The current situation and associated factors of preoperative frailty in elderly patients undergoing abdominal surgery

Abstract

Background

This study aimed to investigate the current preoperative frailty status of elderly patients undergoing abdominal surgery and identify its associated factors. The objective of this study was to provide clinicians with valuable insights for implementing frailty intervention strategies.

Methods

A cross-sectional study was conducted with 375 elderly patients who underwent abdominal surgery at a tertiary hospital in Chengdu, Sichuan Province, between October 2021 and August 2022. The data were collected using various instruments, including a general information questionnaire, the FRAIL frailty assessment scale, the West China Mood Index, the Nutritional Risk Screening 2002, and the Barthel Index. Multivariate logistic regression analysis was conducted to investigate the factors influencing preoperative frailty in this patient population.

Results

Among the 375 elderly patients who underwent abdominal surgery, 59 were identified as having preoperative frailty, resulting in a preoperative frailty rate of 15.7%. Multivariate analysis revealed that multiple chronic diseases, malnutrition risk, and limited ability to perform daily life activities were significant associated factors for preoperative frailty in these patients (P < 0.05).

Conclusion

Clinical medical staff should prioritize the preoperative frailty assessment of elderly patients undergoing abdominal surgery, particularly those with multiple chronic diseases, malnutrition risk, and limited daily life activities.

Background

In 2019, statistics revealed that the global proportion of the elderly population aged over 65 years reached 9%. It is anticipated that by 2050, this figure will increase significantly to 16% (United Nations, Department of Economic and Social Affairs, Population Division 2019). With the increase in the elderly population and improvements in surgical techniques, the probability of elderly patients receiving surgical treatment will also increase. Research indicates that surgical procedures for this age group account for one-third of all surgeries globally (Weiser et al., 2012). Elderly patients who undergo abdominal surgery are susceptible to postoperative complications due to a decrease in their physiological functions, which has a negative impact on their quality of life and lifespan. Frailty refers to a non-specific state of abnormal function and decreased physiological reserve, which leads to a reduction in the body’s stress resistance. According to research reports, the incidence of frailty in elderly patients receiving surgical treatment ranges between 25 and 40% (Kenig et al., 2015). Frail patients often face a greater risk of adverse clinical events (Huang and Zhong, 2022). Multiple studies have confirmed a strong correlation between preoperative frailty and the occurrence of postoperative complications (Huang et al., 2022; Lin et al., 2022). However, frailty is not irreversible. Timely identification and effective intervention can help improve frailty status, delay its progression, and minimize adverse health outcomes. The primary objective of this research is to investigate the prevalence of preoperative frailty among elderly patients undergoing abdominal surgery and to accurately identify the contributing factors to its development. This endeavor will facilitate early and rapid identification of preoperative frailty in the future, thereby enabling the development of more detailed and individualized preoperative nursing strategies specifically tailored to frail elderly patients. These strategies, in turn, will provide support for the rapid postoperative recovery of patients.

Methods

Study design

This was a cross-sectional study that received approval from the Ethical Research Committee of Sichuan University West China Hospital [approval number: 2021 (No. 1059)].

Setting and participants

Between October 2021 and August 2022, 375 elderly patients were prospectively enrolled as study subjects at a tertiary hospital in Chengdu, Sichuan Province, China, using a convenience sampling method. These patients underwent elective abdominal surgery under general anesthesia. The inclusion criteria were as follows: aged ≥ 60 years; had normal cognitive function and ability to communicate normally with others; signed the informed consent form. The exclusion criteria were patients with a history of mental illness; and patients with hearing impairment that significantly affects communication. These study subjects gave informed consent and participated in this study voluntarily.

Data collection

The questionnaire was read aloud to the patient in turn by three uniformly trained clinical practice nurses within 48 h of admission before surgery. The researchers then recorded the patient’s answers on the questionnaire without providing any prompting to the patient. It took approximately 15–20 min to complete the questionnaire. Each nurse individually reviewed the completed questionnaires, verbally recorded the responses in a standardized format, and conducted a quality control check to ensure the accuracy of their entries.

Sample size calculation

The formula utilized for calculating the sample size in this study was N = {Uα/△}² × P(1 − P). N represents the total number of subjects we plan to include in the study; P represents the incidence of frailty that we expect to observe in elderly patients undergoing abdominal surgery. Based on a previous study in which P = 40% (Kenig et al., 2015), the allowable error was set to 5%. This calculation yielded a required sample size of 369 patients. To account for attrition and other factors, we added an additional 5%, resulting in a total enrollment target of 387 patients.

Research tool

• (1) General information survey form: created by the researchers, this survey covers diverse aspects, such as sex, age, height, weight, educational attainment, monthly household income, marital status, alcohol consumption habits, smoking history, emotional well-being, and chronic conditions, such as diabetes, coronary heart disease, hypertension, and chronic bronchitis. This comprehensive survey form aims to provide a detailed overview of the participants' demographic and health profiles, enabling a thorough analysis of the factors that may influence their health outcomes.

• (2) FRAIL Frailty Assessment Scale: the FRAIL frailty scale used in this study is a validated Chinese version that exhibits high reliability and validity, with a Cronbach’s α coefficient of 0.826 (Wei et al., 2018). This scale has been widely used in clinical settings. It comprises five items: (1) feeling exhausted for most or all of the time during the past 4 weeks; (2) having difficulty climbing one flight of stairs without resting or using any assistive devices or help from others; (3) finding it difficult to walk one block (100 m) without using any assistive devices or help from others; (4) having more than five of the following conditions: hypertension, diabetes, acute heart disease, stroke, malignancy (excluding minor skin cancer), congestive heart failure, asthma, arthritis, chronic lung disease, kidney disease, angina pectoris, etc.; (5) experiencing a weight loss of ≥ 5% within 1 year or less. The diagnostic criteria were as follows: individuals who met ≥ 3 criteria were diagnosed with frailty, while those who met 0–2 criteria were considered non-frail.

• (3) West China Hospital Mood Index Scale: this scale was developed by West China Hospital, Sichuan University, and has a Cronbach’s α coefficient of 0.917 (Meng, et al., 2017). It serves as a tool for rapid screening of adverse emotions and related mental health issues. It consists of nine items, and a 5-point Likert scoring system is adopted. Specifically, 0 represents “none at all”, 1 represents “occasionally”, 2 represents “some of the time”, 3 represents “most of the time”, and 4 represents “all of the time”. The total score ranges from 0 to 36, with 0–8 indicating no adverse emotions and normal mental health; 9–12 indicating mild adverse emotions; 13–16 indicating moderate adverse emotions; and 17 or above indicating severe adverse emotions. In this study, a total score of ≤ 8 was defined as the absence of adverse emotions, while a score of > 8 was defined as the presence of adverse emotions.

• (4) Nutrition Risk Screening (NRS 2002): this is a method recommended by the European Society for Parenteral and Enteral Nutrition (ESPEN) for screening nutritional risk in hospitalized patients. It assesses three key areas: nutritional status, disease severity, and age-related factors. The total score ranges from 0 to 7, with a score of ≥ 3 indicating the presence of nutritional risk and the need for nutritional support, while a score of < 3 suggests no nutritional risk and no need for nutritional support. This scale was developed by Kondrup et al., (2002) in 2002 based on evidence-based medicine methods and has been widely used in clinical practice.

• (5) Barthel Index (BI): the BI is a globally recognized tool for evaluating patients’ activities of daily living (ADL). It comprises ten areas: feeding, bathing, grooming, dressing, bowel and bladder control, toileting, transfers (bed to chair and back), walking, and climbing stairs. The total score ranges from 0 to 100, with a lower score indicating poorer self-care ability and a greater degree of dependency on others for care (Pashmdarfard and Azad 2020). Self-care ability can be categorized into four levels: severe dependency, with a total score of ≤ 40; moderate dependency, with a score between 41 and 60; mild dependency, with a score between 61 and 99; and no dependency, with a total score of 100.

Statistical methods

An Excel spreadsheet was created to record the raw data of the studies, with double-checking and entry performed by two individuals. Statistical analysis of the data was conducted using SPSS 23.0 software. General information count data are presented as frequencies and percentages (%), while measurement data are presented as means (standard deviations) or medians with interquartile ranges [M(P25-P75)]. For comparisons of count data between groups, the chi-square test or Fisher’s exact test was applied. For normally distributed measurement data, the t test was utilized for group comparisons. For non-normally distributed measurement data, the non-parametric rank sum test was used. Variables with a P-value of less than 0.05 were considered statistically significant and were subsequently included as independent variables in the logistic regression model. Logistic regression was employed to explore the associated factors of frailty, with a significance level set at 0.05. A P-value less than 0.05 was considered to indicate statistical significance.

Results

Study procedure

A total of 396 elderly patients who underwent abdominal surgery were enrolled in this study, and 375 were ultimately analyzed. The flow chart is shown in Fig. 1.

Fig. 1

Study flowchart

Prevalence and univariate analysis of preoperative frailty

A total of 59 elderly patients (15.7%) were identified as preoperatively frail. The most prevalent item on the frailty scale was weight loss occurring within 1 year or less, with an incidence rate of 37.3%. The specific occurrence of each item was presented in Table 1 for detailed analysis. Univariate analysis revealed significant differences in the occurrence of preoperative frailty among elderly patients who underwent abdominal surgery, which was specifically related to factors such as age, comorbidities, nutritional status, and independence from daily living (ADL) (P < 0.05). These findings are summarized in Table 2.

Table 1 Detailed variables of preoperative frailty

Table 2 Univariate analysis of preoperative frailty

Multivariable logistic regression modeling

Using the occurrence of preoperative frailty status as the dependent variable (non-frail group = 0, frail group = 1), When selecting variables to include in the regression model, we adhered to the commonly used statistical significance level of P < 0.05 as the criterion. This criterion aims to ensure that the variables included have statistically significant independent effects, thereby reducing the risk of overfitting in the model due to excessive variables. There is no multicollinearity in the factors included in the regression. The final logistic regression model included four independent variables: age, number of comorbidities, ability to perform ADL, and nutritional status.

The logistic regression model was constructed utilizing the enter method to incorporate the independent variables, with all four variables simultaneously integrated into the regression model. The results of the multivariate analysis revealed that the high number of comorbid chronic diseases, malnutrition risk, and limited ability to perform daily living activities are significant risk factors for preoperative frailty in elderly patients undergoing abdominal surgery. The specific results are comprehensively outlined in Table 3.

Table 3 Multivariate analysis of preoperative frailty

Discussion

The incidence of preoperative frailty is high among elderly patients undergoing abdominal surgery. The findings of this study revealed that the incidence of preoperative frailty in this patient population was 15.7%. This finding aligns with the 15.4% reported incidence among elderly patients undergoing breast cancer surgery reported by Lu et al., (2023) but is lower than the 26.67% reported in a study of elderly patients scheduled for elective abdominal surgery conducted by Niu et al., (2023). One possible explanation for this difference is that the study by Niu et al. included patients aged 65 years and older, whereas our study included patients aged 60 years and older. Previous research has also indicated that advanced age is associated with a greater likelihood of experiencing preoperative frailty (Zhang et al., 2023). Furthermore, this study utilized convenience sampling, potentially resulting in constraints on the sample’s representativeness and, consequently, influencing the accuracy of frailty incidence assessment to a certain degree. Despite the inherent limitations associated with this sampling approach, our study retains a degree of reference significance and offers valuable insights for future research endeavors aimed at assessing frailty incidence through the application of more suitable sampling methodologies.

Notably, our study also found that a weight loss of ≥ 5% within 1 year or less was a major manifestation of preoperative frailty in elderly patients undergoing abdominal surgery, with an incidence rate of 37.3%.The elevated percentage underscores the likelihood that rapid weight loss could be a crucial indicator of preoperative frailty among elderly patients scheduled for abdominal surgery. This observation may be associated with factors previously identified in studies, including malnutrition and the progression of chronic diseases, further highlighting the complexity and multifactorial nature of frailty in elderly surgical patients. Conversely, Zhang et al., (2022) and Lu et al., (2023) observed fatigue as the primary manifestation. This discrepancy could be attributed to the fact that their studies primarily focused on tumor patients, who often exhibit persistent cancer-related fatigue from diagnosis onward (Peng and Chen 2022). Notably, not all elderly patients included in our study had tumors and abdominal surgery often carries a risk of malnutrition (Jia, et al. 2011; Sorensen et al. 2008). Body weight is a commonly used and straightforward indicator for assessing nutritional status, reflecting an individual's overall nutritional well-being (Yu, 2010). Therefore, it is reasonable to assume that elderly patients with preoperative frailty who undergo abdominal surgery are more likely to experience weight loss. Future research can further explore the specific mechanisms between weight changes and preoperative frailty, as well as how to delay or reverse this process through interventions, providing a scientific basis for perioperative management of elderly patients undergoing abdominal surgery.

A high incidence of comorbid chronic diseases has been identified as a significant associated factor for preoperative frailty among elderly patients undergoing abdominal surgery. Our study revealed that patients with three or more comorbid chronic diseases exhibited a markedly elevated risk of preoperative frailty, specifically 2.694 times higher, compared to those with 0–2 chronic diseases. This notable correlation underscores the importance of the chronic disease burden in predicting the likelihood of frailty, demonstrating a clear trend of increasing frailty risk as the number of diseases increases. Our findings align with previous research conducted by MA (2018). Furthermore, a study by Han Yuzhu and colleagues (2019) reported a 1.63-fold increase in frailty risk for each additional chronic disease, which supports our observations. Regarding potential underlying mechanisms, it is plausible that the cumulative impact of multiple chronic diseases leads to a substantial decline in the overall physiological reserve capacity of elderly patients. Each chronic disease independently contributes to the deterioration of one or more bodily systems, thereby compromising the body's inherent self-regulatory and compensatory mechanisms. Preoperative frailty, as a manifestation of this widespread functional decline, becomes increasingly prevalent under the combined pressure of these multiple stressors. Moreover, patients with a higher number of comorbid chronic diseases often require a broader range of medications. The complex interactions between these medications can exacerbate the burden on the liver and kidneys (Han et al., 2019), potentially disrupting essential physiological functions such as appetite and sleep, further compromising patients’ resilience. Therefore, chronic medication use and the accumulation of potential adverse effects are pivotal factors contributing to the heightened association with preoperative frailty. Furthermore, chronic diseases frequently impair digestive and absorptive functions, hindering patients' ability to obtain adequate nutritional support. As the number of chronic diseases increases, so do the nutritional and metabolic impairments, creating an environment conducive to malnutrition. In turn, malnutrition not only weakens patients' immune defenses but also undermines muscle strength and other vital physiological parameters, thereby strengthening the association with preoperative frailty. Additionally, elderly patients with a heavier chronic disease burden often struggle with heightened psychological stress, with negative emotions triggering physiological sequelae such as reduced sleep quality, further exacerbating their physical and mental well-being. This vicious cycle may intensify the association with preoperative frailty. In light of these findings, clinical practice should prioritize the assessment of frailty status during preoperative evaluations for elderly abdominal surgery patients with three or more chronic diseases. By implementing individualized interventions tailored to mitigate the association with preoperative frailty, we can enhance patients’ surgical tolerance and improve postoperative recovery outcomes. It is crucial to acknowledge that our study does not establish causality but provides valuable insights into the association between chronic disease burden and preoperative frailty, guiding future research endeavors and clinical decision-making.

The findings of this study indicated an association between preoperative frailty and the risk of malnutrition in elderly patients undergoing abdominal surgery, which was consonant with prior research. A study conducted by Cao Ting et al., (2019) further supports this observation, demonstrating that elderly patients with preoperative malnutrition have a 2.656-fold increased likelihood of experiencing frailty compared to those with normal nutritional status. Nutritional status emerges as a pivotal factor influencing frailty, with malnutrition identified as a significant biological contributor to its development and progression. Conversely, frailty may also influence nutritional status, potentially exacerbating malnutrition (Wang et al., 2021). Albumin (Alb), a traditional nutritional biomarker, occupies a central position in this context. Inadequate protein and energy intake can lead to decreased serum Alb levels, which may subsequently result in reduced skeletal muscle mass, an elevated risk of osteoporosis, fractures, falls, and other adverse events, potentially accelerating the onset of frailty. Nutritional guidelines underscore the importance of increasing protein intake to improve the nutritional status of frail elderly patients, as this may aid in mitigating the risks associated with frailty (Elderly Nutrition Support Group of the Extracorporeal and Enteral Nutrition Branch of the Chinese Medical Association, 2020). Based on the outcomes of nutritional assessments, clinical healthcare professionals should provide health education and early intervention to elderly patients scheduled for abdominal surgery who have preoperative malnutrition or are at risk of malnutrition. They should counsel patients to augment their protein intake, enhance their nutritional status, and increase muscle mass, which may assist in reducing the risk of frailty (Li et al., 2023).

The findings of this study established an association between limited ability to perform activities in daily living (ADL) and preoperative frailty in patients, which concurred with previous research. Cao Ting et al., (2019), in their investigation of preoperative frailty among elderly patients undergoing abdominal surgery, similarly found that those with impaired ADL exhibited a 4.088-fold increased incidence of frailty compared to those with intact ADL prior to surgery. Furthermore, Fried et al., (2001) demonstrated that elderly individuals classified as frail or prefrail often exhibit a decline in self-care abilities. Elderly patients with limited ADL capacity may encounter challenges such as ambulatory impairments, difficulties with stair climbing, and an increased risk of falls, which suggest reduced activity tolerance and mobility limitations. These mobility restrictions may further lead to decreased motivation for physical exercise, limited engagement in daily activities, muscle weakness, and diminished cardiopulmonary function, potentially elevating the risk of frailty. Therefore, nurses should be vigilant in assessing the ADL of elderly patients prior to surgery and, when their condition and physical status permit, encourage them to engage in appropriate physical function exercises. By maintaining their daily living activities, patients may be able to mitigate the occurrence of frailty, thereby reducing surgical risks and improving postoperative recovery outcomes. It is crucial to emphasize that this study does not establish causality but rather highlights associations; hence, any interventions proposed should be implemented with caution, and further research is warranted to fully understand the relationships and potential causal mechanisms involved.

Limitations

Nevertheless, it is worth noting that this study has limitations. As this was a single-center study with a convenience sampling method, it may introduce systematic bias, potentially leading to an over-selection of patients with more severe conditions or greater frailty, or an underestimation due to difficulties in participation. Moreover, the study did not delve into the potential impact of nutritional-related biochemical markers or sleep status on preoperative frailty among elderly patients undergoing abdominal surgery. Future investigations could therefore aim to bridge these knowledge gaps. For example, we can further expand the sample size and conduct multicenter cohort studies to further verify the impact of different factors on preoperative frailty in elderly patients undergoing abdominal surgery.

Although various validated measurement tools were used in this study to collect data, the quality of the data may still be influenced by the subjective feelings and cooperation level of the patients.

This study primarily focuses on assessing preoperative frailty status and analyzing its associated factors, without involving specific intervention measures and their effectiveness evaluations. Consequently, specific suggestions on implementing effective intervention strategies cannot be directly provided to clinical healthcare professionals. Future studies can incorporate intervention trials to further explore effective methods for improving preoperative frailty status.

This study is a cross-sectional study, which helps to reveal the correlation between preoperative frailty status and its associated factors but cannot fully determine the causal relationship. Future studies could consider adopting more rigorous research designs such as randomized controlled trials to further validate the research findings.

Conclusions

The study found that the preoperative frailty rate among elderly patients undergoing abdominal surgery was 15.7%, and it was influenced by various factors, including the presence of multiple chronic diseases, risk of malnutrition, and limited ability in activities of daily living. Given the significance of preoperative frailty in elderly patients, clinical healthcare professionals should place high importance on preoperative frailty assessment. It should be noted that the conclusions of this study merely reflect the current status in the studied hospital during a specific period, yet they offer valuable references and insights, to a certain extent, on how to more effectively identify and manage preoperative frailty in clinical practice.