with known age-related susceptibility to gingival changes due to reduced salivary flow, immune dysregulation, and cumulative plaque exposure. However, because standard periodontal probing measures (CAL, PPD, BOP) were not used, the ability to assess periodontal breakdown was limited. The Modified Gingival Index was selected due to its feasibility, non-invasive nature, and acceptability in older or potentially frail populations, but this decision constitutes an important methodological limitation.

P. gingivalis and F. nucleatum are Gram-negative anaerobes strongly implicated in periodontal disease and increasingly associated with cognitive decline in older adults. P. gingivalis secretes gingipains and lipopolysaccharides that induce chronic inflammation, promote periodontal tissue destruction, and evade host immune surveillance, mechanisms that may extend systemically to trigger neuroinflammation and contribute to neurodegenerative processes such as Alzheimer’s disease. F. nucleatum, a key bridging organism within dysbiotic biofilms, facilitates the co-aggregation and dissemination of other periodontal pathogens. Its FadA adhesin binds to epithelial and endothelial cells, enhancing bacterial invasion, vascular permeability, and inflammatory signaling. Together, these mechanisms may promote systemic inflammatory burden and microbiota translocation, ultimately impacting brain health and accelerating cognitive decline in the elderly [29].

Microbiological analysis revealed the presence of P. gingivalis in both age groups and a non-significant trend toward increased detection of F. nucleatum among older adults. Although these microorganisms have been associated with neuroinflammatory pathways in previous studies, the absence of significant between-group differences may reflect the small sample size and the qualitative nature of qPCR detection.

The interpretation of bacterial load or relative abundance was constrained using Ct thresholds without quantitative calibration. Nonetheless, the detection of these pathogens in both middle-aged and older adults suggests that microbial dysbiosis may begin earlier in life, supporting emerging evidence on the oral–systemic axis.

This study includes middle-aged adults (35–59 years), a population not typically included in research. However, it has been reported that this stage of life is when systemic and cognitive diseases often begin, frequently going undiagnosed. One of the identified critical ages for aging is 44, due to the metabolic changes observed at this time. Furthermore, individuals between 30 and 35 years of age are often at the onset of acute or transient disorders such as post-traumatic stress disorder, generalized anxiety disorder, and depression. Data obtained from the middle-aged adult population provides information that contributes to understanding early markers of cognitive vulnerability [30,31].

Overall, the findings support the feasibility of integrating cognitive, frailty, periodontal, and microbiological assessments in older adults. They also highlight the importance of considering characteristics such as education, general health status, and oral inflammation as early markers of cognitive vulnerability. While these results do not allow us to infer causality, the observed trends provide preliminary effect size estimates that could inform future longitudinal or multivariate studies analyzing early oral-systemic-cognitive interactions.

Limitations

This study has several limitations. First, the sample size was small, and no formal a priori sample size calculation was performed, consistent with the exploratory pilot nature of the project. The limited sample reduces statistical power and restricts the generalizability of the findings.

Second, the frequency of mild cognitive impairment was low (n = 4), which prevented the use of a multivariable logistic regression model. The number of events was insufficient to meet stability requirements for multivariate analysis, and therefore only bivariate categorical comparisons were performed.

Third, periodontal status was assessed using the Modified Gingival Index, a non-invasive measure suitable for older or frail adults but not a substitute for periodontal probing indices such as clinical attachment loss or probing depth. Thus, conclusions regarding periodontal breakdown should be interpreted with caution.

Fourth, the microbiological analysis was qualitative, based on Ct thresholds without a standard calibration curve to quantify bacterial load. The interpretations were limited to the presence/absence of P. gingivalis and F. nucleatum, rather than quantitative differences.

Fifth, potential confounders such as medication use, dietary habits, and objectively measured oral hygiene behaviors may influence cognitive, periodontal, and microbiological outcomes. These factors were not fully controlled due to the sample size and pilot design.

Finally, the cross-sectional design precludes causal inference. Larger and more diverse longitudinal studies are needed to confirm the associations suggested by this pilot study and to determine the directionality of oral–systemic–cognitive relationships.

5. Conclusions

This analytical cross-sectional pilot study explored the relationship between cognitive function, frailty, oral health indicators, and the presence of Porphyromonas gingivalis and Fusobacterium nucleatum in middle-aged and older adults. Although age-related differences in cognitive performance, gingival inflammation, and the number of natural teeth were observed, no statistically significant associations were found between age group and bacterial detection or oral frailty.

The findings suggest that early functional and oral changes may emerge before clinically evident frailty or cognitive impairment, and that pathogenic oral bacteria are present across age groups. However, due to the small sample size, qualitative microbial assessment, and the use of non-invasive periodontal indices, these results should be interpreted cautiously.

Overall, this study provides preliminary effect-size estimates and demonstrates the feasibility of integrating cognitive, functional, periodontal, and microbiological assessments in community-dwelling adults. This data contributes to the planning and design of future robust studies.

These findings underscore the importance of early oral and systemic health monitoring, particularly in adults transitioning into older ages. Clinically, integrating oral health assessments into cognitive screening protocols may support earlier identification of individuals at increased risk and guide targeted preventive strategies.

Future Research Directions

Future studies should address the limitations of the present work and expand upon its exploratory findings through:

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Larger, adequately powered samples.

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Longitudinal study designs.

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Comprehensive periodontal assessment.

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Quantitative microbiological evaluation.

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Developing and using calibration curves for qPCR to estimate bacterial load and relative abundance.

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Integrating education level, comorbidities, medications, oral hygiene behaviors, and microbial profiles.

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Inclusion of middle-aged adults in greater depth.

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Assessment of additional biomarkers of inflammation, such as IL-6, TNF-α, and CRP.