Construction of a risk prediction model for postoperative cognitive dysfunction in colorectal cancer patients

Abstract

BACKGROUND

Colorectal cancer (CRC) is one of the most prevalent and lethal malignant tumors worldwide. Currently, surgical intervention was the primary treatment modality for CRC. However, increasing studies have revealed that CRC patients may experience postoperative cognitive dysfunction (POCD).

AIM

To establish a risk prediction model for POCD in CRC patients and investigate the preventive value of dexmedetomidine (DEX).

METHODS

A retrospective analysis was conducted on clinical data from 140 CRC patients who underwent surgery at the People’s Hospital of Qian Nan from February 2020 to May 2024. Patients were allocated into a modeling group (n = 98) and a validation group (n = 42) in a 7:3 ratio. General clinical data were collected. Additionally, in the modeling group, patients who received DEX preoperatively were incorporated into the observation group (n = 54), while those who did not were placed in the control group (n = 44). The incidence of POCD was recorded for both cohorts. Data analysis was performed using statistical product and service solutions 20.0, with t-tests or χ² tests employed for group comparisons based on the data type. Least absolute shrinkage and selection operator regression was applied to identify influencing factors and reduce the impact of multicollinear predictors among variables. Multivariate analysis was carried out using Logistic regression. Based on the identified risk factors, a risk prediction model for POCD in CRC patients was developed, and the predictive value of these risk factors was evaluated.

RESULTS

Significant differences were observed between the cognitive dysfunction group and the non-cognitive dysfunction group in diabetes status, alcohol consumption, years of education, anesthesia duration, intraoperative blood loss, intraoperative hypoxemia, use of DEX during surgery, intraoperative use of vasoactive drugs, surgical time, systemic inflammatory response syndrome (SIRS) score (P < 0.05). Multivariate Logistic regression analysis identified that diabetes [odds ratio (OR) = 4.679, 95% confidence interval (CI) = 1.382-15.833], alcohol consumption (OR = 5.058, 95%CI: 1.255-20.380), intraoperative hypoxemia (OR = 4.697, 95%CI: 1.380-15.991), no use of DEX during surgery (OR = 3.931, 95%CI: 1.383-11.175), surgery duration ≥ 90 minutes (OR = 4.894, 95%CI: 1.377-17.394), and a SIRS score ≥ 3 (OR = 4.133, 95%CI: 1.323-12.907) were independent risk factors for POCD in CRC patients (P < 0.05). A risk prediction model for POCD was constructed using diabetes, alcohol consumption, intraoperative hypoxemia, non-use of DEX during surgery, surgery duration, and SIRS score as factors. A receiver operator characteristic curve analysis of these factors revealed the model’s predictive sensitivity (88.56%), specificity (70.64%), and area under the curve (AUC) (AUC = 0.852, 95%CI: 0.773-0.919). The model was validated using 42 CRC patients who met the inclusion criteria, demonstrating sensitivity (80.77%), specificity (81.25%), and accuracy (80.95%), and AUC (0.805) in diagnosing cognitive impairment, with a 95%CI: 0.635-0.896.

CONCLUSION

Logistic regression analysis identified that diabetes, alcohol consumption, intraoperative hypoxemia, non-use of DEX during surgery, surgery duration, and SIRS score vigorously influenced the occurrence of POCD. The risk prediction model based on these factors demonstrated good predictive performance for POCD in CRC individuals. This study offers valuable insights for clinical practice and contributes to the prevention and management of POCD under CRC circumstances.

Key Words: Colorectal cancer; Postoperative; Cognitive dysfunction; Anesthesia; Risk prediction model; Dexmedetomidine; Preventive value

Core Tip: This study developed a risk prediction model for postoperative cognitive dysfunction (POCD) in colorectal cancer (CRC) patients, identifying key risk factors such as diabetes, alcohol consumption, intraoperative hypoxemia, non-use of dexmedetomidine (DEX), surgery duration ≥ 90 minutes, and a systemic inflammatory response syndrome score ≥ 3. The model demonstrated good predictive performance, with high sensitivity and specificity, and highlights the preventive value of DEX in reducing POCD incidence. This research provides valuable insights for improving POCD prevention and management in CRC patients.

INTRODUCTION

Colorectal cancer (CRC) is one of the most prevalent and lethal malignant tumors worldwide. According to the International Agency for Research on Cancer, CRC ranks third among all cancer types, with incidence rates steadily increasing over the past few decades[1]. Advances in medical technology and the promotion of early screening improves early diagnosis rate, making surgical intervention as the primary treatment modality for CRC[2]. Nevertheless, surgery exerts a huge impact on patients both physiologically and psychologically, particularly concerning postoperative cognitive function. An increasing number of studies have revealed that CRC patients may experience cognitive impairments post-surgery, which adversely affects their quality of life, their postoperative recovery and overall prognosis[3-5]. Recent studies have shown growing interest in postoperative cognitive dysfunction (POCD), identifying factors such as surgery, anesthesia, length of hospitalization, and complications as potential contributors. Additionally, patient-specific characteristics including age, gender, underlying health conditions, and psychological status are also considered potential risk factors for developing cognitive impairments postoperatively[6]. Therefore, developing a risk prediction model specifically for POCD under CRC conditions can help identify those at high risk, enabling timely interventions and management to attenuate the incidence of POCD.

In the realm of preventing POCD, dexmedetomidine (DEX) has emerged as a novel sedative, widely used in surgical anesthesia due to its effective sedation and analgesic properties[7]. Studies have demonstrated that DEX reduce the amount of anesthetic required, minimizes postoperative complications, and promotes recovery[8]. Preliminary clinical studies suggests that DEX may offer protective effects on postoperative cognitive function. However, systematic and large-scale studies are still needed to validate its efficacy and elucidate its mechanisms[9]. Thus, exploring the preventive value of DEX against POCD in CRC patients is of significant clinical relevance.

This research retrospectively analyzed the data from 140 CRC patients to evaluate the preventive effects of DEX on POCD. It also examined the differences in baseline characteristics between patients with and without POCD to identify the factors influencing postoperative cognitive function in CRC patients. A risk prediction model was subsequently developed to provide new insights and evidence for postoperative management in these patients while fostering a deeper understanding of POCD and its interventions.

MATERIALS AND METHODS

Materials and methods

General data: A stratified multi-stage sampling method was adopted to estimate the sample size. In the sample mean formula N = (U × α × σ/δ) × 2, U represents the value corresponding to the significance level α, σ denotes the population standard deviation, and δ is the allowable error. With the use of this formula, a preliminary experiment yielded the following parameters: Σ = 1.06, α = 0.07, and δ = 0.1. This calculation resulted in a sample size of 130. Considering a sampling error of 10% to 13%, the sample size was enlarged to 140 cases. Researchers obtained written informed consent from all patients prior to their participation in the study. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki and applicable local regulatory requirements. The study was approved by the People’s Hospital of Qian Nan ethics committee (No. 2024-qnzy-25).

Inclusion criteria: (1) Diagnosed with CRC[10]; (2) Complete general clinical data; (3) American Society of Anesthesiologists (ASA) classification of I to III; (4) No evidence of cancer metastasis or spreading; and (5) Mentally stable individuals.

Exclusion criteria: (1) Pre-existing cognitive dysfunction; (2) History of traumatic brain injury; (3) Patients who had undergone major surgery within the last three months; and (4) Presence of other malignant tumors.

Methods and observation indicators

Preventive treatment: Prior to the induction of anesthesia, DEX, provided by Jiangsu Hengrui Medicine Co., Ltd., was intravenously administered at a dosage of 0.5 μg/kg. Following induction, a continuous infusion at a rate of 0.3 μg/kg/hour was maintained until 30 minutes before the end of the procedure. All participants received sufentanil at doses of 0.3-0.4 μg/kg, propofol at 1.0-2.0 mg/kg, and rocuronium at 0.6 mg/kg for induction, followed by orotracheal intubation for mechanical ventilation. During the procedure, propofol was administered intravenously at a rate of 4-8 mg/kg/hour, along with remifentanil at 0.05-0.20 μg/kg/minute to sustain anesthesia, while intermittent intravenous administration of rocuronium was implemented to maintain muscle relaxation.

Cognitive dysfunction: Cognitive function in patients was assessed through the mini-mental state examination (MMSE) scale[11], which evaluates various domains comprising language ability, attention, recall, memory, orientation, and calculation skills. MMSE consists of 30 items, with a maximum total score of 30, and the assessment needs to be completed within 8 minutes. A score of ≤ 18 is considered indicative of severe cognitive impairment, 19-23 reflects moderate cognitive impairment, 24-27 signifies mild cognitive dysfunction, and scores of 28-30 indicate no cognitive impairment. The MMSE scale is assessed by a trained attending physician before and on the first postoperative day.

Multivariate analysis

Patient data regarding gender, age, body mass index (BMI), ASA classification, hypertension, tumor node metastasis (TNM) staging, smoking history, marital status, intraoperative use of vasoactive drugs, tumor location, diabetes, alcohol consumption, years of education, anesthesia duration, intraoperative blood loss, intraoperative hypoxemia, use of DEX, surgery duration, systemic inflammatory response syndrome (SIRS) score, and postoperative fasting duration were recorded and analyzed via electronic medical records. The SIRS score was calculated as per the following criteria: A temperature > 38 °C or < 36 °C scores 1 point; A heart rate > 90 beats per minute scores 1 point; A respiratory rate > 20 breaths per minute or arterial blood gas analysis denoting partial pressure of carbon dioxide < 32 mmHg scores 1 point; and A white blood cell count > 12 × 10⁹/L or < 4 × 10⁹/L, or > 10% immature cells scores 1 point. A Postoperative 24-hour assessment of systemic inflammatory response using SIRS scores. SIRS score of 0 suggests no inflammatory response, 1-2 indicates mild inflammatory response, and 3-4 signifies moderate to severe inflammatory response[12]. Logistic regression analysis was taken to confirm various factors influencing POCD in CRC patients.

Construction of a risk prediction model

Based on the identified risk factors, a risk prediction model for POCD in CRC patients was established. The partial regression coefficients obtained from the Logistic regression analysis were incorporated into the prediction model. The predictive performance of the model was confirmed through the area under the receiver operating characteristic (ROC) curve (AUC), with an AUC value exceeding 0.7 regarded as indicative of good predictive performance for the endpoint event.

Statistical analysis

Statistical product and service solutions 20.0 software (SPSS Inc., Chicago, IL, United States) was introduced for statistical analysis. The Shapiro-Wilk test is used to assess normality. For unordered categorical data, the χ² test or Fisher’s precise test was employed, while measurement data were reported as (mean ± SD) and analyzed via t-tests. In the univariate analysis, variables with P < 0.05 are considered potential predictors. To refine these predictors, a multicollinearity test was conducted and least absolute shrinkage and selection operator (LASSO) regression was employed for variable selection using R version 4.0.5. Multivariate analysis was conducted through Logistic regression to develop a risk prediction model based on identified risk factors, and cross-validation was utilized to determine the model’s predictive performance. Using GraphPad Prism software (GraphPad Software, Inc., San Diego, CA, United States), we plotted calibration curves to assess the efficacy of the risk prediction model in postoperative cognitive impairment among patients with rectal cancer. Additionally, we utilized R statistical software (University of Auckland, New Zealand) to plot decision curve analysis curves to evaluate the clinical applicability of the risk prediction model. A P value of < 0.05 was deemed to hold statistical significance.

RESULTS

Baseline data

The sampling period lasted from February 2020 to May 2024. All 140 CRC patients underwent surgical treatment at The People’s Hospital of Qian Nan, and they were divided into a modeling group (n = 98) and a validation group (n = 42) in a 7:3 ratio. No significant differences in baseline characteristics were observed between the two cohorts (P > 0.05), as illustrated in Table 1. Additionally, in the modeling group, patients receiving DEX preoperatively were incorporated into the observation group (n = 54), whereas those not subjected to DEX were placed in the control cohort (n = 44). No remarkable differences were found in baseline data between the two cohorts (P > 0.05), as displayed in Table 2.

Table 1 General data, mean ± SD.

General data	Modeling group (n = 98)	Validation group (n = 42)	χ2/t	P value
Gender			0.136	0.712
Male	48	22
Female	50	20
Age (years)	56.12 ± 6.33	56.23 ± 6.27	0.094	0.925
ASA classification			1.979	0.159
Class I-II	41	23
Class III	57	19
TNM staging			0.510	0.775
Stage I	38	19
Stage II	29	11
Stage III	31	12

TNM: Tumor node metastasis; ASA: American Society of Anesthesiologists.

Table 2 Baseline data, mean ± SD.

Baseline data	Observation group (n = 54)	Control group (n = 44)	χ2/t	P value
Gender			0.347	0.556
Male	25	23
Female	29	21
Age (years)	56.08 ± 6.23	56.04 ± 6.17	0.032	0.975
ASA classification			0.059	0.807
Class I-II	22	19
Class III	32	25
TNM staging			0.298	0.862
Stage I	21	17
Stage II	17	12
Stage III	16	15

TNM: Tumor node metastasis; ASA: American Society of Anesthesiologists.

Univariate analysis of POCD in CRC patients

Out of 98 patients, 37 exhibited POCD, culminating in an incidence rate of 37.76%, and they were classified into the cognitive dysfunction cohort. The remaining 61 patients, who demonstrated normal cognitive function, were placed in the non-cognitive dysfunction cohort.

A comparison of general clinical data between the two cohorts displayed no significant differences in terms of gender, age, BMI, ASA classification, hypertension, TNM staging, smoking history, marital status, tumor location and postoperative fasting duration (P > 0.05). Nevertheless, significant differences were observed between the two cohorts regarding diabetes, alcohol consumption, years of education, anesthesia duration, intraoperative blood loss, intraoperative hypoxemia, use of DEX during surgery, use of vasoactive agents during surgery, surgical time, SIRS scores (P < 0.05), as illustrated in Table 3.

Table 3 Univariate analysis of postoperative cognitive dysfunction in colorectal cancer patients, mean ± SD.

General data	Cognitive dysfunction group (n = 37)	Non-cognitive dysfunction group (n = 61)	χ2/t	P value
Gender			0.219	0.640
Male	17	31
Female	20	30
Age (years)	56.44 ± 6.12	55.83 ± 7.12	0.433	0.666
BMI			1.255	0.263
≥ 24 kg/m2	11	25
< 24 kg/m2	26	36
ASA classification			1.097	0.295
Class I-II	13	28
Class III	24	33
Hypertension			0.188	0.665
Presence	10	19
Absence	27	42
Diabetes			4.353	0.037
Presence	25	28
Absence	12	33
Alcohol consumption			4.183	0.041
Presence	26	30
Absence	11	31
TNM staging			2.834	0.242
Stage I	17	21
Stage II	12	17
Stage III	8	23
Smoking history			0.414	0.520
Presence	11	22
Absence	26	39
Education (years)			4.389	0.036
≥ 10 years	22	23
< 10 years	15	38
Marital status			0.794	0.373
Married	13	27
Unmarried/widowed	24	34
Anesthesia duration			5.143	0.023
≥ 4 hours	25	22
< 4 hours	12	29
Intraoperative blood loss			4.832	0.028
≥ 300 mL	26	29
< 300 mL	11	32
Intraoperative hypoxemia			8.543	0.003
Presence	27	26
Absence	10	35
Use of DEX during surgery			9.770	0.002
Absence	26	23
Presence	11	38
Use of vasoactive agents during surgery			4.353	0.037
Presence	25	28
Absence	12	33
Surgical duration			7.368	0.007
≥ 90 minutes	29	31
< 90 minutes	8	30
Tumor location			0.149	0.928
Proximal colon	13	22
Distal colon	11	16
Rectum	13	23
SIRS scores			5.939	0.015
≥ 3 points	28	31
< 3 points	9	30
Postoperative fasting duration			0.103	0.748
≥ 3 days	20	35
< 3 days	17	26

BMI: Body mass index; DEX: Dexmedetomidine; SIRS: Systemic inflammatory response syndrome; TNM: Tumor node metastasis; ASA: American Society of Anesthesiologists.

Multivariate analysis of factors influencing POCD in CRC patients

As per the methods outlined in Table 2, values were assigned to the aforementioned single factors and incorporated into the Logistic regression model for multivariate analysis. Before multivariate analysis, we used LASSO regression to select influencing factors and eliminate multicollinearity among variables. The data demonstrated that diabetes, alcohol consumption, intraoperative hypoxemia, non-use of DEX during surgery, surgical duration of ≥ 90 minutes, and SIRS scores of ≥ 3 were identified as independent risk factors for POCD in CRC patients (P < 0.05), as exhibited in Table 4 and Table 5.

Table 4 Assignment method.

Factors	Assignment
Diabetes	1: Presence; 0: Absence
Alcohol consumption	1: Presence; 0: Absence
Years of education	1: ≥ 10 years; 0: < 10 years
Anesthesia duration	1: ≥ 4 hours; 0: < 4 hours
Intraoperative blood loss	1: ≥ 300 mL; 0: < 300 mL
Intraoperative hypoxemia	1: Presence; 0: Absence
Intraoperative use of DEX	1: Absence; 0: Presence
Surgical time	1: ≥ 90 minutes; 0: < 90 minutes
Intraoperative use of vasoactive drugs	1: Absence; 0: Presence
SIRS score	1: ≥ 3 points; 0: < 3 points

DEX: Dexmedetomidine; SIRS: Systemic inflammatory response syndrome.

Table 5 Risk factors of postoperative cognitive dysfunction in colorectal cancer patients.

Factors	β value	SE value	χ2 value	OR	95%CI	P value
Diabetes	1.613	0.713	5.118	5.018	1.241-20.297	0.024
Alcohol consumption	1.589	0.623	6.505	4.899	1.445-16.611	0.011
Years of education	1.317	0.723	3.318	3.732	0.905-15.396	0.069
Anesthesia duration	1.369	0.933	2.153	3.931	0.631-24.476	0.143
Intraoperative blood loss	1.283	0.689	3.467	3.607	0.935-13.922	0.063
Intraoperative hypoxemia	1.592	0.634	6.305	4.914	1.418-17.024	0.012
Non-use of DEX during surgery	1.337	0.629	4.518	3.808	1.110-13.064	0.034
Intraoperative use of vasoactive drugs	1.371	0.735	3.479	3.939	0.933-16.637	0.063
Surgical time	1.592	0.633	6.325	4.914	1.421-16.991	0.012
SIRS scores	1.432	0.588	5.931	4.187	1.322-13.256	0.015

DEX: Dexmedetomidine; SIRS: Systemic inflammatory response syndrome; OR: Odds ratio; CI: Confidence interval.

Establishment of a risk prediction model for POCD in CRC patients

A risk prediction model for POCD in CRC individuals was developed based on the factors of diabetes, alcohol consumption, intraoperative hypoxemia, non-use of DEX during surgery, surgical duration, and SIRS scores. The probability formula is P = 1/[1 + e^{(1.543 × diabetes + 1.621 × alcohol consumption + 1.547 × intraoperative hypoxemia + 1.369 × non-use of DEX + 1.588 × surgical duration + 1.419 × SIRS score)}]. ROC curve analysis of these risk factors revealed a sensitivity of 88.56% and specificity of 70.64% for predicting POCD, with an AUC of 0.852, as presented in Figure 1A.

Figure 1 Receiver operating characteristic curve. A: The risk prediction model for Receiver operating characteristic in colorectal cancer patients; B: Postoperative cognitive impairment in the validation group of colorectal cancer patients using a risk prediction model. AUC: Area under the curve; CI: Confidence interval.

Model validation

This investigation encompassed 42 CRC individuals from the validation cohort who met the inclusion criteria. The aforementioned model was applied for prediction, using cross-validation. Among these 42 patients, 26 actually experienced cognitive impairment, while the model identified 21 cases of cognitive impairment. The model demonstrated a sensitivity of 80.77%, a specificity of 81.25%, and an accuracy of 80.95% in predicting cognitive dysfunction, AUC was 0.805, with a 95%CI: 0.635 to 0.896, as shown in Figure 1B and Table 6. Additionally, the results of the calibration curve analysis indicated that the predictive model’s calibration curve for postoperative cognitive impairment closely matched the ideal curve for both the modeling group and the validation group of CRC patients (Figure 2). A decision curve analysis was conducted to assess the model’s clinical effectiveness. The results showed that the model provided better clinical benefits when the high-risk threshold probability ranged from 0.17 to 0.89, as demonstrated in Figure 3.

Figure 2 Calibration curve. A: The predictive model for postoperative cognitive impairment in colorectal cancer patients in the modeling group; B: The predictive model for postoperative cognitive impairment in colorectal cancer patients in the validation group.

Figure 3  Decision curve analysis curve of the risk prediction model for predicting postoperative cognitive impairment in colorectal cancer patients in the modeling group.

Table 6 Model validation.

Model		Actual cognitive dysfunction
		Positive	Negative	Total
Prediction of cognitive dysfunction	Positive	21	4	25
	Negative	5	12	17
	Total	26	16	42

DISCUSSION

CRC is one of the most prevalent malignant tumors worldwide, and surgical treatment is a common clinical intervention. Nonetheless, increasing evidence suggests that patients with CRC may undergo cognitive impairment postoperatively, which can adversely affect their quality of life and recovery process[13]. The mechanisms behind POCD are complex and may involve factors such as postoperative inflammatory responses, the use of anesthetic agents, and the overall health status of the patients[14]. Therefore, early identification and prediction of these risk factors are crucial for improving outcomes. Recently, DEX has emerged as a novel anesthetic that shows promise in mitigating postoperative delirium and improving cognitive function[15,16]. This research aims to develop a risk prediction model that incorporates multiple clinical, preoperative, and postoperative factors, while also assessing the preventive value of DEX for POCD under CRC circumstances, ultimately providing valuable insights for clinical management and treatment strategies.

Here, it was found that 37 out of 98 patients experienced POCD, resulting in an incidence rate of 37.76%, consistent with previous findings[17]. Despite the use of DEX, a residual risk of cognitive impairment remains, indicating that while DEX can partially mitigate these issues, it cannot entirely suppress POCD in CRC patients, making it necessary to observe, evaluate, and give strategies to lower the risk of cognitive dysfunction. Logistic regression analysis identified diabetes, alcohol consumption, intraoperative hypoxemia, non-use of DEX, surgical duration of 90 minutes or more, and SIRS scores of 3 or higher as independent risk factors for POCD.

This analysis revealed several factors associated with POCD: (1) Diabetes often results in fluctuating blood glucose levels, leading to inadequate or excessive energy supply to the brain, adversely affecting neurological function and cognitive abilities. Postoperative conditions, particularly those involving anesthesia and surgical stress, can exacerbate these fluctuations, increasing the risk of cognitive dysfunction[18]. Furthermore, diabetes is associated with a chronic inflammatory state, where augmented release of inflammatory factors can negatively affect the nervous system. Chronic inflammation has been linked to cognitive decline, which may exacerbate this risk of cognitive impairment in diabetic patients[19]. Therefore, it is essential to closely monitor blood glucose levels in CRC patients both preoperatively and postoperatively. Appropriate pharmacological interventions should be implemented to maintain stable blood glucose in diabetic patients, attenuating the likelihood of cognitive impairment; (2) Chronic heavy drinking can damage neurological function, including cognitive decline and memory loss. Alcohol directly impacts brain structure and function, causing neuronal damage and even cell death, thus affecting postoperative cognitive performance[20]. Moreover, alcohol can affect vascular function, leading to reduced cerebral blood flow and potentially resulting in inadequate oxygen supply to the brain following surgery, which elevate the risk of cognitive impairment in postoperative patients[21,22]; (3) Hypoxemia directly causes insufficient oxygen supply to brain, disrupting the metabolism and function of neuronal cells, which results in neuronal damage. The brain, which has a high demand for oxygen, is vulnerable to prolonged hypoxic conditions[23]. Intraoperative hypoxemia can also affect the brain’s neuroplasticity, which refers to the ability of neural networks to reorganize and recover function. An imbalance in this neuroplasticity may result in delayed or incomplete recovery of cognitive function postoperatively[24]; (4) DEX, a steroid with potent anti-inflammatory properties, is often implicated in the pathogenesis of POCD triggered by surgery. The absence of DEX use may give rise to a more pronounced inflammatory response post-surgery, which can negatively influence brain function[25]. When DEX was not applied, stress response induced by surgery could be out of control, leading to excessive neuroendocrine activation postoperatively, thereby heightening the risk of POCD[26]. Moreover, DEX has demonstrated neuroprotective effects by reducing neuronal apoptosis and mitigating brain damage. The omission of DEX during surgery may cause the loss of this neuroprotective benefits, further impacting postoperative cognitive function[27,28]. Therefore, in clinical practice, the preventive use of DEX preoperatively is necessary to attenuate the incidence of POCD. Besides, a recent study specifically studied the underlying mechanism by which DEX prevent POCD. They found that DEX upregulated PINK1 in aged rats, a key regulator of mitophagy, thereby enhancing mitochondrial autophagy and reducing caspase-1/11-GSDMD-mediated pyroptosis in neurons[29], providing a clear rationale for the neuroprotective effects of DEX and explaining the lower incidence of POCD after DEX use; (5) Prolonged surgeries are often accompanied by extended periods of general anesthesia, which may impact the central nervous system and contribute to POCD postoperatively. The extended duration alters the metabolism and clearance of anesthetic drugs, augmenting the risk of POCD[30,31]. Longer surgery duration may indicate heightened physiological stress during the procedure, including blood loss, hypoxia, and inflammatory responses. These stressors can exert a negative impact on brain function, culminating in cognitive decline following surgery[32]; and (6) The SIRS, characterized by the release of inflammatory factors such as cytokines and interleukins, could be assessed using the SIRS score. The accumulation of these substances in the brain can impair neuronal function, leading to cognitive decline[33,34]. The onset of SIRS may also be followed by a drop in blood pressure and inadequate tissue perfusion, which can result in hypoxia and insufficient nutrient supply to the brain, causing cognitive impairment, especially during postoperative recovery[35,36].

Based on our findings, we propose the following targeted clinical recommendations for addressing independent risk factors associated with POCD in CRC patients: For diabetic patients, it is essential to strengthen preoperative and postoperative blood glucose management, employing individualized strategies to control glucose fluctuations. For patients with alcohol dependence, preoperative interventions should include alcohol cessation or reduction, and postoperative cognitive function should be closely monitored to mitigate long-term neurological damage. Besides, DEX should be administrated prophylactically during the preoperative and intraoperative period based on patient-specific conditions. Optimizing the dosage and timing of DEX administration can suppress systemic inflammatory responses, reduce neuronal apoptosis, and enhance cognitive protection. Lastly, for patients with high SIRS scores, their inflammatory status should be closely monitored. By implementing these comprehensive intervention measures, the risk of POCD in CRC patients can be significantly reduced, enhancing postoperative recovery quality and improving long-term patient satisfaction.

Here, a risk prediction model was developed based on various risk factors, including diabetes, alcohol consumption, intraoperative hypoxemia, use of DEX during surgery, surgery duration, and SIRS score. These factors were discovered to have predictive value for POCD in CRC patients. This study offers valuable insights for clinicians, especially in the management of high-risk CRC patients. By identifying and addressing the aforementioned risk factors, the incidence of POCD can be effectively reduced. Additionally, a group of 42 CRC patients who met the inclusion criteria was selected for validation via a cross-validation method. The model demonstrated a sensitivity of 80.77%, a specificity of 75.00%, and an accuracy of 78.57% in forecasting cognitive impairment, further confirming its effectiveness in assessing the likelihood of POCD in this patient population. This study, in comparison to previous research on POCD predictive models[37], has significantly enhanced predictive performance by introducing the use of DEX and SIRS scores as new risk factors. Additionally, this study validated the known risk factors for POCD, including diabetes, alcohol consumption, intraoperative hypoxemia, and surgery lasting ≥ 90 minutes. Notably, it identified the independent impact of DEX use and SIRS scores on POCD. These findings not only improve the accuracy of POCD prediction but also provide additional early intervention points, having broad clinical application value, particularly for CRC patients.

Nevertheless, this study has several limitations, including potential biases arising from its retrospective design, limited sample size impacting the generalizability of the results, data originating from a single hospital restricting external validity, and non-standardized administration of DEX potentially affecting outcome consistency. Additionally, model validation was conducted on only a subset of the data, and key variables such as preoperative cognitive assessments and detailed drug regimens were not included. Addressing these limitations, future efforts should focus on conducting larger, prospective, multicenter studies to enhance the robustness and applicability of the findings. Emphasis should also be placed on incorporating key variables to further refine the model’s accuracy and clinical utility.

CONCLUSION

In conclusion, the preoperative administration of DEX demonstrated potential in preventing POCD. The risk prediction model incorporates factors such as diabetes, alcohol consumption, intraoperative hypoxemia, DEX usage during surgery, operation time ≥ 90 minutes, and SIRS score ≥ 3 demonstrated good predictive performance for POCD among CRC patients. Identifying high-risk patients preoperatively and implementing preventive measures can provide valuable clinical guidance, ameliorating cognitive outcomes for these patients. These recommendations and interventions will help reduce the occurrence of postoperative cognitive impairment and enhance the overall therapeutic efficacy for patients.