Frailty is a geriatric syndrome caused by a cumulative decline in multiple physiological systems, leading to a decrease in the reserve and resistance to stressors (1). It is associated with longer hospital stays, increased medical costs, and increased mortality (2–4). Coronary heart disease (CHD) is a common chronic disease in the elderly. Studies have shown that frailty is an independent risk factor for the accelerated development of age-related diseases in patients with CHD (5). Yoshioka et al. (6) have found that intermediate mortality in patients with ST-segment myocardial infarction is associated with frailty. Frailty can be reversed with intervention, especially in the early stages (7). A recent review and meta-analysis found that only 3% of frail older adults can spontaneously return to a robust state (8). Therefore, frailty risk prediction and decision-making has an important role in patients with CHD.

It is well-known that a complete blood count (CBC) is part of a routine checkup for patients upon admission to the hospital. Several studies have shown that certain markers in CBC are strongly associated with frailty (9–12). Bodolea et al. (9) found a correlation between platelet count (PLT) and frailty in patients with cardiovascular disease. The neutrophil-to-lymphocyte ratio (NLR) is another example that has been widely studied by researchers in recent years. Hou et al. (10) showed that NLR is an independent risk factor for frailty in elderly patients with CHD. Nishijima et al. (13) found a significant positive association between frailty and NLR in older cancer patients.

Hemoglobin (Hb) is an important parameter of CBC, to some extent reflecting the degree of anemia in patients. A prior meta-analysis (11) identified five biomarkers (C-reactive protein (CRP), Hb, albumin, 25-hydroxyvitamin D (25OHD), and free testosterone) that are strongly associated with frailty. In the findings from the Singapore Longitudinal Study of Aging, Hb (g/dL; adjusted for sex, age, and education) was found to be a debilitating risk factor (14).

Red cell distribution width (RDW) is another important parameter of CBC, which has been used to measure the variability of red blood cell (RBC) count to diagnose different types of anemia and for differential diagnosis. In recent years, it has been found that the changes in RDW are closely related to the inflammatory response of the host system (15, 16). In subjects with joint pain, RDW interpretation, like CRP, is a useful tool in clinical practice to distinguish between inflammatory and non-inflammatory joint diseases (17). Hou et al. (10) found that RDW is an independent risk factor for frailty in elderly patients with CHD.

Since RDW is affected by complex clinical conditions, the effect of RDW on frailty is not only related to its inflammatory response, but also to overall sub-optimal health, indicating a decrease in the ability of the system to repair recovery and oxygen. Although previous studies have shown encouraging results, we believe that RDW without other indicators by itself may not be able to reflect systemic inflammatory status and provide definitive predictive information. The peripheral hemoglobin-to-red blood cell distribution width ratio (Hb/RDW, HRR) is a novel marker of inflammation. It was first proposed by Sun et al. (18) and verified in patients with esophageal squamous cell carcinoma. They found that HRR was a more powerful prognostic indicator than either Hb or RDW alone. This is thought to be because HRR combines prognostic information from Hb and RDW and provides more information than a single variable (18).

In conclusion, it is reasonable to believe that HRR is a more stable predictor of frailty. To our knowledge, however, no studies have assessed the relationship between HRR and frailty intensity. The purpose of this study was to understand the relationship between HRR and the severity of frailty in order to provide a simple and convenient indicator for clinicians to identify frailty risk in a timely manner, for the sake of improving patient quality of life and reducing the risk of complications.

As the world's elderly population continues to grow, so does the number of frail older people. The number of frail aging individuals is expected to double in the coming decades (21). Whether in clinical nursing or in aging research, frailty is becoming an increasingly important concept. From a pathophysiological perspective, the asthenia syndrome is due to the chronic low-grade and non-infectious state of infectious inflammation (9). In systemic inflammation, inflammatory factors promote the formation of lysophosphatidylcholine, and increased exposure to phosphatidylserine leads to lipid remodeling of erythrocyte membranes, which in turn affects erythrocyte function and longevity. Inflammation also accelerates the clearance of red blood cells by activating macrophages, shortening the lifespan of red blood cells and decreasing hemoglobin (22, 23).

In our study, the Fried scale was used to evaluate 233 elderly inpatients with CHD. It was found that the incidence of frailty was 33.48% (78), which is slightly higher than the prevalence of frailty of 20.8% that was proposed by Hou et al. (24), which may be related to respondent age, condition, and medication. Our study found that pre-frail individuals accounted for about half of the elderly inpatients. Data showed that pre-frail patients were more likely to progress to frailty (25), while certain interventions may delay or even reverse the decline (26). This suggests that clinical workers should pay close attention to pre-frail patients, as their early identification and intervention is more consequential than that of frail patients.

In Table 4, taking frailty as the dependent variable and HRR as the independent variable, Kendall's tau-b grade correlation analysis found that HRR (K = −0.296, P < 0.001) was inversely associated with frailty. In Table 5, ordered logistic regression analysis found that in Model 1 without adjustment, Model 2 after adjustment for age, BMI, number of drugs, CCI and heart failure, and Model 3 after adjustment for age, BMI, number of drugs, comorbidity index, heart failure, RBC, albumin, total cholesterol, triglyceride, LDL-C and HDL-C, the lower HRR was an independent risk factor for frailty (P < 0.05). At present, specific reasons for the correlation between decreased HRR and frailty remain unclear and are worth exploring further.

A decrease in HRR may be related to a decrease in Hb. That is, patients with a lower HRR are more likely to be in a debilitating state, which may be related to anemia. The prevalence of anemia in patients with acute coronary syndrome in China was found to be 10%~45% (27). In terms of type, the most common anemia associated with CHD was nutritional anemia (47.1%), among which iron deficiency anemia (25.5%), megaloblastic anemia (21.6%) and renal anemia (23.5%) were more common (28). Domestic scholars have found that mild anemia can also aggravate myocardial ischemia, leading to acute coronary syndrome, and found that the incidence of angina is higher than that of non-anemia group. When coronary artery occlusion is incomplete, anemia will break the micro-balance between myocardial oxygen supply and myocardial oxygen consumption, and then lead to the occurrence of myocardial ischemia (29).

A study on the correlation between anemia and frailty in the elderly from Spain (30) found that the probability of anemia occurrence in the elderly was 19.6%, while the prevalence of anemia in frail individuals was 29.6%, significantly higher than that in the pre-frail (16.6%) and non-frail (6%). In the fully adjusted regression model, anemia was associated with frailty (OR = 1.95, 95%CI: 1.02–3.73, P < 0.05). Consistent with the results of this study, Hb (K = −0.224, P < 0.001) was negatively correlated with frailty in the present investigation. Ordered logistic regression analysis found that in Models 1, lower Hb was an independent risk factor for frailty (P < 0.001), although no statistical significance was observed in Model 3 (P = 0.105)and Model 4 (P = 0.057).

Anemia reduces the ability of RBCs to carry oxygen, causing tissue to lack oxygen and leading to a number of adverse outcomes, including reduced aerobic capacity, decreased muscle strength, cognitive impairment, and increased fatigue, which can also increase the risk of frailty in older people (31). Röhrig (32) found that underlying diseases and inflammation can lead to chronic inflammatory anemia, the most common type of anemia in the elderly. Increased RBC adherence to the endothelium during inflammation is most likely due to the increased expression of endothelial adhesion molecules and phosphatidylserine on the erythrocyte membrane, as well as decreased capillary blood flow (33). Therefore, primary health care providers need to pay attention to anemia, determine its causes, and execute timely correction in order to prevent the occurrence of frailty.

A decrease in HRR is not only related to a decrease in Hb, but also to an increase in RDW. The present study found that RDW (K = 0.248, P < 0.001) was positively correlated with frailty, which was confirmed in the regression analysis. In addition, RDW was an independent risk factor for frailty in elderly patients with CHD. This is consistent with the results by Hou et al. (10). Ming et al. (12) analyzed 2,932 elderly community-dwelling adults and found that elevated RBCs were independently associated with a higher risk of frailty. Frailty is associated with an altered inflammatory status. Inflammation can increase erythrocyte clearance, inhibit erythropoietin, reduce iron utilization, and increase RDW (33). Some studies have shown that RDW is also significantly associated with other inflammatory cytokines, such as serum malondialdehyde levels, tumor necrosis factor-α, interleukin-6, and interleukin-10 (34, 35).

Both Hb and RDW are important components of HRR, and the relationship between lower Hb, higher RDW, and frailty in elderly CHD patients has been confirmed. However, considering that both Hb and RDW are susceptible to diseases other than CHD, HRR may be a more reliable parameter. The predictive analysis showed that AUC, Youden index, sensitivity, and specificity of HRR in senile frailty patients were 0.652, 0.268, 0.575, and 0.693, respectively. AUC and Youden index were higher than Hb and RDW.

There are some limitations in the present study. First, the study was only conducted in a tertiary hospital and cannot be considered comprehensive. It is hoped that there will be multi-center, large sample trials in the future. Second, only the blood parameters upon admission were obtained in the study. If the blood parameters of interest were measured, the relationship between them and frailty might be better described. Third, due to the limited knowledge of drugs in the elderly, the collection of names of drugs taken before admission was largely missing, and the drug type was not analyzed to exclude its influence on frailty. In addition, this was a cross-sectional study that can only represent an association between blood parameters and frailty, but not a cause-and-effect relationship. We will continue a further follow-up study of patients' details.

In conclusion, lower HRR is associated with increased frailty risk and has a certain predictive value in elderly hospitalized patients with CHD. As a simple, effective, and economical blood parameter, HRR should be carefully considered by clinicians in order to identify the risk of frailty in a timely manner, and to monitor the effectiveness of frailty interventions, delay the progression of frailty, prevent the occurrence of disability, reduce adverse outcomes and medical costs, and improve quality of life.

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

The studies involving human participants were reviewed and approved by the Ethics Review Committee of the School of Nursing, Yangzhou University (ethical batch number: YZUHL20200012). The patients/participants provided their written informed consent to participate in this study.

YL conceived the study. JQ, TZ, MX, HS, YS, YC, LT, LQ, JY, and RY collected, verified, and analyzed the data. JQ drafted the manuscript. All authors provided critical revision of the manuscript for important intellectual content.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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