**6.1 Study for a particular parameter couple** ð Þ *Ca***,** *a=***ℓ**

The objective of this subsection being to illustrate the methods on an example and show how to apply them, we only consider the snapshot FOM solutions for ð Þ¼ *Ca*, *a=*ℓ ð Þ 0*:*1, 0*:*9 for the sake of simplicity and brevity. **Figure 1** shows both membrane shapes and positions in the channel at different instants.

At each time *t n* ¼ *n*Δ*t*, where the time step is equal to Δ*t* ¼ 0*:*04, a snapshot is saved and stored in the database. Note that all time quantities are nondimensionalized by the factor ℓ*=V*. The resulting generated data matrix is used as the entry matrix for the ROM learning process. Then a truncated SVD is applied to get the spatial POD modes. In **Figure 2**, the four first eigenmodes Φ*k* are plotted (more precisely this is a superposition of each mode onto the original spherical shape for a better visualization and understanding of their influence). Based on, the graphics *k*↦1 � *RIC k*ð Þ plotted in log scale in **Figure 3**, we decide to use a truncation rank *K* equal to *K* ¼ 10, returning a relative information content of about 1 � 3*:*5 � 10�5 .

Then a reduced-order dynamical system for the capsule time evolution is searched. In this example, we compare two models: the first one is the affine approximation (denoted by ROM-A)

$$\mathfrak{a}\_{\mu}^{n+1} = A\_{\mu}\mathfrak{a}\_{\mu}^{n} + \mathfrak{b}\_{\mu} \tag{39}$$

with the matrix *A* and the vector *b* to identify. It is equivalent to consider the vector of features *η*ð Þ¼ *a* ð Þ *a*, 1 *T*. The second nonlinear model is built from the observable vector *η*ð Þ¼ *a* ð Þ *a*, *κ*ð Þ *a* , 1 *T* with the recurrent time scheme

$$\boldsymbol{\sigma}\_{\mu}^{n+1} = \boldsymbol{A}\_{\mu} \boldsymbol{\eta} \left( \boldsymbol{\sigma}\_{\mu}^{n} \right) \tag{40}$$

**Figure 1.**

*Example of a microcapsule dynamics within a square-base channel for (Ca*, *a=*ℓ*) = (0.1, 0.90). Shapes and locations of the initially spherical capsule are shown at t* ¼ 0 *(in transparency), 0.4, 2.8, 5.2, 7.6.*

*Space-Time-Parameter PCA for Data-Driven Modeling with Application to Bioengineering DOI: http://dx.doi.org/10.5772/intechopen.103756*

**Figure 2.**

*SVD: Four first spatial principal components computed by the HOSVD. Each mode has been added on the initial spherical shape and amplified by a factor 2 for better visualization. Higher-order modes show oscillations at the rear of the capsule.*

**Figure 3.**

*SVD: Plot of k*↦1 � RICð Þ*k , where* RICð Þ*k represents the relative information content at truncation rank k.*

(ROM-B). For ROM-B, the Gaussian kernel function (21) is used. The standard deviation parameter *σ* in (21) is chosen as *σ* ¼ max *n*∥*an μ*∥ ¼ ∥*aN*þ1 *μ* ∥2. In both cases ROM-A and ROM-B, the determination of the matrix *Aμ* by minimization of the least square problem (37) leads to a very small residual. In **Figure 4**, the logarithm of the relative time residual

$$n \mapsto \log\_{10} \left( \left\| \boldsymbol{\sigma}\_{\mu}^{n+1} - \boldsymbol{A}\_{\mu} \boldsymbol{\eta} \left( \boldsymbol{a}\_{\mu}^{n} \right) \right\|^{2} / \left\| \boldsymbol{a}\_{\mu}^{n+1} \right\|^{2} \right) \tag{41}$$

is plotted for each ROM model. One can observe values between 10�14 and 10�8. The residual for ROM-B appears to be slightly smaller than that of ROM-A thanks to the added nonlinear terms. A surprising result is that the affine ROM-A model returns rather accurate results whereas the fluid–structure interaction problem is intrinsically nonlinear. In order to study the stability of the model ROM-A, in **Figure 5** we plot the complex eigenvalues of the square matrix *Aμ*. We observe that all the eigenvalues have a modulus less or equal to one. One of the eigenvalues is equal to 1 exactly up to Double Precision roundoff errors, meaning that there is a physical invariant in the system. It is known that the capsule volume is kept constant during time, because of the incompressibility of the fluid. For ROM-A, since *an*þ1 *μ* ¼ *Aμan μ* þ *b* and *a*0 *μ* ¼ **0**, we have

$$\mathfrak{a}\_{\mu}^{n} = A\_{\mu}^{n} \mathfrak{a}\_{\mu}^{0} + \sum\_{k=0}^{n-1} A\_{\mu}^{k} \mathfrak{b} = \sum\_{k=0}^{n-1} A\_{\mu}^{k} \mathfrak{b}. \tag{42}$$

The matrix *Aμ* is observed to be diagonalizable in ℂ. There is an invertible matrix *Pμ* such that *Aμ* ¼ *Pμ*Λ*μP*�1 *μ* where Λ*μ* is the diagonal matrix of the eigenvalues. Since it is observed that *ρ* Λ*μ* � � ¼ 1, we have

$$\|\boldsymbol{\mathfrak{a}}\_{\mu}^{n}\| \leq \text{Cond}\left(P\_{\mu}\right)n\|\mathbf{b}\|, \quad \forall n \in \mathbb{N},\tag{43}$$

#### **Figure 4.**

*Matrix identification. Log of the normalized residual n*↦ log 10 ∥*an*þ1 *μ* � *Aμη an μ* � �∥2*=*∥*an*þ1 *μ* ∥2 � � *for both ROM-A and ROM-B.*

*Space-Time-Parameter PCA for Data-Driven Modeling with Application to Bioengineering DOI: http://dx.doi.org/10.5772/intechopen.103756*

**Figure 5.**

*Matrix identification. Eigenvalues of the computed matrix Aμ plotted in the complex plane for the ROM-A model. One of the eigenvalue is* 1 *up to round-off error.*

showing that the coefficients in the PCA space grow at most linearly in time.

In **Figure 6**, we compare the computed capsule shapes and positions in the channel for the computed FOM capsules obtained at different times: *t* ¼ 0, 0*:*4, 2*:*8, 5*:*2 and 7*:*6. What can be observed is that the ROM-B model returns very satisfactory results where the shape solutions fully overlap the FOM ones'at the eye norm'. Finely, we plot in **Figure 7** the time evolution of the errors in the capsule 3D shape of the ROM solutions as compared to the FOM solutions. The difference between the shapes are quantified by *ε*Shapeð Þ*t* , the ratio between the modified Hausdorff distance (MHD) computed between the FOM shape SFOMð Þ*t* and the ROM shape SROMð Þ*t* and the channel characteristic length ℓ:

$$\varepsilon\_{\text{Shape}}(t) = \frac{\text{MHD}(\mathcal{S}\_{\text{FOM}}(t), \mathcal{S}\_{\text{ROM}}(t))}{\ell}. \tag{44}$$

The modified Hausdorff distance measures the maximum value of the mean distance between the two shapes to compare [17]. The ROM-A and ROM-B

#### **Figure 6.**

*Sequence of cross-section capsule shapes and positions in the microchannel from the initial spherical shape shown in light green at the beginning of the channel: Comparison of the FOM solutions (gray dots) and of the solutions computed from the dynamical k-DMD reduced-order model (dark green solid line) at the same instants as in Figure 1: t* ¼ 0, 0*:*4, 2*:*8, 5*:*2, 7*:*6*.*

#### **Figure 7.**

*(a) Comparison of the time evolution of the shape error between the affine DMD model (ROM-A with K* ¼ 10*) and the kernel-based one (ROM-B with K* ¼ 10*, M* ¼ 5*). One can observe a maximum error less than 0.1% in both cases. (b) Sensitivity analysis of the parameter σ (*∥*aN*þ1∥2 ¼ 667*:*14*.)*

models return very accurate solutions with maximum 0.1% error. It is also observed that the ROM-B models is slightly more accurate than the affine approximation.

### **6.2 HOSVD on the whole data tensor and error measurements on the whole database**

Now the consider the whole database made of 55 samples in the parameter domain. In **Figure 8** we plot the location of the 55 chosen samples in the plane ð Þ *Ca*, *a=*ℓ . The design zone of interest corresponds to capsule shapes that can reach a steady state after a certain time.

A SVD is first performed on the *μ*-flattening of the data tensor T *x*. In **Figure 9**, we plot the four first parameter (normalized) eigenmodes in the parameter domain.

*Space-Time-Parameter PCA for Data-Driven Modeling with Application to Bioengineering DOI: http://dx.doi.org/10.5772/intechopen.103756*

#### **Figure 8.**

*Samples of the design of experiment in the parameter space Ca* ð Þ , *a=*ℓ . *The zone of interest corresponds to capsule shapes that reach a steady state after a certain time.*

**Figure 9.** *HOSVD: The first four parameter eigenmodes in the parameter domain, computed from the μ-flattening of the data cube.*

These modes give an idea on the dependency of the capsule shapes with respect to the parameters. To complete the analysis, we show in **Figure 10** the spectrum of the singular values for the *μ*-flattening matrix. One can observe a rather fast decay of the singular values especially for the ten first modes.

**Figure 10.** *Spectrum of the singular values of the μ-flattening matrix.*

Next, we perform the SVD of the time *t*-flattening matrix of T *x*. The SVD provides us temporal eigenmodes. In **Figure 11**, the four first temporal eigenmodes *ωm*, *m* ¼ 1, … , 4 are plotted. The first one appears to be the linear function while the others add details especially in the transient zone of the capsule dynamics. The spectrum of the singular values again shows a fast decay especially for the six first modes.

To conclude this section, we have tested the accuracy of both ROM-A and ROM-B on the whole database. For each sample, we have derived a ROM model, i.e. a loworder dynamical system formulated in the PCA space. Then we have compared the ROM solution to the FOM solution by calculating *ε*Shape between the two capsule shapes. In **Figure 12**, the heat maps of *ε*Shape are plotted for ROM-A and ROM-B. One can observe a uniform accuracy over the whole parameter domain, with errors less than 0.1%, thus showing the efficiency of the approach. Reported computational speedups are between 5000 and 10,000 using ROM models. A computer with two Intel Xeon GOLD 6130 CPU (2.1 Ghz) has been used for the numerical tests.

*HOSVD. Left: First four temporal eigenmodes computed from the SVD decomposition of the t-flattening data tensor. Right: Spectrum of the singular values.*

*Space-Time-Parameter PCA for Data-Driven Modeling with Application to Bioengineering DOI: http://dx.doi.org/10.5772/intechopen.103756*

**Figure 12.**

*Heat maps of the modified Hausdorff distance between the FOM solutions and the ROM ones at dimensionless time Vt=*ℓ ¼ 10. *Left: ROM-A, right: ROM-B. Errors are less than 0.1%.*


**4.2 Simulation conditions**

#### **4.2.1 Geometric model and grid**

As we all know, in numerical simulation process, the grid structure has a greatly effect on the calculation precision. Mesh with bad structure may lead to the enlargement of relative error and stability degradation or even simulation procedure divergent.

Fig. 5. Diagram of grid for geometric model.

Meanwhile, the grid formation technique has become a critical part in modern computational fluid dynamics. The mesh formation method can be divided two ways. One is algebraic method and the other is differential method. Thereinto, differential method can be used to produce smooth grid to suit complex flow domain. Of course, we can adjust the mesh degree of closeness by changing the control function. And if more accurate solution needed, mash must be thicker.

In this study, horizontal pipe section with 1 meter length, 0.08 meter diameter and range from 127.7 to 128.7m were chosen as research object. In this pipe section, fly ash was conveyed by compressed gas. Fig.5 gave the pipe geometric model with full grid.

#### **4.2.2 Boundary conditions**

384 Computational Simulations and Applications

*e g*

 2 0 4 1 3 *s s sp*

It must be noted that, in the equations above, the symbol of e stands for granule collision

*e*

As we all know, in numerical simulation process, the grid structure has a greatly effect on the calculation precision. Mesh with bad structure may lead to the enlargement of relative

*e e*

*dg e*

0 ,max 1 /*s s g*

>

> >

1 1/3

(37)

(39)

(38)

(40)

The expression of granule phase pressure is given as below.

0 1 21 *s ss s p*

When e= 1, it means elastic collision, which is in case of no energy loss.

When 0 1 *e* , it means energy will diffuse in form of elastic collision.

error and stability degradation or even simulation procedure divergent.

The total viscosity of granule phase is the below equation.

recovery coefficient. And it obeys the following rule.

When e=0, it means complete inelastic collision.

Fig. 5. Diagram of grid for geometric model.

**4.2 Simulation conditions 4.2.1 Geometric model and grid**

	- Inlet boundary for gas

There are the assumptions that the gas axial velocity cross-section of the entrance with the fully developed turbulent flow of smooth pipe, radial velocity is zero, given the pressure of the entrance, turbulent kinetic energy expression is

$$k = \frac{\Im}{2} \left(\mu\_{\mathcal{S}} I\_{\mathcal{S}}\right)^2 \tag{41}$$

Turbulent dissipation rate can be expressed by

$$
\omega = \mathcal{C}\_{\mu}^{0.75} \frac{k^{1.5}}{l} \tag{42}
$$

Where Ig is gas turbulent intensity, to the fully arisen turbulent flow, then,

$$I\_{\mathcal{g}} = 0.16 \left( \text{Re}\_{\mathcal{g}D\_H} \right)^{1/8} \tag{43}$$

To the equation, *DH* is hydraulic diameter. From the equation above, it can be concluded, the Reynolds number in the gas turbulent intensity equation is regard hydraulic diameter as characteristic length.

*L* is length dimension, to circle pipe,

$$I = 0.07L\_{\nu}$$

*L* is pipe diameter.

The gas velocity of inlet is set 9.9m/s.

Outlet boundary for gas

The assumption that the fully developed conditions of the pipe flow, namely the normal derivative of the variables solved is zero, given the export pressure.

$$\frac{\partial \phi}{\partial \mathbf{x}\_i} = 0 \quad \text{ (} \boldsymbol{\phi}\_{\mathcal{S}} = \boldsymbol{\mu}\_{\mathcal{S}^i}, \boldsymbol{k}\_\star \text{\textquotedblleft} \text{\textquotedblright} \end{bmatrix} \tag{44}$$

#### Pipe wall surface

In the study, no-slip condition was adapted. Each parameter near the pipe wall was considered as zero. And wall function method was applied. So

Numerical Simulation of Dense Phase Pneumatic Conveying in Long-Distance Pipe 387

It must be noted that, in this paper, the turbulent kinetic energy and turbulent dissipation

In this paper, Finite Volume Method was utilized to discrete the governing equations above. The selected pipe section was divided into many non-concurrent domains which was called calculating grid. And then, each nodal point of stationary divided domain and its controlled volume were confirmed. In the process of discretization, the physical quantity of this

In this study, we used SIMPLE method to carry out two phase flow simulation. And the gas solid two phase flow were coupled each other. First of all, on the basis of initial condition and boundary condition, pure gas phase governing equation can be solved. And then, we can resolve granule phase governing equations which are based on gas flow characteristics. The last step was to gain the gas and solid flow field respectively by combining with this

Solid phase gas phase pipe ρs=770kg·m-3 ρg=2.03kg·m-3 D=0.08m ds=60μm μg=1.85×10-5 L=1m

rate near the pipe wall were defined zero.

**4.2.3 Basic parameter in process of simulation**

Table 2. Basic parameter used for simulation.

**4.3 Numerical simulation process 4.3.1 Equation discretization**

**4.3.2 Numerical calculation method**

**4.3.3 Numerical calculation circuitry**

two single flow and coupling effect between two phases.

The numerical calculation circuitry is shown as below.

Table 2 gave the basic parameter in process of numerical simulation

controlled volume were defined and stored in the determined nodal point.

$$\pi\_w = \begin{cases} \frac{\overline{\mu\_g} k C\_\mu^{0.25} \rho\_g k^{0.5}}{\ln \left( E Y^+ \right)} & Y^+ \ge 11.63 \\\\ \frac{\overline{\mu\_g} \mu\_g}{\delta\_g} & Y^+ \le 11.63 \end{cases} \tag{45}$$

Where *ugi* stands for the gas velocity which is parallel to the pipe axis near the pipe wall. / 5.025.0 *g y kCY* , *δy* is the distance between calculated nodes and pipe wall. *E*=9.793. 2. Boundary condition for solid phase

Inlet boundary for solid

Homogeneous inlet conditions are set and the volume fraction of particles is given. The expressions of turbulent kinetic energy and turbulent dissipation rate are set as following.

$$k\_s = \frac{\mathfrak{B}}{2} \left(\mu\_s I\_s\right)^2, \mathcal{E}\_s = \mathbb{C}\_{\mu}^{3/4} \frac{k\_s^{3/2}}{l} \tag{46}$$

Where

$$I\_s = 0.16 \left(\text{Re}\_{sD\_H}\right)^{1/8} \tag{47}$$

The solid velocity is set 4.3 m/s based on experiment data.

Outlet boundary for solid

The assumption that the solid phase was the fully developed conditions of the pipe flow, namely the normal derivative of the variables solved is zero.

$$\frac{\partial \phi\_s}{\partial \mathbf{x}\_i} = \mathbf{0} \left( \phi\_s = \mathbf{u}\_{si}, k\_{s\prime}, \mathbf{z}\_s \right) \tag{48}$$

Pipe wall surface

To granule phase, the velocity doesn't agree with no-slip condition, thus the velocity value can't be equal to zero. According to particles collision near pipe wall research, the granule phase normal velocity can be given as following.

$$\left(\left(\lambda\_1-\lambda\_2\right)\left(u\_{si}\right)\_w+\lambda\_1 h \text{Kn}\left(\frac{\partial u\_{si}}{\partial \mathbf{x}\_i}\right)\_w\right)\_w=0\tag{49}$$

where,

$$
\mathcal{A}\_1 = \left(1 - \frac{e^2}{2}\right)^{1/2}, \mathcal{A}\_2 = \left[\frac{e(1-e)}{1+e}\right]^{1/2}
$$

h means the distance between the center point of the first control bulk and the pipe wall. Kn is Knudsen number, which can be given as following.

$$\text{Kn} = \pi\_s \left| \mu\_{gi} - \mu\_{si} \right|\_w = \pi\_s \left| \mu\_{si} \right|\_w \tag{50}$$

It must be noted that, in this paper, the turbulent kinetic energy and turbulent dissipation rate near the pipe wall were defined zero.

## **4.2.3 Basic parameter in process of simulation**

Table 2 gave the basic parameter in process of numerical simulation

Table 2. Basic parameter used for simulation.

### **4.3 Numerical simulation process 4.3.1 Equation discretization**

386 Computational Simulations and Applications

*Y*

*l*

(46)

0.16 Re *s sDH I* (47)

(48)

(49)

(50)

*Y*

11.63

(45)

11.63

0.25 0.5

Where *ugi* stands for the gas velocity which is parallel to the pipe axis near the pipe wall.

*g y kCY* , *δy* is the distance between calculated nodes and pipe wall. *E*=9.793.

Homogeneous inlet conditions are set and the volume fraction of particles is given. The expressions of turbulent kinetic energy and turbulent dissipation rate are set as following.

> 3/2 3 2 3/4 , 2 *s s ss s k k uI C*

The assumption that the solid phase was the fully developed conditions of the pipe flow,

0 ,, *s s si s s*

To granule phase, the velocity doesn't agree with no-slip condition, thus the velocity value can't be equal to zero. According to particles collision near pipe wall research, the granule

> 12 1 0 *si si w i w u u hKn*

> > 1 , 2 1 *e e e*

h means the distance between the center point of the first control bulk and the pipe wall.  Boundary condition for solid phase Inlet boundary for solid

Outlet boundary for solid

Pipe wall surface

1/8

The solid velocity is set 4.3 m/s based on experiment data.

namely the normal derivative of the variables solved is zero.

phase normal velocity can be given as following.

is Knudsen number, which can be given as following.

 / 5.025.0

Where

where,

*w*

In this paper, Finite Volume Method was utilized to discrete the governing equations above. The selected pipe section was divided into many non-concurrent domains which was called calculating grid. And then, each nodal point of stationary divided domain and its controlled volume were confirmed. In the process of discretization, the physical quantity of this controlled volume were defined and stored in the determined nodal point.


**2. Incidence, prevalence and prognosis**

Although tachycardia-induced cardiomyopathy is considered to be a relatively rare instance, its precise incidence is not described well yet. In fact, this disease is very likely to be under‐ diagnosed in the clinical practice despite that the link between tachycardia and dilated cardiomyopathy pattern has been known for a long time [3-5]. One reason for its underesti‐ mation may be the uncertainty whether the detected tachycardia is the primary cause of the cardiomyopathy, or whether it is rather a consequence of cardiomyopathy of different origin.

Tachycardia-induced cardiomyopathy may develop at any age. It has been documented in fetuses with persistent supraventricular tachycardias [6], in children and adolescents [7] as well as in adults [8].

Virtually, any type of arrhythmia is capable of inducing ventricular dysfunction or cardiomy‐ opathy; however, supraventricular arrhythmias are the most commonly reported causes of tachycardia-induced cardiomyopathy. It has been predominanly described in association with atrial fibrillation, but other supraventricular arrhythmias may lead to this pathology too. Tachycardia-induced cardiomyopathy may also develop as a result of persistent ventricular tachycardia, rapid atrial and/or ventricular pacing or as a consequence of some extracardiac diseases that are associated with persistent tachycardia (Table 1). Importantly, it may also occur in patients with "only" frequent ventricular premature beats [9].

**Atrial fibrillation** (the most frequently reported arrhythmia associated with tachycardiainduced cardiomyopathy development) is a frequent type of supraventricular tachycardia

sion, congenital heart diseases or valvular diseases. Although tachycardia-induced cardiomy‐ opathy may be seen as secondary due to well-defined causal cardiovascular factor, this disorder ranks among cardiomyopathies also in the current definition and classification of

Tachycardia-induced cardiomyopathy is a disease with attributes of dilated cardiomyopathy that develop as a consequence of persistent tachycardia. It is characterized by systolic ventric‐ ular dysfunction and dilatation with heart failure symptoms that occur as a result of long-term tachycardia of either supraventricular or ventricular origin. This disease should be also considered as a cause of ventricular dysfunction in the absence of tachycardia at the time of patient presentation since the tachyarrhythmia could disappear spontaneously before the initiation of patient examination, while the hemodynamic and especially structural changes of the heart induced by long-term tachycardia may persist even weeks after arrhythmia

The key feature of tachycardia-induced cardiomyopathy is the reversibility of both functional and structural changes as soon as the heart rate/rhythm is well controlled. In such case, improvement or even complete functional and structural normalization may be found. A correct diagnosis is thus often stated retrospectively based on the observation of ventricular systolic function improvement and regression of ventricular dilatation after appropriate rate/

Although tachycardia-induced cardiomyopathy is considered to be a relatively rare instance, its precise incidence is not described well yet. In fact, this disease is very likely to be under‐ diagnosed in the clinical practice despite that the link between tachycardia and dilated cardiomyopathy pattern has been known for a long time [3-5]. One reason for its underesti‐ mation may be the uncertainty whether the detected tachycardia is the primary cause of the cardiomyopathy, or whether it is rather a consequence of cardiomyopathy of different origin. Tachycardia-induced cardiomyopathy may develop at any age. It has been documented in fetuses with persistent supraventricular tachycardias [6], in children and adolescents [7] as

Virtually, any type of arrhythmia is capable of inducing ventricular dysfunction or cardiomy‐ opathy; however, supraventricular arrhythmias are the most commonly reported causes of tachycardia-induced cardiomyopathy. It has been predominanly described in association with atrial fibrillation, but other supraventricular arrhythmias may lead to this pathology too. Tachycardia-induced cardiomyopathy may also develop as a result of persistent ventricular tachycardia, rapid atrial and/or ventricular pacing or as a consequence of some extracardiac diseases that are associated with persistent tachycardia (Table 1). Importantly, it may also occur

**Atrial fibrillation** (the most frequently reported arrhythmia associated with tachycardiainduced cardiomyopathy development) is a frequent type of supraventricular tachycardia

in patients with "only" frequent ventricular premature beats [9].

cardiomyopathies [1, 2].

76 Abnormal Heart Rhythms

rhythm control.

well as in adults [8].

disappearance and/or rate control achievement.

**2. Incidence, prevalence and prognosis**

**Table 1.** Disorders associated with tachycardia-induced cardiomyopathy development (adapted from [81])

in patients with dilated cardiomyopathy and heart failure. It appears that there is a close relationship between atrial fibrillation and heart failure: heart failure progression sup‐ ports electrical and structural remodeling of the heart, which finally leads to atrial fibrilla‐ tion development. On the other hand, epidemiological studies have demonstrated that patients with atrial fibrillation are at higher risk of heart failure [10] and that abnormal leftventricular systolic function is 2.5 times more likely in elderly patients (> 65 years) with atrial fibrillation than in those without this arrhythmia [11]. In addition, sinus rhythm restoration or adequate rate control of ongoing arrhythmia are associated with the improve‐ ment or even normalization of left-ventricular ejection fraction in some of these patients. These findings indicate that at least in some cases, left-ventricular dysfunction is primari‐ ly caused by rapid heart rate during atrial fibrillation rather than by preexisting dilated cardiomyopathy. Moreover, some studies indicate that approximately 25–50% of patients with atrial fibrillation, who simultaneously suffer from ventricular dysfunction, have some degree of tachycardia-induced cardiomyopathy [12, 13].

Another instance of tachyarrhythmia that used to be associated with a relatively higher prevalence of cardiomyopathy pattern is **atrial flutter**. Some observational studies indicated that left-ventricular systolic dysfunction is present in up to 25% of patients reported to atrial flutter ablation, and in more than half of these, it is possible to observe a significant improve‐ ment or even normalization of ejection fraction during the first twelve months after successful elimination of the tachycardia [14].

Prevalence of ventricular dysfunction is relatively high also in incessant **atrial tachycardia,** since it has been reported in approximately 10–19% of cases [15, 16]. It seems that children are more susceptible to tachycardia-induced cardiomyopathy than adults. Among adults, tachycardia-induced cardiomyopathy appears to be present more often in younger adult patients with persistent atrial tachycardia than in those of a higher age, although the lower prevalence in the older population may be partially caused by difficulties to distinguish the effect of tachycardia alone from that of the underlying heart disease with regard to the systolic ventricular function. Interestingly, elimination of the arrhytmia leads to the restoration of leftventricular function in up to 97% [16].

**Supraventricular reentrant tachycardias** (atrioventricular nodal reentry tachycardia (AVNRT) and atrioventricular reciprocating tachycardia (AVRT)) have usually only paroxys‐ mal nature. If persistent, these may also induce cardiomyopathy and heart failure that are reversible after catheter ablation [17-20].

**Ventricular tachycardias** are usually associated with some forms of underlying structural heart diseases. Therefore, it is difficult to distinguish whether and to what extent is the observed systolic ventricular dysfunction caused by the primary disease, and how much has persistent tachycardia contributed to its severity. This may be determined more precisely in patients with idiopathic ventricular tachycardias, which (if persistent or repetitive enough) may lead to cardiomyopathy. Restoration of normal systolic performance of the left ventricle has been described in patients with successful elimination of both right-ventricular outflow tract tachycardia [8] and left-ventricular outflow tract tachycardia [7].

However, cardiomyopathy with or without symptomatic heart failure may be present also in patients with "only" **frequent premature beats.** It has been described mainly in patients with frequent ventricular ectopy [9, 21-23], but high burden of atrial premature beats may also lead to reversible cardiomyopathy [24, 25]. A prospective multicenter study that included patients with reduced left-ventricular ejection fraction due to suspected ventricu‐ lar premature beat-associated cardiomyopathy has found that both systolic function and neurohumoral response (levels of natriuretic peptide) improve as soon as the ectopy is successfully eliminated and that the extent of improvement is comparable between patients with and without known structural heart disease [26]. These authors suggested that the higher the burden of ventricular premature beats (VPB), the higher the probability of systolic function improvement after ectopy elimination, with 13% baseline VPB burden being 100% sensitive and 85% specific to predict left-ventricular ejection fraction increase by ≥5% after elimination of the ectopic focus. Although not confirmed in all studies [26], some research‐ ers have also suggested that the QRS duration of VPB is an important factor in the development of cardiomyopathy, with wider QRS complexes more likely to lead to cardiomyopathy pattern with a lower total burden of PVBs [27, 28] and that epicardial origin of VPBs is also associated with delayed LV function recovery [29].

**Prognosis** of dilated cardiomyopathy may vary depending on the cause. Tachycardia-induced cardiomyopathy ranks among forms of dilated cardiomyopathy with (if treated appropriately) generally good prognoses. Although studies describing recovery of patients with tachycardiainduced cardiomyopathy after sinus rhythm restoration or rate control include only small samples of patients, it appears that these causal therapeutic options may result in an improve‐ ment of left-ventricular function, positive change in neurohumoral cascade (reduced levels of natriuretic peptides) [26] and that it is likely to be linked to a generally good prognosis of tachycardia-induced cardiomyopathy.

### **3. Pathogenesis**

prevalence in the older population may be partially caused by difficulties to distinguish the effect of tachycardia alone from that of the underlying heart disease with regard to the systolic ventricular function. Interestingly, elimination of the arrhytmia leads to the restoration of left-

**Supraventricular reentrant tachycardias** (atrioventricular nodal reentry tachycardia (AVNRT) and atrioventricular reciprocating tachycardia (AVRT)) have usually only paroxys‐ mal nature. If persistent, these may also induce cardiomyopathy and heart failure that are

**Ventricular tachycardias** are usually associated with some forms of underlying structural heart diseases. Therefore, it is difficult to distinguish whether and to what extent is the observed systolic ventricular dysfunction caused by the primary disease, and how much has persistent tachycardia contributed to its severity. This may be determined more precisely in patients with idiopathic ventricular tachycardias, which (if persistent or repetitive enough) may lead to cardiomyopathy. Restoration of normal systolic performance of the left ventricle has been described in patients with successful elimination of both right-ventricular outflow

However, cardiomyopathy with or without symptomatic heart failure may be present also in patients with "only" **frequent premature beats.** It has been described mainly in patients with frequent ventricular ectopy [9, 21-23], but high burden of atrial premature beats may also lead to reversible cardiomyopathy [24, 25]. A prospective multicenter study that included patients with reduced left-ventricular ejection fraction due to suspected ventricu‐ lar premature beat-associated cardiomyopathy has found that both systolic function and neurohumoral response (levels of natriuretic peptide) improve as soon as the ectopy is successfully eliminated and that the extent of improvement is comparable between patients with and without known structural heart disease [26]. These authors suggested that the higher the burden of ventricular premature beats (VPB), the higher the probability of systolic function improvement after ectopy elimination, with 13% baseline VPB burden being 100% sensitive and 85% specific to predict left-ventricular ejection fraction increase by ≥5% after elimination of the ectopic focus. Although not confirmed in all studies [26], some research‐ ers have also suggested that the QRS duration of VPB is an important factor in the development of cardiomyopathy, with wider QRS complexes more likely to lead to cardiomyopathy pattern with a lower total burden of PVBs [27, 28] and that epicardial

tract tachycardia [8] and left-ventricular outflow tract tachycardia [7].

origin of VPBs is also associated with delayed LV function recovery [29].

**Prognosis** of dilated cardiomyopathy may vary depending on the cause. Tachycardia-induced cardiomyopathy ranks among forms of dilated cardiomyopathy with (if treated appropriately) generally good prognoses. Although studies describing recovery of patients with tachycardiainduced cardiomyopathy after sinus rhythm restoration or rate control include only small samples of patients, it appears that these causal therapeutic options may result in an improve‐ ment of left-ventricular function, positive change in neurohumoral cascade (reduced levels of natriuretic peptides) [26] and that it is likely to be linked to a generally good prognosis of

ventricular function in up to 97% [16].

78 Abnormal Heart Rhythms

reversible after catheter ablation [17-20].

tachycardia-induced cardiomyopathy.

Our current knowledge about the pathogenesis of tachycardia-induced cardiomyopathy is predominantly based on animal models that have been introduced to study heart failure [30-35]. In these experiments, heart failure is induced by rapid cardiac pacing of certain duration, at the atrial and/or ventricular level. Hemodynamic changes that result from such pacing strongly resemble findings in humans [31-35]. Similar abnormalities have been also identified in animals with "only" ventricular premature beats delivered artificially in bigemi‐ nal pattern, and these changes are reminiscent of those in humans as well [36]. Observations proving that all these alterations are fully or at least partially reversible with cessation of tachycardia also correspond with results found in humans [32, 37].

**Figure 1.** Tachycardia-induced cardiomyopathy in a 38-years old male with no previous history of any heart disease or arrhythmia. First episode of persistent atrial fibrillation with rapid heart rate (1a, 1b) in his life caused progressive de‐ terioration of ventricular systolic function leading to clinical manifestation of heart failure during 4 weeks. 1c shows significantly reduced ejection fraction of the left ventricle with its incipient enlargement during the tachycardia. Both heart failure symptoms and left-ventricular systolic function rapidly improved during the following 3 weeks after si‐ nus rhythm restoration (2a). Size and systolic function of the left ventricle then almost normalized in the horizon of 3 months after the tachycardia termination (2b).

#### **3.1. Hemodynamic changes**

Rapid atrial or ventricular pacing in experimental models leads to biventricular systolic and diastolic dysfunctions that occur relatively early after the onset of tachycardia [38, 39]. Typical findings include reduced systolic function of both ventricles reaching up to 55%, decline in cardiac output, elevation of ventricular filling pressures, systemic vascular resistance as well as ventricular systolic wall stress [33-35, 40, 41]. Systolic ventricular dysfunction is caused by the loss of contractility. In addition, contractile reserve in response to volume, inotropic agents or post-extrasystolic potentiation is affected [42, 43] and myocardial relaxation is impaired [44]. As a consequence of altered hemodynamic situation, mitral regurgitation may develop in longer-term perspective that leads to volume overload of the failing heart [45].

#### **3.2. Structural changes**

Persistent tachycardia, either induced artificially by chronic cardiac pacing or resulting from persistent tachyarrhythmia, finally leads to the dilatation of all cardiac chambers. Left ventricle increases both its end-systolic and end-diastolic volume (with end-systolic volume being affected more [33, 34]) and it further changes its geometry to a spherical shape [46]. This dilatation is usually associated with wall thinning or preservation of wall thickness without either increased heart weight or hypertrophy [45, 46].

On microscopical level, remodeling of both cardiomyocytes and extracellular matrix may be detected: disruptions of sarcolemma-basement membrane interface, myofibrillar misalign‐ ment, cellular elongation and myocyte loss (up to 39% of the total myocyte mass) have been found [40, 47, 48]. Architecture of the extracellular matrix is usually remarkably modified as well and this also contributes to myocyte misalignment and adversely affects force coupling and transmission.

In addition to functional and structural changes, electrophysiologic remodeling has been documented. Abnormal functioning of calcium channels, stretch-sensitive channel dysfunc‐ tion and other abnormalities often affect and prolong repolarization that can finally result in ventricular tachycardias manifestation [49].

#### **3.3. Neurohumoral changes**

Similar to other forms of heart failure, marked neurohumoral activation occurs and leads to elevated plasma levels of natriuretic peptides, epinephrine, norepinephrine, aldosterone and renin activity [39]. Downregulation of beta-1 receptor density with the resulting decrease in beta-adrenergic responsiveness have been found as well [50, 51].

All the above-mentioned hemodynamic, structural and neurohumoral changes have been demonstrated also in humans, which supports the conclusion that pacing-induced model of heart failure could be a useful tool to study pathogenesis of tachycardia-induced cardiomyopathy.

#### **3.4. Pathophysiology of tachycardia-induced cardiomyopathy**

**3.1. Hemodynamic changes**

80 Abnormal Heart Rhythms

**3.2. Structural changes**

and transmission.

cardiomyopathy.

Rapid atrial or ventricular pacing in experimental models leads to biventricular systolic and diastolic dysfunctions that occur relatively early after the onset of tachycardia [38, 39]. Typical findings include reduced systolic function of both ventricles reaching up to 55%, decline in cardiac output, elevation of ventricular filling pressures, systemic vascular resistance as well as ventricular systolic wall stress [33-35, 40, 41]. Systolic ventricular dysfunction is caused by the loss of contractility. In addition, contractile reserve in response to volume, inotropic agents or post-extrasystolic potentiation is affected [42, 43] and myocardial relaxation is impaired [44]. As a consequence of altered hemodynamic situation, mitral regurgitation may develop in

Persistent tachycardia, either induced artificially by chronic cardiac pacing or resulting from persistent tachyarrhythmia, finally leads to the dilatation of all cardiac chambers. Left ventricle increases both its end-systolic and end-diastolic volume (with end-systolic volume being affected more [33, 34]) and it further changes its geometry to a spherical shape [46]. This dilatation is usually associated with wall thinning or preservation of wall thickness without

On microscopical level, remodeling of both cardiomyocytes and extracellular matrix may be detected: disruptions of sarcolemma-basement membrane interface, myofibrillar misalign‐ ment, cellular elongation and myocyte loss (up to 39% of the total myocyte mass) have been found [40, 47, 48]. Architecture of the extracellular matrix is usually remarkably modified as well and this also contributes to myocyte misalignment and adversely affects force coupling

In addition to functional and structural changes, electrophysiologic remodeling has been documented. Abnormal functioning of calcium channels, stretch-sensitive channel dysfunc‐ tion and other abnormalities often affect and prolong repolarization that can finally result in

Similar to other forms of heart failure, marked neurohumoral activation occurs and leads to elevated plasma levels of natriuretic peptides, epinephrine, norepinephrine, aldosterone and renin activity [39]. Downregulation of beta-1 receptor density with the resulting decrease in

All the above-mentioned hemodynamic, structural and neurohumoral changes have been demonstrated also in humans, which supports the conclusion that pacing-induced model of heart failure could be a useful tool to study pathogenesis of tachycardia-induced

longer-term perspective that leads to volume overload of the failing heart [45].

either increased heart weight or hypertrophy [45, 46].

ventricular tachycardias manifestation [49].

beta-adrenergic responsiveness have been found as well [50, 51].

**3.3. Neurohumoral changes**

The development of tachycardia-induced myocardial dysfunction appears to be a result of multiple factors. Various alternations of neurohumoral and cellular activation have been identified; however, it is still uncertain whether they represent the causal factor of the functional and subsequent structural changes in all cases, or whether they are rather a consequence of tachycardia. Although the precise mechanism behind contractile dysfunc‐ tion with the resulting structural changes is not fully understood yet, the research has focused mainly on three potential factors: *1) depletion of high-energy stores in the myocardi‐ um with impaired energy utilization, 2) myocardial ischemia and 3) abnormality in calcium handling*.

On subcellular level, persistent tachycardia leads to energy-stores depletion, which is associated with the reduction of adenosin-triphosphate (ATP), phosphocreatinine and creatinine levels in the myocardium. In addition, a reduced activity of the Na/K-ATPase pump has been described [52, 53a, 53b]. It is very likely due to enhanced activity of Krebs cycle oxidative enzymes and mitochondrial injury [40, 41].

Similar findings have been described in the case of myocardial ischemia. In the ischemic model, rapid depletion of energy-stores and left-ventricular dysfunction occur shortly after vessel occlusion [54]. However, their return to normal values lasts mostly about days long after the ischemic attack, which also corresponds with findings in tachycardia-induced cardiomyop‐ athy where altered hemodynamic and structural changes resolve in prolonged time interval. Proceeding from these facts, myocardial ischemia is considered to be a potential factor that contributes to the tachycardia-induced cardiomyopathy development. In fact, abnormal coronary flow and changed ratios of subendocardial and subepicardial flow have been observed in tachycardia-induced cardiomyopathy [55, 56].

The hypothesis that abnormal handling of calcium plays a role in the genesis of tachycardiainduced cardiomyopathy has received substantial support, because the severity of calcium cycling abnormalities has been shown to correlate with the extent of ventricular dysfunction [41]. Abnormal calcium handling occurs already in the first 24 hours of rapid cardiac pacing and it may persist for more than 4 weeks after tachycardia termination [41]. Altered functions of calcium channels and transport system of the sarcoplasmatic reticulum have been identified [41, 57] and they may thus contribute to myocardial dysfunction observed in tachycardiainduced cardiomyopathy due to lower calcium availability to myocytes with the resulting contractility reduction. Some other studies suggest altered calcium-sensitivity and excitationcontraction coupling [57, 58].

An observation that tachycardia-induced cardiomyopathy does not evolve in every patient with the same type, duration and rate of a tachycardia implies *possible genetic predisposition* of some patients to develop a dilated cardiomyopathy pattern during tachycardia. In fact, one study [59] suggests that polymorphism in angiotensin-converting enzyme (ACE) gene may be involved, since one type of such polymorphism (which is associated with higher serum levels of ACE) is more frequently linked to idiopathic and ischemic cardiomyopathy manifestation. Looking at the prevalence of this polymorphism among 20 patients with tachycardia-induced cardiomyopathy as compared to another sample of 20 patients without this pattern, the authors reported a higher detection of this ACE polymorphism in the cardiomyopathic group [59].

#### **3.5. Course of the changes over time and their reversibility**

Experimental studies demonstrate that changes of hemodynamics with the reduction of cardiac output or altered systemic arterial pressure occur already in the first 24 hours of rapid pacing [32]. When continued, fast cardiac pacing then induces an elevation of ventricular filling pressures, pulmonary artery pressure and a decrease of systemic arterial pressure that reach certain plateau after one week, while cardiac output, volumes and ejection fraction deteriorate continually for 3–5 weeks with the final end-stage heart failure development [35, 45].

Cessation of tachycardia results in a resolution of these changes: in the first 48 hours after termination of cardiac pacing, a significant improvement of cardiac output, systemic vascular resistance, mean arterial pressure and filling pressures are present [39]. Left-ventricular ejection fraction also improves dramatically and normalizes within 1–2 weeks [39]. All hemodynamic variables normalize within the horizon of four weeks after tachycardia inter‐ ruption, but diastolic dysfunction remains detectable even after the first month period. Importantly, elevated end-diastolic and end-systolic volumes are still present after twelve weeks of pacing discontinuation, which is consistent with substantial ventricular remodeling [33, 46], that requires longer time for its resolution.

Although the hallmark of tachycardia-induced cardiomyopathy is an improvement or even normalization of cardiac function and size with the resulting disappearance of heart failure symptoms after cessation of tachycardia or rate control achievement, there is growing evidence that the ultrastructural abnormalities of the myocardium and residual contractility dysfunc‐ tion may persist. This has already been suggested in the experimental studies [53b], but similar conclusions have also been made in clinical observational reports [60, 61]. In one of these studies, ventricular function has been assessed using specle tracking and contrast-enhanced MRI with ventricular T1 mapping used as an index of diffuse fibrosis. Although the ejection fraction normalized three months after a successful ablation of initial tachycardia already, it has been possible to detect a somewhat greater indexed end-diastolic and end-systolic volume of the left ventricle in patients with tachycardia-induced cardiomyopathy as compared to healthy controls. Moreover, patients with previous tachycardia-induced cardiomyopathy have demonstrated reduced global left-ventricular corrected T1 time that implies a diffuse fibrosis [61]. In addition, another study [60] suggests that tachycardia tends to recur in some patients initially diagnosed with tachycardia-induced cardiomyopathy pattern and this recurrence of arrhythmia leads to a new decline of systolic ventricular function. Moreover, sudden death may occur in some of these patients despite normal or almost normal systolic function during the last evaluation [60].


**3. Clinical trials on effectiveness of preprandial complementary (= supplementary) insulin boluses in T2D**

Disturbed dynamics of insulin secretion in T2D (**Figure 10**) makes the need of small complementary preprandial boluses of rapid insulin understandable. In the years 1991–2019 we carried out three single centre trials to this topic.

### **3.1 Trial on effectiveness of rapid insulin**

In 1991–1994, a nonrandomized uncontrolled study with 251 T2D assessed the effectiveness of supplementary insulin regimen [40, 41] The complementary insulin therapy using insulin pen MADI started in hospital following the baseline PG profile on day 2. The final ten-point PG profile was performed on day 4. (**Figures 11** and **12**) At a check-up 8–10 weeks later a decrease of HbA1c, BMI and improved lipoprotein-spectrum was found (**Figures 13** and **14**).

We concluded that in T2D better metabolic control can be achieved with complementary insulin therapy than with oral antidiabetic drugs or long-acting insulin 1–2 times daily. Our "surprising" results were based on pathophysiologic concept of Bruns, Berger and Kalfhaus. [7–9] To date, intensive insulin therapy in people with T2D appears to be more accepted in daily routine. [6, 23]

#### **Figure 10.**

*Dynamics of insulin secretion in blood in healthy people (initial postprandial peak is present, insulin concentration returns to baseline within 3 h); in T2D (missing Initial peak, maximum is delayed and hyperinsulinaemia remains over 3 h) [7] (1995).*

*Type 2 Diabetes - From Pathophysiology to Cyber Systems*

the switch back to SMPG. (**Figure 9**).

*Benefits of CGM in individuals on insulin pump [36] (2013).*

**Figure 9.**

*(2005–2009)*

control in T1D in everyday practice settings.

implementation of CGM in perioperative care of T2D.

In the CGM group (but not in the SMPG group) HbA1c significantly dropped within one month and remained reduced as long as the CGM was applied, i.e., until

regular part of treatment in educated persons on insulin pumps.

a suitable alternative to CGM augmented insulin pump therapy.

*<IP_ADDRESS> Multicenter trial on CGM-augmented insulin pump therapy in T1D*

benefits of CGM-augmented insulin pump therapy for persons with T1D. Community or academic practices in six Central and Eastern European/ Mediterranean countries established a registry of people with T1D starting CGMaugmented insulin pump therapy with the pump PARADIGM® X22 under everyday conditions. We compared HbA1c values before and after 3 months of CGM and assessed relationships between insulin therapy and glycaemia-related variables. Sensor data and HbA1c data were evaluated in 85 of 102 enrolled persons with longstanding T1D, mean age 33.2 ± 16.9 years. Mean HbA1c declined after 3 months of CGM from 59.0 ± 8.9 mmol/mol at baseline to 50.9 ± 11.7 mmol/mol

*<IP_ADDRESS> The trial for CGM benefits in perioperative care (2009–2013)*

The multicenter CGM study (2005–2009) [38] aimed to the assessment of

Hence, CGM-augmented insulin pump therapy appeared to improve glycaemic

Our third CGM study (2009–2013) [39] payed attention to the assessment of

Hence, continuous glucose monitoring with transcutaneous sensors appeared to be an important measure for improving metabolic compensation in people with diabetes. With CGM, the evolution of HbA1c showed metabolic improvement. The PARASEN study demonstrated that continuous self-monitoring should become a

Several years later, the COMISAIR study [37] demonstrated that also a conventional intensive multiple dose insulin regimen (MDI), if supported by CGM, can be

**10**

(P < 0.001).

#### **Figure 11.**

*Ten- point BG profiles (mean ± SE) in insulin-naïve-T2D treated on baseline with oral antidiabetic drugs and/ or diet (upper curve) and then with complementary boluses (4 to 6 U each = 26 U/d) of rapid insulin (lower curve) \*P < 0,05. [40] (1997).*

#### **Figure 12.**

*Ten- point BG profiles (mmol/l, mean ± SE) in T2D treated on baseline with long-acting insulin (1 to 2 boluses/d = 47 U/d) and/or diet and then with complementary boluses (4 to 6 U each = 32 U/d) of rapid insulin (lower curve) \*P < 0,05. [40] (1997).*

#### **Figure 13.**

*Lipoprotein apoLpA1 at baseline and after 8–10 weeks of complementary insulin therapy [41] (1997).*

**13**

**Figure 15.**

*with T2D (\* P < 0,05) [44] (2007).*

*Pathophysiologic Approach to Type 2 Diabetes Management: One Centre Experience 1980–2020*

**3.2 Trial on effectiveness of complementary boluses of rapid insulin analog**

*Lipoprotein apo LpB at baseline and after 8–10 weeks of complementary insulin therapy [41] (1997).*

the end of the 20th century.  Their treatment with human regular insulin lasted 5.2 ± 0.44 years. Human regular insulin was replaced with insulin analog aspart. Two check-ups in the course of 330 ± 11.1- day sequential period were carried out. The control group consisted of

Following the switch from human regular insulin to insulin analog aspart,

*Impact of insulin aspart (given according the same algorhithms as human insulin) on HbA1c in 57 persons*

17 persons of equivalent age, duration of diabetes and insulin dosing.

HbA1c concentration in blood decreased **Figure 15**, while plasma glucose

*DOI: http://dx.doi.org/10.5772/intechopen.96237*

human insulin. [42, 43]

**Figure 14.**

according to identical algorithms.

*Pathophysiologic Approach to Type 2 Diabetes Management: One Centre Experience 1980–2020 DOI: http://dx.doi.org/10.5772/intechopen.96237*

#### **Figure 14.**

*Type 2 Diabetes - From Pathophysiology to Cyber Systems*

*Ten- point BG profiles (mmol/l, mean ± SE) in T2D treated on baseline with long-acting insulin (1 to 2 boluses/d = 47 U/d) and/or diet and then with complementary boluses (4 to 6 U each = 32 U/d) of rapid insulin*

*Ten- point BG profiles (mean ± SE) in insulin-naïve-T2D treated on baseline with oral antidiabetic drugs and/ or diet (upper curve) and then with complementary boluses (4 to 6 U each = 26 U/d) of rapid insulin (lower*

*Lipoprotein apoLpA1 at baseline and after 8–10 weeks of complementary insulin therapy [41] (1997).*

**12**

**Figure 13.**

**Figure 12.**

**Figure 11.**

*curve) \*P < 0,05. [40] (1997).*

*(lower curve) \*P < 0,05. [40] (1997).*

*Lipoprotein apo LpB at baseline and after 8–10 weeks of complementary insulin therapy [41] (1997).*

#### **3.2 Trial on effectiveness of complementary boluses of rapid insulin analog**

The rapid acting insulin anologs (aspart, lispro and glulisin) are available since the end of the 20th century. Their absorption rates prevail over that of regular human insulin. [42, 43]

The aim of our prospective observational open-label controlled study (2004– 2007) [44] was to compare the effects of insulin analog aspart and human regular insulin resulting from their routine administration in small preprandial boluses according to identical algorithms.

Fifty-seven persons with T2D aged 64.0 ± 1.29 (mean ± SE) years, diabetes duration of 12.4 ± 1.06 years, C-peptide positive, were enrolled into the study. Their treatment with human regular insulin lasted 5.2 ± 0.44 years. Human regular insulin was replaced with insulin analog aspart. Two check-ups in the course of 330 ± 11.1- day sequential period were carried out. The control group consisted of 17 persons of equivalent age, duration of diabetes and insulin dosing.

Following the switch from human regular insulin to insulin analog aspart, HbA1c concentration in blood decreased **Figure 15**, while plasma glucose

#### **Figure 15.**

*Impact of insulin aspart (given according the same algorhithms as human insulin) on HbA1c in 57 persons with T2D (\* P < 0,05) [44] (2007).*

concentrations in 10-point profiles, daily insulin dose, BMI, and frequency of hypo−/hyperglycemic episodes did not change.

No significant influence of insulin aspart on serum concentrations of triacylglycerols, total cholesterol, and LDL-cholesterol was found. Patients' satisfaction was good. No adverse events were recorded. In the control group, no significant changes of baseline HbA1c, insulin dose and BMI were found.

Hence, insulin analog aspart appears to be more effective than human regular insulin in intensive (complementary) treatment in individuals with T2D.

#### **3.3 Trial on effectiveness of Faster (ultrarapid) Insulin ASPart (FIASP)**

The benefits of faster insulin aspart (insulin aspart + nicotinamid) were described and discussed. [45, 46]

Aim of our prospective monocentric uncontrolled Real World Evidence study (2017–2019) [47] was to compare the efficacy of FIASP with the efficacy of previous therapy with insulin aspart in people with T1D and T2D on MDI or on insulin pump.

No adverse events appeared in any group. In T2D groups (N < 24) an unsignificant tendency to reduction of PG, MPG, HbA1c, body mass and total daily dose of insulin in the course of FIASP therapy was shown.

So, only the evidence of noninferiority of FIASP versus insulin aspart was demonstrated. Introduction of improved algorithms together with intensive patients´ education appears necessary to improve the expected outcomes of FIASP therapeutic regimen.


**7. Infection control measures**

Prevention of infection by following strict infection control measures is an essential aspect of clinical care. In cupping therapy, such measures are of paramount importance since the therapy necessitates direct contact with the skin and body fluids. Several infection control measures should be considered. These measures include hand hygiene and washing, and wearing personal protective equipment like gloves, masks, protective eyewear and gowns. Disinfection of the patient's skin with approved disinfectants is required before starting the procedure. Also, disinfection of the patient's bed or use of disposable bed covers is needed. It is recommended to use disposable cups, vacuum pumps, and surgical blades to avoid cross-transmission of infection. Lastly, adhering to proper medical waste segregation system is crucial [63, 64].

#### **Table 1.**

*Contraindications to cupping therapy (adapted from Ahmedi* et al *[5]).*