PLZEŇSKÝ LÉKAŘSKÝ SBORNÍK PILSEN MEDICAL REPORT 80. SVAZEK

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PLZEŇSKÝ LÉKAŘSKÝ SBORNÍK

PILSEN MEDICAL REPORT

80. SVAZEK

UNIVERZITA KARLOVA V PRAZE NAKLADATELSTVÍ KAROLINUM

LÉKAŘSKÁ FAKULTA UNIVERZITY KARLOVY V PLZNI 2015

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OBSAH

J. Kobr, J. Framuth, L. Šašek, R. Hrdlička, J. Racek, K. Pizingerová:

Hemodynamické změny u dětí s hyperkapnickým respiračním selháním

v průběhu RSV infekce . . . 9 M. Casova, R. Kučera, S. Svobodová, J. Presl, O. Topolčan,

Z. Novotný, J. Windrichová, R. Fuchsová, L. Betincová:

HE4 v porovnání s ostatními biomarkery v diagnóze rakoviny vaječníku . . . 21 P. Sobotka:

Metabolismus a elektrogeneze mozku u fenylketonurie . . . 27 I. Khadang, P. Fiala, V. Křiklán, P. Chacon Gil:

Vena cava inferior duplex – kazuistika . . . 31 J. Kotyza:

Prognostická hodnota solubilní intercelulární adhezní molekuly-1 (sICAM-1)

v tělních tekutinách onkologických pacientů . . . 37 Z. Houdek:

Myší modely spinocerebelární ataxie typu 2 . . . 45 P. Sobotka:

EEG nálezy u pracovníků exponovaných akrylátům . . . 51 J. Cibulková:

Poruchy placentace – placenta percreta s následnou hysterektomií

po porodu – kazuistika . . . 57 A. Bartáková, J. Presl, P. Vlasák, Z. Novotný, J. Bouda:

Nádorové kmenové buňky – možnost cílené terapie karcinomu ovaria? . . . 63 P. Vlasák, J. Presl, J. Bouda, A. Bartáková, Z. Novotný, O. Topolčan:

Předoperační diagnostika ovariálních nádorů a management pacientek

s primárně inoperabilním maligním nádorem vaječníku . . . 67 P. Sobotka, V. Matoušek, J. Berger:

Creutzfeldt-Jakobova nemoc . . . 81 D. Slouka:

Zkušenosti s laserovou operativou na ORL klinice FN a LF UK v Plzni . . . 85

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J. Novák, O. Topolčan, J. Šmejkal, R. Fuchsová:

Problém dostatečné saturace vitaminu D ve sportu . . . 91

J. Šmejkal, V. Zeman, J. Novák, O. Topolčan: Výskyt a počítačová objektivizace svalových dysbalancí u nespecifických bolestí zad . . . 99

R. Pomahačová: Současný stav léčby poruch růstu . . . 107

M. Chottová-Dvořáková, J. Slavíková: Nervová regulace srdce. Funkční význam neadrenergní necholinergní inervace . . . . 113

J. Švíglerová, J. Kuncová, M. Štengl: Kardiovaskulární systém a pohlavní rozdíly . . . 125

H. Rosolová: Preventivní kardiologie v posledních 25 letech . . . 129

F. Vožeh: Elektromagnetická pole jako možný patogenetický činitel . . . 137

O. Dolejšová, J. Kouba: Vezikoureterální reflux . . . 147

Ze života fakulty Opustil nás primář MUDr. Jiří Jeschke, CSc. (1926–2013) . . . 153

In memory prof. MUDr. et RNDr. Jaroslav Slípka, DrSc. (1926–2013) . . . 155

Významné životní jubileum prof. MUDr. Hany Rosolové . . . 157

Zemřel prof. MUDr. Jiří Šolc, CSc. (1929–2014) . . . 160

Vzpomínka na doc. MUDr. Helenu Zavázalovou, CSc. . . . 162

Bibliografie vědeckých prací ústavů a klinik Lékařské fakulty UK v Plzni za rok 2013 . . . 164

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HEMODYNAMICS CHANGES IN CHILDREN WITH HYPERCAPNIC RESPIRATORY FAILURE

DURING RESPIRATORY SYNCYTIAL VIRUS INFECTION J. Kobr

¹

, J. Fremuth

¹

, L. Šašek

¹

, R. Hrdlička

¹

, J. Racek

²

, K. Pizingerová

1 Department of Paediatrics -PICU

2 Department of Clinical Biochemistry and Hematology, Medical Faculty, Charles University, Pilsen

Acute bronchiolitis associated with Respiratory Syncytial Virus (RSV) infection is an example of progressive hypercapnic hypoventilation. Acute bronchiolitis is the most difficult course of the disease, and lower airways’ obstruction is difficult to control (1, 2).

Typical symptoms are progressive tachypnoea, grunting, chest retraction, increased dif- ficulty in breathing, hypoventilation, and mixed dyspnoea, all of which are resistant to bronchodilatory or anti-inflammatory therapy (3). Increased airway resistance causes parallel hyperinflation and alveoli consolidation. These pulmonary pathophysiological changes are a source of such complications as pneumonia, fluidothorax, and others (4, 5).

Severe pulmonary pathology causes cardiopulmonary interaction that has an adverse impact on blood circulation. The consequences of such interaction are right ventricle pressure overload, a reduction in pulmonary flow, and a decrease in cardiac output. This situation has caused complications and limits the possibilities of conventional ventilation (6).

Effective protection against this serious infection is not reliable. Active immunization is not possible for multiple RSV genome polymorphisms. Continuous immunoprophylaxis with monoclonal antibodies or antiviral therapy also has not produced the expected results (7, 8).

A reliable, effective treatment can be addressed only by the consequences of RSV infection. Our research was motivated by clinical experience.

PATIENTS AND METHODS

Inclusion criteria of this study confirmed RSV infection, acute hypercapnic respiratory failure, a predicted Pediatric Risk Index Scoring of Mortality (PRISM) of more than 10 points, and a Lung Injury Score (LIS) above 1.0 point (9, 10). Exclusion criteria included an end of mechanical ventilation within 48 hours of initiation.

The study population was divided into two groups according to severity of the pulmonary affection. Group A included at-risk patients with PRISM values of more than 20 points and LIS above 1.5 points. Children without risk and with PRISM values from 10 to 19 points and LIS from 1.0 to 1.4 points were placed in Group B.

For rapid diagnosis of the active RSV infection, the Rapid-VIDI test was used (www.

vidia .cz). PCR RNA of RSV isolation of real-time and KFR RSV antibodies were used for a definitive laboratory diagnosis.

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After the patients’ admission to the Pediatric Intensive Care Unit (PICU), basic input information was obtained. Standard examinations, such as a chest X-ray, an ECG, transthoracic echocardiography, microbiological analysis of tracheal aspirate, and biochemical analysis of blood and urine, complemented anamnesis and clinical examinations. The ECG waveform, respiratory/breath rate (RR/BR; breath/min), heart rate (HR; beat/min), mean central venous pressure (CVP; mmHg), systolic (SBP; mmHg), mean (MAP; mmHg) and diastolic arterial blood pressure (DBP; mmHg), pulse oximetry (SpO₂; %), core temperature (°C) by bedside monitoring system (Diascope G2; USA), and urine output (UO; ml/kg/h) were monitored continuously.

Study protocol and data collection

Data in the study were recorded after recovery, i.e., one hour after the introduction (time- 1), and, subsequently, after 24 hours and 48 hours of comprehensive treatment (time-2 and time-3), for statistical evaluation.

Conventional mechanical ventilation was conducted, based on the protective princi- ple, by positive pressure mode (Evita-4, Dräger Medical; Germany or Avea, Bird Viasys Healthcare, Care Fusion; USA). Unconventional forms of ventilation used were high-fre- quency oscillatory ventilation (SensorMedics 3100A, Viasys Healthcare; the Netherlands);

exogenous surfactant replacement therapy (Curosurf, Chiesi Farmaceutici, S.p.A.; Parma, Italy); inhalation of nitric oxide (Pulmonox-Mini NO, Messer Griesheim; Austria); prone position ventilation, and tracheal gas insufflation (11).

The study collected the data with the following parameters: alveolar-arterial oxygen difference (AaDO₂; kPa), arterial-alveolar oxygen difference (a/ADO₂; kPa), hypoxic ratio (PaO₂/FiO₂; mmHg), oxygenation index (OI; –), ventilation index (VI; –), dead space- to-tidal volume ratio (V_D/V_T; %), dynamic lung compliance (C_dyn; ml/cmH₂O/kg), and dynamic airway resistance (R_aw; cmH₂O/l/s). These parameters were calculated to assess the quality of ventilation.

Hemodynamics was monitored by noninvasive techniques. The ultrasound cardiac output monitor (USCOM; Spacelabs Healthcare; Australia) is a device that converts a real-time continuous Doppler signal from the transthoracic probe (2.2 MHz) to a pulse waveform.

From the left, the parasternal approach displays on the screen USMOM a pulse waveform from pulmonary annulus; the suprasternal approach shows an aortic pulse waveform. The pulse waves are analyzed beat-to-beat to obtain hemodynamic parameters. In the study, we collected data with the following parameters: stroke volume (SV; ml), stroke volume index (SVI; ml/m²), stroke volume variation (SVV; %), stroke work (SW; mJ), peak velocity of flow (Vpk; m/s), velocity time integral (Vti; cm), flow time (FT; ms), flow time corrected (FTc; ms), ejection time percent (ET%; %), pulmonary vascular resistance (PVR; dyn.sec/cm⁵), pulmonary vascular resistance index (PVRI; dyn.sec/cm⁵/m²), systemic vascular resistance (SVR; dyn.sec/cm⁵), systemic vascular resistance index (SVRI; dyn.sec/cm⁵/m²), mean pressure gradient (Pmn; mmHg), minute distance (MD; m/min.), cardiac output (CO; l/min.), cardiac index (CI; l/min/m²), and cardiac power output (CPO; W) (12).

On the basis of current and real-time information on hemodynamics, a strategy was chosen of pharmacological support of circulation by the following means: vasoactive (noradrenalin 0.01–0.25 mikrog/kg/min. intravenously), inotropes support (dobutamine 3.0–8.0 mikrog/kg/min.

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intravenously), ino-vasodilatation (milrinone 0.35–0.75 microg/kg/min. intravenously), selective vasodilatation (inhaled nitric oxide; INO 30–40 ppm; Pulmonox-Mini NO, Messer Griesheim; Austria), and nonselective vasodilatation (sildenafil 1.0–2.0 mg/kg/day enterally). Treatment was accompanied by fluid management, nutrition, analgosedation (sufentanil 0.8–1.3 microg/kg/hr with midazolam 0.2–0.3 mg/kg/hr) intravenously, and inhalations of 3% sodium chloride solution. Antibiotics were used causally according to the results of a microbiological analysis of tracheal aspirate. Pleural and pericardial fluid collections were drained under general anesthesia and ultrasonographic navigation (Vygon, SA; France and Arrow ECS; Czech Republic). Permanent suction was used in a closed system (Atrium Ocean, Mediform; Czech Republic) for complete evacuation.

Statistical analysis

All data were presented as a mean with a standard deviation (mean ± SD). For analysis, a student’s t-test, a distribution-free Wilcoxon’s test, and a two-way ANOVA test were applied. Levels of statistical significance of P < 0.05 were accepted. The data were analyzed using Statistica® software (StatSoft; Tulsa, Oklahoma, U.S.A.).

Ethical consideration

This study was preformed according principles of the Declaration of Helsinki. The study protocol was approved by the Ethics Committee of the Faculty of Medicine in Pilsen, Czech Republic.

RESULTS

In total, from 2008 to 2012, 324 children were admitted to our PICU for respiratory insufficiency heterogeneous etiology. Only 58 children (18%) met the inclusion criteria of the study. The clinical and complementary characteristics of the study cohorts, on admission, in both groups are listed in (Tab. 1).

Tab. 1 The input characteristics of the study population on admission to the PICU

Characteristics Group A

N = 28 Group B

N = 30 Values

P<

AgeYears; mean ± SD 0.76 ± 0.42 1.30 ± 0.34 0 .05

Male/female

N 13 / 15 12 / 17 NS

Body weight

Kg; mean ± SD 8.92 ± 5.04 9.05 ± 6.01 NS

Risk factors

N (%) 18 (64) 8 (27) 0 .05

Immunoprophylaxis

N (%) 6 (21) 1 (3) 0 .01

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Characteristics Group A

N = 28 Group B

N = 30 Values

P<

Treatment before admission

Days; mean ± SD 6.23 ± 1.16 3.07 ± 1.07 0 .05

Complications

N (%) 10 (36) 1 (3) 0 .01

PRISM

Points; mean ± SD 20.73 ± 2.25 12.06 ± 1.14 0 .01

LISPoints; mean ± SD 2.57 ± 0.38 1.35 ± 0.17 0 .01

PaO₂/FiO₂

Torr; mean ± SD 196.60 ± 53.43 285.78 ± 50.33 0 .01

MAPmmHg; mean ± SD 58.81 ± 7.22 64.17 ± 7.64 NS

Risk factors in group A represented the seven times low age, six times congenital heart defect with left-to-right shunt, seven times bronchopulmonary dysplasia premature and twice children with a genetic abnormality defect and hypoxic encephalopathy. Group B had only a potential risks, such as the five families of smokers and three families with low socio-economic standard.

Life-threatening complications in Group A consisted of seven times more acute respiratory distress syndrome with the multiple organ dysfunction syndromes, six times more unilateral fluidothorax, and one exudative pericarditis. Group B had only one parainfec- tious fluidothorax.

Transthoracic echocardiography at 6-month girl with exudative pericarditis cased by RSV infection is shown in (Fig. 1).

Fig. 1 Cardiac tamponade with exudative pericarditis

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On the left, echocardiography view in the left parasternal short axis. At admission the patient‘s heart sections were compressed an extensive pericardial fluid collection. Re:

significant cardiac tamponade.

The study had data on 1392 ventilation parameters. Comparison of input data of ventilation parameters in both groups are shown in (Tab. 2).

Tab. 2 Differences input data of ventilation parameters between groups

Parameters Group A Group B Values P<

AaDO₂ 16.74 ± 5.11 12.21 ± 4.70 0 .05

a/ADO₂ 0.64 (0.41 to 0.99) 0.52 (0.23 to 0.54) 0 .05

OI 15.14 ± 1.44 11.24 ± 1.14 0 .05

PaO₂/FiO₂ 203.42 ± 75.73 297.17 ± 52.22 0 .01

VI 49.64 ± 19.30 30.189 ± 11.32 0 .01

V_D/V_T 51.16 ± 9.04 33.52 ± 7.78 0 .01

C_dyn 27.92 ± 3.13 36.35 ± 2.07 0 .001

R_awe 1.86 ± 0.91 1.04 ± 0.34 0 .05

Changes in ventilation parameters at time-2 were not significant for either group, but the difference in dates of the groups remained the same. The insignificant, but expected, increasing hypoxic ratio and decrease in oxygenation index were at time-3 in both groups. However, some differences in the groups persisted, as higher VI (26.64 ± 13.06 vs. 20.75 ± 8.47;

P < 0.05), V_D/V_T (29.14 ± 8.55 vs. 23.81 ± 5.80; P < 0.05), R_awe (1.22 ± 0.81 vs. 0.77 ± 0.16;

P < 0.05) in group A compared with group B. Differences in other parameters were not statistically significant.

The study obtained data on 3132 the right ventricle and the same number of data from the left ventricle. No significant difference in load of the left ventricle existed in the groups.

At time-1, higher mean values of PVR (2802 ± 193 vs. 1065 ± 155 dyn.sec/cm⁵; P < 0.01) were found in both groups compared with reference values. Tab. 3 and Tab. 4 document the development of the preload stroke volume, myocardial contractility, stroke work, afterload, and cardiac output of the right ventricle during the study period for each group.

Tab. 3 Overview of right ventricular hemodynamic data obtained in Group A

Parameters TIME ‑1 TIME ‑2 TIME ‑3 Values P<

CVP 7.06 ± 1.58 6.72 ± 1.94 7.32 ± 3.44 NS

SV _RV 5.42 ± 1.59 7.78 ± 1.25 9.07 ± 0.96 0 .05

Vpk _RV 0.56 ± 0.19 0.73 ± 0.20 1.12 ± 0.25 0 .05

PVR 2667.52 ± 456.57 2030.15 ± 417.30 1715.38 ± 507.03 0 .01

SW _RV 67.85 ± 4.51 57.72 ± 2.20 51.33 ± 3.74 0 .05

CO _RV 1.04 ± 0.03 1.67 ± 0.06 2.23 ± 0.12 0 .05

CI _RV 2.11 ± 0.17 3.20 ± 0.12 3.87 ± 0.20 0 .05

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Tab. 4 Overview of right ventricular hemodynamic data obtained in Group B

Parameters TIME ‑1 TIME ‑2 TIME ‑3 Values P<

CVP 6.87 ± 1.06 7.27 ± 2.11 7.35 ± 3.08 NS

SV _RV 5.68 ± 2.60 7.16 ± 1.32 9.43 ± 1.06 0 .05

Vpk _RV 0.74 ± 0.28 0.82 ± 0.31 1.09 ± 0.14 0 .05

PVR 2052.07 ± 506.15 1974.05 ± 431.19 1484.72 ± 338.67 0 .05

SW _RV 52.04 ± 2.01 50.77 ± 4.03 49.23 ± 3.97 NS

CO _RV 1.93 ± 0.09 2.04 ± 0.11 2.34 ± 0.10 0 .05

CI _RV 2.87 ± 0.22 3.85 ± 0.17 4.07 ± 0.19 0 .05

Legend to Tab. 3 and Tab. 4: SW, stroke work (mJ); Vpk, peak velocity of flow (ml/s); Vti, velocity time integral (cm);

PVR, pulmonary vascular resistance (dyn.sec/cm⁵); PVRI, pulmonary vascular resistance index (dyn.sec/cm⁵/m²);

CO, cardiac output (l/min.); CI, cardiac index (l/min/m²); CPO, cardiac power output (W); CVP, central venous pressure (mmHg). All data are presented as mean ± standard deviation.

Tab. 5 presents a comparison of right ventricular hemodynamics data between groups at time intervals of the study.

Tab. 5 Comparison of data between groups A and B

Parameters TIME ‑1

Values P< TIME ‑2

Values P< TIME ‑3

Values P<

CVP NS NS NS

SV _RV NS NS NS

Vpk RV 0 .05 NS NS

PVR 0 .05 NS 0 .05

SW _RV 0 .05 NS NS

CO _RV 0 .05 0 .01 NS

CI _RV 0 .05 0 .05 NS

Tab. 6 presents the characteristics of the study population during hospitalization.

The mean duration of ventilation time was 7.8 ± 1.18 days with a 1.7% real mortality rate of the file study.

Tab. 6 Characteristics of the study population during hospitalization

Characteristics Group A

N = 28 Group B

N = 30 Values

P<

Non-conventional ventilation

N (%) 23 (82) 7 (23) 0 .01

Associated bacterial infection

N (%) 7 (25) 6 (20) NS

Associated viral infection

N (%) 5 (18) 7 (23) NS

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Characteristics Group A

N = 28 Group B

N = 30 Values

P<

Ventilation time

Days; mean ± SD 8.45 ± 2.06 5.75 ± 1.82 0 .05

Deaths during hospitalization

N (%) 1 (3.6) 0 (0) 0 .05

Total duration of hospitalization

Days; mean ± SD 14.0 ± 2.66 8.5 ± 1.74 0 .05

DISCUSSION

The microbiological characteristics of RSV infection, pathogenesis, and diagnosis op- tions are well known. Human RSV is classified in the family Paramyxoviridae, subfamily Pneumovirinae. It occurs in two subtypes with multiple polymorphisms. The genome of a single coil of viral RNA is composed of 11 structural proteins and two nonstructural proteins. Structural proteins penetrate the syncytia and paralyze intercellular communication.

Nonstructural proteins inhibit interferon IFN-1 synthesis. High invasiveness and immuno- suppressive activity are typical features of human RSV. Droplet transmission of an RSV infection usually occurs seasonally. During the 2- to 7-day asymptomatic incubation period, the RSV replicates and floods all the respiratory tract mucosa. The infected mucosa with cytolysis, necrosis, and loss of cilia are potent stimulators of the body’s immune system.

The local inflammatory response leads to the activation of macrophages, the release of the pro-inflammatory mediators, and the formation of specific IgE antibodies. The result of these processes is a progressive obliteration lower airway, increasing dynamic resistance (13–15).

In the present study, acute bronchiolitis was diagnosed based on the typical clinical pre- sentation and confirmation of an active RSV infection. Microbiological analysis of tracheal aspirate confirmed an active RSV infection in all enrolled patients. In accordance with recent literature data, we observed, in the study, that children with acute RSV bronchiolitis responded or did not respond well to acute bronchodilators or anti-inflammatory treatment (16–18)]. Many studies recommended ribavirin, RSV immunoglobulin, and palivizumab for emergency therapy of RSV infection (19–21). At the conclusion of this study, we cannot fully agree. In the high-risk group was greater number of children with immunoprophylaxis, paradoxically, the more numerous complications and significantly severe respiratory failure and especially right ventricular overload. We believe that hypercapnic respiratory failure or complications of the RSV infection come many days after RSV virus incubation, when immunoprophylaxis or antiviral treatment was not effective. For these reasons, antiviral therapy and immunological prophylaxis were not included in the treatment of acute conditions in this study. The main problem of the acute phase of the disease is that immunoprophylaxis or antiviral treatment could not handle progressive obstruction of lower airways. The severity of pulmonary lesion in the high-risk group shows that it was necessary to use unconventional ventilation to stabilize lung function in 82% of the subjects.

Early conversion of conventional to nonconventional ventilation contributed to optimizing

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lung function and reducing overload in the right ventricle. Many high-quality studies addressed in detail the need for urgent treatment of an RSV infection, but did not emphasize the issue of blood circulation (22–24). Our study demonstrates a direct correlation between the severity of pulmonary lesion and right ventricular overload. The pulmonary vascular bed of premature, chronic lung diseases or congenital heart defects with a left-to-right shunt or hypoxemic children rapidly react by increasing pulmonary vascular resistance.

The higher pulmonary vascular resistance is related to the development of pulmonary and extra-pulmonary complications, including adverse effects on blood circulation. The blood circulation of children with hypercapnic respiratory failure is not preload dependent, as is true for most critically ill patients. It depends exclusively on right ventricle afterload. The contribution of this study is that we find that effective treatment of hypercapnic respiratory failure requires parallel modifications of ventilation and blood circulation. Myocardial performance was monitored and evaluated using the recommendations of professional societies only noninvasive, i.e., by ultrasound with the continuous Doppler wave (24–29).

In this study, when they were admitted to the PICU, both groups of patients had signs of severe respiratory failure because of high dynamic airway resistance and right-ventricular overload. The results confirm that comprehensive therapy with individual modification of ventilation and pulmonary hemodynamics resulted in a decrease in airway resistance to improve ventilation in 48 hours. The authors are aware that echocardiography during mechanical ventilation has limitations related to methodology, parameter selection, and investigator experience. Choosing the optimal axis of the Doppler probe may be a limitation of the investigator, depending on his experience. These limitations do not detract from the importance of cardiac output and other hemodynamic parameters as noninvasive, easily obtainable, and reproducible tools for the assessment of cardiac load in clinical intensive care. Based on our experience and the experience of others, serial measurements of these indices are likely to be a valuable tool in the close monitoring of hemodynamics in critically ill patients (30). The study demonstrated that the data from the separate monitoring of hemodynamics were easily interpretable. A high pulmonary vascular resistance increased right ventricle afterload. Increased end-diastolic volume of the right ventricle activates neurohumoral regulation. Higher concentrations of the endogenous catecholamine in the myocardium of the right ventricle supported the inotropes activity of the myocardium (Vpk), contributed to an increase in stroke work (SW), and stabilized the decline of right ventricular cardiac output (CO_RV, CI_RV). By adequate saturation of endogenous catecholamine, the myocardium did not require a further increase in inotropes. By reducing the right-ventricular overload, selective and non-selective vasodilatation stabilized cardiac output (32–35). The aim of the study was met. Easily available information and its cor- rect interpretation have contributed to the successful treatment of patients in critical care.

CONCLUSIONS

The course of hypercapnic respiratory failure was complicated by the adverse change in pulmonary haemodynamics. Right ventricular afterload increased, depending on the

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duration of the hypoventilation. To handle blood circulation safely, up to date and easily evaluable hemodynamic information are required. Reliable control of pulmonary haemodynamics and management of complications in therapy provide the noninvasive hemodynamic monitoring.

SUMMARY

The aim of the study was to evaluate the cotribution of monitoring hemodynamics for therapy optimization. Included in the study were 58 children (age of 1.57 ± 1.13 years).

The children were divided into two groups according to the severity of respiratory failure.

Group A (n = 28) included patients with risks and with LIS ≥ 1.5 points; PRISM ≥ 20 points.

Group B (n = 30) included children without risks and with LIS values from 1.0 to 1.4 points; PRISM values from 10 to 19 points. Hemodynamics was measured using an ultrasound cardiac output monitor. Data were collected one hour after initiation (time-1), and after 24 hours and 48 hours (time-2, 3) of treatment. At time-1, there was higher right ventricular afterload in Group A (p < 0.05) compared to that of group B. At intervals of time-2, 3, there was decreased right ventricular overload in both groups. Mean ventilation time in the study was 7.8 ± 1.18 days with a 1.7% real mortality rate.

Conclusion: Hemodynamic monitoring provides real-time relevant information for in- dividualizing and optimizing the treatment of critically ill patients.

Hemodynamické změny u dětí s hyperkapnickým respiračním selháním v průběhu RSV infekce

SOUHRN

Cílem studie bylo vyhodnotit přínos monitorace hemodynamiky pro optimalizaci léčby.

Do studie bylo zařazeno celkem 58 dětí (průměrný věk 1,57 ± 1,13 roku). Děti byly rozdě- leny do dvou skupin podle závažnosti respiračního selhání a rizika komplikací. Ve skupině A (n = 28) byly děti s vysokým rizikem komplikací, LIS skóre ≥1,5 bodů a PRISM ≥20 bodů.

Do skupiny B (n = 30) byly zařazeny děti bez rizika s LIS skóre mezi 1,0–1,4 body a PRISM od 10 do 19 bodů. Hemodynamika byla monitorována a měřena metodikou USCOM (ultrasound cardiac output monitor). Data byla získávána hodinu po zahájení ventilace (čas -1) a po 24 a 48 hodinách (čas -3, 3) léčby. V čase -1 bylo vyšší dotížení pravé komory ve skupině A (p < 0,05) v porovnání se skupinou B. V dalším průběhu (čase -2, 3) pozvolna klesala tlaková zátěž pravé komory v obou skupinách. Průměrná doba ventilace dětí ve studii byla 7,8 ± 1,18 dne, reálná mortalita 1,7 %.

Závěry: Hemodynamická monitorace v reálném čase přinesla relevantní informace pro individualizaci a optimalizaci léčby kriticky nemocných pacientů.

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ACKNOWLEDGEMENTS

The study was supported by Research Program MSM 0021620819 and PRVOUK P36;

Specific University Research SVV 262802 of the Ministry of Education, and Charles Uni- versity in Prague, Czech Republic. The author would like to thank Dr. Frantisek Sefrna, PhD, who carried out the statistical data processing.

ABBREVIATIONS PICU – Pediatric Intensive Care Unit

RSV – Respiratory Syncytial Virus

PRISM – pediatric Predicted Risk Index Scoring of Mortality LIS – Lung Injury Score

CVP – mean central venous pressure (mmHg) SV _RV – right ventricle stroke volume (ml) Vpk _RV – right ventricle peak velocity of flow (m/s) PVR – pulmonary vascular resistance (dyn.sec/cm⁵) SW _RV – right ventricle stroke work (mJ)

CO_RV – right ventricle cardiac output (l/min.) CI_RV – right ventricle cardiac index (l/min/m²)

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407–411.

Author’s address: J. K., Alej Svobody 80, 304 60 Pilsen, Czech Republic

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Plzeň. lék. Sborn. 80, 2014: 21–26

HE4 IN COMPARISON WITH OTHER BIOMARKERS IN OVARIAN CANCER DIAGNOSTICS

M. Casova¹, R. Kučera¹, S. Svobodová¹, J. Presl², O. Topolčan¹, Z. Novotný², J. Windrichová¹, R. Fuchsová¹, L. Betincová²

1 Laboratory of Immunoanalysis

2 Department of Gynecology and Obstetrics, Faculty Hospital in Pilsen, Czech Republic

Ovarian cancer is the leading cause of gynecological cancer death, representing 5% of all cancers in women and 23% of gynecological cancer. Ovarian cancer has a poor progno- sis, mainly because of the late detection. Mortality, despite the decline in the last 10 years, is still very high. Worldwide attention is therefore focused on the potential research and the subsequent treatment of this cancer (1, 2).

The first aim of our study was to evaluate if human epididymis protein 4 (HE4) is a useful biomarker and broadens the possibilities in ovarian cancer diagnostics. The second aim was to evaluate the benefits of each biomarker of our panel for the ovarian cancer diagnostics. We compared the results of following tumor markers: cancer antigen 125 (CA 125), HE4, cancer antigen 19-9 (CA 19-9), cancer embryonic antigen (CEA), thymidinkinase (TK), tissue polypeptidic antigen (TPS) and tissue polypeptidic antigen (MonoTotal).

MATERIAL AND METHODS

The total number of females in our study was 266. We divided the patients into two groups. The age characteristic of both groups is shown in the Tab. 1. The first group consisted of 19 females with ovarian cancer with equal representation of stages FIGO I–IV.

Second group included 247 patients with benign diseases (ovarian cysts, myomas, endometrial polyps). Serum samples were collected prior to surgery or any other form of treatment. All cancer diagnoses were histologically verified.

The serum samples were analyzed at the Laboratory of Immunoanalysis, Faculty of Medi- cine in Pilsen, (Czech Republic) from March 2010 to January 2012. Samples of venous blood were collected using the VACUETTE blood collection system (Greiner Bio-one Company, Kremsmünster, Austria). Blood was centrifuged for 10 minutes at 1700 ×g. Serum samples were immediately frozen to –80 °C. Samples were thawed only once, just prior to analyses.

Serum levels of CA 125, CEA and CA 19-9 were measured using a DxI instrument (Beck- man Coulter, Brea, California, USA). Serum levels of HE4 were measured using an enzyme immunometric assay kit (Fujirebio Diagnostics, Göteborg, Sweden). TK was measured using radioisotope assay kit (Immunotech, Prague, Czech Republic). TPS and MonoTotal were measured using IRMA radioisotope assay kits (IDL Biotech, Bromma, Sweden).

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The SAS 9.2 (Statistical Analysis Software release 9.2; SAS Institute Inc., Cary, NC, USA) was used for all statistical analysis. A summary of statistical findings for age and serum levels of each of the analytes was presented. The Wilcoxon test was used to compare distributions of values between benign and malignant tumors.

RESULTS

Comparing the parameters of serum level markers between the benign and malignant groups of patients a statistically significant differences were found in the following biomarkers: CA 125, HE4, MonoTotal and TPS (p < 0.0001 for each analyte). CA 19-9, TK and CEA were not significant. All the results are shown in Tab. 2.

Tab. 1 Age characteristic of the patient groups

Diagnosis Count

(N)

Age (years)

Mean Median Min. Max.

Ovarian cancer 19 65 .63 62 43 84

Benign ovarian tumor 247 61 .24 54 33 79

Tab. 2 Ovarian cancer vs. benign tumor Parameter

(units) Diagnosis N Mean Median Range p ‑Value

Wilcoxon test CA 125

(kIU/l)

Cancer 19 1669 .00 1725 .00 54.00 – 4621

<0 .0001

Benign 247 27 .50 14 .00 23.00 – 1244

HE4(pmol/l)

Cancer 19 595 .06 421 .9 50.87 – 3266

<0 .0001

Benign 247 80 .24 52 .70 23.00 – 1570

MonoTotal (IU/l)

Cancer 19 626 .9 501 .7 710.9 – 2844

<0 .0001

Benign 247 79 .50 49 .90 5.00 – 2255

TPS(IU/l)

Cancer 19 309 .1 144 .0 25.00 – 1453

<0 .0001

Benign 247 83 .27 46 .00 10.00 – 1226

TK(IU/l)

Cancer 19 11 .11 9 .50 3.50 – 24.10

0 .3022

Benign 247 9 .56 5 .90 2.50 – 29.80

CA 19‑9 (kIU/l)

Cancer 19 23 .00 11 .00 1.00 – 124.0

0 .3060

Benign 247 16 .27 8 .00 1.00 – 428.0

CEA(µg/l)

Cancer 19 25 .00 5 .30 2.50 – 225.0

0 .1471

Benign 247 1 .83 1 .20 0.50 – 20.60

CA 125 (cancer antigen 125), HE4 (human epididymis protein 4), MonoTotal (tissue polypeptidic antigen), TPA (tissue polypeptidic antigen), TK (thymidinkinase), CA 19-9 (cancer antigen 19-9), CEA (cancer embryonic antigen)

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Tab. 3 shows the analytical parameters of all biomarkers which were used in the study.

We have evaluated cut-off, sensitivity, positive predictive value (PPV) and negative predictive value (NPV) at 95% specificity. We have calculated area under the curve (AUC) and the biomarkers in Tab. 2. and Tab. 3. are ranked according this parameter. The highest level of AUC was achieved for CA 125 (AUC = 0.987), the second highest level was achieved for HE4 (AUC = 0.907) and the lowest level was achieved for CEA (AUC = 0.483).

DISCUSSION

Tumor markers are currently used for the follow-up and therapy effect monitoring. In evaluating data, we have focused on the possibilities of using selected biomarkers in ovarian cancer diagnostics. Our panel of biomarkers consisted of the traditional tumor markers (CA125, CA19-9, CEA) which have been used in relations to the ovarian cancer for a long time. Then we evaluated a relatively new marker HE4, which we started to measure in 2010. In addition we have filled in the biomarker panel with the proliferative tumor markers from the group of cytokeratins (TPS, MonoTotal) and non-specific tumor marker TK.

CA 125 determination in combination with ultrasonography was used in the past for the diagnosis of ovarian cancer (3, 4). A major disadvantage of CA 125 is that up to 20%

of ovarian cancers lack expression of this antigen. The second disadvantage is a low specificity of CA 125. Abnormal serum levels of CA 125 may be observed in several benign and malignant diseases (5, 6). It is therefore necessary to combine CA 125 with the other tumor markers to provide a better diagnostic efficiency.

The combination of CA125 and HE4 improves the results achieved by CA125 alone.

About 20% of epithelial ovarian cancer show a slight elevation of CA125. For more than 50% of these malignancies, elevated levels of HE4 can be observed, and combinations of these markers may therefore optimize the potential for a successful diagnosis of ovarian malignancy in these patients. Another factor supporting a combination of both markers is that elevated levels of CA125 can be observed as a result of physiological conditions such as menstruation or pregnancy, as well as in benign ovarian tumor, inflammation and the presence of endometriosis and fibroids. This false positivity in the group of premeno- pausal patients may cause problems in routine clinical practice. Therefore, a combination of HE4 and CA125 increases specificity and sensitivity of testing in ovarian cancer diagnostics.

Using of biomarker HE4 as a single test in ovarian cancer testing is also problematic.

Mucinous ovarian cancer has almost no expression of HE4. HE4 serum levels are very low or negative. HE4 is overexpressed in serous and endometroid histotype of the ovarian cancer. Preliminary studies of HE4 reported a higher specificity than CA 125 in different benign and malignant conditions, excluding renal failure (7). Patients with renal failure had very high HE4 serum levels. Patients with this disease were excluded from our study.

The major part of the studies in serum has been already published that HE4 sensitivity and specificity were better than CA 125 (8–12). Our results didn’t confirm this fact. If we con- sider our results, we see that the best values were achieved for CA125 followed by HE4.

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Our data are consistent with the second group of the studies with the higher sensitivity of CA 125 than HE4 (13, 14).

Cytokeratins were included in our panel because significantly elevated serum levels of TPS were found in serum samples from patients who had ovarian carcinoma compared with patients who had benign tumors (6, 15).

Tumor markers CA 19-9, TK and CEA didn’t show statistically significant different serum levels in the group of malignant tumors, compared to other benign ovarian diagnoses.

These two markers are often elevated in relation to the benign or malignant disease of the gastrointestinal tract and therefore they are not directly related to gynecological diagnosis.

CA 19-9 can be useful as an additional parameter in diagnostics of the mucinous type of ovarian cancer. In this case is the CA 19-9 elevated (16). However, their ability to distin- guish between benign and malignant tumor is limited. Elevated serum levels may be found in benign mucinous tumors as well as in malignant tumors (17). In conclusion, determination of HE4 levels, together with CA125 improves a primary detection of ovarian cancer and broadens the range of differential diagnostic possibilities for distinguishing between malignant and benign tumors. MonoTotal and TPS confirmed their status of markers of proliferation and can be used to the monitoring the activity and aggressiveness of the tumor.

Tumor markers CA 19-9, TK and CEA didn’t show statistically significant different results.

ACKNOWLEDGEMENTS

Supported by Ministry of Health, Czech Republic – conceptual development of research organization (Faculty Hospital in Pilsen – FNPl, 00669806).

SUMMARY

Ovarian cancer is the leading cause of gynecological cancer death. The first aim of our study was to evaluate if HE4 broadens the possibilities in ovarian cancer diagnostics. The second aim was to evaluate the benefits of each biomarker of our panel. We compared the results of following tumor markers: CA 125, HE4, CA 19-9, CEA, TK, TPS, MonoTotal.

Tab. 3 Analytical parameters of individual analytes at specificity 95%

Analyte

(units) CA 125

(kIU/l) HE4

(pmol/l) MonoTotal

(IU/l) TPS

(IU/l) TK

(IU/l) CA 19‑9

(kIU/l) CEA

(µg/l)

AUC 0.987 0.907 0.836 0.755 0.676 0.573 0.483

Cut ‑off 70 .000 124 .100 231 .100 248 .700 17 .000 43 .000 4 .600 Sensitivity 89 .500 73 .330 63 .280 36 .810 22 .280 16 .710 11 .100

PPV 50 .000 50 .180 63 .160 29 .210 18 .280 15 .840 11 .170

NPV 99 .000 97 .510 97 .900 96 .520 96 .000 95 .400 95 .000

AUC: area under the curve; PPV: positive predictive value; NPV: negative predictive value

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The total number of females in our study was 266. We divided the patients into two groups.

The first consisted of 19 females with ovarian cancer and the second of 247 females with benign ovarian tumors. Serum samples were collected prior to surgery or any other form of treatment.

Significant difference between the benign and malignant group was found in follow- ing biomarkers: CA 125, HE4, MonoTotal and TPS. CA 19-9, TK and CEA were not significant. We have evaluated cut-off, sensitivity, positive predictive value and negative predictive value at 95% specificity and area under the curve (AUC). The highest level of AUC was achieved for CA 125 (AUC = 0.9951), the second highest level (AUC = 0.9534) was achieved for HE4 and the lowest level (AUC = 0.5324) was achieved for CEA marker. In conclusion determination of HE4 levels, together with CA125 improves a primary detection of ovarian cancer. MonoTotal and TPS confirmed their status of marker of proliferation and they can be used for the monitoring the activity and aggressiveness of the tumor. Tumor markers CA 19-9, TK and CEA didn’t show statistically significant different results.

HE4 v porovnání s ostatními biomarkery v diagnóze rakoviny vaječníku

SOUHRN

Rakovina vaječníku je nejčastější příčinou úmrtí v oblasti zhoubných gynekologic- kých onemocnění. Cílem naší studie bylo v první řadě zhodnotit, zda vyšetření HE4 je schopno rozšířit možnosti v diagnostice karcinomu vaječníku. Naším dalším cílem bylo zhodnotit přínos jednotlivých biomarkerů námi vybraného panelu. V naší práci jsme po- rovnali výsledky těchto nádorových markerů: CA 125, HE4, CA 19-9, CEA, TK, TPS a MonoTotal. Celkový počet žen v naší studii byl 266. Soubor jsme rozdělili do dvou skupin. První skupina se skládala z 19 žen s rakovinou vaječníku a druhá z 247 žen s be- nigními ovariálními tumory. Vzorky séra byly odebrány před operací nebo zahájením jiné formy léčby. Statisticky významný rozdíl mezi benigní a maligní skupinou byl nalezen v hodnotách následujících biomarkerů: CA 125, HE4, MonoTotal a TPS. Rozdíly v hod- notách CA 19-9, CEA a TK nebyly statisticky významné. Zhodnotili jsme cut -off, citlivost, pozitivní prediktivní hodnotu (PPV) a negativní prediktivní hodnotu (NPV) při 95 % specificitě a plochu pod křivkou (AUC).Nejvyšší úrovně AUC bylo dosaženo u CA 125 (AUC = 0,9951), druhé nejvyšší úrovně (AUC = 0,9534) bylo dosaženo u HE4 a nejnižší hladina (AUC = 0,5324) byla naměřena u CEA. Závěrem je možná říci, že stanovení HE4, spolu s CA125 zlepšuje primární detekci rakoviny vaječníku. Nádorové markery Mono- Total a TPS potvrdily svůj status markerů proliferace a mohou být použity pro sledování růstu a agresivitu nádoru. Nádorové markery CA 19-9, TK a CEA nevykazovaly statisticky významně odlišné výsledky.

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REFERENCES

1. Oberaigner W., Minicozzi P., Bielska -Lasota M. et al.: Survival for Ovarian Cancer in Europe: The across-country variation did not shrink in the past decade. Acta Oncol. 51, 2012: 441–3. – 2 Jemal A., Siegel R., Ward E. et al.: Cancerstatistics. CA Cancer J. Clin. 57, 2007: 43–66. – 3. Bast Jr R. C., Badgwell D., Lu Z. et al.: New tumour markers: CA 125 and beyond. Int. J. Gynecol. Cancer 15, 2005: 274–81. – 4. Rosenthal A. N., Menon U., Jacobs I. J.: Screening for ovarian cancer. Clin. Obstet. Gynecol. 49, 2006: 433–47. – 5. Li J., Dowdy S., Tip- ton T. et al.: HE4 as a biomarker for ovarian and endometrial cancer management. Expert Rev. Mol. Diagn. 9, 2009: 555–66. – 6. Fritsche H. A., Bast R. C.: CA 125 in Ovarian Cancer: Advances and Controversy. Clin.

Chem. 44, 1988: 1379–80. – 7. Escudero J. M., Auge J. M., Filella X. et al.: Comparison of serum human epididymis protein 4 with cancer antigen 125 as a tumor marker in patients with malignant and nonmalignant diseases. Clin. Chem. 57, 2011: 1534–44. – 8. Moore R. G., McMeekin D. S., Brown A. K. et al.: A novel multiple marker bioassay utilizing HE4 and CA125 for the prediction of ovarian cancer in patients with a pelvic mass.

Gynecol. Oncol. 112, 2009: 40–6. – 9. Van Gorp T., Cadron I., Despierre E. et al.: HE4 and CA125 as a diagnostic test in ovarian cancer: prospective validation of the Risk of Ovarian Malignancy Algorithm. Br. J. Cancer 104, 2011: 863–70. – 10. Anastasi E., Marchei G. G., Viggiani V. et al.: HE4: a new potential early biomarker for the recurrence of ovarian cancer. Tumour Biol. 31, 2010: 113–119. – 11. Sandri M. T., Bottari F., Franchi D. et al.:

Comparison of HE4, CA125 and ROMA algorithm in women with a pelvic mass: Correlation with pathological outcome. Gynecol. Oncol. 128, 2013: 233–8. – 12. Azzam A. Z., Hashad D. I., Kamel N. A.: Evaluation of HE4 as an extrabiomarker to CA125 to improve detection of ovarian carcinoma: is it time for a step forward? Arch.

Gynecol. Obstet. 287, 2013: 404–13. – 13. Partheen K., Kristjansdottir B., Sundfeldt K.: Evaluation of ovarian cancer biomarkers HE4 and CA-125 in women presenting with a suspicious cystic ovarian mass. J. Gynecol.

Oncol. 22, 2011: 244–52. – 14. Chang X., Ye X., Dong L. et al. : Human epididymis protein 4 (HE4) as a serum tumor biomarker in patients with ovarian carcinoma. Int. J. Gynecol. Cancer 21, 2011: 852–8. – 15. Sedlaczek P., Frydecka I., Gabryś M. et al.: Comparative analysis of CA125, tissue polypeptide specific antigen, and soluble interleukin-2 receptor alpha levels in sera, cyst, and ascitic fluids from patients with ovarian carcinoma. Cancer 95, 2002: 1886–93. – 16. Engelen M. J., de Bruijn H. W., Hollema H. et al.: Serum CA 125, carcinoembryonic antigen, and CA 19-9 as tumor markers in borderline ovarian tumors. Gynecol. Oncol. 78, 2000: 16–20. – 17. Kelly P. J., Archbold P., Price J. H. et al.: Serum CA19.9 levels are commonly elevated in primary ovarian mucinous tumours but cannot be used to predict the histological subtype. J. Clin. Pathol. 63, 2010: 169–73.

Author’s address: R. K., E. Beneše 13, 305 99 Pilsen Czech Republic

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Plzeň. lék. Sborn. 80, 2014: 27–30

BRAIN METABOLISM AND ELECTROGENESIS IN PHENYLKETONURIA

P. Sobotka

Department of Pathophysiology, Faculty of Medicine in Pilsen, Czech Republic

Phenylketonuria is an autosomal recessive disease due to the deffect of enzyme phenyl- alaninehydroxylase which metabolizes aminoacid phenylalanine to tyrozine (18). Rapid postnatal elevation of phenylalanine in the blood may soon exceed the norm by 20 up to 30 times. Phenylalanine actively passes the hematoencephalic barrier and leads to severe neural retardation with low IQ (1, 2). Hyperphenylalaninemia may be also responsible for the imbalance of the protein metabolism (4).

In the present paper we investigated the metabolism of aminoacids of the brain in rats with experimental hyperphenylalaninemia. In the second part we examined the effect of local application of phenylalanine (FA) and of phenylpyruvic acid (FP) to the brain cortex of rats.

MATERIAL AND METHODS

To ten fife day old rats there was applied either combination of DL alfa-methylphenylala- nine and L phenylalanine (MEPH 2.4 and PHE 5.2 mMol ∙ kg^–1) twice a day, or combination of DL p-chlorphenylalanine and L phenylalanine (pC1PHE 0.9 and PHE 5.2 mMol ∙ kg^–1) once a day. After 5 days the animals were decapitated. Tissue extraction and biochemical analysis were described in detail in the previous paper (21).

The second part of experiments was performed with 21 days old rats anesthetised with pentobarbital. Electrocorticogram was registered by means of silver ball electrodes placed to intact pia mater bilaterally to the right and to the left hemisphere. Small strips of filter paper soaked with warm solution either of phenylalanine, phenylpyruvate or physiological solution were placed closely to the electrodes.

RESULTS

Application of PHE leads to rapid elevation of this aminoacid in the blood and in the brain followed by a slow decline. Addition of MPHE prolongs this effect. Hyperphenyl- alaninemia leads to important changes of metabolism of other brain aminoacids (Tab. 1).

Especially striking is the elevation of glycine (Fig. 1). Significantly are elevated tyrosine

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and asparagine, contrary lower concentration had glutamine, valine, methionine and leucine, concentration of serine and valine was not influenced.

Local application of phenylalanine and especially of its metabolite phenylacetic acid to the brain cortex elicited typical high voltage epileptogenic discharges (Fig. 2).

DISCUSSION

Phenylketonuria is a clinical important metabolic disease with the incidence of 1 : 8,000 deliveries in our country. With regard to weighty consequences of the disease still contin- ues clinical and experimental research (7, 16, 18). Owing to the results there is nowadays possible a prenatal (15, 19) and early postnatal diagnosis (5, 11, 23), detection of asymptomatic heterozygotes and successful dietetic therapy (3, 6, 10, 12, 25).

It is not surprising that phenylketonuria not only blocks the production of tyrosine but influences also the metabolism of other brain aminoacids (8, 13, 20). The elevation of glycine in our experiments approached values which are characteristic for the cogent brain syndrome of nonketotic hyperglycinemia (14). In the case of defective enzyme phenylalanine hydroxylase, phenylalanine can be partially metabolised to phenylpyruvic, phenylbutyric and phenylaceti acid (9). These metabolites manifest itself in the characteristic odour of urine and sweat. Evidently they participate also on varied symptoms of the disease. In our experiments we confirmed their role in epileptogenesis (17, 22, 24).

SUMMARY

Experimental phenylketonuria in young rats leads besides hyperphenylalaninemia to changes of brain aminoacids. Elevation of glycine approaches values characteristic for cogent syndrome of nonketotic hyperglycinemia. Local application of phenylalanine and its metabolites to the brain cortex is epileptogenic.

Tab. 1 Brain aminoacids in hyperphenylalaninemic rats (µMol/1g wet weight)

Aminoacid 0.9% pClPHE + PHE

Glycine 0.085 ± 0.007 1.24 ± 0. 210

Asparagine 1.870 ± 0.107 2.62 ± 0.290

Tyrosine 0.260 ± 0.018 0.33 ± 0.290

Glutamine 5.130 ± 0.533 3.970 ± 0.416

Valine 1.590 ± 0.010 0.106 ± 0.023

Methionine 0.048 ± 0.004 0.034 ± 0.009

Leucine 0.148 ± 0.029 0.103 ± 0.010

Serine 1.150 ± 0.098 1.320 ± 0.243

Alanine 0.726 ± 0.730 0.686 ± 0.046

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Fig. 1 The dependence of free glycine in the brain to the concentration of free phenylalanine. Elipses present 4 groups of experimental animals. Semiaxes of elipses correspond to ± SD. Empty circles experiments with MEPH + PHE, full circles experiments with pC1PHE (left side) and with pC1PHE + PHE (right side).

Fig. 2 Electrocorticogram of 21 days old rat. K – control recording FA – phenylalanine, FR – physiological solu- tion, FP – phenylpyruvate.

Metabolismus a elektrogeneze mozku u fenylketonurie SOUHRN

Experimentální fenylketonurie vyvolaná u mláďat potkanů vede kromě hyperfeylala- ninemie ke změně spektra aminokyselin mozku. Zvýšení glycinu je obdobné syndromu neketotické hyperglycinemie mozku. Lokální aplikace fenylalaninu a jeho metabolitů na mozkovou kůru má epileptogenní účinek.

PLZEŇSKÝ LÉKAŘSKÝ SBORNÍK PILSEN MEDICAL REPORT 80. SVAZEK

PLZEŇSKÝ LÉKAŘSKÝ SBORNÍK

80. SVAZEK

OBSAH

CONTENTS

HEMODYNAMICS CHANGES IN CHILDREN WITH HYPERCAPNIC RESPIRATORY FAILURE

DURING RESPIRATORY SYNCYTIAL VIRUS INFECTION J. Kobr

, J. Fremuth

, L. Šašek

, R. Hrdlička

, J. Racek

, K. Pizingerová

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