Can Novel Inflammatory Parameters (UHR, MHR, THR, CAR, CHR, SII) Predict Sarcopenia In Older Adults With Weight Loss?

Can Novel Inflammatory Parameters (UHR, MHR, THR, CAR, CHR, SII) Predict Sarcopenia In Older Adults With Weight Loss? | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Can Novel Inflammatory Parameters (UHR, MHR, THR, CAR, CHR, SII) Predict Sarcopenia In Older Adults With Weight Loss? Elif Gecegelen¹, Mete Üçdal2, Arzu Okyar Baş1, Didem Karaduman1, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7075695/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Sarcopenia is characterized by age-related loss of muscle mass and function and is associated with chronic low-grade inflammation (inflammaging). Novel inflammation- based indices – including the Uric acid to HDL-cholesterol ratio (UHR), Monocyte to HDL ratio (MHR), Triglyceride to HDL ratio (THR), C-reactive protein (CRP) to albumin ratio (CAR), CRP to HDL ratio (CHR), and Systemic immune-inflammation index (SII) – have emerged as markers of inflammaging. This study investigated the relationship between these inflammatory parameters and probable sarcopenia (PS) in older adults. Methods: 490 patients aged 65 years and older who applied to the geriatric medicine outpatient clinic of a university hospital with complaints of weight loss were evaluated retrospectively cross-sectionally (2022-2023). PS was assessed by SARC-F questionnaire, handgrip strength test (HGST), and the 5 times-sit-to-stand-test (STST), and patients were grouped into probable sarcopenia (PS, n=259) or non-sarcopenia (NS, n=231) based on these criteria. UHR, MHR, THR, CAR, CHR, and SII were calculated from laboratory values. Group differences in demographics, comorbidities, geriatric assessment scores, and these inflammatory markers were analyzed. The correlations between new inflammatory markers and standard inflammatory indicators (CRP, neutrophil) were evaluated. Receiver operating characteristic (ROC) analysis determined the ability of each parameter to discriminate PS. Results: The PS group was older than NS (median 76 vs 71 years, p<0.001) and had higher prevalence of atrial fibrillation (p=0.002) and dementia (p<0.001), while other comorbidities were similar between groups. All inflammatory indices were elevated in the PS group: median UHR 0.11 vs 0.09, MHR (higher in PS), CAR 1.37 vs 1.02, CHR 0.13 vs 0.07 and SII 623.5 vs 479.5 (all p<0.001), and THR higher (2.19 vs 2.15, p=0.012). Serum uric acid, monocyte count and CRP levels were higher in PS than in NS, while albumin and HDL levels were lower (all p<0.01). UHR, CAR, MHR and SII correlated with one another and with CRP and neutrophils (p<0.001 for all). In ROC analysis, UHR showed the area under the curve (AUC 0.638, 95%CI 0.586–0.690) and a cutoff of 0.1204 (sensitivity 44%, specificity 83%) for identifying PS. CAR and SII showed predictive value (AUC 0.602 and 0.626, respectively), while THR had weaker association (AUC 0.566). UHR performed best with 83% specificity, while CAR and SII performed best with 71% sensitivity. Conclusion: Older adults with PS show higher UHR, MHR, THR, CAR, CHR, and SII, reflecting increased inflammatory status. Among them, UHR, CAR and SII have demonstrated the ability to distinguish PS; UHR has high specificity, while CAR and SII have high sensitivity. These available, cost-effective inflammatory markers are associated with sarcopenia-related pathophysiology and established inflammatory markers (CRP, neutrophil). Our findings suggest that inflammatory parameters, especially UHR, CAR and SII may serve as biomarkers to identify older patients at risk for sarcopenia. Future prospective studies are needed to validate their predictive values and to determine whether interventions targeting modifiable components [such as serum uric acid, HDL levels, CRP, albumin, CBC(complete blood count)] affect sarcopenia outcomes. sarcopenia new inflammatory markers Uric acid to HDL ratio CRP to albumin ratio Systemic immune-inflammation index biomarkers Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Sarcopenia is a loss of skeletal muscle mass and strength associated with aging [ 1 ]. It has been linked to inflammaging – a chronic, low-grade pro-inflammatory state that develops during aging. Inflammaging is characterized by increased levels of inflammatory mediators and is implicated in age-related diseases such as type 2 diabetes, osteoarthritis, and sarcopenia [ 2 ]. With advancing age, the prevalence of conditions related to metabolic dysfunction and inflammaging (e.g. diabetes, obesity, hypertension) rises, suggesting that virtually everyone may face sarcopenia and its complications [ 3 ]. The inflammaging involved in the sarcopenia process is exacerbated by changes in glucose and lipid metabolism, insulin resistance, and oxidative stress, leading to increased production of inflammatory cytokines. In addition to primary aging, secondary causes of sarcopenia are associated with lipid metabolism disorders[ 4 ]. For example, replacement of type II muscle fibers with fat is a hallmark of sarcopenia, contributing to muscle atrophy [ 5 ]. Chronic low- grade inflammation in sarcopenia causes oxidative stress-induced redox imbalance and upregulation of pro-inflammatory mediators [ 1 ]. This chronic inflammatory milieu drives tissue degeneration in age-related diseases [ 6 ]. However, the contribution of the pro-inflammatory mediators involved to sarcopenia and other age-related conditions is still poorly understood [ 7 ]. Recent studies have identified inflammatory biomarkers associated with inflammatory conditions that contribute to sarcopenia. These include Uric Acid/HDL-Cholesterol Ratio (UHR), C-Reactive Protein (CRP)/Albumin Ratio (CAR), Monocyte/HDL-Cholesterol Ratio (MHR), CRP/HDL- Cholesterol Ratio (CHR), Systemic Immunity-Inflammation Index (SII), and Triglyceride/HDL- Cholesterol Ratio (THR) [ 8 – 10 ]. These indices are derived from routine laboratory parameters and reflect the degree of systemic inflammation in an accessible and cost-effective manner. Given the evidence that sarcopenia in older individuals may be a consequence of chronic inflammatory and metabolic disorders, examining inflammatory markers in older adults with sarcopenia may provide valuable insights. According to our studies, this wide range of new inflammatory markers has not been studied as a whole in older people at risk for sarcopenia. In this study, we aimed to evaluate the characteristics and levels of inflammatory markers (UHR, MHR, THR, CAR, CHR, SII) in patients aged 65 years and older with and without probable sarcopenia. We sought to observe differences in these parameters between the probable sarcopenia (PS) group and controls. We hypothesized that these inflammation-based markers may be elevated in sarcopenic patients and serve as indicators of sarcopenia risk. This study provides important information regarding the rapid and easy screening of sarcopenia in the geriatric population during outpatient patients with new inflammatory markers. Methods Study Population This retrospective cross-sectional study was conducted at the Department of Geriatrics, Hacettepe University Hospital, following ethical approval from the Hacettepe University Faculty of Health Sciences Ethics Committee (Date: January 9, 2024; Approval No: 2024/01–01, SBA 23/411). Patient records were reviewed between January 2024 and December 2024. Patients aged 65 years and older who presented to the geriatric outpatient clinic with complaints of weight loss between June 1, 2021, and June 30, 2023, were evaluated for inclusion. After ethical approval, patient data between March 1, 2024 and May 30, 2025 were analyzed. We applied the following inclusion criteria: patients aged ≥ 65 years who had undergone a comprehensive geriatric evaluation and documented weight loss. Since all of the patient population included in the study had a weight loss statement at presentation, in order to clearly evaluate the weight loss that could also affect probable sarcopenia, patients with 5% and more weight loss in 6 months were accepted as patients who applied to the outpatient clinic with unintentional weight loss (UWL) [11]. Patients were excluded if they were (a) younger than 65 years, (b) had a known condition that could affect physical performance tests (e.g., chair stand test, hand grip strength test) such as severe dementia, neuromuscular disease, rheumatologic disease, corticosteroid therapy with those taking > 5 mg prednisolone or equivalent per day for the last 3 years or those with physical limitations to perform these tests (having had surgery that would prevent movement within the last 1–3 months or having infectious findings in both extremities), (c) had incomplete medical history or incomplete clinical data, or (d) had incomplete laboratory results to calculate inflammatory indices. Data from patients with stroke sequelae, severe osteoarthritis, or extrapyramidal movement disorders (such as Parkinson's disease) who were disabled or immobile were also excluded. After applying the exclusion criteria, 490 older adults were included in the study. These patients were divided into two groups according to sarcopenia status: Probable Sarcopenia (PS) and Non-Sarcopenia (NS). The study flow and patient allocation process are shown in Fig. 1. PS was defined according to revised criteria from the European Working Group on Sarcopenia in Older Adults (EWGSOP2) definition, with an emphasis on low muscle strength. To assess muscle strength and the risk of sarcopenia, the SARC-F questionnaire, handgrip strength test (HGST), and 5-times chair sit-to-stand test (STST) were performed. Patients with a SARC-F score ≥ 4 were considered at risk for sarcopenia. Muscle strength was measured using the HGST with a calibrated handheld dynamometer (TKK5401; Takei III Smedley Type Digital Dynamometer Takei Scientific Instruments, Tokyo, Japan) [12]. Measurements were made while participants were standing with their arms positioned parallel to the floor. The highest value of 3 repeated measurements was taken in the analysis. HGST < 16 and < 27 kg for women and men, respectively, were taken as the cut-off values to assess muscle strength [13]. In terms of the ability to predict outcomes associated with sarcopenia, poor physical performance was defined as walking speed ≤ 0.8 m/s during a 4 m walking test using a manual stopwatch [13]. When evaluating walking speed, the average of two measurements was taken. Patients with low grip strength (men < 27 kg, women 15 seconds for 5 times) were classified as having PS according to the EWGSOP2 guidelines (sarcopenia confirmed by low muscle mass was not assessed in this study due to its retrospective nature, therefore termed “probable” sarcopenia). Those not meeting these criteria were classified as Non-sarcopenia. For each patient, we recorded demographic information (age, gender), comprehensive geriatric assessment results, comorbidities, and laboratory values at baseline assessment in Table-1 . Comparison of geriatric evaluations in patients with and without UWL and differences between groups with new inflammatory markers are shown in Table-2. Common comorbid conditions included diabetes mellitus (DM), hypertension (HT), coronary artery disease (CAD), chronic kidney disease (CKD), atrial fibrillation (AF), and dementia. Geriatric assessment measures such as Clinical Frailty Scale (CFS), Katz Activities of Daily Living (ADL) index, Lawton Instrumental Activities of Daily Living (IADL) scale, standardized Mini-Mental State Examination (s-MMSE), 15-item Geriatric Depression Scale (GDS), and Mini Nutritional Assessment-Short Form (MNA-SF) were obtained from patient records. Laboratory values including C-reactive protein (CRP), serum albumin, serum uric acid, triglycerides, high-density lipoprotein cholesterol (HDL-C), 25-hydroxyvitamin D, complete blood count parameters [(CBC), total leukocyte count, hemoglobin, hematocrit, platelet count, and differential counts] were obtained from the institutional database. These laboratory measurements were performed from fasting blood samples as part of the routine geriatric assessment of patients. Comprehensive Geriatric Assessment All participants underwent a Comprehensive Geriatric Assessment (CGA). Basic activities of daily living (ADL) [14, 15] (0–6 points) and instrumental activities of daily living (IADL) were used to measure the independence and functional ability of the patients [16]. Basic ADLs consist of six activities; bathing, dressing, going to the toilet, incontinence, transferring and feeding. IADL consists of using the phone, shopping, preparing food, housework, doing laundry, transportation, taking medication and managing financial affairs. MNA-SF (0–14 points) was used to determine the nutritional status of the patients and scores below 11 were considered as malnutrition and malnutrition risk [17]. The weakness status of the patients was defined by the CFS (1–9 points) [18]. According to the CFS, patients who were level 4 and more were accepted as living with frailty. Geriatric syndromes (osteoporosis, dementia, depression, falls, and polypharmacy) identified by the CGA were also recorded. s-MMSE and GDS were performed to assess cognitive function and depressive symptoms, respectively [19–22]. Depression was defined as a score of 5 or more. The SARC-F questionnaire was used to determine the risk of sarcopenia. The questionnaire screens patients for self-reported symptoms suggestive of sarcopenia, including lack of strength, walking assistance, getting up from a chair, climbing stairs, and falling. Each of the self-reported parameters has a minimum and maximum score of 0 and 2, with the largest maximum SARC-F score being 10, with a score of 4 or more being considered as a risk of sarcopenia [23]. Calculation of Inflammatory Indices The inflammatory parameters were calculated for each patient from the laboratory data as follows: UHR (Uric Acid to HDL-C Ratio) = Serum uric acid level (mg/dL) ÷ HDL cholesterol level (mg/dL) MHR (Monocyte to HDL-C Ratio) = Absolute monocyte count (10³/µL) ÷ HDL cholesterol level (mg/dL) THR (Triglyceride to HDL-C Ratio) = Serum triglyceride level (mg/dL) ÷ HDL cholesterol level (mg/dL) CAR (CRP to Albumin Ratio) = C-reactive protein level (mg/L) ÷ serum albumin level (g/dL) CHR (CRP to HDL-C Ratio) = C-reactive protein level (mg/L) ÷ HDL cholesterol level (mg/dL) SII (Systemic Immune-Inflammation Index) = Neutrophil count × Platelet count ÷ Lymphocyte count (all counts from CBC, with neutrophils, platelets, lymphocytes in 10³/µL) These indices were derived for each patient to quantify systemic inflammation and metabolic imbalance. They were chosen based on prior studies indicating their relevance in chronic inflammatory states and age-related diseases. Statistical Analysis Statistical analyses were performed using IBM SPSS Statistics (Version 24 for Windows; IBM Corp., Chicago, IL, USA). We evaluated the distribution of continuous variables using the Kolmogorov–Smirnov test. For continuous variables that followed a normal distribution, comparisons between the PS and NS groups were made using the Independent-Samples T- test, and results are presented as mean ± standard deviation. For continuous variables not normally distributed, we used the Mann–Whitney U test, and data are presented as median with interquartile range (IQR). Categorical variables were compared using the chi-square test and are presented as number (percent). Spearman's rank correlation test was employed to analyze the relationships between the inflammatory parameters (UHR, MHR, THR, CAR, CHR, SII) and other variables, including traditional inflammatory markers (CRP, Neutrophil) and clinical measures. In order to demonstrate the discriminatory power of the diagnostic performance of new inflammation indices in determining PS, we constructed ROC curves and calculated the area under the ROC curve (AUC) for each index. Areas with AUC < 0.6 were not considered significant to determine the cut-off value. Cutoff values for sensitivity and specificity were determined using the Youden Index [24]. A two-tailed p value 0.2 or 0.2) were considered to reflect the value of the underlying entity [25]. To compare the distribution of inflammatory indices between groups, kernel density plots were generated using the ggplot2 package in R. Each index was visualized with overlaid density curves for the possible sarcopenic and non-sarconepic groups, shown in different colors for clarity. Optimal cut-off values determined by ROC analysis were indicated with vertical dashed lines on each plot. This approach allowed for visual assessment of distribution differences and the discriminative capacity of the cut-off values across groups Ethical Considerations The study protocol was approved by the Non-Interventional Research Ethics Committee of Hacettepe University Faculty of Medicine (Date: 09.01.24; Approval No: 2024/01–01, SBA 23/411). The study was conducted in accordance with the principles of the Declaration of Helsinki. Informed consent was not required from individuals due to the retrospective nature of the study using de-identified patient data. No interventions or blood draws were performed for the purposes of this research, and all data were derived from routine clinical care records. Results Study Population Characteristics The study included 490 older patients (median age 73 years, range 65–95; 66.3% female). Of these, 259 patients (52.9%) were classified as having PS group, and 231 (47.1%) were NS group. The PS group was older than the NS group (median age 76 [72–80] vs 71 [68–76] years, p < 0.001). The proportion of females was similar between groups (65.6% in PS vs 67.1% in NS, p = 0.732), indicating no sex difference in sarcopenia prevalence in our cohort. Comorbidity profiles of the two groups were comparable in terms of chronic diseases such as diabetes mellitus (DM), hypertension (HT), coronary artery disease (CAD), and chronic kidney disease (CKD), dementia and atrial fibrilliation (AF) ( Table 1 ). The prevalence of DM, HT, CAD and CKD did not differ between PS and NS groups (p > 0.10 for each). However, dementia and AF were more common in the PS group: AF was present in 12.7% of PS patients versus 4.8% of NS (p = 0.002), and clinically diagnosed dementia in 18.5% of PS vs 5.6% of NS (p < 0.001) group. These findings suggest that PS in older adults may associate with a higher burden of conditions like AF and dementia, even though other comorbidities were similar. Since all patients included in the evaluation had weight loss, those with a weight loss of 5% and above in 6 months were accepted as UWL for classification, a total of 118 people had UWL (24.1%) and when subgroup analyses were performed, it was seen that those with UWL were more dependent in daily living and instrumental living activities (all p = 0.002), were more fraile than the other group and had a higher risk of malnutrition and sarcopenia (all p values < 0.001) (Table 2). Among laboratory parameters, serum uric acid, monocyte count, and inflammatory markers differed between groups, whereas lipid profiles showed differences in HDL but not triglycerides. Patients with PS had higher median serum uric acid (5.70 vs 5.10 mg/dL, p < 0.001) and higher monocyte counts (median 0.56 vs 0.51 ×10³/µL, p = 0.002) compared to controls. They also had elevated CRP levels (median 6.79 vs 3.59 mg/L, p = 0.001) and lower serum albumin (median 4.20 vs 4.35 g/dL, p < 0.001), consistent with a more inflammatory and less nourished state in probable sarcopenic patients. HDL cholesterol was lower in the PS group (median 53 vs 56 mg/dL, p = 0.001). In contrast, median triglyceride levels were not different (115 vs 113 mg/dL, p = 0.565), and 25(OH) vitamin D levels tended to be lower in PS (median 28.9 vs 30.4 µg/L) but without statistical significance (p = 0.095). Functional and Geriatric Assessment As expected, patients in the PS group had worse performance on physical tests and functional scales ( Table 1 ). The PS group was more frail when assessed by CFS (4 [3–6] vs. 3 [3–4], p < 0.001). Although Katz (ADL) was the same in both groups as a median, there was a significant difference in maximal values (median 6 vs. 6, p < 0.001, and Lawton (IADL) was lower in the PS group (median 7 vs. 8, p < 0.001), indicating that probable sarcopenic patients were more dependent on daily and instrumental activities. Cognitive screening scores, s- MMSE, were lower in PS (median 27 vs. 29, p < 0.001), consistent with a higher prevalence of dementia. The risk of malnutrition measured by MNA-sf was higher in PS (median 12 vs. 13, p < 0.001) and depressive symptoms (according to GDS) were more pronounced (median 2 vs. 1, p = 0.002). The SARC-F questionnaire score, which is part of the sarcopenia case finding, was higher in PS (median 2 vs. Objective physical performance measures reinforced these differences: median handgrip strength was lower in PS (16.2 kg vs. 23.0 kg, p < 0.001), 4-m walking test was slower (5.00 s vs. 3.78 s for 4 m, p < 0.001), Timed Up and Go (TUG) was longer (12.03 s vs. 8.75 s, p < 0.001) and STST was slower (16.07 s vs. 12.00 s, p < 0.001). These results confirm that the PS group had physical dysfunctions consistent with PS. In addition, the PS group had a higher mean body mass index (BMI) (median 29.0 vs. 26.7 kg/m², p = 0.006), suggesting that some subjects with sarcopenic obesity may reflect the inclusion of patients with lower muscle mass (despite higher weight). Inflammatory Markers – Group Differences All inflammatory indices examined were higher in the PS group than in controls ( Table 1 ). UHR was higher in PS with a median of 0.11 compared to 0.09 in NS (p < 0.001). MHR was also higher (median of 0.0100 vs. 0.089, p < 0.001). The median of CAR in PS was 1.37, with the NS median above 1.02 (p < 0.001). The CHR was also higher in PS (PS median 0.13 vs. NS 0.07; p < 0.001 for group difference). SII was higher in PS, median 623.5 (×10⁹/L) and 479.5 in NS (p < 0.001). THR showed a smaller but statistically significant difference (PS median 2.19 vs. NS 2.15, p = 0.012). Figure 2 shows the distribution of selected inflammatory parameters between PS and NS groups. Overall, these findings suggest that older adults with PS have an elevated inflammatory profile as reflected by these composite indices. Diagnostic performance of inflammatory indices is shown in Table 3 . The largest relative differences were observed for UHR, MHR, CAR, CHR, and SII, all of which were elevated in probable sarcopenic individuals, while THR showed only a modest increase. When subgroup analyses were examined (Table 2), 107 (41.3%) of those who lost 5% or more weight in 6 months had PS. While no significant difference was found between the groups with and without UWL in terms of gender (p = 0.373); the group with UWL was more dependent in daily and instrumental life activities (p = 0.002). Although the same values were seen in the table, the difference between the two groups was caused by the difference in the lower and upper cut-off values. The group with UWL was more frail (p < 0.001); and had a greater risk in terms of malnutrition and sarcopenia (p < 0.001). The risk of sarcopenia was significantly higher in patients admitted to the hospital with UWL (p = 0.034). A significant difference was observed only with SII among inflammatory markers such as UHR, MHR, THR, CAR, SII and CHR between the groups with and without UWL (p = 0.009). Correlation and ROC Analyses The relationship between standard inflammation markers (such as CRP, uric acid, albumin, etc.) and new inflammation markers was evaluated. Table 4 presents the correlation coefficients between biomarkers related to inflammation parameters. The correlations between UHR, MHR, CAR and SII reached significant statistical significance (Spearman's τ ranged from 0.57 to 0.93, all p < 0.001). For example, UHR showed a significant (p < 0.001) correlation with MHR (τ = 0.57) and THR (τ = 0.55). UHR also had the expected negative correlation with HDL-C (τ = − 0.76, p < 0.001) and a high positive correlation with serum uric acid (τ = 0.81, p < 0.001) (since UHR components include serum uric acid and HDL). Table-3: presents ‘’Diagnostic Performance of Inflammatory Indexes’’ Abbreviations: AUC, area under the receiver-operating characteristic curve; CI, confidence interval; UHR, Uric acid-to-high-density lipoprotein cholesterol ratio; MHR, Monocyte-to-high-density lipoprotein cholesterol ratio; ROC, receiver-operating characteristic; THR, total cholesterol-to-high-density lipoprotein cholesterol ratio; CAR, C-reactive protein to albumin ratio; CHR, C-reactive protein to HDL ratio; SII, systemic immune-inflammation index. Table 4 presents the correlation coefficients between inflammatory parameters and related biomarkers τ value P value UHR-HDL -0.757 < 0.001 UHR-s Uric Acid 0.810 < 0.001 UHR-Neutrophil 0.235 < 0.001 UHR- MHR 0.570 < 0.001 UHR-THR 0.554 < 0.001 UHR-CHR 0.271 < 0.001 CAR- CRP 0.963 < 0.001 CAR- Albumin -0.368 < 0.001 CAR-CHR 0.930 < 0.001 MHR-HDL -0.757 < 0.001 MHR-s Uric Acid 0.810 < 0.001 MHR- Neutrophil 0.235 < 0.001 MHR- CHR 0.271 < 0.001 MHR-THR 0.458 < 0.001 MHR-CAR 0.208 < 0.001 THR-DM 0.320 < 0.001 THR-HDL -0.643 < 0.001 SII-Neutrophil 0.692 < 0.001 SII- CRP 0.102 0.024 SII-CAR 0.117 0.01 SII-UHR 0.148 0.001 SII-CHR 0.137 0.002 SII-MHR 0.200 0.2 or < − 0.2 are underlined, P < 0.05 is shown as significant. Similarly, MHR had a negative correlation with HDL (τ = − 0.76, p < 0.001) as expected by definition, while it had a high positive correlation with uric acid (τ = 0.81, p < 0.001). There was also a high correlation with CAR and CHR (τ = 0.93, p < 0.001). MHR and CHR were also moderate correlated than other inflammatory indices (τ = 0.27, p < 0.001). The least correlation was generally seen between SII and other inflammatory indices. All of these new inflammatory indices were associated with classical inflammatory markers such as CRP and neuthrophil. For example, CAR is mathematically related to CRP and albumin; as expected, CAR was highly correlated with CRP level (τ = 0.96), while it had a moderate and expected inverse correlation with albumin (τ = − 0.37 ), reaching statistical significance (p < 0.001). MHR showed a moderate positive correlation with CHR (τ = 0.27, p < 0.001) and a similar correlation with CAR (τ = 0.20, p < 0.001). SII, which combines blood cell counts, showed a positive correlation with the neutrophil component (τ = 0.69, p < 0.001) and also with CRP (τ = 0.10, p = 0.024). These correlations confirm that higher values of UHR, MHR, CAR, CHR and SII reflect increased systemic inflammation, consistent with elevations in traditional inflammatory biomarkers. We assessed the potential utility of each inflammatory index in distinguishing patients with PS from those without. Figure 3 shows the ROC curves for all inflammatory parameters in detecting PS. Table 2 summarizes the results of the ROC analysis. UHR emerged as the most promising discriminator between the indices with AUC of 0.638 (95% confidence interval approximately 0.59–0.69, p < 0.001). The optimal cut-off value for UHR was approximately 0.1204, providing 44% sensitivity and 83% specificity for detecting PS. Although the sensitivity for UHR at this threshold is modest, the high specificity suggests that patients with a UHR above 0.12 are likely to have sarcopenia, although many sarcopenic patients will have a lower UHR. The AUC of MHR was 0.616 (p < 0.001). A cut-off value of approximately 0.011 for MHR provided 45% sensitivity and 74% specificity. The CAR index showed an AUC of 0.602 (p < 0.001) and had an optimum CAR cut-off of approximately 0.79 (given CRP in mg/L and albumin in g/dL). At this threshold, CAR had a sensitivity of 71% and a specificity of 45% for sarcopenia - CAR had lower specificity but much higher sensitivity compared to UHR and MHR. CHR had an AUC of 0.608 (p < 0.001); the best cut-off (0.07 mg/L per mg/dL unit) provided 68% sensitivity and 51% specificity. The AUC value of SII was 0.626 (p < 0.001), the optimum cut-off point was 481.8 (corresponding to approximately 4.82×10¹¹ in SI units, combining neutrophils, platelets, lymphocytes), providing 71% sensitivity and 51% specificity. Although THR was significantly higher in those with PS (p = 0.012 ), it was not considered significant in terms of sensitivity and specificity since the AUC value was < 0.6 when calculated, and cut-off values were not determined (Fig. 4). Discussion Our study investigated the relationship between new inflammatory parameters and PS in older adults presenting to the geriatric outpatient clinic with complaints of weight loss. We evaluated six inflammation-based indices (UHR, MHR, THR, CAR, CHR, and SII) in 490 patients aged 65 years and older and compared those with PS with controls at no risk of sarcopenia. To our knowledge, this is the first study to comprehensively examine these inflammatory markers collectively in relation to sarcopenia in an elderly population. Our findings show that all investigated inflammatory parameters were significantly higher in patients with PS, supporting the hypothesis that sarcopenia is closely associated with a high inflammatory state. Subgroup analyses of the study population showed that PS was higher in the group with UWL at 6 months and that this group was more frail and more dependent on daily and instrumental activities. All inflammatory parameters were higher in this group. However, only SII reached statistical significance among these indices, which means that SII may be more sensitive to weight loss and related muscle mass loss than other inflammatory parameters. In a study supporting this, SII values were higher in sarcopenic obese patients who underwent bariatric surgery and subsequently lost more weight and experienced muscle loss [ 26 ]. This situation draws attention to the negative impact of significant weight loss, such as 5% or more in 6 months, on inflammation and sarcopenia in the elderly population during the aging process. In this study, we found that inflammation-based parameters (UHR, CAR, MHR, THR, CHR, and SII) were higher in older adults with PS compared to those without sarcopenia. Our findings suggest that these easily calculated indices may reflect the high inflammatory status underlying the pathology of sarcopenia. We also observed that UHR, CAR, MHR, and SII were associated not only with each other but also with classical inflammatory markers such as CRP, albumin and neutrophil. Finally, UHR, MHR, CAR, and SII showed high sensitivity and specificity in detecting probable sarcopenia (CAR and SII showed the highest sensitivity and UHR the highest specificity). The results support the idea that chronic low-grade inflammation contributes to sarcopenia and that markers that integrate metabolic and inflammatory information may serve as proxies for this process. Serum uric acid (sUA), the end product of purine metabolism produced mainly by the liver, has pro-oxidant effects. High sUA together with low HDL-C has been associated with pro-inflammatory conditions such as autoimmune thyroiditis, metabolic syndrome (MetS) and type 2 diabetes mellitus [ 27 ]. Li et al reported that hyperuricemia is associated with MetS and diabetes [ 27 ]. UHR has emerged as a predictor of metabolic and glycemic disorders by combining these two parameters: Kocak et al showed that UHR predicted MetS in type 2 diabetics [ 7 ]. Aktas et al found that UHR predicted poor glycemic control in men with type 2 diabetes [ 8 ]. Evidence suggests that UHR and CAR may serve as markers for inflammatory metabolic diseases [ 28 , 29 ]. HDL cholesterol plays an anti-inflammatory and antioxidant role by protecting the vascular endothelium from oxidation and inflammation [ 30 ]. Therefore, low HDL is a risk factor for cardiovascular disease and is therefore frequently found in pro-inflammatory states. Low HDL cholesterol has been associated with inflammatory diseases such as metabolic syndrome, diabetes mellitus and cancer [ 31 ]. One consequence of low HDL is an increase in UHR. In our study, the PS group had both higher UHR and lower HDL levels than controls, consistent with this concept. This is not a confusing coincidence; rather, it reflects the fact that sarcopenia – like the disorders mentioned above – is characterized by chronic inflammation and metabolic deterioration, which tend to lower HDL [ 31 ]. Chronic low-grade inflammation (as seen in sarcopenia and related disorders) is characterized by decreases in HDL and changes in HDL particles [ 32 ]. It should be noted that UHR values may be affected by gender distribution, as men generally have lower HDL levels than women; However, the gender composition of the groups in our study was similar, so gender is unlikely to confound UHR differences [ 33 ]. CAR, defined as the CRP/albumin ratio, is an inflammation-based prognostic index that reflects both inflammation and nutritional status. It has attracted attention because it outperforms other indices. High CAR values are associated with outcomes in sepsis, pancreatitis, and cancer, including poorer performance status and reduced overall and cancer-specific survival in gastric cancer [ 33 ]. In metastatic gastric cancer patients receiving chemotherapy, CAR predicted overall survival, disease-free survival, and cancer- specific survival [ 34 ]. By integrating systemic inflammation and nutritional status, CAR provides insights beyond traditional markers of inflammation. Toyokawa et al. reported that preoperative CAR, together with other markers, has prognostic significance in stage II gastric cancer [ 34 ]. Therefore, CAR captures the effects of inflammation and malnutrition in chronic disease states. In our patients at risk for sarcopenia, high CAR values likely reflect both the inflammatory environment and the impaired nutritional status commonly seen in this population. In addition to UHR, CAR and MHR has attracted attention as a marker of chronic inflammation and cardiovascular risk. Evidence suggests that high MHR reflects chronic, low-grade inflammation and is associated with pathological conditions. The finding of a significant correlation between MHR and CVD in our study supports this notion. MHR has been found in patients with poorly controlled hypertension and has been associated with blood pressure levels in primary hypertensives [ 35 ]. In cross-sectional studies, MHR has been associated with the incidence of nonalcoholic fatty liver disease (NAFLD), coronary heart disease, and the prevalence of chronic kidney disease [ 36 – 38 ]. These conditions share chronic inflammation as a feature, supporting the idea that MHR captures an aspect of systemic inflammation. In the present study, consistent with the inflammatory nature of sarcopenia, higher MHR in patients with probable sarcopenia compared with nonsarcopenic controls and its correlation with CVD also confirm these studies. In our study, no significant correlation was found between MHR and HT, DM or CKD. This may be due to the fact that the sample size did not reflect the entire sample or that it did not include hospitalized patients who were more frail and dependent in their daily activities, who may have higher inflammation rates. Emerging evidence in the medical literature suggests that UHR may serve as a marker of chronic low-grade inflammation in a number of conditions, including hypertension, fatty liver disease, coronary heart disease and chronic kidney disease [ 39 , 40 ]. All of these conditions are characterized by marked or mild inflammation [ 41 , 42 ]. Consistently, we found that UHR levels were higher in probable sarcopenic patients in parallel with these conditions. To our knowledge, our study is the first to report an association between UHR and PS (or low muscle strength) in older adults. Given that sarcopenia and metabolic syndrome share inflammatory pathways, it is possible that high UHR reflects inflammatory processes common to both conditions. However, due to the cross- sectional design of our study, we cannot establish a causal relationship between high UHR and sarcopenia. It remains unclear whether high UHR contributes to muscle loss or is merely a by-product of metabolic disorders associated with sarcopenia. SII is utilized as a biomarker in ulcerative colitis and chronic kidney disease. SII functions as a guide in predicting postoperative tumor recurrence in colorectal cancer and in prognosis prediction for immunotherapy treatments in various cancers [ 43 , 44 ]. The association between systemic immune-inflammation index and chronic obstructive pulmonary disease in adults aged 40 years and above in the United States: a cross-sectional study based on the NHANES 2013–2020 [ 45 ]. Rheumatoid arthritis and liver fibrosis are also among the most important effective parameters in all of these diseases. Neutrophils are key inflammatory cells in the pathogenesis of these diseases, and an increase in the number of neutrophils in the blood is a feature of these diseases. This explains why SII is significantly higher in patients with probable sarcopenia [ 46 , 47 ]. Our findings suggest a significant correlation between MHR and the likelihood of developing cardiovascular disease in the context of sarcopenia, and between THR and DM. The interaction between lipid metabolism and inflammation is critical in the pathogenesis of DM. The multifaceted protective roles of HDL, including reverse cholesterol transport and antioxidant, anti-inflammatory and anti-thrombotic effects, are well documented [ 48 ]. The anti-inflammatory properties of HDL help prevent oxidative modification of LDL. HDL may counteract inflammation by reducing the expression of adhesion molecules (such as P-selectin, E-selectin, ICAM-1, VCAM-1) on endothelial cells and by inhibiting the adhesion of immune cells to the endothelium. Inflammation may impair their function, leading to decreased HDL levels and qualitative changes in HDL particles. Proteins and enzymes associated with HDL metabolism undergo changes during systemic inflammation [ 49 ]. In our sarcopenic patients, the higher CHR suggests a scenario of higher CRP relative to HDL – essentially combining a marker of inflammation with a marker of cardiometabolic health [ 49 ]. This higher CHR in sarcopenia is consistent with the concept that sarcopenia may be part of a broader inflammatory cardiometabolic risk profile. However, further research is needed to validate CHR as a risk indicator in sarcopenia and to understand whether it provides prognostic information beyond its individual components. To our knowledge, our study is the first in the literature to present the association between a wide range of inflammatory parameters, such as UHR, CAR, CHR, MHR, THR, SII and sarcopenia-related outcomes. However, several limitations should be noted. First, the cross-sectional design inherently limits our ability to establish causal relationships; for example, whether high UHR contributes to or is caused by sarcopenia. We cannot infer temporality or causality from this temporal snapshot. Second, our study population (n = 490) may have been relatively small to optimize cut-off values for biomarkers such as UHR; a larger sample may have better defined the distribution and thresholds of these indices in sarcopenia. Third, the retrospective nature of the study is another limitation. We relied on available medical records and therefore could not control for all potential confounders or ensure uniform testing conditions (e.g., timing of blood draws, fasting status, or consistency in physical performance tests). A prospective, multicenter study with a large sample of older adults—ideally including many individuals with diabetes and metabolic syndrome who typically have high UHR and SII—would be valuable to confirm and refine the usefulness of these inflammatory markers in sarcopenia. Finally, given the cross-sectional design, our study cannot answer whether interventions that alter these parameters (such as improving HDL or lowering uric acid, or by increasing albumin and lowering CRP) would alter the course of sarcopenia or related outcomes in conditions such as diabetic kidney disease. For example, we observed that patients at risk for sarcopenia had lower HDL and higher uric acid; whether aggressive management of dyslipidemia or hyperuricemia would improve muscle outcomes remains an open question that our data cannot address. The low UHR values in the already probable sarcopenic group may suggest that these values or aggressive management of weight may increase malnutrition and worsen sarcopenia. CAR can be an independent predictor of prognosis and mortality in malignant diseases such as malignant pleural mesothelioma [ 50 ]. However, since our study was cross- sectional and did not have sufficient follow-up time, these contributions could not be evaluated. Despite these limitations, we believe that our report provides a basis for future prospective cohort studies and hypothesis-generating insights into the links between inflammatory markers and sarcopenia. Conclusions We showed that older adults with probable sarcopenia exhibited higher levels of inflammation-based markers, including UHR, MHR, CAR, CHR, SII, and to a lesser extent THR. These findings highlight the close interaction between chronic systemic inflammation (inflammaging) and sarcopenia. Among the indices investigated, UHR emerged as a notable marker in terms of specificity, while CAR and SII emerged as a notable marker in terms of sensitivity, demonstrating their ability to discriminate inflammation for sarcopenia and reflecting the combined effects of hyperuricemia and hypoalphalipoproteinemia (low HDL); CRP and albumin; and monocyte and lymphocyte counts in this population. Our results suggest that these inexpensive and readily available indices may serve as proxies for inflammation and metabolic disorders in sarcopenia. They were also associated with each other and with well-known inflammatory markers such as CRP and ESR, and had significant correlations with CVD and DM. This strengthened their validity as indicators of systemic inflammation. Although none of these markers alone is sufficient to diagnose sarcopenia, they may have potential as part of a multifactorial risk assessment or as targets for monitoring intervention effects. For example, an elderly patient with unusually high UHR, CAR, or SII may warrant closer assessment of muscle strength and function. In summary, inflammatory markers such as UHR, MHR, CAR, CHR, and SII are elevated in sarcopenic older adults and are associated with functional decline associated with sarcopenia. These parameters, particularly UHR, may help identify individuals at risk for sarcopenia or serve as objective measures to monitor the inflammatory aspect of sarcopenia progression. Future prospective studies are needed to determine the predictive value of these indices for the onset of sarcopenia, to investigate the underlying mechanisms, and to assess whether altering these parameters (e.g., through lifestyle changes or pharmacotherapy) has a beneficial effect on muscle health and functional outcomes in older adults. Abbreviations AUC, area under the receiver-operating characteristic curve; CI, confidence interval; UHR, Uric acid-to-high-density lipoprotein cholesterol ratio; MHR, Monocyte-to-high-density lipoprotein cholesterol ratio; ROC, receiver-operating characteristic; THR, total cholesterol-to-high-density lipoprotein cholesterol ratio; CAR, C-reactive protein to albumin ratio; CHR, C-reactive protein to HDL ratio; SII, systemic immune-inflammation index. Declarations Author Contribution Elif Gecegelen took part in obtaining ethics committee approval, including patients in the study according to the eligibility criteria, and together with Mete Üçdal, evaluating the patient records, performing statistical analyses, and writing the article. Arzu Okyar Baş, Didem Karaduman, and Cansu Atbas took part in evaluating the patients, checking appropriate statistical analyses, and checking the tables and figures. Mert Eşme, Cafer Balcı, Burcu Balam Doğu, and Meltem Gülhan Halil took part in writing the article appropriately, checking the patient data, and conducting the study. Mustafa Cankurtaran took part in conducting the entire process of the article, checking the suitability of the statistical methods, and controlling the data. References Franceschi, C., et al., Inflamm-aging. An evolutionary perspective on immunosenescence. Ann N Y Acad Sci, 2000. 908 : p. 244-54. Franceschi, C. and J. 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Tani, S., et al., Development of a model for prediction of coronary atherosclerotic regression: evaluation of high-density lipoprotein cholesterol level and peripheral blood monocyte count. Heart Vessels, 2012. 27 (2): p. 143-50. Toyokawa, T., et al., Comparison of the prognostic impact and combination of preoperative inflammation-based and/or nutritional markers in patients with stage II gastric cancer. Oncotarget, 2018. 9 (50): p. 29351-29364. Ganjali, S., et al., Monocyte-to-HDL-cholesterol ratio as a prognostic marker in cardiovascular diseases. J Cell Physiol, 2018. 233 (12): p. 9237-9246. Wang, L., et al., Association Between Monocyte to High-Density Lipoprotein Cholesterol Ratio and Risk of Non-alcoholic Fatty Liver Disease: A Cross-Sectional Study. Frontiers in Medicine, 2022. Volume 9 - 2022 . Yang, Y., et al., The correlation between serum MHR and NLR and the severity of coronary lesions in NSTE-ACS patients of different genders. Front Cardiovasc Med, 2024. 11 : p. 1469730. Xu, L., et al., The association between monocyte to high-density lipoprotein cholesterol ratio and chronic kidney disease in a Chinese adult population: a cross-sectional study. Ren Fail, 2024. 46 (1): p. 2331614. Yazdi, F., et al., Investigating the relationship between serum uric acid to high-density lipoprotein ratio and metabolic syndrome. Endocrinol Diabetes Metab, 2022. 5 (1): p. e00311. Li, S., Z. Liu, and C. Lu, Association of uric acid to high-density lipoprotein cholesterol ratio with the presence or absence of hypertensive kidney function: results from the China Health and Retirement Longitudinal Study (CHARLS). BMC Nephrol, 2025. 26 (1): p. 123. Cheng, Y., et al., Association between serum uric acid/HDL-cholesterol ratio and chronic kidney disease: a cross-sectional study based on a health check-up population. BMJ Open, 2022. 12 (12): p. e066243. Park, B., D.H. Jung, and Y.J. Lee, Predictive Value of Serum Uric Acid to HDL Cholesterol Ratio for Incident Ischemic Heart Disease in Non-Diabetic Koreans. Biomedicines, 2022. 10 (6). Yan, J., et al., Systemic immune-inflammation index as a potential biomarker to monitor ulcerative colitis. Curr Med Res Opin, 2023. 39 (10): p. 1321-1328. Huang, P., et al., Association of systemic immune-inflammation index and systemic inflammation response index with chronic kidney disease: observational study of 40,937 adults. Inflamm Res, 2024. 73 (4): p. 655-667. Xu, Y., et al., The association between systemic immune-inflammation index and chronic obstructive pulmonary disease in adults aged 40 years and above in the United States: a cross-sectional study based on the NHANES 2013-2020. Front Med (Lausanne), 2023. 10 : p. 1270368. Xie, R., et al., Association between SII and hepatic steatosis and liver fibrosis: A population-based study. Front Immunol, 2022. 13 : p. 925690. Liu, B., et al., The association between systemic immune-inflammation index and rheumatoid arthritis: evidence from NHANES 1999–2018. Arthritis Research & Therapy, 2023. 25 (1): p. 34. Li, J. and H. Ma, Associations of the hs-CRP/HDL-C ratio with cardiovascular disease among US adults: Evidence from NHANES 2015-2018. Nutr Metab Cardiovasc Dis, 2025. 35 (4): p. 103814. Riwanto, M. and U. Landmesser, High density lipoproteins and endothelial functions: mechanistic insights and alterations in cardiovascular disease. J Lipid Res, 2013. 54 (12): p. 3227-43. Takamori, S., et al., The C-Reactive Protein/Albumin Ratio is a Novel Significant Prognostic Factor in Patients with Malignant Pleural Mesothelioma: A Retrospective Multi-institutional Study. Ann Surg Oncol, 2018. 25 (6): p. 1555-1563. Table 1 and 2 Table 1 and 2 are available in the Supplementary Files section. Additional Declarations No competing interests reported. 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2","display":"","copyAsset":false,"role":"figure","size":289072,"visible":true,"origin":"","legend":"\u003cp\u003eshows the distribution of inflammatory parameters between the ‘’Probable sarcopenia and Non-sarcopenia groups.\"\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7075695/v1/c9ecdf3669c642e58c891a97.png"},{"id":86665825,"identity":"0f5fa625-3aab-4bed-b629-25e99391e18a","added_by":"auto","created_at":"2025-07-14 11:07:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":236970,"visible":true,"origin":"","legend":"\u003cp\u003edemonstrates the ROC curves for all inflammatory parameters in detecting probable 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0.6.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7075695/v1/f76c6758e5db33a5963d520d.png"},{"id":87981801,"identity":"494090a9-8767-4468-b051-659e1ce77e50","added_by":"auto","created_at":"2025-07-31 06:17:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2696037,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7075695/v1/3b9a81e3-e273-4659-b3be-47ce8d49597e.pdf"},{"id":86665817,"identity":"f1ca97eb-309b-4a22-aef0-1ea345c533f1","added_by":"auto","created_at":"2025-07-14 11:07:20","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":27339,"visible":true,"origin":"","legend":"","description":"","filename":"Table1and2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7075695/v1/4ffbf3bff066bfc1139d6696.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eCan Novel Inflammatory Parameters (UHR, MHR, THR, CAR, CHR, SII) Predict Sarcopenia In Older Adults With Weight Loss?\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eSarcopenia is a loss of skeletal muscle mass and strength associated with aging [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It has been linked to inflammaging – a chronic, low-grade pro-inflammatory state that develops during aging. Inflammaging is characterized by increased levels of inflammatory mediators and is implicated in age-related diseases such as type 2 diabetes, osteoarthritis, and sarcopenia [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. With advancing age, the prevalence of conditions related to metabolic dysfunction and inflammaging (e.g. diabetes, obesity, hypertension) rises, suggesting that virtually everyone may face sarcopenia and its complications [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe inflammaging involved in the sarcopenia process is exacerbated by changes in glucose and lipid metabolism, insulin resistance, and oxidative stress, leading to increased production of inflammatory cytokines. In addition to primary aging, secondary causes of sarcopenia are associated with lipid metabolism disorders[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. For example, replacement of type II muscle fibers with fat is a hallmark of sarcopenia, contributing to muscle atrophy [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Chronic low- grade inflammation in sarcopenia causes oxidative stress-induced redox imbalance and upregulation of pro-inflammatory mediators [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This chronic inflammatory milieu drives tissue degeneration in age-related diseases [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, the contribution of the pro-inflammatory mediators involved to sarcopenia and other age-related conditions is still poorly understood [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Recent studies have identified inflammatory biomarkers associated with inflammatory conditions that contribute to sarcopenia. These include Uric Acid/HDL-Cholesterol Ratio (UHR), C-Reactive Protein (CRP)/Albumin Ratio (CAR), Monocyte/HDL-Cholesterol Ratio (MHR), CRP/HDL- Cholesterol Ratio (CHR), Systemic Immunity-Inflammation Index (SII), and Triglyceride/HDL- Cholesterol Ratio (THR) [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e–\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. These indices are derived from routine laboratory parameters and reflect the degree of systemic inflammation in an accessible and cost-effective manner.\u003c/p\u003e\u003cp\u003eGiven the evidence that sarcopenia in older individuals may be a consequence of chronic inflammatory and metabolic disorders, examining inflammatory markers in older adults with sarcopenia may provide valuable insights. According to our studies, this wide range of new inflammatory markers has not been studied as a whole in older people at risk for sarcopenia. In this study, we aimed to evaluate the characteristics and levels of inflammatory markers (UHR, MHR, THR, CAR, CHR, SII) in patients aged 65 years and older with and without probable sarcopenia. We sought to observe differences in these\u003c/p\u003e\u003cp\u003eparameters between the probable sarcopenia (PS) group and controls. We hypothesized that these inflammation-based markers may be elevated in sarcopenic patients and serve as indicators of sarcopenia risk. This study provides important information regarding the rapid and easy screening of sarcopenia in the geriatric population during outpatient patients with new inflammatory markers.\u003c/p\u003e\u003c/div\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective cross-sectional study was conducted at the Department of Geriatrics, Hacettepe University Hospital, following ethical approval from the Hacettepe University Faculty of Health Sciences Ethics Committee (Date: January 9, 2024; Approval No: 2024/01–01, SBA 23/411). Patient records were reviewed between January 2024 and December 2024. Patients aged 65 years and older who presented to the geriatric outpatient clinic with complaints of weight loss between June 1, 2021, and June 30, 2023, were evaluated for inclusion. After ethical approval, patient data between March 1, 2024 and May 30, 2025 were analyzed. We applied the following inclusion criteria: patients aged ≥ 65 years who had undergone a comprehensive geriatric evaluation and documented weight loss. Since all of the patient population included in the study had a weight loss statement at presentation, in order to clearly evaluate the weight loss that could also affect probable sarcopenia, patients with 5% and more weight loss in 6 months were accepted as patients who applied to the outpatient clinic with unintentional weight loss (UWL) [11].\u003c/p\u003e\n\u003cp\u003ePatients were excluded if they were (a) younger than 65 years, (b) had a known condition that could affect physical performance tests (e.g., chair stand test, hand grip strength test) such as severe dementia, neuromuscular disease, rheumatologic disease, corticosteroid therapy with those taking \u0026gt; 5 mg prednisolone or equivalent per day for the last 3 years or those with physical limitations to perform these tests (having had surgery that would prevent movement within the last 1–3 months or having infectious findings in both extremities), (c) had incomplete medical history or incomplete clinical data, or (d) had incomplete laboratory results to calculate inflammatory indices. Data from patients with stroke sequelae, severe osteoarthritis, or extrapyramidal movement disorders (such as Parkinson's disease) who were disabled or immobile were also excluded. After applying the exclusion criteria, 490 older adults were included in the study.\u003c/p\u003e\n\u003cp\u003eThese patients were divided into two groups according to sarcopenia status: Probable Sarcopenia (PS) and Non-Sarcopenia (NS). The study flow and patient allocation process are shown in Fig. 1. PS was defined according to revised criteria from the European Working Group on Sarcopenia in Older Adults (EWGSOP2) definition, with an emphasis on low muscle strength. To assess muscle strength and the risk of sarcopenia, the SARC-F questionnaire, handgrip strength test (HGST), and 5-times chair sit-to-stand test (STST) were performed.\u003c/p\u003e\n\u003cp\u003ePatients with a SARC-F score ≥ 4 were considered at risk for sarcopenia. Muscle strength was measured using the HGST with a calibrated handheld dynamometer (TKK5401; Takei III Smedley Type Digital Dynamometer Takei Scientific Instruments, Tokyo, Japan) [12].\u003c/p\u003e\n\u003cp\u003eMeasurements were made while participants were standing with their arms positioned parallel to the floor. The highest value of 3 repeated measurements was taken in the analysis. HGST \u0026lt; 16 and \u0026lt; 27 kg for women and men, respectively, were taken as the cut-off values to assess muscle strength [13]. In terms of the ability to predict outcomes associated with sarcopenia, poor physical performance was defined as walking speed ≤ 0.8 m/s during a 4 m walking test using a manual stopwatch [13]. When evaluating walking speed, the average of two measurements was taken. Patients with low grip strength (men \u0026lt; 27 kg, women \u0026lt; 16 kg) or poor chair stand performance (\u0026gt; 15 seconds for 5 times) were classified as having PS according to the EWGSOP2 guidelines (sarcopenia confirmed by low muscle mass was not assessed in this study due to its retrospective nature, therefore termed “probable” sarcopenia). Those not meeting these criteria were classified as Non-sarcopenia. For each patient, we recorded demographic information (age, gender), comprehensive geriatric assessment results, comorbidities, and laboratory values at baseline assessment in \u003cstrong\u003eTable-1\u003c/strong\u003e. Comparison of geriatric evaluations in patients with and without UWL and differences between groups with new inflammatory markers are shown in \u003cstrong\u003eTable-2.\u003c/strong\u003e Common comorbid conditions included diabetes mellitus (DM), hypertension (HT), coronary artery disease (CAD), chronic kidney disease (CKD), atrial fibrillation (AF), and dementia. Geriatric assessment measures such as Clinical Frailty Scale (CFS), Katz Activities of Daily Living (ADL) index, Lawton Instrumental Activities of Daily Living (IADL) scale, standardized Mini-Mental State Examination (s-MMSE), 15-item Geriatric Depression Scale (GDS), and Mini Nutritional Assessment-Short Form (MNA-SF) were obtained from patient records.\u003c/p\u003e\n\u003cp\u003eLaboratory values including C-reactive protein (CRP), serum albumin, serum uric acid, triglycerides, high-density lipoprotein cholesterol (HDL-C), 25-hydroxyvitamin D, complete blood count parameters [(CBC), total leukocyte count, hemoglobin, hematocrit, platelet count, and differential counts] were obtained from the institutional database. These laboratory measurements were performed from fasting blood samples as part of the routine geriatric assessment of patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComprehensive Geriatric Assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants underwent a Comprehensive Geriatric Assessment (CGA). Basic activities of daily living (ADL) [14, 15] (0–6 points) and instrumental activities of daily living (IADL) were used to measure the independence and functional ability of the patients [16]. Basic ADLs consist of six activities; bathing, dressing, going to the toilet, incontinence, transferring and feeding. IADL consists of using the phone, shopping, preparing food, housework, doing laundry, transportation, taking medication and managing financial affairs. MNA-SF (0–14 points) was used to determine the nutritional status of the patients and scores below 11 were considered as malnutrition and malnutrition risk [17]. The weakness status of the patients was defined by the CFS (1–9 points) [18]. According to the CFS, patients who were level 4 and more were accepted as living with frailty.\u003c/p\u003e\n\u003cp\u003eGeriatric syndromes (osteoporosis, dementia, depression, falls, and polypharmacy) identified by the CGA were also recorded. s-MMSE and GDS were performed to assess cognitive function and depressive symptoms, respectively [19–22]. Depression was defined as a score of 5 or more. The SARC-F questionnaire was used to determine the risk of sarcopenia. The questionnaire screens patients for self-reported symptoms suggestive of sarcopenia, including lack of strength, walking assistance, getting up from a chair, climbing stairs, and falling. Each of the self-reported parameters has a minimum and maximum score of 0 and 2, with the largest maximum SARC-F score being 10, with a score of 4 or more being considered as a risk of sarcopenia [23].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCalculation of Inflammatory Indices\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe inflammatory parameters were calculated for each patient from the laboratory data as follows:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eUHR (Uric Acid to HDL-C Ratio) = Serum uric acid level (mg/dL) ÷ HDL cholesterol level (mg/dL)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eMHR (Monocyte to HDL-C Ratio) = Absolute monocyte count (10³/µL) ÷ HDL cholesterol level (mg/dL)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eTHR (Triglyceride to HDL-C Ratio) = Serum triglyceride level (mg/dL) ÷ HDL cholesterol level (mg/dL)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eCAR (CRP to Albumin Ratio) = C-reactive protein level (mg/L) ÷ serum albumin level (g/dL)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eCHR (CRP to HDL-C Ratio) = C-reactive protein level (mg/L) ÷ HDL cholesterol level (mg/dL)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eSII (Systemic Immune-Inflammation Index) = Neutrophil count × Platelet count ÷ Lymphocyte count (all counts from CBC, with neutrophils, platelets, lymphocytes in 10³/µL)\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThese indices were derived for each patient to quantify systemic inflammation and metabolic imbalance. They were chosen based on prior studies indicating their relevance in chronic inflammatory states and age-related diseases.\u003c/p\u003e\n\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n\u003cp\u003eStatistical analyses were performed using IBM SPSS Statistics (Version 24 for Windows; IBM Corp., Chicago, IL, USA). We evaluated the distribution of continuous variables using the Kolmogorov–Smirnov test.\u003c/p\u003e\n\u003cp\u003eFor continuous variables that followed a normal distribution, comparisons between the PS and NS groups were made using the Independent-Samples T- test, and results are presented as mean ± standard deviation. For continuous variables not normally distributed, we used the Mann–Whitney U test, and data are presented as median with interquartile range (IQR).\u003c/p\u003e\n\u003cp\u003eCategorical variables were compared using the chi-square test and are presented as number (percent).\u003c/p\u003e\n\u003cp\u003eSpearman's rank correlation test was employed to analyze the relationships between the inflammatory parameters (UHR, MHR, THR, CAR, CHR, SII) and other variables, including traditional inflammatory markers (CRP, Neutrophil) and clinical measures.\u003c/p\u003e\n\u003cp\u003eIn order to demonstrate the discriminatory power of the diagnostic performance of new inflammation indices in determining PS, we constructed ROC curves and calculated the area under the ROC curve (AUC) for each index.\u003c/p\u003e\n\u003cp\u003eAreas with AUC \u0026lt; 0.6 were not considered significant to determine the cut-off value. Cutoff values for sensitivity and specificity were determined using the Youden Index [24]. A two-tailed p value \u0026lt; 0.05 was considered statistically significant for all analyses. Spearman Correlation analysis was recorded for correlation analyses, τ \u0026gt; 0.2 or \u0026lt; − 0.2 (|τ|\u0026gt;0.2) were considered to reflect the value of the underlying entity [25].\u003c/p\u003e\n\u003cp\u003eTo compare the distribution of inflammatory indices between groups, kernel density plots were generated using the ggplot2 package in R. Each index was visualized with overlaid density curves for the possible sarcopenic and non-sarconepic groups, shown in different colors for clarity. Optimal cut-off values determined by ROC analysis were indicated with vertical dashed lines on each plot. This approach allowed for visual assessment of distribution differences and the discriminative capacity of the cut-off values across groups\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Non-Interventional Research Ethics Committee of Hacettepe University Faculty of Medicine (Date: 09.01.24; Approval No: 2024/01–01, SBA 23/411). The study was conducted in accordance with the principles of the Declaration of Helsinki. Informed consent was not required from individuals due to the retrospective nature of the study using de-identified patient data. No interventions or blood draws were performed for the purposes of this research, and all data were derived from routine clinical care records.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv\u003e\n \u003cp\u003e\u003cstrong\u003eStudy Population Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe study included 490 older patients (median age 73 years, range 65–95; 66.3% female). Of these, 259 patients (52.9%) were classified as having PS group, and 231 (47.1%) were NS group. The PS group was older than the NS group (median age 76 [72–80] vs 71 [68–76] years, p \u0026lt; 0.001). The proportion of females was similar between groups (65.6% in PS vs 67.1% in NS, p = 0.732), indicating no sex difference in sarcopenia prevalence in our cohort.\u003c/p\u003e\n \u003cp\u003eComorbidity profiles of the two groups were comparable in terms of chronic diseases such as diabetes mellitus (DM), hypertension (HT), coronary artery disease (CAD), and chronic kidney disease (CKD), dementia and atrial fibrilliation (AF) (\u003cstrong\u003eTable\u0026nbsp;1\u003c/strong\u003e). The prevalence of DM, HT, CAD and CKD did not differ between PS and NS groups (p \u0026gt; 0.10 for each). However, dementia and AF were more common in the PS group: AF was present in 12.7% of PS patients versus 4.8% of NS (p = 0.002), and clinically diagnosed dementia in 18.5% of PS vs 5.6% of NS (p \u0026lt; 0.001) group. These findings suggest that PS in older adults may associate with a higher burden of conditions like AF and dementia, even though other comorbidities were similar.\u003c/p\u003e\n \u003cp\u003eSince all patients included in the evaluation had weight loss, those with a weight loss of 5% and above in 6 months were accepted as UWL for classification, a total of 118 people had UWL (24.1%) and when subgroup analyses were performed, it was seen that those with UWL were more dependent in daily living and instrumental living activities (all p = 0.002), were more fraile than the other group and had a higher risk of malnutrition and sarcopenia (all p values \u0026lt; 0.001) (Table\u0026nbsp;2).\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eAmong laboratory parameters, serum uric acid, monocyte count, and inflammatory markers differed between groups, whereas lipid profiles showed differences in HDL but not triglycerides. Patients with PS had higher median serum uric acid (5.70 vs 5.10 mg/dL, p \u0026lt; 0.001) and higher monocyte counts (median 0.56 vs 0.51 ×10³/µL, p = 0.002) compared to controls. They also had elevated CRP levels (median 6.79 vs 3.59 mg/L, p = 0.001) and lower serum albumin (median 4.20 vs 4.35 g/dL, p \u0026lt; 0.001), consistent with a more inflammatory and less nourished state in probable sarcopenic patients. HDL cholesterol was lower in the PS group (median 53 vs 56 mg/dL, p = 0.001). In contrast, median triglyceride levels were not different (115 vs 113 mg/dL, p = 0.565), and 25(OH) vitamin D levels tended to be lower in PS (median 28.9 vs 30.4 µg/L) but without statistical significance (p = 0.095).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional and Geriatric Assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs expected, patients in the PS group had worse performance on physical tests and functional scales (\u003cstrong\u003eTable\u0026nbsp;1\u003c/strong\u003e). The PS group was more frail when assessed by CFS (4 [3–6] vs. 3 [3–4], p \u0026lt; 0.001). Although Katz (ADL) was the same in both groups as a median, there was a significant difference in maximal values (median 6 vs. 6, p \u0026lt; 0.001, and Lawton (IADL) was lower in the PS group (median 7 vs. 8, p \u0026lt; 0.001), indicating that probable sarcopenic patients were more dependent on daily and instrumental activities. Cognitive screening scores, s- MMSE, were lower in PS (median 27 vs. 29, p \u0026lt; 0.001), consistent with a higher prevalence of dementia. The risk of malnutrition measured by MNA-sf was higher in PS (median 12 vs. 13, p \u0026lt; 0.001) and depressive symptoms (according to GDS) were more pronounced (median 2 vs. 1, p = 0.002). The SARC-F questionnaire score, which is part of the sarcopenia case finding, was higher in PS (median 2 vs. Objective physical performance measures reinforced these differences: median handgrip strength was lower in PS (16.2 kg vs. 23.0 kg, p \u0026lt; 0.001), 4-m walking test was slower (5.00 s vs. 3.78 s for 4 m, p \u0026lt; 0.001), Timed Up and Go (TUG) was longer (12.03 s vs. 8.75 s, p \u0026lt; 0.001) and STST was slower (16.07 s vs. 12.00 s, p \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003eThese results confirm that the PS group had physical dysfunctions consistent with PS. In addition, the PS group had a higher mean body mass index (BMI) (median 29.0 vs. 26.7 kg/m², p = 0.006), suggesting that some subjects with sarcopenic obesity may reflect the inclusion of patients with lower muscle mass (despite higher weight).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInflammatory Markers – Group Differences\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll inflammatory indices examined were higher in the PS group than in controls (\u003cstrong\u003eTable\u0026nbsp;1\u003c/strong\u003e). UHR was higher in PS with a median of 0.11 compared to 0.09 in NS (p \u0026lt; 0.001). MHR was also higher (median of 0.0100 vs. 0.089, p \u0026lt; 0.001). The median of CAR in PS was 1.37, with the NS median above 1.02 (p \u0026lt; 0.001). The CHR was also higher in PS (PS median 0.13 vs.\u003c/p\u003e\n\u003cp\u003eNS 0.07; p \u0026lt; 0.001 for group difference). SII was higher in PS, median 623.5 (×10⁹/L) and 479.5 in NS (p \u0026lt; 0.001). THR showed a smaller but statistically significant difference (PS median 2.19 vs. NS 2.15, p = 0.012). Figure 2 shows the distribution of selected inflammatory parameters between PS and NS groups. Overall, these findings suggest that older adults with PS have an elevated inflammatory profile as reflected by these composite indices. Diagnostic performance of inflammatory indices is shown in \u003cstrong\u003eTable\u0026nbsp;3\u003c/strong\u003e. The largest relative differences were observed for UHR, MHR, CAR, CHR, and SII, all of which were elevated in probable sarcopenic individuals, while THR showed only a modest increase.\u003c/p\u003e\n\u003cp\u003eWhen subgroup analyses were examined (Table\u0026nbsp;2), 107 (41.3%) of those who lost 5% or more weight in 6 months had PS. While no significant difference was found between the groups with and without UWL in terms of gender (p = 0.373); the group with UWL was more dependent in daily and instrumental life activities (p = 0.002). Although the same values were seen in the table, the difference between the two groups was caused by the difference in the lower and upper cut-off values. The group with UWL was more frail (p \u0026lt; 0.001); and had a greater risk in terms of malnutrition and sarcopenia (p \u0026lt; 0.001). The risk of sarcopenia was significantly higher in patients admitted to the hospital with UWL (p = 0.034). A significant difference was observed only with SII among inflammatory markers such as UHR, MHR, THR, CAR, SII and CHR between the groups with and without UWL (p = 0.009).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation and ROC Analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe relationship between standard inflammation markers (such as CRP, uric acid, albumin, etc.) and new inflammation markers was evaluated. Table\u0026nbsp;4 presents the correlation coefficients between biomarkers related to inflammation parameters. The correlations between UHR, MHR, CAR and SII reached significant statistical significance (Spearman's τ ranged from 0.57 to 0.93, all p \u0026lt; 0.001). For example, UHR showed a significant (p \u0026lt; 0.001) correlation with MHR (τ = 0.57) and THR (τ = 0.55). UHR also had the expected negative correlation with HDL-C (τ = − 0.76, p \u0026lt; 0.001) and a high positive correlation with serum uric acid (τ = 0.81, p \u0026lt; 0.001) (since UHR components include serum uric acid and HDL).\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003cstrong\u003e\u003cu\u003eTable-3:\u003c/u\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003epresents \u0026lsquo;\u0026rsquo;Diagnostic Performance of Inflammatory Indexes\u0026rsquo;\u0026rsquo;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Abbreviations: AUC, area under the receiver-operating characteristic curve; CI, confidence interval; UHR, \u0026nbsp; \u0026nbsp; Uric acid-to-high-density lipoprotein cholesterol ratio; MHR, Monocyte-to-high-density lipoprotein cholesterol ratio; ROC, receiver-operating characteristic; THR, total cholesterol-to-high-density lipoprotein cholesterol ratio; CAR, C-reactive protein to albumin ratio; CHR, C-reactive protein to HDL ratio; SII, systemic immune-inflammation index.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003epresents the correlation coefficients between inflammatory parameters and related biomarkers\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eτ\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUHR-HDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUHR-s Uric Acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUHR-Neutrophil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUHR- MHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.570\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUHR-THR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUHR-CHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCAR- CRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCAR- Albumin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCAR-CHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.930\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMHR-HDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMHR-s Uric Acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMHR- Neutrophil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMHR- CHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMHR-THR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMHR-CAR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTHR-DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTHR-HDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSII-Neutrophil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSII- CRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSII-CAR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSII-UHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSII-CHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSII-MHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003eCorrelation findings are shown as Spearman correlation coefficient (P value); significant correlations\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003ewith |τ| \u0026gt;0.2 or \u0026lt; − 0.2 are underlined, P \u0026lt; 0.05 is shown as significant.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eSimilarly, MHR had a negative correlation with HDL (τ = − 0.76, p \u0026lt; 0.001) as expected by definition, while it had a high positive correlation with uric acid (τ = 0.81, p \u0026lt; 0.001). There was also a high correlation with CAR and CHR (τ = 0.93, p \u0026lt; 0.001). MHR and CHR were also moderate correlated than other inflammatory indices (τ = 0.27, p \u0026lt; 0.001). The least correlation was generally seen between SII and other inflammatory indices.\u003c/p\u003e\n\u003cp\u003eAll of these new inflammatory indices were associated with classical inflammatory markers such as CRP and neuthrophil. For example, CAR is mathematically related to CRP and albumin; as expected, CAR was highly correlated with CRP level (τ = 0.96), while it had a moderate and expected inverse correlation with albumin (τ = − 0.37 ), reaching statistical significance (p \u0026lt; 0.001). MHR showed a moderate positive correlation with CHR (τ = 0.27, p \u0026lt; 0.001) and a similar correlation with CAR (τ = 0.20, p \u0026lt; 0.001). SII, which combines blood cell counts, showed a positive correlation with the neutrophil component (τ = 0.69, p \u0026lt; 0.001) and also with CRP (τ = 0.10, p = 0.024). These correlations confirm that higher values of UHR, MHR, CAR, CHR and SII reflect increased systemic inflammation, consistent with elevations in traditional inflammatory biomarkers. We assessed the potential utility of each inflammatory index in distinguishing patients with PS from those without. Figure 3 shows the ROC curves for all inflammatory parameters in detecting PS. Table 2 summarizes the results of the ROC analysis. UHR emerged as the most promising discriminator between the indices with AUC of 0.638 (95% confidence interval approximately 0.59–0.69, p \u0026lt; 0.001). The optimal cut-off value for UHR was approximately 0.1204, providing 44% sensitivity and 83% specificity for detecting PS. Although the sensitivity for UHR at this threshold is modest, the high specificity suggests that patients with a UHR above 0.12 are likely to have sarcopenia, although many sarcopenic patients will have a lower UHR. The AUC of MHR was 0.616 (p \u0026lt; 0.001). A cut-off value of approximately 0.011 for MHR provided 45% sensitivity and 74% specificity. The CAR index showed an AUC of 0.602 (p \u0026lt; 0.001) and had an optimum CAR cut-off of approximately 0.79 (given CRP in mg/L and albumin in g/dL). At this threshold, CAR had a sensitivity of 71% and a specificity of 45% for sarcopenia - CAR had lower specificity but much higher sensitivity compared to UHR and MHR. CHR had an AUC of 0.608 (p \u0026lt; 0.001); the best cut-off (0.07 mg/L per mg/dL unit) provided 68% sensitivity and 51% specificity. The AUC value of SII was 0.626 (p \u0026lt; 0.001), the optimum cut-off point was 481.8 (corresponding to approximately 4.82×10¹¹ in SI units, combining neutrophils, platelets, lymphocytes), providing 71% sensitivity and 51% specificity. Although THR was significantly higher in those with PS (p = 0.012 ), it was not considered significant in terms of sensitivity and specificity since the AUC value was \u0026lt; 0.6 when calculated, and cut-off values were not determined (Fig. 4).\u003c/p\u003e"},{"header":"Discussion","content":"\n\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eOur study investigated the relationship between new inflammatory parameters and PS in older adults presenting to the geriatric outpatient clinic with complaints of weight loss. We evaluated six inflammation-based indices (UHR, MHR, THR, CAR, CHR, and SII) in 490 patients aged 65 years and older and compared those with PS with controls at no risk of sarcopenia. To our knowledge, this is the first study to comprehensively examine these inflammatory markers collectively in relation to sarcopenia in an elderly population. Our findings show that all investigated inflammatory parameters were significantly higher in patients with PS, supporting the hypothesis that sarcopenia is closely associated with a high inflammatory state. Subgroup analyses of the study population showed that PS was higher in the group with UWL at 6 months and that this group was more frail and more dependent on daily and instrumental activities. All inflammatory parameters were higher in this group.\u003c/p\u003e\n \u003cp\u003eHowever, only SII reached statistical significance among these indices, which means that SII may be more sensitive to weight loss and related muscle mass loss than other inflammatory parameters. In a study supporting this, SII values were higher in sarcopenic obese patients who underwent bariatric surgery and subsequently lost more weight and experienced muscle loss [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. This situation draws attention to the negative impact of significant weight loss, such as 5% or more in 6 months, on inflammation and sarcopenia in the elderly population during the aging process.\u003c/p\u003e\n \u003cp\u003eIn this study, we found that inflammation-based parameters (UHR, CAR, MHR, THR, CHR, and SII) were higher in older adults with PS compared to those without sarcopenia. Our findings suggest that these easily calculated indices may reflect the high inflammatory status underlying the pathology of sarcopenia. We also observed that UHR, CAR, MHR, and SII were associated not only with each other but also with classical inflammatory markers such as CRP, albumin and neutrophil. Finally, UHR, MHR, CAR, and SII showed high sensitivity and specificity in detecting probable sarcopenia (CAR and SII showed the highest sensitivity and UHR the highest specificity).\u003c/p\u003e\n \u003cp\u003eThe results support the idea that chronic low-grade inflammation contributes to sarcopenia and that markers that integrate metabolic and inflammatory information may serve as proxies for this process. Serum uric acid (sUA), the end product of purine metabolism produced mainly by the liver, has pro-oxidant effects. High sUA together with low HDL-C has been associated with pro-inflammatory conditions such as autoimmune thyroiditis, metabolic syndrome (MetS) and type 2 diabetes mellitus [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e]. Li et al reported that hyperuricemia is associated with MetS and diabetes [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e]. UHR has emerged as a predictor of metabolic and glycemic disorders by combining these two parameters: Kocak et al showed that UHR predicted MetS in type 2 diabetics [\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e]. Aktas et al found that UHR predicted poor glycemic control in men with type 2 diabetes [\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e]. Evidence suggests that UHR and CAR may serve as markers for inflammatory metabolic diseases [\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eHDL cholesterol plays an anti-inflammatory and antioxidant role by protecting the vascular endothelium from oxidation and inflammation [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]. Therefore, low HDL is a risk factor for cardiovascular disease and is therefore frequently found in pro-inflammatory states. Low HDL cholesterol has been associated with inflammatory diseases such as metabolic syndrome, diabetes mellitus and cancer [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. One consequence of low HDL is an increase in UHR. In our study, the PS group had both higher UHR and lower HDL levels than controls, consistent with this concept. This is not a confusing coincidence; rather, it reflects the fact that sarcopenia \u0026ndash; like the disorders mentioned above \u0026ndash; is characterized by chronic inflammation and metabolic deterioration, which tend to lower HDL [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. Chronic low-grade inflammation (as seen in sarcopenia and related disorders) is characterized by decreases in HDL and changes in HDL particles [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e]. It should be noted that UHR values may be affected by gender distribution, as men generally have lower HDL levels than women; However, the gender composition of the groups in our study was similar, so gender is unlikely to confound UHR differences [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]. CAR, defined as the CRP/albumin ratio, is an inflammation-based prognostic index that reflects both inflammation and nutritional status. It has attracted attention because it outperforms other indices. High CAR values are associated with outcomes in sepsis, pancreatitis, and cancer, including poorer performance status and reduced overall and cancer-specific survival in gastric cancer [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]. In metastatic gastric cancer patients receiving chemotherapy, CAR predicted overall survival, disease-free survival, and cancer- specific survival [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]. By integrating systemic inflammation and nutritional status, CAR provides insights beyond traditional markers of inflammation. Toyokawa et al. reported that preoperative CAR, together with other markers, has prognostic significance in stage II gastric cancer [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]. Therefore, CAR captures the effects of inflammation and malnutrition in chronic disease states. In our patients at risk for sarcopenia, high CAR values likely reflect both the inflammatory environment and the impaired nutritional status commonly seen in this population.\u003c/p\u003e\n \u003cp\u003eIn addition to UHR, CAR and MHR has attracted attention as a marker of chronic inflammation and cardiovascular risk. Evidence suggests that high MHR reflects chronic, low-grade inflammation and is associated with pathological conditions. The finding of a significant correlation between MHR and CVD in our study supports this notion. MHR has been found in patients with poorly controlled hypertension and has been associated with blood pressure levels in primary hypertensives [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e]. In cross-sectional studies, MHR has been associated with the incidence of nonalcoholic fatty liver disease (NAFLD), coronary heart disease, and the prevalence of chronic kidney disease [\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]. These conditions share chronic inflammation as a feature, supporting the idea that MHR captures an aspect of systemic inflammation. In the present study, consistent with the inflammatory nature of sarcopenia, higher MHR in patients with probable sarcopenia compared with nonsarcopenic controls and its correlation with CVD also confirm these studies.\u003c/p\u003e\n \u003cp\u003eIn our study, no significant correlation was found between MHR and HT, DM or CKD. This may be due to the fact that the sample size did not reflect the entire sample or that it did not include hospitalized patients who were more frail and dependent in their daily activities, who may have higher inflammation rates. Emerging evidence in the medical literature suggests that UHR may serve as a marker of chronic low-grade inflammation in a number of conditions, including hypertension, fatty liver disease, coronary heart disease and chronic kidney disease [\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e]. All of these conditions are characterized by marked or mild inflammation [\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e]. Consistently, we found that UHR levels were higher in probable sarcopenic patients in parallel with these conditions. To our knowledge, our study is the first to report an association between UHR and PS (or low muscle strength) in older adults. Given that sarcopenia and metabolic syndrome share inflammatory pathways, it is possible that high UHR reflects inflammatory processes common to both conditions. However, due to the cross- sectional design of our study, we cannot establish a causal relationship between high UHR and sarcopenia. It remains unclear whether high UHR contributes to muscle loss or is merely a by-product of metabolic disorders associated with sarcopenia.\u003c/p\u003e\n \u003cp\u003eSII is utilized as a biomarker in ulcerative colitis and chronic kidney disease. SII functions as a guide in predicting postoperative tumor recurrence in colorectal cancer and in prognosis prediction for immunotherapy treatments in various cancers [\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe association between systemic immune-inflammation index and chronic obstructive pulmonary disease in adults aged 40 years and above in the United States: a cross-sectional study based on the NHANES 2013\u0026ndash;2020 [\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e]. Rheumatoid arthritis and liver fibrosis are also among the most important effective parameters in all of these diseases. Neutrophils are key inflammatory cells in the pathogenesis of these diseases, and an increase in the number of neutrophils in the blood is a feature of these diseases. This explains why SII is significantly higher in patients with probable sarcopenia [\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eOur findings suggest a significant correlation between MHR and the likelihood of developing cardiovascular disease in the context of sarcopenia, and between THR and DM. The interaction between lipid metabolism and inflammation is critical in the pathogenesis of DM. The multifaceted protective roles of HDL, including reverse cholesterol transport and antioxidant, anti-inflammatory and anti-thrombotic effects, are well documented [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe anti-inflammatory properties of HDL help prevent oxidative modification of LDL. HDL may counteract inflammation by reducing the expression of adhesion molecules (such as P-selectin, E-selectin, ICAM-1, VCAM-1) on endothelial cells and by inhibiting the adhesion of immune cells to the endothelium. Inflammation may impair their function, leading to decreased HDL levels and qualitative changes in HDL particles. Proteins and enzymes associated with HDL metabolism undergo changes during systemic inflammation [\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e]. In our sarcopenic patients, the higher CHR suggests a scenario of higher CRP relative to HDL \u0026ndash; essentially combining a marker of inflammation with a marker of cardiometabolic health [\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e]. This higher CHR in sarcopenia is consistent with the concept that sarcopenia may be part of a broader inflammatory cardiometabolic risk profile. However, further research is needed to validate CHR as a risk indicator in sarcopenia and to understand whether it provides prognostic information beyond its individual components. To our knowledge, our study is the first in the literature to present the association between a wide range of inflammatory parameters, such as UHR, CAR, CHR, MHR, THR, SII and sarcopenia-related outcomes.\u003c/p\u003e\n \u003cp\u003eHowever, several limitations should be noted. First, the cross-sectional design inherently limits our ability to establish causal relationships; for example, whether high UHR contributes to or is caused by sarcopenia. We cannot infer temporality or causality from this temporal snapshot. Second, our study population (n\u0026thinsp;=\u0026thinsp;490) may have been relatively small to optimize cut-off values for biomarkers such as UHR; a larger sample may have better defined the distribution and thresholds of these indices in sarcopenia. Third, the retrospective nature of the study is another limitation. We relied on available medical records and therefore could not control for all potential confounders or ensure uniform testing conditions (e.g., timing of blood draws, fasting status, or consistency in physical performance tests). A prospective, multicenter study with a large sample of older adults\u0026mdash;ideally including many individuals with diabetes and metabolic syndrome who typically have high UHR and SII\u0026mdash;would be valuable to confirm and refine the usefulness of these inflammatory markers in sarcopenia.\u003c/p\u003e\n \u003cp\u003eFinally, given the cross-sectional design, our study cannot answer whether interventions that alter these parameters (such as improving HDL or lowering uric acid, or by increasing albumin and lowering CRP) would alter the course of sarcopenia or related outcomes in conditions such as diabetic kidney disease. For example, we observed that patients at risk for sarcopenia had lower HDL and higher uric acid; whether aggressive management of dyslipidemia or hyperuricemia would improve muscle outcomes remains an open question that our data cannot address. The low UHR values in the already probable sarcopenic group may suggest that these values or aggressive management of weight may increase malnutrition and worsen sarcopenia.\u003c/p\u003e\n \u003cp\u003eCAR can be an independent predictor of prognosis and mortality in malignant diseases such as malignant pleural mesothelioma [\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e]. However, since our study was cross- sectional and did not have sufficient follow-up time, these contributions could not be evaluated.\u003c/p\u003e\n \u003cp\u003eDespite these limitations, we believe that our report provides a basis for future prospective cohort studies and hypothesis-generating insights into the links between inflammatory markers and sarcopenia.\u003c/p\u003e\n\u003c/div\u003e\n"},{"header":"Conclusions","content":"\u003cp\u003eWe showed that older adults with probable sarcopenia exhibited higher levels of inflammation-based markers, including UHR, MHR, CAR, CHR, SII, and to a lesser extent THR. These findings highlight the close interaction between chronic systemic inflammation (inflammaging) and sarcopenia. Among the indices investigated, UHR emerged as a notable marker in terms of specificity, while CAR and SII emerged as a notable marker in terms of sensitivity, demonstrating their ability to discriminate inflammation for sarcopenia and reflecting the combined effects of hyperuricemia and hypoalphalipoproteinemia (low HDL); CRP and albumin; and monocyte and lymphocyte counts in this population. Our results suggest that these inexpensive and readily available indices may serve as proxies for inflammation and metabolic disorders in sarcopenia. They were also associated with each other and with well-known inflammatory markers such as CRP and ESR, and had significant correlations with CVD and DM. This strengthened their validity as indicators of systemic inflammation. Although none of these markers alone is sufficient to diagnose sarcopenia, they may have potential as part of a multifactorial risk assessment or as targets for monitoring intervention effects. For example, an elderly patient with unusually high UHR, CAR, or SII may warrant closer assessment of muscle strength and function. In summary, inflammatory markers such as UHR, MHR, CAR, CHR, and SII are elevated in sarcopenic older adults and are associated with functional decline associated with sarcopenia. These parameters, particularly UHR, may help identify individuals at risk for sarcopenia or serve as objective measures to monitor the inflammatory aspect of sarcopenia progression. Future prospective studies are needed to determine the predictive value of these indices for the onset of sarcopenia, to investigate the underlying mechanisms, and to assess whether altering these parameters (e.g., through lifestyle changes or pharmacotherapy) has a beneficial effect on muscle health and functional outcomes in older adults.\u003c/p\u003e\u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAUC, area under the receiver-operating characteristic curve; CI, confidence interval; UHR, Uric acid-to-high-density lipoprotein cholesterol ratio; MHR, Monocyte-to-high-density lipoprotein cholesterol ratio; ROC, receiver-operating characteristic; THR, total cholesterol-to-high-density lipoprotein cholesterol ratio; CAR, C-reactive protein to albumin ratio; CHR, C-reactive protein to HDL ratio; SII, systemic immune-inflammation index.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAuthor Contribution\u003c/p\u003e\n\u003cp\u003eElif Gecegelen took part in obtaining ethics committee approval, including patients in the study according to the eligibility criteria, and together with Mete \u0026Uuml;\u0026ccedil;dal, evaluating the patient records, performing statistical analyses, and writing the article. Arzu Okyar Baş, Didem Karaduman, and Cansu Atbas took part in evaluating the patients, checking appropriate statistical analyses, and checking the tables and figures. Mert Eşme, Cafer Balcı, Burcu Balam Doğu, and Meltem G\u0026uuml;lhan Halil took part in writing the article appropriately, checking the patient data, and conducting the study. Mustafa Cankurtaran took part in conducting the entire process of the article, checking the suitability of the statistical methods, and controlling the data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFranceschi, C., et al., \u003cem\u003eInflamm-aging. An evolutionary perspective on immunosenescence.\u003c/em\u003e Ann N Y Acad Sci, 2000. \u003cstrong\u003e908\u003c/strong\u003e: p. 244-54.\u003c/li\u003e\n\u003cli\u003eFranceschi, C. and J. 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Landmesser, \u003cem\u003eHigh density lipoproteins and endothelial functions: mechanistic insights and alterations in cardiovascular disease.\u003c/em\u003e J Lipid Res, 2013. \u003cstrong\u003e54\u003c/strong\u003e(12): p. 3227-43.\u003c/li\u003e\n\u003cli\u003eTakamori, S., et al., \u003cem\u003eThe C-Reactive Protein/Albumin Ratio is a Novel Significant Prognostic Factor in Patients with Malignant Pleural Mesothelioma: A Retrospective Multi-institutional Study.\u003c/em\u003e Ann Surg Oncol, 2018. \u003cstrong\u003e25\u003c/strong\u003e(6): p. 1555-1563.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1 and 2","content":"\u003cp\u003eTable 1 and 2 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"sarcopenia, new inflammatory markers, Uric acid to HDL ratio, CRP to albumin ratio Systemic immune-inflammation index, biomarkers","lastPublishedDoi":"10.21203/rs.3.rs-7075695/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7075695/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eSarcopenia is characterized by age-related loss of muscle mass and function and is associated with chronic low-grade inflammation (inflammaging). Novel inflammation- based indices – including the Uric acid to HDL-cholesterol ratio (UHR), Monocyte to HDL ratio (MHR), Triglyceride to HDL ratio (THR), C-reactive protein (CRP) to albumin ratio (CAR), CRP to HDL ratio (CHR), and Systemic immune-inflammation index (SII) – have emerged as markers of inflammaging. This study investigated the relationship between these inflammatory parameters and probable sarcopenia (PS) in older adults.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003e490 patients aged 65 years and older who applied to the geriatric medicine outpatient clinic of a university hospital with complaints of weight loss were evaluated retrospectively cross-sectionally (2022-2023). PS was assessed by SARC-F questionnaire, handgrip strength test (HGST), and the 5 times-sit-to-stand-test (STST), and patients were grouped into probable sarcopenia (PS, n=259) or non-sarcopenia (NS, n=231) based on these criteria. UHR, MHR, THR, CAR, CHR, and SII were calculated from laboratory values. Group differences in demographics, comorbidities, geriatric assessment scores, and these inflammatory markers were analyzed. The correlations between new inflammatory markers and standard inflammatory indicators (CRP, neutrophil) were evaluated. Receiver operating characteristic (ROC) analysis determined the ability of each parameter to discriminate PS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe PS group was older than NS (median 76 vs 71 years, p\u0026lt;0.001) and had higher prevalence of atrial fibrillation (p=0.002) and dementia (p\u0026lt;0.001), while other comorbidities were similar between groups. All inflammatory indices were elevated in the PS group: median UHR 0.11 vs 0.09, MHR (higher in PS), CAR 1.37 vs 1.02, CHR 0.13 vs 0.07 and SII 623.5 vs 479.5 (all p\u0026lt;0.001), and THR higher (2.19 vs 2.15, p=0.012). Serum uric acid, monocyte count and CRP levels were higher in PS than in NS, while albumin and HDL levels were lower (all p\u0026lt;0.01). UHR, CAR, MHR and SII correlated with one another and with CRP and neutrophils (p\u0026lt;0.001 for all). In ROC analysis, UHR showed the area under the curve (AUC 0.638, 95%CI 0.586–0.690) and a cutoff of 0.1204 (sensitivity 44%, specificity 83%) for identifying PS. CAR and SII showed predictive value (AUC 0.602 and 0.626, respectively), while THR had weaker association (AUC 0.566). UHR performed best with 83% specificity, while CAR and SII performed best with 71% sensitivity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eOlder adults with PS show higher UHR, MHR, THR, CAR, CHR, and SII, reflecting increased inflammatory status. Among them, UHR, CAR and SII have demonstrated the ability to distinguish PS; UHR has high specificity, while CAR and SII have high sensitivity. These available, cost-effective inflammatory markers are associated with sarcopenia-related pathophysiology and established inflammatory markers (CRP, neutrophil). Our findings suggest that inflammatory parameters, especially UHR, CAR and SII may serve as biomarkers to identify older patients at risk for sarcopenia. Future prospective studies are needed to validate their predictive values and to determine whether interventions targeting modifiable components [such as serum uric acid, HDL levels, CRP, albumin, CBC(complete blood count)] affect sarcopenia outcomes.\u003c/p\u003e","manuscriptTitle":"Can Novel Inflammatory Parameters (UHR, MHR, THR, CAR, CHR, SII) Predict Sarcopenia In Older Adults With Weight Loss?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-14 11:07:15","doi":"10.21203/rs.3.rs-7075695/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"24b89afc-4f2f-4bda-81b1-3db8e02379f3","owner":[],"postedDate":"July 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-31T19:09:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-14 11:07:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7075695","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7075695","identity":"rs-7075695","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}