Wang Y, Wang C, Guo H, Wang SH, Chen FF, Chen QX, Zhou K. Evaluation and analysis of neurocognitive dysfunction in patients with colorectal cancer after radical resection: A retrospective study. World J Gastrointest Surg 2024; 16(9): 2893-2901 [PMID: 39351576 DOI: 10.4240/wjgs.v16.i9.2893]
Corresponding Author of This Article
Kai Zhou, PhD, Doctor, Department of Gastrointestinal Surgery, The First Affiliated Hospital of Bengbu Medical University, No. 287 Changhuai Road, Bengbu 233000, Anhui Province, China. oakman4202@sina.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Yu Wang, Chao Wang, Han Guo, Su-Hang Wang, Fang-Fang Chen, The Four Branches of General Surgery, The First Affiliated Hospital of Bengbu Medical University, Bengbu 233000, Anhui Province, China
Qiao-Xiang Chen, Department of Anorectal Surgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310030, Zhejiang Province, China
Kai Zhou, Department of Gastrointestinal Surgery, The First Affiliated Hospital of Bengbu Medical University, Bengbu 233000, Anhui Province, China
Author contributions: Wang Y wrote the manuscript; Wang C, Guo H, Wang SH, Chen FF and Chen QX collected the data; Zhou K guided the study; All authors reviewed, edited, and approved the final manuscript and revised it critically for important intellectual content, gave final approval of the version to be published, and agreed to be accountable for all aspects of the work.
Institutional review board statement: This study was approved by the Second Affiliated Hospital of Zhejiang University School of Medicine, No. ZJJC18021102.
Informed consent statement: This study has obtained informed consent and signed treatment consent from patients and their families.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: Statistical analysis plan, informed consent form, and clinical study report will also be shared if requested. Emails could be sent to the address oakman4202@sina.com to obtain the shared data.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Kai Zhou, PhD, Doctor, Department of Gastrointestinal Surgery, The First Affiliated Hospital of Bengbu Medical University, No. 287 Changhuai Road, Bengbu 233000, Anhui Province, China. oakman4202@sina.com
Received: June 6, 2024 Revised: July 31, 2024 Accepted: August 14, 2024 Published online: September 27, 2024 Processing time: 104 Days and 2.7 Hours
Abstract
BACKGROUND
With the continuous progress of colorectal cancer treatment technology, the survival rate of patients has improved significantly, but the problem of postoperative neurocognitive dysfunction has gradually attracted attention.
AIM
To analyze the risk factors for delayed postoperative neurocognitive recovery (DNR) after laparoscopic colorectal cancer surgery and constructed a risk prediction model to provide an evidence-based reference for the prevention and treatment of DNR after laparoscopic colorectal cancer surgery.
METHODS
The clinical data of 227 patients with colorectal cancer who underwent laparoscopic surgery and regional cerebral saturation oxygenation (rScO2) monitoring at our hospital from March 2020 to July 2022 were retrospectively analyzed. Common factors and potential factors affecting postoperative DNR were used as analysis variables, and univariate analysis and multifactor analysis were carried out step by step to determine the predictors of the model and construct a risk prediction model. The predictive performance of the model was assessed by the receiver operating characteristic (ROC) curve, the calibration curve was used to assess the fit of the model to the data, and a nomogram was drawn. In addition, 30 patients who met the inclusion and exclusion criteria from January 2023 to July 2023 were selected for external verification of the prediction model.
RESULTS
The incidence of postoperative DNR in the modeling group was 15.4% (35/227). Multivariate analysis revealed that age, years of education, diabetes status, and the lowest rScO2 value were the independent influencing factors of postoperative DNR (all P < 0.05). Accordingly, a DNR risk prediction model was constructed after laparoscopic colorectal cancer surgery. The area under the ROC curve of the model was 0.757 (95%CI: 0.676-0.839, P < 0.001), and the Hosmer-Lemeshow test of the calibration curve suggested that the model was well fitted (P = 0.516). The C-index for external validation of the row was 0.617.
CONCLUSION
The DNR risk prediction model associated with rScO2 monitoring can be used for individualized assessment of patients undergoing laparoscopic colorectal cancer surgery and provides a clinical basis for the prevention of DNR after surgery.
Core Tip: This study evaluated and analyzed the neurocognitive dysfunction of patients after radical resection of colorectal cancer, and systematically reviewed and analyzed the changes of neurocognitive function and related influencing factors of patients after radical resection of colorectal cancer. Through the preoperative and postoperative cognitive function assessment, the purpose is to reveal the incidence of postoperative neurocognitive dysfunction and its potential mechanism, and provide scientific basis and guidance for clinical intervention and rehabilitation treatment.
Citation: Wang Y, Wang C, Guo H, Wang SH, Chen FF, Chen QX, Zhou K. Evaluation and analysis of neurocognitive dysfunction in patients with colorectal cancer after radical resection: A retrospective study. World J Gastrointest Surg 2024; 16(9): 2893-2901
Colorectal cancer is a kind of malignant neoplasm of the detoxification system that is very serious and dangerous to human health[1-3]. Its incidence rate and death rate rank third and second, respectively. At present, surgery, which has the advantages of minimal trauma and quick recovery, is the first choice for comprehensive clinical treatment and has become the main surgical method[4]. However, long-term CO2 pneumoperitoneum during laparoscopic surgery is likely to lead to increased arterial CO2 partial pressure, excitation of the sympathetic adrenal medullary system, oxygen metabolism imbalance in brain tissue, and increased incidence of postoperative neurological disorders[5-7]. Delayed postoperative neurocognitive recovery (DNR) is a decrease in cognitive function within 30 days after manual intoxication, often manifested as disturbances in memory, recognition, and sleep[8]. Postoperative DNR will lead to prolonged hospital stays, decreased vital masses, and even increased mortality rates, which will impose heavy burdens on families and society[9-11].
In the study of postoperative disability, risk factors such as age, education level, disease combination, and length of manual operation were discussed in previous episodes, but the intervention used for each risk factor was poor, which limited the practical applicability of the previous study[12]. Regional cerebral saturation oxygenation (rScO2) is a new method for monitoring hand segments that can provide real-time and noninvasive reflection of brain perfusion and brain tissue oxygenation[13-15]. It has been shown to sensitively and accurately predict the occurrence of postoperative cognitive dysfunction in cardiothoracic, neurosurgical and orthopedic surgeries[16]. Therefore, actively exploring the correlation between rScO2 and postoperative DNR in laparoscopic colorectal cancer surgery, further understanding the influencing factors of postoperative DNR, and more accurately predicting the risk of postoperative DNR have important clinical significance for doctors to identify and implement intervention measures as soon as possible[17-19].
This study retrospectively collected the clinical data, rScO2 data and postoperative DNR status of patients who underwent laparoscopic colorectal cancer surgery monitored by rScO2 during surgery and analyzed the risk factors for DNR after laparoscopy for colorectal cancer. A reliable pretest model was constructed and verified to provide a reliable evidence-based basis for the early identification and precise intervention of DNR.
MATERIALS AND METHODS
Research subjects
A retrospective cohort of 227 patients who underwent elective laparoscopic colorectal cancer surgery at our hospital from March 2020 to July 2022 was selected as the modeling group for the predictive model.
Inclusion criteria
The exclusion criteria for patients were as follows: (1) Aged ≥ 50 years; (2) American Society of Anesthesiologists grade II-III; (3) Underwent general anesthesia under laparoscopy for nodular bowel cancer; and (4) Continuous rScO2 monitoring was performed during the operation.
Exclusion criteria
The exclusion criteria were as follows: (1) Urgent treatment of patients with hand surgery or dizziness; (2) A history of sudden, short or temporary cerebral hemorrhage, schizospermia, Parkinson’s disease, epilepsy or insanity before surgery; (3) Severe heart disease, including a preoperative left ventricular ejection fraction < 30% or arrhythmia with a pacemaker; (4) A need for liver transplantation or liver function and Child-Pugh grade C liver dysfunction; (5) Preoperative renal dysfunction requiring dialysis; (6) Lack of rScO2 data due to equipment; or (7) Incomplete clinical data.
External validation of the predictive models: Thirty patients who met the inclusion criteria from January 2023 to July 2023 were included in the validation group for external validation of the prediction model. The DNR group included patients whose perioperative mini mental state examination (MMSE) score decreased by ≥ 1 standard deviation on the 7th day after surgery, while the control group included patients without DNR. This study was approved by the Second Affiliated Hospital of Zhejiang University School of Medicine.
Observation indices: General information was collected on the affected person, including age, sex, body mass index (BMI), and years of schooling (6 years of schooling after primary school, 3 years if primary school dropped out, and higher level of schooling years calculation method based on this category). Clinical data, including preoperative results and concomitant glycosuria, high blood pressure, coronary heart disease, and MMSE score data, were collected. Surgical data, including surgical method (whether the operation was converted to laparotomy), operation time, anesthesia time and rScO2 data, were collected.
Receiver operating characteristic curve analysis: A logistic regression model was used to screen meaningful constitutive predictive models, and the predictive efficiency of the model was analyzed by receiver operating characteristic (ROC) curve analysis. The Hosmer-Lemeshow fit excellence test was used to evaluate the calibration curve of the degree of fit of the premeasured model. Furthermore, the rms package of R (version 4.1.2) was used to construct a wind risk pretest line chart, and then the bootstrap method was used to repeat the sampling step 1000 times for internal verification. The data collected from January to July 2023 were used for external validation of the model.
Statistical analysis
SPSS 24.0 was used for analysis. A normal distribution check was first performed for all continuous variables, and the variation from the normal distribution is described as the mean ± SD. Variables with a nonnormal distribution are described as the median number (interquartile distance). Categorical variables are described as the number of cases (centesimal) [n (%)]. A t test was used to compare normally distributed measurement data, and the Mann-Whitney U test was used to compare nonnormally distributed measurement data. Statistical data were compared using the χ2 test. All statistical analyses were statistically significant at P < 0.05.
RESULTS
Establishment of the DNR risk prediction model after laparoscopic colorectal cancer surgery
General characteristics of the patients in the modeling group: The incidence of DNR was 15.4%. According to whether DNR occurred after surgery, the patients were divided into a DNR group (n = 35) and a non-DNR group (n = 192). There were no significant differences in sex, preoperative hemoglobin (Hb) level, combined hypertension, coronary disease or baseline rScO2 between the two groups (all P > 0.05). However, the minimum intraoperative rScO2 (rScO2 min) was lower in the DNR group (P = 0.07). Patients in the DNR group were older, had fewer years of education, had more intraoperative blood loss, had lower BMI values, and had more combined diabetes (all P < 0.05; Table 1).
Table 1 Comparison of clinical data between the delayed postoperative neurocognitive recovery group and non- delayed postoperative neurocognitive recovery group, n (%).
Variable
DNR group (n = 35)
Non DNR group (n = 192)
χ2/Z
P value
General information
Age [years, M (IQR)]
69 (63-72)
63 (57-68)
-3.077
0.002
Sex
Male
27 (77.1)
120 (62.5)
2.781
0.095
Female
8 (22.9)
72 (37.5)
BMI (kg/m², mean ± SD)
22.65 ± 2.30
22.68 ± 2.98
4.191
0.042
Years of education [year, M (IQR)]
7 (6-9)
9 (6-12)
-2.308
0.021
Preoperative medical history data
Hb [g/L, M (IQR)]
128 (115-136)
128 (112-139)
-0.322
-0.322
MMSE score, M (IQR)
28 (26-29)
29 (27-30)
-1.23
-1.23
Diabetes
No
26 (74.3)
169 (88.0)
4.612
0.612
Yes
9 (25.7.0)
23 (12.0)
Hypertension
No
27 (77.1)
135 (70.3)
0.676
0.676
Yes
8 (22.9)
57 (29.7)
Coronary heart disease
No
32 (91.4)
182 (94.8)
0.62
0.62
Yes
3 (8.6)
10 (5.2)
Surgical data
Baseline rScO2
62.89 ± 6.05
64.74 ± 5.18
1.452
0.456
ScO2, M (IQR)
54.5 (52-58.5)
56.5 (53-60)
-1.813
0.070
Intraoperative blood loss [mL, M (IQR)]
100 (100-200)
100 (50-150)
-2.641
0.008
Anesthesia time (minute)
281.31 ± 72.95
267.09 ± 75.74
0.742
0.390
Surgical time (minute)
210.77 ± 65.28
197.43 ± 69.37
0.145
0.704
Laparoscopic conversion to open abdominal surgery
2 (5.7)
13 (6.8)
0.054
0.817
Multivariate logistic regression analysis of DNR independence after surgery: Multivariate logistic regression equations were constructed for risk factors such as age at admission, BMI, age limit of schooling, intraoperative rScO2 min, intraoperative blood loss, combined glycosuria, high blood pressure and coronary heart disease. The results showed that age and glycosuria are independent risk factors for postoperative DNR, while age of education is a protective factor for postoperative DNR. In addition, the intraoperative rScO2 min is correlated with postoperative DNR occurrence. The differences were statistically significant (all P < 0.05; Table 2).
Table 2 Multivariate regression analysis of factors for delayed postoperative neurocognitive recovery in laparoscopic colorectal cancer surgery.
Independent variable
β
SE
Wald
P value
OR (95%CI)
Intraoperative ScO2
-0.074
0.035
4.377
0.036
0.929 (0.867-0.995)
Years of education
-0.118
0.055
4.593
0.032
0.889 (0.789-0990
Intraoperative blood loss
0.001
0.001
1.773
0.183
1.001 (0.999-1.003)
Age
0.071
0.028
6.265
0.012
1.074 (1.016-1.136)
BMI
0.042
0.074
0.329
0.556
1.043 (0.903-1.205)
Diabetes
1.066
0.524
4.131
0.042
2.903 (1.039-8.111)
Hypertension
-0.738
0.500
2.177
0.140
0.478 (0.179-1.274)
Coronary heart disease
0.282
0.774
0.133
0.716
1.326 (0.291-6.048)
Constant
-2.384
3.048
0.612
0.434
0.092
The prediction model of DNR risk after surgery based on polysin: Logistic regression analysis was performed to establish a prediction model: Logit (P) = -2.384 - 0.074 × rScO2 min - 0.118 × years of schooling + 0.071 × age + 1.066 × combined diabetes mellitus. The ROC curve of the model was drawn (Figure 1A), and the area under the curve (AUC) was 0.757 (95%CI: 0.676-0.839, P < 0.001). From this, it can be seen that the differentiation of the models was good. By means of the Hosmer-Lemeshow fit excellence test and the calibration degree of the drawing calibration curve, it was shown that the difference between the predicted value of the model and the observed value was not statistically significant (χ2 = 7.190, P = 0.516). In the calibration curve at the same time, the standard curve line and the premeasured curve line after calibration fit well, indicating that this model has a good fitting range and high calibration degree (Figure 1B).
Figure 1 The postoperative delayed postoperative neurocognitive recovery prediction model.
A: The receiver operating characteristic curve of the prediction model for postoperative delayed postoperative neurocognitive recovery (DNR); B: The calibration curve of the postoperative DNR prediction model for patients who underwent laparoscopic surgery for colorectal cancer.
Analysis of the postoperative DNR risk prediction nomogram: According to the results of multivariate regression analysis, R language was used to further establish a risk prediction diagram of DNR occurrence after laparoscopic colorectal cancer surgery (Figure 2). For a 70-year-old patient with colorectal cancer, a high middle school culture, a preoperative combination of glycosuria, and a selected time to undergo laparoscopy, the intraoperative rScO2 min was 55%. The total score of the patient was 40 + 34 + 38 + 44 = 156, and the risk of postoperative DNR was 32%. According to the column chart, clinicians can easily, visually and accurately assess the risk of postoperative DNR and formulate individualized preventive intervention programs.
Figure 2 Nomogram for risk prediction of the delayed postoperative neurocognitive recovery after laparoscopic colorectal cancer surgery.
rScO2: Regional cerebral saturation oxygenation.
Validation of the DNR risk prediction model after laparoscopic colorectal cancer surgery
Comparison of patient data between the modeling group and the validation group: There were no significant differences between the modeling group and the verification group in terms of sex, BMI, years of education, intraoperative blood loss, combined high blood pressure, coronary disease, glycosuria, or the incidence of DNR after surgery (all P > 0.05). The age and intraoperative rScO2 min of patients in the verification group were greater than those in the modeling group, while the preoperative Hb level was lower than that in the control group (all P < 0.05; Table 3).
Table 3 Comparison of clinical data between the modeling group and external validation group, n (%).
Variables
Modeling group (n = 227)
Verification group (n = 30)
χ2/Z
P value
General information
Age [years, M (IQR)]
64 (58-69)
68.5 (65-71.5)
64 (58-69)
Sex
Male
147 (64.8)
16 (46.7)
1.491
0.222
Female
80 (35.2)
14 (53.3)
BMI [kg/m², M (IQR)]
22.3 (20.5-24.6)
23.1 (21.48-25.8)
-1.329
0.184
Years of education [year, M (IQR)]
9 (6-12)
8.5 (5-12)
-0.789
0.430
Medical history data
Hb [g/L, M (IQR)]
128 (113-138)
110 (99.75-126)
-3.368
0.001
Diabetes
No
195 (85.9)
26 (86.7)
0.013
0.91
Yes
32 (14.1)
4 (13.3)
Hypertension
No
162 (71.4)
23 (76.7)
0.369
0.543
Yes
65 (28.6)
7 (23.3)
Coronary heart disease
No
214 (94.3)
28 (93.3
7.848
0.837
Yes
13 (5.7)
2 (6.7)
Surgical data
Baseline tSO2 (%, mean ± SD)
63.81 ± 5.62
64.58 ± 6.04
2.317
0.721
Intraoperative rScO2 [%, M (IQR)]
56 (52.5-60)
58.5 (55.87-61)
-2.253
0.024
Intraoperative blood loss [mL, M (IQR)]
100 (50-150)
100 (50-200)
-0.969
0.332
DNR
No
192 (84.6)
27 (90.0)
0.617
0.432
Yes
35 (15.4)
3 (10.0)
Internal validation of the prediction models: The bootstrap method was used for internal verification by repeated sampling 1000 times, and the AUC was calculated to be 0.834, indicating that the model was well differentiated.
External validation of the predictive models: The premeasured model was verified using clinical materials collected from January 2023 to July 2023, and the C index was calculated to be 0.617. The goodness of fit test was performed by the Hosmer-Lemeshow test (χ2 = 12.35, P = 0.1363), which indicated that the premeasured model had good differentiation and good fit with the external data.
DISCUSSION
In this study, based on common postoperative DNR influencing factors and intraoperative changes in rScO2, multivariate regression analysis revealed that intraoperative rScO2 min, age, diabetes status and years of education were independent risk factors for postoperative DNR[20-22]. Risk factors were further considered predictive factors[23]. A risk prediction model and line diagram of the DNR after laparoscopic colorectal cancer surgery, which has good predictive ability and has been validated with external data, have been developed[24-26]. It is suggested that this model can be used as a reference for early-stage identification and early dry prewithdrawal of DNR after surgery.
Postoperative DNR has been widely shown to be associated with prolonged hospital stays and increased long-term mortality[27-29]. The incidence rate of DNR after cardiac surgery is as high as 50%-70%, while the incidence rate of DNR after noncardiac surgery is 13%-50%[30].
In this study, the incidence of DNR was 15.8% in patients who underwent laparoscopy for rectal carcinoma. At present, there are many studies on the risk factors for postoperative DNR at home and abroad, among which the relevant studies found that the clinical predictors of postoperative delirium include advanced age, numbness, high blood pressure, glycemia, preoperative recognition status, massive bleeding, postoperative pain status, etc[31-33]. Advanced age is the only known high risk factor, and another study[34] found that the higher the level of education is, the lower the risk of postoperative cognitive impairment. In this study, the risk of postoperative DNR in elderly patients increased by 1.084 times, and the risk of postoperative DNR decreased with increasing years of education, which was consistent with the results of previous studies[35-39]. In addition, this study suggested that preoperative glycosuria was an independent risk factor for DNR after surgery, and the risk of developing DNR after surgery in such patients was 2.903 times that of patients without diabetes, which might be due to the aggravation of diabetes-related neurodegeneration caused by irritation from surgical anesthesia[40]. A number of large-scale studies[41-43] have also shown that preoperative Hb level, hypertension, preoperative MMSE score, surgical method, major bleeding, operation and anesthesia time, etc., are related to impaired postoperative recognition. However, no similar results were found in this study. This may be related to the single source of the study population and the limited sample size.
The different bedside states of patients were reflected by the presence of Apigenin, and the incidence of DNR after surgery could be effectively reduced by identifying the predictive factors that could be used for dry preconditioning[44]. In recent years, a number of studies have confirmed that the magnitude of rScO2 decrease, rScO2 min or minimum duration are risk factors for postoperative recognition impairment. In this study, data related to rScO2 were collected, and statistical analysis was conducted on the baseline value of rScO2, intraoperative rScO2 min and other indicators. Finally, the incidence of postoperative DNR decreased with increasing intraoperative rScO2 min. The rScO2 min is an independent risk factor for DNR. The abdominal cavity was filled with CO2 at a fixed pressure by laparoscopy. Multiple mechanisms work together to increase CO2 partial pressure in arterial blood, dilate the cerebral blood duct, increase cerebral perfusion, and decrease the oxygen content in arteriovenous blood. Therefore, despite the increase in brain perfusion during laparoscopy, there is insufficient oxygenation of the histopetrium and hypoxia in the brain tissue. The rScO2 is an important indicator for monitoring the oxygenation of regional brain tissue. Basic studies have confirmed that a lack of blood and oxygen in brain tissue leads to postoperative recognition impairment, mainly through the mechanism of β-amyloid, interleukin 1β, tumor necrosis factor α and other inflammatory factors, lactic acid and highly active free radicals acting on the DNA chain of neurons, thereby inducing cell apoptosis. Therefore, continuous intraoperative monitoring of rScO2 and real-time attention to the oxygenation of patients' brain tissue are highly important for preventing DNR after surgery.
CONCLUSION
In summary, this study established and validated a postoperative DNR risk prediction model associated with rScO2 monitoring, which can be used to individualize patient assessments and provide a basis for postoperative DNR prevention.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Gastroenterology and hepatology
Country of origin: China
Peer-review report’s classification
Scientific Quality: Grade A, Grade C
Novelty: Grade A, Grade B
Creativity or Innovation: Grade A, Grade B
Scientific Significance: Grade B, Grade B
P-Reviewer: Bahrami M; Sobhi P S-Editor: Li L L-Editor: A P-Editor: Xu ZH
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