Cardiopulmonary exercise testing-guided exercise protocols based on Holistic Integrative Physiology and Medicine theory aim to optimize glucose regulation in chronic type II diabetes mellitus patients
Highlight box
Key findings
• Comprehensive management based on Holistic Integrative Physiology and Medicine, which involves managing eating, drinking, sleeping, and physical activity, can safely, effectively, and quickly change the trend of high blood glucose.
What is known and what is new?
• Exercise increases the uptake, oxidation, and use of glucose by muscles, and also increases the binding of insulin to receptors.
• By using cardiopulmonary exercise testing to develop a personalized and precise lower limb exercise programme, patients can achieve significant reductions in hyperglycemia with just one session, without restricting their diet or calorie intake.
What is the implication, and what should change now?
• Patients can safely and effectively achieve long-term and intensive control through personalized precision exercise programmes.
Introduction
The relationships among the human body’s numerous systems are intricately entwined to form a dynamic, continuous, three-dimensional image that must be understood from an all-encompassing, holistic, and interconnected perspective (1). According to the Holistic Integrative Physiology and Medicine (HIPM), the functional realization of the human body is a complex process of integration and self-regulation, and all human body systems are inextricably linked to one another to maintain homeostasis (2,3). This is achieved through the integration multiple factors, multidimensional and multiphase complex information theories, and cybernetic concepts. Using these perspectives, respiration is described as a symptom, where blood circulation is the foundation and metabolism is necessary for both. Overall, all of these components are linked to the “Y” spindle’s overall regulation. The primary axes of the “Y” shape are respiration, blood circulation, and metabolism. These systems work together with other functional systems, under the regulation of bodily fluids, to maintain the human body’s functions in dynamic equilibrium (4).
Under normal physiological conditions, the body’s two metabolites—O2 and energy substances (glucose, fat, and amino acids)—are balanced (3,4). However, when the body consumes too much energy, it needs more O2 to meet its needs for cellular metabolism. In other situations, oxygen saturation is limited and can only be increased by increasing the heart rate, which increases blood flow and facilitates the transportation of more O2 and nutrients. As a result of insufficient exercise or insulin secretion, the buildup of energy substances like glucose can cause an oxygen imbalance. Over time, this leads to a long-term imbalance in glucose demand and supply, ultimately resulting in the body’s reduced tolerance to glucose (5,6).
Considering the idea that respiration, circulation, and metabolism play a role in the HIPM theory, we use the blood glucose of type II diabetes mellitus (T2DM) patients with chronic diseases as its research subject and combine the principles of “replenishment of capacity” and “replenishment of deficiencies” with Taoist and natural laws (4-6). Patients were provided a variety of natural fruits, vegetables, fiber, and staple foods in adequate amounts or even in relative excess and safe individualized lower limb precision intensity exercises were followed. Patients were monitored through cardiopulmonary exercise testing (CPET), continuous glucose monitoring system (CGMS), and other continuous functional tests. To consume excess energy in the body, the functional metabolism of body cells, material acquisition, product transport, elimination and other aspects of function are improved, which is conducive to the healing of patients with chronic noncommunicable diseases (6). This study provides a theoretical foundation for the long-term control of individualized precision exercise programs. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-632/rc).
Methods
Participants
The study included 11 T2DM patients who were treated by our medical staff between 2020 and 2022. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Fuwai Hospital (No. 2023-2236) and individual consent was duly obtained from all participants.
Inclusion criteria:
- Diagnostic criteria for diabetes mellitus: typical symptoms of diabetes mellitus (polydipsia, polyuria, and unexplained weight loss) plus random blood glucose ≥11.1 mg/dL (200 mg/dL) and/or fasting plasma glucose (FPG) ≥7.0 mg/dL (126 mg/dL) and/or 2-h blood glucose ≥11.1 mg/dL (200 mg/dL) after a 75-g glucose load (7);
- Diagnostic criteria for hyperlipidemia: plasma total cholesterol >6.2 mg/dL (240 mg/dL) and/or plasma triglycerides >2.3 mg/dL (200 mg/dL) and/or low-density lipoprotein (LDL) cholesterol >4.1 mg/dL (160 mg/dL) and/or HDL cholesterol <1.0 mg/dL (40 mg/dL) (8);
- Diagnostic criteria for hypertension: systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg (1 mmHg =0.133 kPa) measured in the office on three occasions on non-simultaneous days without the use of antihypertensive medication (9).
Exclusion criteria for all participants:
- Being in the acute stage of cardiovascular or cerebrovascular diseases;
- Pregnancy;
- Cognitive dysfunction;
- Lower limb dysfunction or other mobility issues.
CPET scheme
The CPET was conducted using the Quark PFT Ergo system manufactured by COSMEDS.R.L. (Rome, Italy). To ensure the accuracy of airflow exchange data, the system was calibrated daily with a metabolic simulator before patient testing (10,11). Before the exercise test commenced, the participants first underwent a comprehensive static pulmonary function test in a seated position. After, an electromagnetically braked cycle ergometer was used. The intensity was incrementally increased according to the standards set by the Harbor-UCLA Medical Center (6,10-14). Initially, participants were given a 3-minute rest period to adjust to the height of the bicycle cushion and to become accustomed to wearing the mouthpiece and nose clip. This was followed by a 3-minute warm-up session where participants pedaled at a consistent speed of 60 rpm without any added load. The rate at which intensity increased on the electromagnetically braked cycle ergometer was preset between 10 and 30 W/min and was tailored according to the participant’s age, sex, and estimated functional state. This ensured that participants would reach their maximum exercise capacity—determined by symptoms such as leg soreness, fatigue, dyspnea, chest pain, dizziness, and nausea—within a 6- to 15-minute timeframe. Following this maximum exercise period, participants then entered a recovery phase, during which data were recorded for an additional 5 minutes (15-19).
CPET data analysis method
Data for all measured parameters were initially extracted from the software of the Quark PFT Ergo CPET system by COSMED S.R.L. The raw data were segmented second-by-second using a breath-by-breath method (20,21). Analysis was then conducted following standard calculation principles.
Implementation of single individualized precision exercise
A foundational exercise regimen was formulated utilizing the CPET outcomes of the participants. The regimen encompassed specifications regarding the type, level of exertion, and duration of exercise. The intensity of exercise was established via the following formula: Δ50% intensity r = [anaerobic threshold (AT) intensity − intensity increment rate ×0.75]/2 + (maximal load intensity − intensity increment rate ×0.75)/2 (22,23). The designated exercise mode was medical grade precision intensity which corresponds to an intensity increase of 50%. Following the fasting fingertip blood glucose measurement, all patients commenced their meals within a 10-minute timeframe. The breakfast menu comprised a variety of 20–30 organic, ecological fruits and vegetables totaling approximately 300 g, in addition to steamed or boiled skinned yam, pumpkin, potatoes, groundnuts, corn-bread, eggs, grains, cereals, porridge, and other staple foods, totaling approximately 500 g. The participants were instructed to consume all fruits and vegetables prior to consuming staple foods and to pedal at a rate of 60 revolutions per minute after the decline in postprandial glucose following breakfast. The duration of exercise was limited to 26 minutes, with an additional 2 minutes allocated for low-intensity (20 W) warm-up and recovery. The participants were allowed to rest and resume exercise based on their individual needs. Throughout the exercise session, vital signs, including blood pressure, heart rate, electrocardiograms, finger pulse oximetry, and other indicators, were closely monitored to ensure participant safety (24-26).
CGMS
The CGMS is a monitoring technology that uses a glucose sensor to measure the glucose concentration in subcutaneous interstitial fluid, providing an indirect reflection of blood glucose levels. This system is capable of continuously and dynamically recording changes in tissue fluid blood glucose for a duration of up to 360 hours (27). Additionally, CGMS is portable, safe, and minimally invasiveness. The sensor is particularly sensitive in determining and recording changes in blood glucose in the tissue fluid of the upper arm and collects blood glucose data every 11 minutes. The device has the ability to capture the average blood glucose concentration every 3 minutes, with a total of 480 blood glucose values per day. This feature offers a continuous, comprehensive, and dependable source of information regarding blood glucose levels throughout the day, enabling the observation of trends in blood glucose fluctuations and the identification of concealed hyperglycemia and hypoglycemia that may not be easily discernible through conventional monitoring techniques (28). Patients utilized the UMedicine continuous glucose monitor for a period of 9–14 days, commencing 1 day prior to lower limb titration. Fasting fingertip glucose readings were recorded once daily.
Dynamic blood glucose data processing and observation indicators
CGMS were utilized to record the breakfast blood glucose peak of individuals, followed by the initiation of lower limb exercise after a 30-minute titration period. Various parameters were meticulously observed and recorded, including fasting and postprandial peak glucose levels, exercise start and end times, post-exercise relative lows, rebound peak, another low before eating fruits and vegetables at lunch, and blood glucose levels for corresponding times at which carbohydrates were eaten. The data were subsequently used to generate response pattern graphs (refer to Figure 1 for further details). Beginning by establishing the initial time point prior to the commencement of exercise as the zero point, the differences and percentage variances in blood glucose levels at subsequent time points were calculated. The difference was derived by subtracting the measured value at each time point from the measured value at the initial time point, whereas the percentage difference was computed as the quotient of the difference divided by the measured value at the initial time point, multiplied by 100%.
Statistical analysis
Quantitative data were presented as mean ± standard deviation (SD). Statistical analyses were conducted using SPSS Statistics, with graphical illustrations generated through OriginPro. Comparisons of all time points and blood glucose levels across the entire cohort were performed using one-way analysis of variance (ANOVA). Paired-sample t-tests were applied to analyze adjacent time points, blood glucose excursion magnitude differences, and relative percentage changes in glucose levels.
Results
Analysis of participants’ general characteristics
The study included 11 patients, comprising seven males and four females. The basic information is presented in Table 1. The mean age, height, weight, and BMI of the patients were 59.4±11.11 (range, 38–74) years old, 166.2±8.23 (range, 154–181) cm, 70.1±13.67 (range, 45–94) kg, and 25.2±3.73 (range, 18.9–30.9) kg/m2.
Table 1
| Patient | Gender (M/F) |
Age (years) |
Height (cm) |
Weight (kg) |
BMI (kg/m2) |
Primary diagnosis | History of diabetes/oral hypoglycemia only or oral hypoglycemia + insulin injection |
|---|---|---|---|---|---|---|---|
| 1 | M | 58 | 180 | 79 | 24.4 | Hypertension, hyperlipidemia, T2DM, fatty liver, liver cysts, kidney cysts | 15 years/biguanide-byzolidine |
| 2 | F | 74 | 154 | 45 | 18.9 | Coronary artery disease exertional angina thanks multiple stents with 1–2 coronary artery bypass grafts, reinfarction after cerebral infarction, reinfarction of old myocardial infarction, hypertension (very high risk), T2DM, hyperlipidemia, carotid plaque, hypoxia SA | 20 years/biguanide-byzolidine |
| 3 | M | 72 | 165 | 84 | 30.9 | Arteriosclerosis, coronary heart disease, reinfarction after cerebral infarction, reinfarction after old myocardial infarction, heart failure, T2DM, hypertension, multiple carotid plaques, sleep apnea syndrome, obesity | 20 years/biguanide-byzolidine |
| 4 | M | 70 | 162 | 75 | 28.6 | T2DM, obesity, hypertension, coronary artery disease, exertional angina pectoris, palpitations, heart failure, atrial fibrillation, arrhythmia, carotid plaque, severe sleep apnea with severe hypoxia | 15 years/biguanide-byzolidine |
| 5 | F | 66 | 160 | 58 | 22.7 | Coronary atherosclerotic heart disease, old myocardial infarction, post coronary stenting, left ventricular enlargement, ventricular wall aneurysm, moderate mitral valve insufficiency, moderate tricuspid valve insufficiency, class II cardiac function, pulmonary hypertension, hypertension class 1 (very high risk), T2DM, hyperlipidemia, hypercholesterolemia, regurgitant esophagitis, severe sleep apnea syndrome | 25 years/biguanide-byzolidine |
| 6 | M | 38 | 181 | 94 | 28.7 | Coronary artery disease, stable angina, enlarged heart, post coronary artery bypass grafting, class II cardiac function, T2DM, hyperlipidemia, hyperuricemia, obesity | 10 years/biguanide-byzolidine, insulin |
| 7 | F | 64 | 161 | 57 | 22.0 | Sequelae of cerebral infarction (limitation of limb movement), very high-risk hypertension, T2DM, hyperlipidemia, multiple carotid plaques | 20 years/biguanide-byzolidine, insulin |
| 8 | M | 49 | 160 | 60 | 23.4 | Dilated cardiomyopathy, hypertension, myocardial infarction, arrhythmia, post-ICD implantation, T2DM, pulmonary embolism, bilateral lower extremity venous thrombosis | 25 years/biguanide-byzolidine, insulin |
| 9 | M | 44 | 173 | 65 | 21.7 | Coronary atherosclerotic heart disease, acute myocardial infarction, hyperlipidemia, T2DM, hypercholesterolemia, acute coronary syndrome, reflux esophagitis | 5 years/biguanide-byzolidine, insulin |
| 10 | F | 58 | 163 | 80 | 30.1 | T2DM, obesity, lacunar cerebral infarction, atherosclerosis, hypertension, palpitations to be investigated | 30 years/biguanide-byzolidine, insulin |
| 11 | M | 61 | 169 | 74 | 25.9 | T2DM, atherosclerosis | 15 years/biguanide-byzolidine |
| All (n=11)† | 7/4 | 59.4±11.11 [38–74] | 166.2±8.23 [154–181] | 70.1±13.67 [45–94] | 25.2±3.73 [18.9–30.9] | 11 patients with T2DM, 7 with hypertension, 5 with hyperlipidemia and 4 with obesity | Oral hypoglycemia 11 cases, insulin injection 5 cases |
†, data are presented as number or mean ± SD [range]. BMI, body mass index; F, female; ICD, implantable cardioverter defibrillator; M, male; SA, sinoatrial; SD, standard deviation; T2DM, type II diabetes mellitus.
CPET core parameters analysis
In this cohort of patients with T2DM, peak oxygen uptake () was 77.51±25.53 (range, 33.54–133.95) %Pred, AT was 74.71±26.16 (range, 32.37–109.46) %Pred, oxygen uptake efficiency plateau (OUEP) was 115.49±19.61 (range, 65.08–136.09) %Pred, lowest value of carbon dioxide ventilatory efficiency () was 109.42±24.58 (range, 90.25–174.07) %Pred, slope of linear regression of minute ventilation over carbon dioxide elimination, but ignoring its intercept () was 115.69±24 (range, 92.07–174.01) %Pred. Forced vital capacity (FVC) was 93.64±17.29 (range, 65–125) %Pred, forced expiratory volume in 1 second (FEV1) was 89.82±16.23 (range, 69–121) %Pred, forced expiratory flow from 25% to 75% of FVC (FEF25–75%) was 67.64±15.02 (range, 42–86) %Pred, maximal ventilatory volume (MVV) was 94±24.57 (range, 49–126) %Pred, and diffusing capacity of the lungs for carbon monoxide (DLCO) was 81.81±22.52 (range, 40–115) %Pred. Further details can be found in Table 2.
Table 2
| Norm | Unit | Data |
|---|---|---|
| L/min | 1.38±0.54 [0.76–2.23] | |
| mL/min/kg | 19.52±6.16 [11.09–30.02] | |
| %Pred | 77.51±25.53 [33.54–133.95] | |
| AT | L/min | 0.78±0.27 [0.4–1.19] |
| mL/min/kg | 12.5±2.85 [5.86–14.82] | |
| %Pred | 74.71±26.16 [32.37–109.46] | |
| OUEP | Ratio | 37.73±5.51 [25.17–44.93] |
| %Pred | 115.49±19.61 [65.08–136.09] | |
| Ratio | 33.31±6.39 [24.82–47.38] | |
| %Pred | 109.42±24.58 [90.25–174.07] | |
| Slope | 33.28±6.54 [24.24–46.69] | |
| %Pred | 115.69±24 [92.07–174.01] | |
| L | 3.22±0.95 [1.78–4.74] | |
| FVC | %Pred | 93.64±17.29 [65–125] |
| L | 2.49±0.73 [1.47–3.63] | |
| FEV1 | %Pred | 89.82±16.23 [69–121] |
| L/s | 2.24±0.78 [1.32–3.63] | |
| FEF25–75% | %Pred | 67.64±15.02 [42–86] |
| L/min | 101.28±35.23 [42.5–155.1] | |
| MVV | %Pred | 94±24.57 [49–126] |
| mL/min/mmHg | 21.56±7.47 [8.72–32.34] | |
| DLCO | %Pred | 81.81±22.52 [40–115] |
Data are presented as mean ± SD [range]. %Pred, percentage estimated value (= measured value/predicted value × 100%); AT, anaerobic threshold; CPET, cardiopulmonary exercise testing; DLCO, diffusing capacity of the lungs for carbon monoxide; FEF25–75%, forced expiratory flow from 25% to 75% of FVC; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; , lowest value of carbon dioxide ventilatory efficiency; MVV, maximal ventilatory volume; OUEP, oxygen uptake efficiency plateau; , peak oxygen uptake; SD, standard deviation; T2DM, type II diabetes mellitus; , slope of linear regression of minute ventilation over carbon dioxide elimination, but ignoring its intercept.
Overall analysis of fasting to pre-lunch blood glucose changes in T2DM patients
Overall, the average fasting blood glucose was 7.31±1.00 (range, 6.3–8.9) mg/dL in all patients to maintain the long-term use of medication. Following breakfast, there was a rapid rise in blood glucose which peaked at 11.9±3.1 (range, 8.2–18.2) mg/dL before the start of exercise at 7.9±4.29 (range, −18 to −3) min (the negative time range indicating time before exercise start). Ten minutes after peak, patients started to exercise. The average pre-exercise blood glucose levels were 11.58±3.16 (range, 8.0–18.0) mg/dL, and after 30 minutes of exercise, the blood glucose level significantly decreased to an average of 9.51±2.70 (range, 6.7–14.3) mg/dL. After the cessation of exercise, blood glucose levels continued to decrease and reached a relatively low level of 7.98±2.29 (range, 5.6–12.6) mg/dL after 61.4±18.77 (range, 36–96) min. Subsequently, blood glucose levels slowly increased at 88.4±24.95 (range, 51–135) min, reaching a peak of 8.7±2.85 (range, 5.9–16) mg/dL. Before gradually decreasing at 153±32.13 (range, 78–198) min to another low level before eating fruits and vegetables [7.3±2.83 (range, 5.2–15.3) mg/dL]. Before carbohydrates were eaten at lunch, the blood glucose levels remained stable at 7.74±2.64 (range, 6.2–15.3) mg/dL (all P<0.001) for a duration of 183.8±13.72 (range, 159–204) min. Please refer to Figure 2 and Table 3 for further details.
Table 3
| Time No. | Fasting | Postprandial peak |
Exercise start | Exercise end | Post-exercise relative lows | Rebound peak | Another low before eating fruits and vegetables | Eating carbohydrate | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Time (min) |
Glucose (mg/dL) |
Time (min) |
Glucose (mg/dL) |
Time (min) |
Glucose (mg/dL) | Time (min) | Glucose (mg/dL) | Time (min) |
Glucose (mg/dL) | Time (min) |
Glucose (mg/dL) | Time (min) |
Glucose (mg/dL) | Time (min) |
Glucose (mg/dL) | ||||||||
| 1 | −60 | 6.3 | −9 | 9.8 | 0 | 9.3 | 30 | 7.1 | 51 | 6.9 | 78 | 7.2 | 126 | 5.2 | 189 | 6.3 | |||||||
| 2 | −75 | 8.9 | −6 | 18.2 | 0 | 18 | 30 | 14.3 | 66 | 12.6 | 135 | 16 | 156 | 15.2 | 159 | 15.3 | |||||||
| 3 | −72 | 6.9 | −6 | 14.5 | 0 | 14.2 | 30 | 10.1 | 72 | 6.8 | 90 | 7.1 | 132 | 6.1 | 180 | 6.2 | |||||||
| 4 | −66 | 6.3 | −15 | 9.8 | 0 | 9.1 | 30 | 6.9 | 45 | 5.6 | 51 | 5.9 | 78 | 5.2 | 174 | 6.2 | |||||||
| 5 | −66 | 6.3 | −18 | 8.2 | 0 | 8 | 30 | 6.7 | 36 | 6.6 | 114 | 8.8 | 195 | 6.5 | 201 | 6.7 | |||||||
| 6 | −72 | 6.5 | −6 | 10 | 0 | 9.8 | 30 | 8.1 | 63 | 7.7 | 69 | 7.8 | 156 | 6.2 | 195 | 7.3 | |||||||
| 7 | −69 | 7.9 | −6 | 14.5 | 0 | 14.1 | 30 | 12.3 | 96 | 7.4 | 108 | 7.6 | 156 | 7 | 162 | 7.1 | |||||||
| 8 | −60 | 8.1 | −3 | 12.4 | 0 | 12.3 | 30 | 11.3 | 45 | 11 | 54 | 11.2 | 198 | 7.2 | 204 | 7.2 | |||||||
| 9 | −66 | 7.1 | −6 | 9.9 | 0 | 9.8 | 30 | 8.2 | 42 | 7.3 | 72 | 7.5 | 180 | 6.2 | 186 | 6.3 | |||||||
| 10 | −69 | 8.8 | −6 | 15.1 | 0 | 14.9 | 30 | 13.1 | 90 | 10.8 | 99 | 10.9 | 156 | 10.2 | 186 | 10.3 | |||||||
| 11 | −60 | 6.1 | −6 | 8.5 | 0 | 7.9 | 30 | 6.5 | 69 | 5.1 | 102 | 5.7 | 150 | 5.4 | 186 | 6.2 | |||||||
| All (n=11)† | 66.8±4.97 (−75 to −60) | 7.31±1.00 (6.3 to 8.9) | 7.9±4.29 (−18 to −3) | 11.9±3.1 (8.2 to 18.2) | 0±0 (0 to 0) | 11.58±3.16 (8.0 to 18.0) | 30±0 (30 to 30) | 9.51±2.70 (6.7 to 14.3) | 61.4±18.77 (36 to 96) | 7.98±2.29 (5.6 to 12.6) | 88.4± 24.95 (51 to 135) |
8.7±2.85 (5.9 to 16) | 153± 32.13 (78 to 198) |
7.3±2.83 (5.2 to 15.3) | 183.8± 13.72 (159 to 204) |
7.74±2.64 (6.2 to 15.3) | |||||||
†, data are presented as mean ± SD (range). No., number; SD, standard deviation; T2DM, type II diabetes mellitus.
Statistically significant differences (P<0.05, P<0.01, or P<0.001) were observed in time, blood glucose levels, differences in blood glucose changes, and percentage difference values at adjacent loci, as presented in Tables 3-8.
Table 4
| Comparison | t | P |
|---|---|---|
| Fasting vs. postprandial peak | 6.35 | <0.001 |
| Postprandial peak vs. exercise start | −5.62 | <0.001 |
| Exercise start vs. exercise end | −7.35 | <0.001 |
| Exercise end vs. post-exercise relative lows | −2.56 | 0.03 |
| Post-exercise relative lows vs. rebound peak | 1.10 | 0.30 |
| Rebound peak vs. another low before lunch | −2.48 | 0.03 |
| Another low before lunch vs. eating carbohydrate | 0.69 | 0.51 |
Comparisons between time points and blood glucose data for the whole group were made using ANOVA, with significant differences (P<0.001); paired-sample t-tests were used for comparisons between adjacent time points and blood glucose. ANOVA, analysis of variance.
Table 5
| No. | Fasting (mg/dL) | Postprandial peak (mg/dL) | Exercise start (mg/dL) | Exercise end (mg/dL) | Post-exercise relative lows (mg/dL) | Rebound peak (mg/dL) | Another low before eating fruits and vegetables (mg/dL) | Eating carbohydrate (mg/dL) |
|---|---|---|---|---|---|---|---|---|
| 1 | −3 | 0.5 | 0 | −2.2 | −2.4 | −2.1 | −4.1 | −3 |
| 2 | −9.1 | 0.2 | 0 | −3.7 | −5.4 | −2 | −2.8 | −2.7 |
| 3 | −7.3 | 0.3 | 0 | −4.1 | −7.4 | −7.1 | −8.1 | −8 |
| 4 | −2.8 | 0.7 | 0 | −2.2 | −3.5 | −3.2 | −3.9 | −2.9 |
| 5 | −1.7 | 0.2 | 0 | −1.3 | −1.4 | 0.8 | −1.5 | −1.3 |
| 6 | −3.3 | 0.2 | 0 | −1.7 | −2.1 | −2 | −3.6 | −2.5 |
| 7 | −6.2 | 0.4 | 0 | −1.8 | −6.7 | −6.5 | −7.1 | −7 |
| 8 | −4.2 | 0.1 | 0 | −1 | −1.3 | −1.1 | −5.1 | −5.1 |
| 9 | −2.7 | 0.1 | 0 | −1.6 | −2.5 | −2.3 | −3.6 | −3.5 |
| 10 | −6.1 | 0.2 | 0 | −1.8 | −4.1 | −4 | −4.7 | −4.6 |
| 11 | −1.8 | 0.6 | 0 | −1.4 | −2.8 | −2.2 | −2.5 | −1.7 |
| All (n=11)† |
−4.38±2.32 (−9.1 to −1.7) | 0.32±0.19 (0.1 to 0.7) |
0±0 (0 to 0) |
−2.07±0.93 (−4.1 to −1) | −3.6±1.98 (−7.4 to −1.3) |
−2.88±2.17 (−7.1 to 0.8) |
−4.27±1.85 (−8.1 to −1.5) |
−3.85±2.02 (−8 to −1.3) |
†, data are presented as mean ± SD (range). No., number; SD, standard deviation; T2DM, type II diabetes mellitus.
Table 6
| Comparison | t | P |
|---|---|---|
| Fasting vs. postprandial peak | 6.26 | <0.001 |
| Postprandial peak vs. exercise start | 5.61 | <0.001 |
| Exercise start vs. exercise end | −7.39 | 0.001 |
| Exercise end vs. post-exercise relative lows | −6.03 | 0.052 |
| Post-exercise relative lows vs. rebound peak | −4.40 | 0.001 |
| Rebound peak vs. another low before lunch | −7.65 | 0.049 |
| Another low before lunch vs. eating carbohydrate | −6.32 | 0.06 |
Comparison of data from neighboring loci was performed using paired samples t-tests.
Table 7
| No. | Fasting (%) | Postprandial peak (%) | Exercise start (%) | Exercise end (%) | Post-exercise relative lows (%) | Rebound peak (%) | Another low before eating fruits and vegetables (%) | Eating carbohydrate (%) |
|---|---|---|---|---|---|---|---|---|
| 1 | −32.26 | 5.38 | 0 | −23.66 | −25.81 | −22.58 | −44.09 | −32.26 |
| 2 | −50.56 | 1.11 | 0 | −20.56 | −30.00 | −11.11 | −15.56 | −15.00 |
| 3 | −51.41 | 2.11 | 0 | −28.87 | −52.11 | −50.00 | −57.04 | −56.34 |
| 4 | −30.77 | 7.69 | 0 | −24.18 | −38.46 | −35.16 | −42.86 | −31.87 |
| 5 | −21.25 | 2.50 | 0 | −16.25 | −17.50 | 10.00 | −18.75 | −16.25 |
| 6 | −33.67 | 2.04 | 0 | −17.35 | −21.43 | −20.41 | −36.73 | −25.51 |
| 7 | −43.97 | 2.84 | 0 | −12.77 | −47.52 | −46.10 | −50.35 | −49.65 |
| 8 | −34.15 | 0.81 | 0 | −8.13 | −10.57 | −8.94 | −41.46 | −41.46 |
| 9 | −27.55 | 1.02 | 0 | −16.33 | −25.51 | −23.47 | −36.73 | −35.71 |
| 10 | −40.94 | 1.34 | 0 | −12.08 | −27.52 | −26.85 | −31.54 | −30.87 |
| 11 | −22.78 | 7.59 | 0 | −17.72 | −35.44 | −27.85 | −31.65 | −21.52 |
| All (n=11)† | −35.39±9.76 (−51.41 to −21.25) | 3.13±2.44 (0.81 to 7.69) | 0±0 (0 to 0) |
−17.99±5.73 (−28.87 to −8.13) | −30.17±11.86 (−52.11 to −10.57) | −23.86±16.17 (−50.00 to 10.00) | −36.98±11.82 (−57.04 to −15.56) | −32.40±12.42 (−56.34 to −15.00) |
†, data are presented as mean ± SD (range). No., number; SD, standard deviation; T2DM, type II diabetes mellitus.
Table 8
| Comparison | t | P |
|---|---|---|
| Fasting vs. postprandial peak | 12.21 | <0.001 |
| Postprandial peak vs. exercise start | −4.27 | 0.001 |
| Exercise start vs. exercise end | −10.28 | <0.001 |
| Exercise end vs. post-exercise relative lows | −2.96 | 0.01 |
| Post-exercise relative lows vs. rebound peak | 1.09 | 0.30 |
| Rebound peak vs. another low before lunch | −2.15 | 0.057 |
| Another low before lunch vs. eating carbohydrate | 1.04 | 0.32 |
Comparison of data from neighboring loci was performed using paired samples t-tests.
Discussion
The findings of the CPET indicated that the majority of T2DM patients exhibited a spectrum of functional impairments ranging from mild to severe cardiogenic limitations during exercise. Despite having oxygen and carbon dioxide ventilation efficiencies within the normal range, these parameters were lower than expected. Lung capacity, lung ventilation, large airway ventilation, small airway ventilation, and diffusion function were within normal limits. These variations were primarily associated with demographic factors, including sex, age, height, body mass, race, and disease severity (20,21).
As stated by the HIPM, life activity is defined by respiration, which is based on blood circulation. This is premised on tissue cell metabolism, and the metabolism of energy substances in cell mitochondria provides the main source of energy for various life activities (1-4). The respiratory circulation metabolism spindle is situated within the neurohumoral system and is regulated by other systems, including digestion, absorption, urinary, excretion, immunity, and skin systems. These systems work in conjunction with one another to facilitate the continuous exchange of substances with the external environment, thereby enabling the overall functional state of activity to reach a state of dynamic equilibrium. However, this equilibrium is not indicative of a true balance in the functional state (1,3). HIPM posits that the primary etiology of cardiovascular and cerebrovascular diseases, hypertension, hyperglycemia, hyperlipidemia, obesity, hyperuricemia, and other related conditions is rooted in the disruption of dynamic equilibrium among the diverse physiological systems of the human body. Specifically, the core imbalance lies in the inadequate function of the body’s various systems, organs, tissues, and cells, resulting in localized and systemic imbalances. The primary factors contributing to the development of diabetes mellitus include a decrease in glucose uptake by local cells during metabolism, leading to an increase in blood glucose levels through endocrine system regulation. Additionally, there is a reduction in glucose utilization; during the metabolic process of an organism, local cells may experience a reduction in glucose utilization when under attack from infection, trauma, or cytotoxic substances (4). Despite this decrease in cellular glucose uptake, overall glucose uptake by the organism remains unaffected, resulting in an accumulation of glucose in the bloodstream. Insufficient glucose uptake by local tissues or organs inhibits insulin secretion, ultimately leading to elevated blood glucose levels. Furthermore, an inadequate local blood supply in the body results in a deficiency in the local energy supply under normal blood glucose conditions (20). This triggers the body’s compensatory response, leading to an elevation in the secretion of glucagon and other glucagon hormones, ultimately resulting in an increase in the overall blood glucose level of the body (21).
Neurohumoral regulation represents merely a component of the functional integration of the human body. Importantly, neurohumoral regulation cannot be considered independent of the overall process of homeostasis. Rather, its role is contingent upon the overall function of multiple systems (22). In particular, metabolism characterized by the oxidation of energy substances is the main factor of the functional activities of the living body. The respiratory circulation, blood, nerve tissue cells, and other components are primarily responsible for cellular metabolism, facilitating the transport of oxygen, carbon dioxide, and other substances along the core axis (23). Physiologically, the respiratory system directly interacts with the external environment of the human body. The gastrointestinal tract, digestive and absorption systems, circulation, blood, nerve tissue cells, and other components are primarily involved in cellular metabolism, enabling the transport of energy substances and metabolic products. The primary pathway of cellular metabolism is the transport of energy substances and metabolites. This transport involves direct contact with the external environment of the human body and also plays a role in the digestive system, which is responsible for the digestion, absorption, and excretion of substances. The human body’s internal circulating blood and nervous system, nor all of the body’s tissues and cells, are in direct contact with the external environment. These elements are part of the aforementioned two pathways (24). It can be reasonably deduced that environmental, genetic, and immunological factors are related to the onset and development of numerous endocrine metabolic diseases, such as diabetes mellitus. Furthermore, an endocrine metabolic disease can involve or affect multiple organs. The functions of the various tissues and organs in the human body are interdependent and regulate one another. Alterations in the internal environment of one tissue or organ may be associated with diseases in other tissues (25).
Physiological studies of the circulatory system generally support the theory that neuroendocrine regulation of sympathetic catecholamines is central to overall blood flow distribution, but the HIPM theory suggests that metabolism is the most important factor. The body’s cardiac output increases by a factor of three to five during intense exercise (1-3). Nearly 90% of cardiac output travels towards the working skeletal muscle, receiving the majority of blood flow. The heart and respiratory muscles, which can stay the same size or grow slightly, are also the primary recipients of blood flow. On the other hand, blood flow to tissues during exercise is much less than it is at rest. Taking cycling as an example, when the blood flow in the leg muscles increases significantly, the level of catecholamines in the exercised muscles also increases dramatically. The metabolic equilibrium of oxygen in the surrounding tissues changes as a result of additional, more complex chemical reactions (1,2,26). Accordingly, for the 11 T2DM patients with elevated blood glucose, the therapeutic principles of “replenishment of deficiency” and “replenishment of capacity” were applied. This involved providing a variety of fruits, vegetables, fiber, and staple and side foods in sufficient or even relative excess quantities, as well as individualized and targeted exercise to burn calories and increase the body’s ability to metabolize glucose. The functional metabolism of the body’s cells, including material acquisition, product transfer and disposal, and other functions are enhanced and improved through targeted and precise exercise to burn energy. This is helpful for improving and effectively maintaining the functional state of healthy, normal individuals as well as for the healing of patients with chronic, noncommunicable diseases. As metabolic function improves, so does the overall functional state of respiration and circulation (27). The results of Nesti’s study validate this claim (28).
Our study revealed a statistically significant decrease in blood glucose levels following a single session of lower limb precision intensity exercise compared with pre-exercise levels (all P<0.001). This is because cycling requires energy to overcome resistance, and all energy is derived from O2 and energy substances through mitochondrial oxidation, which produces heat as a result. Local decreases in O2, energy substances, heat production, metabolite formation, etc., are caused by metabolic impacts. The blood glucose levels of patients with T2DM in this cohort of trials decreased, followed by a rebound post-exercise, which is likely attributed to the increased breakdown of hepatic glycogen and myoglycogen stores within their bodies into glucose (28).
Presently, clinical studies on exercise and glucose reduction have focused primarily on improving abnormal blood glucose levels in patients with T2DM through long-term exercise or dietary control. The innovative contribution of this study lies in the development of a personalized lower limb precision exercise protocol utilizing the CPET with no dietary restrictions for individuals with T2DM. This exercise regimen notably reduced blood glucose levels among patients with T2DM after a single session, with a focus on ensuring safety. These findings serve as a foundation for a comprehensive program centered on personalized precision exercise aimed at enhancing the long-term management of various metabolic abnormalities. Lower limb titration enables the fine-tuning of personalized lower limb precision exercises in patients with T2DM. It may be necessary for certain individuals to adjust the intensity of the exercise regimen, either increasing or decreasing the intensity output from the initial level, to achieve optimal effectiveness and safety (27,28).
Limitations
However, this study has certain limitations. Specifically, the sample size was relatively small and the age range of the patients was wide, potentially introducing bias into the results. Future research should aim to expand the sample size for more robust analysis. The continued decrease in blood glucose to reach the first relatively low point after exercise may have been caused by exercise, whereas the later decrease to another low point after the increase in blood glucose may have compounded the effect of the drug, necessitating further in-depth investigation. In the context of managing abnormal blood glucose levels in patients with T2DM, the impact of a single exercise session on lowering glucose levels was constrained and transient, lasting approximately 1 hour. For subsequent long-term control, the number of individualized and precise exercises should be increased appropriately, and the second exercise should be performed when the patient’s blood glucose begins to rebound to achieve a better glucose-lowering effect.
Conclusions
In summary, the implementation of a personalized lower limb precision exercise regimen, following the CPET, has been shown to effectively lower abnormal blood glucose levels in patients with T2DM within a single session. This approach serves as a foundational element within a comprehensive individualized precision exercise program, offering promise for long-term management of various metabolic abnormalities. However, it is important to note the variability in the response of patients with T2DM, necessitating individualized analysis of each patient’s situation. Consequently, one should focus on integrating respiratory circulation and metabolism when diagnosing and treating chronic diseases, and focus on improving the quality of life for patients with T2DM by applying the principles of “filling in the gap” and “filling in the capacity” through treatment.
Acknowledgments
None.
Footnote
Provenance and Peer Review: This article was commissioned by the editorial office, Journal of Thoracic Disease for the series “Holistic Integrative Physiology Medicine and Health: from theory to clinical practice”. The article has undergone external peer review.
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Funding: This work was supported by
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-632/coif). The series “Holistic Integrative Physiology Medicine and Health: from theory to clinical practice” was commissioned by the editorial office without any funding or sponsorship. X.G.S. served as the unpaid Guest Editor of the series. The authors have no other conflicts of interest to declare.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Fuwai Hospital (No. 2023-2236) and individual consent was duly obtained from all participants.
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References
- Sun XG. New theory of holistic integrative physiology and medicine I: New insight of mechanism of control and regulation of breathing. Chinese Journal of Applied Physiology 2015;31:295-301.
- American Diabetes Association Professional Practice Committee. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2022. Diabetes Care 2022;45:S17-38. [Crossref] [PubMed]
- Sun XG. New theory of holistic integrative physiology and medicine III: New insight of neurohumoral mechanism and pattern of control and regulation for core axe of respiration, circulation and metabolism. Chinese Journal of Applied Physiology 2015;31:308-15.
- Compilation Group of the Clinical Guidelines for the Prevention and Treatment of Elderly Diabetes in China. Clinical guidelines for the prevention and treatment of type II diabetes mellitus in the elderly in China (2022 edition). Chinese Journal of Diabetes 2022;30:2-51.
- Joint Committee for the Revision of the Guidelines for the Prevention and Treatment of Dyslipidemia in Chinese Adults. 2016 Chinese guideline for the management of dyslipidemia in adults. Chinese Journal of General Practitioners 2017;16:15-35.
- Chinese Guidelines for the Management of Hypertension. Chinese guidelines for the prevention and treatment of hypertension (2018 revision). Chinese Journal of Cardiovascular Medicine 2019;24:24-56.
- Colberg SR, Sigal RJ, Yardley JE, et al. Physical Activity/Exercise and Diabetes: A Position Statement of the American Diabetes Association. Diabetes Care 2016;39:2065-79. [Crossref] [PubMed]
- Hansen JE, Sun XG, Stringer WW. A simple new visualization of exercise data discloses pathophysiology and severity of heart failure. J Am Heart Assoc 2012;1:e001883. [Crossref] [PubMed]
- Sun XG. Cardiac Rehabilitation: Sun Xingguo's Viewpoints 2020-Holistic Integration of Physiology and Medicine New Theory Guiding Individualised Cardiopulmonary Exercise Holistic Programmes for Effective Diagnosis and Treatment of Chronic Diseases and Effective Management of Health. Beijing: Science and Technology Literature Press; 2020.
- Xia R, Sun XG. Application of ventilation efficiency in cardiopulmonary exercise test in cardiopulmonary diseases. Chinese Journal of Geriatric Care 2018;16:70-3.
- Sun XG, Hansen JE, Stringer WW. Oxygen uptake efficiency plateau best predicts early death in heart failure. Chest 2012;141:1284-94. [Crossref] [PubMed]
- Sun XG. Application value and prospect of cardiopulmonary exercise test in clinical cardiovascular pathology. Chinese Journal of Cardiology 2014;42:347-51.
- Sun XG, Hansen JE, Stringer WW. Oxygen uptake efficiency plateau: physiology and reference values. Eur J Appl Physiol 2012;112:919-28. [Crossref] [PubMed]
- Tai WQ, Sun XG, Hao L, et al. Changes of radial artery pulse wave in patients with newly diagnosed chronic disease before and after a single precisely individualized exercise. Chinese Journal of Hypertension 2022;30:451-8.
- Yu JY, Sun XG, Lu L, et al. Cardiopulmonary exercise test accurately prognoses risk of postoperative complications in patients undergoing lung resection in good functional status. Chinese Journal of Applied Physiology 2021;37:195-201. [Crossref] [PubMed]
- Kanaley JA, Colberg SR, Corcoran MH, et al. Exercise/Physical Activity in Individuals with Type 2 Diabetes: A Consensus Statement from the American College of Sports Medicine. Med Sci Sports Exerc 2022;54:353-68. [Crossref] [PubMed]
- Zhou J, Jia WP, Yu M, et al. The reference values of glycemic parameters for continuous glucose monitoring and its clinical application. Chinese Journal of Internal Medicine 2007;46:189-92.
- Zhang YY, Tao HY, Jin D, et al. Clinical analysis of blood glucose monitoring by real-time insulin pump system. Chinese Journal of General Practice 2018;16:2024-7.
- He ZW, Lu XX. Individualised assessment of blood glucose fluctuation in newly diagnosed early-onset type II diabetes mellitus patients using an ambulatory glucose monitoring system. Medical Diet and Health 2022;20:1-3, 14.
- Yu XF, Zhang L, Zhang SF, et al. Consistence of interstitial glucose measured by the flash glucose monitoring system with capillary blood glucose. Zhejiang Medical Journal 2018;40:1217-20.
- Meng KS, Wang XR. The Value of Real-time Ambulatory Blood Glucose Monitoring System in the Monitoring of Blood Glucose Fluctuation in Intensive Treatment of Insulin Pump in Patients with Type 2 Diabetes Mellitus. Labeled Immunoassays and Clinical Medicine 2017;24:1280-3.
- Sun XG, Stringer WW, Yin X, et al. Human experiments of metabolism, blood alkalization and oxygen effect on control and regulation of breathing II: room air exercise test after blood alkalization. Chinese Journal of Applied Physiology 2015;31:345-8.
- Sun XG, Stringer WW, Yin X, et al. Human experiments of metabolism, blood alkalization and oxygen effect on control and regulation of breathing III: pure oxygen exercise test after blood alkalization. Chinese Journal of Applied Physiology 2015;31:349-52, 356.
- Sun XG. New theoretical system of holistic integrated physiological medicine: autonomous regulation of human body function integration. Chinese Circulation Journal 2013;28:88-92.
- Sun XG. New Theoretical System of Holistic Control and Regulation for Life and Cardiopulmonary Exercise Testing. Medicine & Philosophy 2013;34:22-7.
- Sun XG. Establishing the idea of holistic integrative medicine, optimizing the quality of health care service in prevention and treatment. Chinese Journal of Applied Physiology 2015;31:289-94.
- Sun XG. A new vision of respiratory regulation mechanism--a theory of integrated regulation of human life multi-system functions. China Medical News 2013;28:18.
- Nesti L, Pugliese NR, Sciuto P, et al. Type 2 diabetes and reduced exercise tolerance: a review of the literature through an integrated physiology approach. Cardiovasc Diabetol 2020;19:134. [Crossref] [PubMed]

