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23MEDICAL SCIENCES
CARDIAC HEMODYNAMICS AND OXYPROLINE EXCHANGE IN PATIENTS WITH MITRAL VALVE PROLAPSE IN COMBINATION WITH TYPE 1 DIABETES MELLITUS
Nikolenko O.
Assistant of the Department of General Practice-Family Medicine, V. N. Karazin Kharkiv National University, Kharkiv, Ukraine
ORCID: 0000-0002-8312-8506
Abstract
Both mitral valve prolapse and diabetes mellitus, in particular the first type, and especially their combination, are among the key problems of modern medicine. Because they are diagnosed mainly among young people, this causes large medical and social, economic losses. Aim of the study was to evaluate the cardiac hemodynamics and oxyproline exchange in patients with mitral valve prolapse in combination with type 1 diabetes mellitus. Serum oxyproline (free and protein bound) levels was determined to study connective tissue metabolism.
Keywords: mitral valve prolapse, type 1 diabetes mellitus, oxyproline, hemodynamics.
Background. Both mitral valve prolapse (MVP) and diabetes mellitus (DM), in particular DM or the first type (T1DM), and especially their combination, are among the key problems of modern medicine [110]. They are associated with a broad range of pathologies: cardiac arrhythmias and hypertrophy, brain dyscirculation and even sudden death etc. [1, 2, 11-18]. Because both of them are diagnosed mainly among young people, this causes large medical and social, economic losses and appropriate burden [19, 20].
Cardiac hemodynamic abnormalities in general and mitral prolapse related are relatively frequent in an urban population [21-38]. While, known studies concern mostly mature age population even if consist young people. Or, vice versa, they concern children. Multiple are the researches of cardiac hemodynamics in patients with T1DM of different ages, even with relatively novel three-dimensional speckle tracking echo-cardiography [31, 39-53]. And there is a lack of studies focused on population aged 18-30 years. Especial lack is in studies dedicated to echocardiographic changes in young people with type 1 diabetes mellitus.
In turn, the condition of connective tissue, more specifically, collagen, for one hand, plays fundamental role in the functionality of the whole organism, for other - it is more or less altered in both MVP and T1DM [54-69]. Concentration of oxyproline or more often synonym, hydroxyproline, in blood or urine is one of the main marker of collagen, a main component of connective tissue, metabolism, as it was shown in multiple studies since the 60's and remain a topical objective in scientific studies and medical practice till now [70-83]. It also plays significant role in the physiology of different polypeptides [84]. Oxyproline contributes to the collagen structural stability [85, 86]. Oxyproline main fractions available for detection are: free oxyproline (FOP) and protein-bound oxyproline (PBOP), multiple methods of their detection are available [85, 8794]. Blood concentrations of oxyproline correlate with the severity of ischemic heart disease, extent and depth of myocardial infarction [95]. Relatively successful (according to the author's data) attempts to normalize the oxyproline metabolism in L-hydroxyproline trial
are well-known [96]. Approaches to optimize it by nutrition modification were performed as well [97-99].
Since the Framingham Heart Study (which was one of the most fundamental), epidemiological, clinical, diagnostic studies have been performed, but mostly separately for MVP and T1DM, and very few - for their comorbid course [100-107].
Despite a plenty of studies, the peculiarities of cardiac hemodynamics and oxyproline exchange in patients with mitral valve prolapse in combination with type 1 diabetes mellitus remain unclear and require a specific research in order to improve the diagnostic, therapeutic and prophylactic approaches to this medical problem.
Aim: to evaluate the cardiac hemodynamics and oxyproline exchange in patients with mitral valve prolapse in combination with type 1 diabetes mellitus.
Material and methods:
Clinical randomized sectional cohort controlled study with retrospective and prospective stages was conducted with the participation of 93 patients: 24 patients with MVP (1st group); 33 patients with MVP and T1DM (2nd group), 36 patients with T1DM (3rd group). Control group included 20 healthy people. The age of all participants varied from 19 to 35 years, each group was comparative by age of participants: 1st group -23.9 ± 1.3 years, 2nd group - 26.88 ± 1.05 years, 3rd group - 27.43 ± 1.17 years, control group -22.7 ± 2.30 years.
Standard diagnostic criteria were used for both MVP and T1DM, based on international and local (Ukrainian) protocols and guidelines [103, 108-110].
The study was performed on the base of Municipal Non-Commercial Enterprise of Kharkiv Regional Council "Regional Clinical Hospital" as a part of the research work of the Department of General Practice-Family Medicine, Medical Faculty of V. N. Karazin Kharkiv National University of the Ministry of Education and Science of Ukraine on the topic: "Remodeling of elastic-tissue structures in the early diagnosis of heart disease in undifferentiated connective tissue dys-plasia in young people with dysmetabolic changes" (state registration number 0116u002834), 2016-2021.
The author is a co-executor of this work. The study has been allowed by the bioetics Committee of V. N. Karazin Kharkiv National University.
Cardiac hemodynamics was evaluated by standard echocardiography with detection of the following parameters: left ventricle (LV) end-diastolic diameter (LV EDD), LV end-systolic diameter (LV ESD), LV end-diastolic volume (LV EDV), LV end-systolic volume (LV ESV), interventricular septal thickness (IVST), left ventricle posterior wall thickness (LV PWT), stroke volume (SV), degree of the mitral valve leaflets prolapse, index of the relative wall thickness of the left ventricle by the formula (IVST + LV PWT) / LV EDD.
Serum oxyproline (free and protein-bound) levels in patients with mitral valve prolapse, type 1 diabetes mellitus, and a combination of these pathologies was determined by standard biochemical methods to study connective tissue metabolism.
In all statistical calculations, the threshold value of the significance level p was chosen to be 0.05. In a case of multiple comparisons, the Bonferroni correction was used (the product of the threshold value p 0.05 and the number of comparisons was taken as the p-level critical value).
Maintenance of the research data bank, basic calculations of derivative indicators, frequencies, construction of diagrams were performed using Microsoft
Parameters cardiac hemodynamics in patients with
diabetes
365 software, all calculations were performed using Statsoft Statistica 8.0.
Results and discussion.
The MVP is stated as one of forms of systemic connective tissue dysplasia ("weakness"), together with joints hypermobility etc. [21, 37, 111-120]. There are multiple clinical and pathophysiological interrelations of MVP and T1DM with their mutual burdening. Thus, connective tissue dysplasia in combination with diabetes mellitus promotes to metabolic and vascular affections. At the same time, the probability of myxomatous degeneration of mitral leaflets is relatively higher in patients with diabetes mellitus, and this predisposes to MVP in turn.
One of the problems is a subclinical or even totally clinically latent hemodynamic changes in young patients with MVP and (or) T1DM and thorough additional investigations are required to detect them, predict the outcomes, including the dangerous ones, and one of the basic and standard is echocardiography [121-128].
Echocardiographycally it was found that when studying the indicators of intracardiac hemodynamics, significant differences relate to the thickness of the interventricular septum and the thickness of the posterior wall, which differed both in comparison with the control and between groups of patients, as well as left ventricle end-diastolic and end-systolic diameters, which differed significantly from the corresponding values in the control group (Table. 1).
Table 1
isolated mitral valve prolapse and comorbid type 1 mellitus
Parameters of hemodynamics 1st group (isolated MVP), n = 24 2nd group (MVP + T1DM), n = 33 Control group, n = 20
LV EDD, mm 45.6 ± 0.57 44.1 ± 0.54Î 46.3 ± 0.51
LV ESD, mm 29.8 ± 0.41 29.2 ± 0.33Î 31.4 ± 0.36
LV EDV, mm 92.6 ± 2.4 89.4 ± 2.26 94.1 ± 2.24
LV ESV, mm 34.8 ± 1.12 33.1 ± 1.02 36.5 ± 0.98
IVST, mm 8.3 ± 0.15t 8.9 ± 0.16*i 8.0 ± 0.11
LV PWT, mm 8.1 ± 0.10t 8.7 ± 0.12*i 8.2 ± 0.09
SV, ml 59.0 ± 1.10 55.6 ± 1.52Î 62.1 ± 1.18
Degree of the mitral valve leaflets prolapse, mm 4.8 ± 0.09 4.9 ± 0.07 -
Index of the relative wall thickness of the left ventricle, mm 0.38 ± 0.19 0.40 ± 0.20Î 0.35±0.16
Note. Differences are statistically significant (p < 0.05) comparing with mean parameter in: * - 1st group; t - 2nd group; i - control group; LV - left ventricle, EDD - end-diastolic diameter, ESD - end-systolic diameter, EDV -end-diastolic volume, ESV - end-systolic volume, IVST - interventricular septal thickness, PWT - left ventricle posterior wall thickness, SV - stroke volume.
As soon as these indicators form an index of the relative wall thickness of the left ventricle, the value of the last one was higher in the group with comorbid pathology, which may indicate the initiation of LV remodeling processes.
Different visualization modalities are used to clarify the aspects of mitral valve abnormalities, i. e. MVP [129-131].
Among adults in urban regions, about quarter is expected to have some echocardiography abnormalities [33].
An impairment of LV has been reported in connective tissue pathology, including an early one [131137].
It was shown that values of diastolic strain parameters can serve for detection of the earliest myocardial affection in children with MVP [132].
In terms of metabolic disturbances of connective tissue, oxyproline evaluation let us detect a set of peculiarities in young patients with MVP, T1DM - separate and comorbid (Table. 2).
Table 2
Parameters of oxyproline metabolism in the serum of patients with mitral valve prolapse, type 1 diabetes
mellitus and their combination
Parameters 1st group (isolated MVP), n = 24 2nd group (MVP + T1DM), n = 33 3rd group (isolated T1DM), n = 36 Control group, n = 20
Free oxyproline, ^mol / l 14.37 ± 2.69 17.98 ± 2.02§ 15.10 ± 1.21 13.2 ± 1.16
PBOP, ^mol / l 10.18 ± 1.85+ 16.06 ± 1.54* i § 12.38 ± 1.34 8.7 ± 0.81
FOP / PBOP ratio 1.41 ± 0.72t 1.12 ± 0.57§ 1.22 ± 0.61 1.52 ± 0.75
Note. Differences are statistically significant (p < 0.05) comparing with mean parameter in: * — 1st group; t — 2nd group; i — 3rd group; § — control group; MVP - mitral valve prolapse, T1DM - type 1 diabetes mellitus, PBOP -protein-bound oxyproline.
The elevation of PBOP in all patients, especially in 2nd group of patients with comorbid pathology, reflects a relationship with the magnitude of dystrophic processes in connective tissue [93], more specifically -stability of collagen molecules [85]. Similar increase of peptide-bound oxyproline was found in onychodystrophy (nail hyperkeratosis) [93, 138], free oxyproline - in hereditary collagenoses [139].
Apart of appropriate elevation of FOP as well, FOP / PBOP ratio remains significantly lower in patients with MVP and T1DM comparing with control. Similar tendency to elevation of oxyproline blood serum concentrations were detected in multiple pathologies concerning connective tissue metabolism disturbance [140]. This and other data proves the use of it as a biochemical marker [141-143]. Collagen hydroxyla-tion reflects on the properties of extracellular matrix and cell behavior [144].
From a pathophysiological point of view, limitation of proline hydroxylation in a collagen structure may lead to affection of integrin binding directly or via structural destabilization of the helix [81, 144-147].
There could be a role of cytoplasmic glycosylation associated with hydroxyproline and collagen in total [148-150] in patients with T1DM, along or in combination with MVP.
On this way, a pharmacological regulation of prolidase (cytosolic imidodipeptidase, one of actions of which there is imidodipeptides specific splitting with C-terminal proline or hydroxyproline in the collagen molecule) by beta(1)-integrin receptor stimulation might be applicable [151].
A perspective is elaboration of a predictive math-ematic model basing on cardiac hemodynamics and ox-yproline exchange in patients with mitral valve prolapse in combination with type 1 diabetes mellitus, in addition to other valuable parameters, clinical or instrumental, laboratory. A hybrid deep learning modeling or other approaches might be applicable [152-158].
Conclusions:
1. Echocardiographic screening is important for young patients with connective tissue dysplasia (e. g. mitral valve prolapse), especially in comorbid type 1 diabetes mellitus.
2. Elevation of oxyproline blood concentration and especially - disproportion of its fractions, free ox-yproline and protein-bound oxyproline, reflect the dys-trophic changes in connective tissue with collagen molecule instability, in both mitral valve prolapse and type 1 diabetes mellitus, but the most strong in patients with comorbidity.
The prospects of further research are thorough evaluation of connective tissue metabolism, fibroblast growth factor in relation with hemodynamic changes (including diastolic strain parameters detection) and study of clinical epidemiology, diagnostic, treatment, prophylaxis aspects in young people with mitral valve prolapse and comorbid type 1 diabetes mellitus.
REFERENCES:
1. Althunayyan A, Petersen SE, Lloyd G, Bhattacharyya S. Mitral valve prolapse. Expert Rev Cardiovasc Ther. 2019 Jan;17[1]:43-51.
2. Basso C, Iliceto S, Thiene G, Perazzolo Marra M. Mitral Valve Prolapse, Ventricular Arrhythmias, and Sudden Death. Circulation. 2019 Sep 10;140[11]:952-64.
3. Desai S, Deshmukh A. Mapping of Type 1 Diabetes Mellitus. Curr Diabetes Rev. 2020;16[5]:438-41.
4. Hoogwerf BJ. Type of diabetes mellitus: Does it matter to the clinician? Cleve Clin J Med. 2020 Feb;87[2]:100-8.
5. Norris JM, Johnson RK, Stene LC. Type 1 diabetes-early life origins and changing epidemiology. Lancet Diabetes Endocrinol. 2020 Mar;8[3]:226-38.
6. Shah SN, Gangwani MK, Oliver TI. Mitral Valve Prolapse. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2020 [cited 2021 Jan 19]. Available from: http ://www. ncbi.nlm. nih. gov/books/NBK470288/
7. Warshauer JT, Bluestone JA, Anderson MS. New Frontiers in the Treatment of Type 1 Diabetes. Cell Metab. 2020 Jan 7;31[1]:46-61.
8. Liu P-Y, Tsai K-Z, Lin Y-P, Lin C-S, Zeng H-C, Takimoto E, et al. Prevalence and characteristics of mitral valve prolapse in military young adults in Taiwan of the CHIEF Heart Study. Sci Rep. 2021 Feb 1;11[1]:2719.
9. Turker Y, Turker Y, Baltaci D, Basar C, Ak-kaya M, Ozhan H, et al. The prevalence and clinical
characteristics of mitral valve prolapse in a large population-based epidemiologic study: the MELEN study. Eur Rev Med Pharmacol Sci. 2015 Jun;19[12]:2208-12.
10. Donal E, Galli E, Letourneau T. Need for expertise in mitral valve regurgitation. Open Heart. 2019;6[1]:e001039.
11. Antoine C, Michelena HI, Enriquez-Sarano M. Mitral valve prolapse: where is the missing link? J Thorac Dis. 2016 Sep;8[9]:2394-6.
12. Jin Y-M, Zhao S-Z, Zhang Z-L, Chen Y, Cheng X, Chuai M, et al. High Glucose Level Induces Cardiovascular Dysplasia During Early Embryo Development. Exp Clin Endocrinol Diabetes. 2019 Oct;127[9]:590-7.
13. Muthukumar L, Jahangir A, Jan MF, Perez Moreno AC, Khandheria BK, Tajik AJ. Association Between Malignant Mitral Valve Prolapse and Sudden Cardiac Death: A Review. JAMA Cardiol. 2020 Sep 1;5[9]:1053—61.
14. Spartalis M, Tzatzaki E, Spartalis E, Athana-siou A, Moris D, Damaskos C, et al. Mitral valve prolapse: an underestimated cause of sudden cardiac death-a current review of the literature. J Thorac Dis. 2017 Dec;9[12]:5390-8.
15. Yedidya I, van Wijngaarden AL, Ajmone Marsan N. Malignant Arrhythmic Mitral Valve Prolapse: A Continuum of Clinical Challenges from Diagnosis to Risk Stratification and Patient Management. J Cardiovasc Dev Dis. 2020 Dec 29;8[1].
16. Han H-C, Ha FJ, Teh AW, Calafiore P, Jones EF, Johns J, et al. Mitral Valve Prolapse and Sudden Cardiac Death: A Systematic Review. J Am Heart Assoc. 2018 Dec 4;7[23]:e010584.
17. Nalliah CJ, Mahajan R, Elliott AD, Haqqani H, Lau DH, Vohra JK, et al. Mitral valve prolapse and sudden cardiac death: a systematic review and meta-analysis. Heart. 2019 Jan;105[2]:144-51.
18. Narayanan K, Uy-Evanado A, Teodorescu C, Reinier K, Nichols GA, Gunson K, et al. Mitral valve prolapse and sudden cardiac arrest in the community. Heart Rhythm. 2016 Feb;13[2]:498-503.
19. Putnam AJ, Kebed K, Mor-Avi V, Rashedi N, Sun D, Patel B, et al. Prevalence of mitral annular disjunction in patients with mitral valve prolapse and severe regurgitation. Int J Cardiovasc Imaging. 2020 Jul;36[7]:1363-70.
20. Tural U, Iosifescu DV. The Prevalence of Mitral Valve Prolapse in Panic Disorder: A Meta-Analy-sis. Psychosomatics. 2019 Aug;60[4]:393-401.
21. Antoine C, Benfari G, Michelena HI, Maalouf JF, Nkomo VT, Thapa P, et al. Clinical Outcome of Degenerative Mitral Regurgitation: Critical Importance of Echocardiographic Quantitative Assessment in Routine Practice. Circulation. 2018 Sep 25;138[13]:1317-26.
22. Badie SM, Rasoulinejad M, Salehi MR, Kochak HE, Alinaghi SAS, Manshadi SAD, et al. Evaluation of Echocardiography Abnormalities in HIV Positive Patients Treated with Antiretroviral Medications. Infect Disord Drug Targets. 2017;17[1]:43-51.
23. Bagardi M, Bionda A, Locatelli C, Cortellari M, Frattini S, Negro A, et al. Echocardiography Evaluation of the Mitral Valve in Cavalier King Charles Spaniels. Animals (Basel). 2020 Aug 19;10[9].
24. Baron Toaldo M, Poser H, Menciotti G, Bat-taia S, Contiero B, Cipone M, et al. Utility of Tissue Doppler Imaging in the Echocardiographic Evaluation of Left and Right Ventricular Function in Dogs with Myxomatous Mitral Valve Disease with or without Pulmonary Hypertension. J Vet Intern Med. 2016 May;30[3]:697-705.
25. Baron Toaldo M, Romito G, Guglielmini C, Diana A, Pelle NG, Contiero B, et al. Prognostic value of echocardiographic indices of left atrial morphology and function in dogs with myxomatous mitral valve disease. J Vet Intern Med. 2018 May;32[3]:914-21.
26. Boswood A, Gordon SG, Häggström J, Wess
G, Stepien RL, Oyama MA, et al. Longitudinal Analysis of Quality of Life, Clinical, Radiographic, Echocar-diographic, and Laboratory Variables in Dogs with Pre-clinical Myxomatous Mitral Valve Disease Receiving Pimobendan or Placebo: The EPIC Study. J Vet Intern Med. 2018 Jan;32[1]:72-85.
27. Gao Z, Bortman JM, Mahmood F, Matyal R, Khabbaz KR. Crossed Swords Sign: A 3-Dimensional Echocardiography Appearance. A A Pract. 2019 Jun 1;12[11]:416-9.
28. Ghulam Ali S, Fusini L, Tamborini G, Mura-tori M, Gripari P, Mapelli M, et al. Detailed Transtho-racic and Transesophageal Echocardiographic Analysis of Mitral Leaflets in Patients Undergoing Mitral Valve Repair. Am J Cardiol. 2016 Jul 1;118[1]:113-20.
29. de Groot-de Laat LE, Ren B, McGhie J, Oei FBS, Strachinaru M, Kirschbaum SWM, et al. The role of experience in echocardiography identification of location and extent of mitral valve prolapse with 2D and 3D echocardiography. Int J Cardiovasc Imaging. 2016 Aug;32[8]:1171-7.
30. Kagiyama N, Shrestha S. Echocardiographic assessment of mitral regurgitation. J Med Ultrason (2001). 2020 Jan;47[1]:59-70.
31. Kamysheva EP, Panova EI, Shestakova GV. [Study of the functional status of the heart in diabetes mellitus based on echocardiographic data]. Kardi-ologiia. 1989 Jan;29[1]:75-8.
32. Kim K-J, Kim H-K, Park J-B, Hwang H-Y, Yoon YE, Kim Y-J, et al. Transthoracic Echocardio-graphic Findings of Mitral Regurgitation Caused by Commissural Prolapse. JACC Cardiovasc Imaging. 2018 Jun;11[6]:925-6.
33. Kopec G, Sobien B, Podolec M, Waligora M, Brozda M, Zarzecka J, et al. The prevalence of abnormal echocardiographic findings in a sample of urban adult population. Kardiol Pol. 2014;72[1]:42-9.
34. Ong G, Connelly KA, Goodman J, Leong-Poi
H, Evangelista V, Levitt K, et al. Echocardiography Assessment of Young Male Draft-Eligible Elite Hockey Players Invited to the Medical and Fitness Combine by the National Hockey League. Am J Cardiol. 2017 Jun 15;119[12]:2088-92.
35. Vairo A, Marro M, De Ferrari GM, Rinaldi M, Salizzoni S. Use of a photo-realism 3D rendering technique to enhance echocardiography visualization of the
anatomical details during beating-heart mitral valve repair. Echocardiography. 2019 Nov;36[11]:2090-3.
36. Wilhelm CM, Truxal KV, McBride KL, Ko-valchin JP, Flanigan KM. Natural history of echocardiography abnormalities in mucopolysaccharidosis III. Mol Genet Metab. 2018 Jun;124[2]:131-4.
37. Wislowska M, Sypula S, Kowalik I. Echocardiography findings, 24-hour electrocardiographic Holter monitoring in patients with rheumatoid arthritis according to Steinbrocker's criteria, functional index, value of Waaler-Rose titre and duration of disease. Clin Rheumatol. 1998;17[5]:369-77.
38. Wislowska M, Sypula S, Kowalik I. Echocar-diographic findings and 24-h electrocardiographic Holter monitoring in patients with nodular and non-nodular rheumatoid arthritis. Rheumatol Int. 1999;18[5-6]:163-9.
39. Abdel-Salam Z, Khalifa M, Ayoub A, Hamdy A, Nammas W. Early changes in longitudinal deformation indices in young asymptomatic patients with type 1 diabetes mellitus: assessment by speckle-tracking echocardiography. Minerva Cardioangiol. 2016 Apr;64[2]:138-44.
40. Altun G, Babaoglu K, Binnetoglu K, Ozsu E, Ye§iltepe Mutlu RG, Hatun §. Subclinical Left Ventricular Longitudinal and Radial Systolic Dysfunction in Children and Adolescents with Type 1 Diabetes Melli-tus. Echocardiography. 2016 Jul;33[7]:1032-9.
41. Ayerst BI, Smith RAA, Nurcombe V, Day AJ, Merry CLR, Cool SM. Growth Differentiation Factor 5-Mediated Enhancement of Chondrocyte Phenotype Is Inhibited by Heparin: Implications for the Use of Hep-arin in the Clinic and in Tissue Engineering Applications. Tissue Eng Part A. 2017 Apr;23[7-8]:275-92.
42. Caglar Acar O, Epcacan S, Uner A, Ece I, Dogan M. Evaluation of left and right ventricular functions using conventional and tissue Doppler echocardi-ography in children with type 1 diabetes mellitus. J Pe-diatr Endocrinol Metab. 2016 Aug 1;29[8]:885-91.
43. El Razaky O, El Amrousy D, Elrifaey S, Elgendy M, Ibrahim W. Three-dimensional speckle tracking echocardiography: Is it the magic wand in the diagnosis of subclinical myocardial dysfunction in children with type 1 diabetes mellitus? Echocardiography. 2018 Oct;35[10]:1657-63.
44. Ernande L, Beaudoin J, Piro V, Meziani S, Scherrer-Crosbie M. Adverse impact of diabetes melli-tus on left ventricular remodelling in patients with chronic primary mitral regurgitation. Arch Cardiovasc Dis. 2018 Sep; 111 [8-9] :487-96.
45. Ifuku M, Takahashi K, Hosono Y, Iso T, Ishi-kawa A, Haruna H, et al. Left atrial dysfunction and stiffness in pediatric and adult patients with Type 1 diabetes mellitus assessed with speckle tracking echocardiography. Pediatr Diabetes. 2020 Oct 22;
46. Jensen MT, Sogaard P, Andersen HU, Gus-tafsson I, Bech J, Hansen TF, et al. Early myocardial impairment in type 1 diabetes patients without known heart disease assessed with tissue Doppler echocardiography: The Thousand & 1 study. Diab Vasc Dis Res. 2016 Jul;13[4]:260-7.
47. Jensen MT, Sogaard P, Gustafsson I, Bech J, Hansen TF, Almdal T, et al. Echocardiography improves prediction of major adverse cardiovascular events in a population with type 1 diabetes and without known heart disease: the Thousand & 1 Study. Diabetologie 2019 Dec;62[12]:2354-64.
48. Nouhravesh N, Andersen HU, Jensen JS, Ros-sing P, Jensen MT. Retinopathy is associated with impaired myocardial function assessed by advanced echo-cardiography in type 1 diabetes patients - The Thousand & 1 Study. Diabetes Res Clin Pract. 2016 Jun;116:263-9.
49. Ozdemir O, Koksoy AY, Bulus AD, Andiran N, Yagli E. The effects of type 1 diabetes mellitus on cardiac functions in children: evaluation by conventional and tissue Doppler echocardiography. J Pediatr Endocrinol Metab. 2016 Dec 1;29[12]:1389-95.
50. Rakha S, Aboelenin HM. Left ventricular functions in pediatric patients with ten years or more type 1 diabetes mellitus: Conventional echocardiography, tissue Doppler, and two-dimensional speckle tracking study. Pediatr Diabetes. 2019 Nov;20[7]:946-54.
51. R0rth R, J0rgensen PG, Andersen HU, Christoffersen C, G0tze JP, K0ber L, et al. Cardiovascular prognostic value of echocardiography and N terminal pro B-type natriuretic peptide in type 1 diabetes: the Thousand & 1 Study. Eur J Endocrinol. 2020 May;182[5]:481-8.
52. Suran D, Kanic V, Naji F, Krajnc I, Cokolic M, Zemljic E, et al. Predictors of early cardiac changes in patients with type 1 diabetes mellitus: An echocardi-ography-based study. Bosn J Basic Med Sci. 2019 Jun 18;19[4]:384-91.
53. Zoppini G, Bergamini C, Trombetta M, Sab-bagh L, Dauriz M, Mantovani A, et al. Increased aortic stiffness index in patients with type 1 diabetes without cardiovascular disease compared to controls. J Endocrinol Invest. 2019 Sep;42[9]:1109-15.
54. Argyropoulos AJ, Robichaud P, Balimunkwe RM, Fisher GJ, Hammerberg C, Yan Y, et al. Alterations of Dermal Connective Tissue Collagen in Diabetes: Molecular Basis of Aged-Appearing Skin. PLoS One. 2016;11[4]:e0153806.
55. Boudoulas KD, Pitsis AA, Boudoulas H. Floppy Mitral Valve (FMV) - Mitral Valve Prolapse (MVP) - Mitral Valvular Regurgitation and FMV/MVP Syndrome. Hellenic J Cardiol. 2016 Apr;57[2]:73-85.
56. Boudoulas KD, Pitsis AA, Mazzaferri EL, Gumina RJ, Triposkiadis F, Boudoulas H. Floppy mitral valve/mitral valve prolapse: A complex entity with multiple genotypes and phenotypes. Prog Cardiovasc Dis. 2020 Jun;63[3]:308-26.
57. Boudoulas KD, Pitsis AA, Theofilogiannakos EK, Madiai F, Koenig S, Kelpis TG, et al. Floppy Mitral Valve/Mitral Valve Prolapse (FMV/MVP): An un-revealed genotype - Phenotype relationship. Hellenic J Cardiol. 2020 Oct;61[5]:354-6.
58. Lekkala S, Taylor EA, Hunt HB, Donnelly E. Effects of Diabetes on Bone Material Properties. Curr Osteoporos Rep. 2019 Dec;17[6]:455-64.
59. Li P, Wu G. Roles of dietary glycine, proline, and hydroxyproline in collagen synthesis and animal growth. Amino Acids. 2018 Jan;50[1]:29-38.
60. Lima SM, Pitsis AA, Kelpis TG, Shahin MH, Langaee TY, Cavallari LH, et al. Matrix Metallopro-teinase Polymorphisms in Patients with Floppy Mitral Valve/Mitral Valve Prolapse (FMV/MVP) and FMV/MVP Syndrome. Cardiology. 2017;138[3]:179-85.
61. Muona P, Kalliomäki M, Peltonen J. [Diabetes-induced connective tissue changes]. Duodecim. 1993;109[8]:667-71.
62. Muona P, Peltonen J. Connective tissue metabolism in diabetic peripheral nerves. Ann Med. 1994 Feb;26[1]:39-43.
63. Murray CE, Coleman CM. Impact of Diabetes Mellitus on Bone Health. Int J Mol Sci. 2019 Sep 30;20[19].
64. Myers SF, Ross MD. Morphological evidence of vestibular pathology in long-term experimental diabetes mellitus. II. Connective tissue and neuroepithelial pathology. Acta Otolaryngol. 1987 Aug;104[1-2]:40-9.
65. Pietschmann P, Patsch JM, Schernthaner G. Diabetes and bone. Horm Metab Res. 2010 Oct;42[11]:763-8.
66. Skrha J. [Pathogenesis of the connective tissue in diabetes]. Vnitr Lek. 2006 May;52[5]:446-50.
67. Sternberg M, Cohen-Forterre L, Peyroux J. Connective tissue in diabetes mellitus: biochemical alterations of the intercellular matrix with special reference to proteoglycans, collagens and basement membranes. Diabete Metab. 1985 Feb;11[1]:27-50.
68. Woitge HW, Seibel MJ. Markers of Bone and Cartilage Turnover. Exp Clin Endocrinol Diabetes. 2017 Jul;125[7]:454-69.
69. Zamfirov K, Philippe J. [Musculoskeletal complications in diabetes mellitus]. Rev Med Suisse. 2017 Apr 26;13 [560] :917-21.
70. Borel JP. [Techniques for studying collagen in medical practice]. Ann Biol Clin (Paris). 1982;40[5]:551-60.
71. Fernández-Madrid F. Collagen biosynthesis. A review. Clin Orthop Relat Res. 1970 Feb;68:163-81.
72. Frey J, Farjanel J, Crouzet B. [Study in vitro of the biosynthesis and incorporation of hydroxyproline into soluble and insoluble collagen in liver, aorta, and cutaneous tissue]. Bull Soc Chim Biol (Paris). 1969 Jul 25;51[3]:471-9.
73. Fujimoto D. [Biosynthesis of hydroxyproline of collagen]. Tanpakushitsu Kakusan Koso. 1966 Oct;11[12]:1151-9.
74. Grant ME, Prockop DJ. The biosynthesis of collagen. 1. N Engl J Med. 1972 Jan 27;286[4]:194-9.
75. Grant ME, Prockop DJ. The biosynthesis of collagen. 2. N Engl J Med. 1972 Feb 3;286[5]:242-9.
76. Grant ME, Prockop DJ. The biosynthesis of collagen. 3. N Engl J Med. 1972 Feb 10;286[6]:291-300.
77. Gross J. Collagen biology: structure, degradation, and disease. Harvey Lect. 1974;68:351-432.
78. Juva K. Hydroxylation of proline in the biosynthesis of collagen. An experimental study with
chick embryo and granulation tissue of rat. Acta Physiol Scand Suppl. 1968;308:1-73.
79. Karna E, Szoka L, Huynh TYL, Palka JA. Pro-line-dependent regulation of collagen metabolism. Cell Mol Life Sci. 2020 May;77[10]:1911-8.
80. §ahin M, Aydin H, Altun A, Derin ME, §ahin A. The Effects of Tofacitinib-Mediated Janus Ki-nase/Signal Transducers and Activators of the Transcription Signal Pathway Inhibition on Collagen Biosynthesis in Hepatic and Skin Fibroblast Cell Culture. Arch Rheumatol. 2020 Sep;35[3]:343-50.
81. Sipila KH, Drushinin K, Rappu P, Jokinen J, Salminen TA, Salo AM, et al. Proline hydroxylation in collagen supports integrin binding by two distinct mechanisms. J Biol Chem. 2018 May 18;293[20]:7645-58.
82. Udenfriend S. Formation of hydroxyproline in collagen. Science. 1966 Jun 3;152[3727]:1335-40.
83. Vijayasarathy M, Balaram P. Cone snail prolyl-4-hydroxylase a-subunit sequences derived from transcriptomic data and mass spectrometric analysis of variable proline hydroxylation in C. amadis venom. J Proteomics. 2019 Mar 1;194:37-48.
84. Heyns K, Konigsdorf W. [Physiology of poly-peptids containing proline and oxyproline in desamina-tion and destruction. Nitrosoproline and nitrosooxypro-line]. Hoppe Seylers Z Physiol Chem. 1952;290[3-6]:171-6.
85. Buijanadze TV, Veis A. A thermodynamic analysis of the contribution of hydroxyproline to the structural stability of the collagen triple helix. Connect Tissue Res. 1997;36[4]:347-65.
86. Kuznetsova TP, Proshina LI, Privalenko MN. [Modification of the determination of the oxyproline content in the blood serum]. Lab Delo. 1982;[8]:456-9.
87. Akita M, Nishikawa Y, Shigenobu Y, Ambe D, Morita T, Morioka K, et al. Correlation of proline, hydroxyproline and serine content, denaturation temperature and circular dichroism analysis of type I collagen with the physiological temperature of marine tele-osts. Food Chem. 2020 Nov 1;329:126775.
88. Langrock T, Hoffmann R. Analysis of hydroxyproline in collagen hydrolysates. Methods Mol Biol. 2012;828:271-80.
89. Langrock T, Hoffmann R. Analysis of Hydroxyproline in Collagen Hydrolysates. Methods Mol Biol. 2019;2030:47-56.
90. McAnulty RJ. Methods for measuring hydrox-yproline and estimating in vivo rates of collagen synthesis and degradation. Methods Mol Med. 2005;117:189-207.
91. Stegemann H, Stalder K. Determination of hydroxyproline. Clin Chim Acta. 1967 Nov;18[2]:267-73.
92. Taga Y, Kusubata M, Mizuno K. Quantitative Analysis of the Positional Distribution of Hydroxyproline in Collagenous Gly-Xaa-Yaa Sequences by LC-MS with Partial Acid Hydrolysis and Precolumn Deri-vatization. Anal Chem. 2020 Jun 16;92[12]:8427-34.
93. Urazovskaia EV, Mikashinovich ZI, Temni-kov VE, Olempieva EV. [Peptide-bound oxyproline
content in patients with nail hyperkeratosis and lactic acidosis]. Klin Lab Diagn. 2011 Jan;[1]:14-5.
94. Wei Z, Zhou H, Zhang Y, Zhang Q, Zhang W, Mai K. Integrative analysis of transcriptomics and metabolomics profiling on flesh quality of large yellow croaker Larimichthys crocea fed a diet with hydroxy-proline supplementation. Br J Nutr. 2018 Feb;119[4]:359-67.
95. Nikitin IP, Korobkova EN. [Hydroxyproline content in blood and urine in ischemic heart disease]. Kardiologiia. 1977 Aug;17[8]:84-9.
96. Akiduki S, Ito H, Morishita K, Kamimura A. A single-blind, parallel trial of L-hydroxyproline in healthy adult subjects. Urolithiasis. 2015 Jun;43[3]:289-92.
97. Alcock RD, Shaw GC, Burke LM. Bone Broth Unlikely to Provide Reliable Concentrations of Collagen Precursors Compared With Supplemental Sources of Collagen Used in Collagen Research. Int J Sport Nutr Exerc Metab. 2019 May 1;29[3]:265-72.
98. Alcock RD, Shaw GC, Tee N, Burke LM. Plasma Amino Acid Concentrations After the Ingestion of Dairy and Collagen Proteins, in Healthy Active Males. Front Nutr. 2019;6:163.
99. Wu G, Bazer FW, Burghardt RC, Johnson GA, Kim SW, Knabe DA, et al. Proline and hydroxy-proline metabolism: implications for animal and human nutrition. Amino Acids. 2011 Apr;40[4]:1053-63.
100. Delling FN, Rong J, Larson MG, Lehman B, Fuller D, Osypiuk E, et al. Evolution of Mitral Valve Prolapse: Insights From the Framingham Heart Study. Circulation. 2016 Apr 26;133[17]:1688-95.
101. Delling FN, Li X, Li S, Yang Q, Xanthakis V, Martinsson A, et al. Heritability of Mitral Regurgitation: Observations From the Framingham Heart Study and Swedish Population. Circ Cardiovasc Genet. 2017 0ct;10[5].
102. Delling FN, Gona P, Larson MG, Lehman B, Manning WJ, Levine RA, et al. Mild expression of mitral valve prolapse in the Framingham offspring: expanding the phenotypic spectrum. J Am Soc Echocar-diogr. 2014 Jan;27[1]:17-23.
103. Freed LA, Benjamin EJ, Levy D, Larson MG, Evans JC, Fuller DL, et al. Mitral valve prolapse in the general population: the benign nature of echocar-diographic features in the Framingham Heart Study. J Am Coll Cardiol. 2002 Oct 2;40[7]:1298-304.
104. Niu Z, Chan V, Mesana T, Ruel M. The evolution of mitral valve prolapse: insights from the Framingham Heart Study. J Thorac Dis. 2016 Aug;8[8]:E827-828.
105. Savage DD, Levy D, Garrison RJ, Castelli WP, Kligfield P, Devereux RB, et al. Mitral valve prolapse in the general population. 3. Dysrhythmias: the Framingham Study. Am Heart J. 1983 Sep;106[3]:582-6.
106. Savage DD, Devereux RB, Garrison RJ, Castelli WP, Anderson SJ, Levy D, et al. Mitral valve prolapse in the general population. 2. Clinical features: the Framingham Study. Am Heart J. 1983 Sep;106[3]:577-81.
107. Savage DD, Garrison RJ, Devereux RB, Castelli WP, Anderson SJ, Levy D, et al. Mitral valve
prolapse in the general population. 1. Epidemiologic features: the Framingham Study. Am Heart J. 1983 Sep;106[3]:571-6.
108. Цукровий дiабет 1 типу у молодих людей та дорослих [Internet]. [cited 2020 Oct 14]. Available from: https://www.dec.gov.Ua//mtd/czukrovyj-diabet-1 -typu-u-molodyh-lyudej -ta-doroslyh/
109. Unified Clinical Protocol (Type 1 Diabetes Mellitus) [Internet]. [cited 2020 Oct 22]. Available from: https://extra-net.who.int/ncdccs/Data/UKR_D1_%D0%A6%D0%9 4%201.pdf
110. Про затвердження клшчних протоколiв надання медично1 допомоги за спещальнутю "х1рурпя серця i мапстральних судин" [Internet]. Офщшний вебпортал парламенту Украши. [cited 2020 Oct 22]. Available from: https://za-kon.rada.gov.ua/go/v0622282-08
111. Kozanoglu E, Coskun Benlidayi I, Eker Akilli R, Tasal A. Is there any link between joint hyper-mobility and mitral valve prolapse in patients with fibromyalgia syndrome? Clin Rheumatol. 2016 Apr;35[4]:1041-4.
112. Pitcher D, Grahame R. Mitral valve prolapse and joint hypermobility: evidence for a systemic connective tissue abnormality? Ann Rheum Dis. 1982 Aug;41[4]:352-4.
113. Grahame R, Edwards JC, Pitcher D, Gabell A, Harvey W. A clinical and echocardiography study of patients with the hypermobility syndrome. Ann Rheum Dis. 1981 Dec;40[6]:541-6.
114. Leite GCP, Ururahy MAG, Bezerra JF, Lima VMGDM, Costa MIF, Freire SSC, et al. Cardiovascular abnormalities in patients with oral cleft: a clinical-electrocardiographic-echocardiographic study. Clinics (Sao Paulo). 2018;73:e108.
115. Rubino AS, Mignosa C, Di Bartolo M, Ca-vallaro A, Castorina S, Gentile M, et al. [Long-term clinical and echocardiography follow-up of the edge-to-edge technique for surgical mitral valve repair]. G Ital Cardiol (Rome). 2020 Mar;21[3]:209-15.
116. Yousif UN, Bird HA. Haemorrhoids and joint hypermobility: a new extra-articular association. Clin Rheumatol. 2013 Apr;32[4]:523-5.
117. Reimer LCU, Jacobsen JS, Mechlenburg I. Hypermobility among patients with greater trochan-teric pain syndrome. Dan Med J. 2019 Apr;66[4].
118. Steinberg N, Tenenbaum S, Zeev A, Pan-tanowitz M, Waddington G, Dar G, et al. Generalized joint hypermobility, scoliosis, patellofemoral pain, and physical abilities in young dancers. BMC Musculo-skelet Disord. 2021 Feb 9;22[1]:161.
119. Reuter PR, Fichthorn KR. Prevalence of generalized joint hypermobility, musculoskeletal injuries, and chronic musculoskeletal pain among American university students. PeerJ. 2019;7:e7625.
120. Boudoulas H, Kolibash AJ, Baker P, King BD, Wooley CF. Mitral valve prolapse and the mitral valve prolapse syndrome: a diagnostic classification and pathogenesis of symptoms. Am Heart J. 1989 Oct;118[4] :796-818.
121. Le Tourneau T, Mérot J, Rimbert A, Le Scouarnec S, Probst V, Le Marec H, et al. Genetics of
syndromic and non-syndromic mitral valve prolapse. Heart. 2018 Jun;104[12]:978-84.
122. Parwani P, Avierinos J-F, Levine RA, Delling FN. Mitral Valve Prolapse: Multimodality Imaging and Genetic Insights. Prog Cardiovasc Dis. 2017 Dec;60[3]:361-9.
123. Pradella S, Grazzini G, Miele V. Mitral valve prolapse imaging: the role of tissue characterization. Quant Imaging Med Surg. 2020 Dec;10[12]:2396-400.
124. Ermakov S, Gulhar R, Lim L, Bibby D, Fang Q, Nah G, et al. Left ventricular mechanical dispersion predicts arrhythmic risk in mitral valve prolapse. Heart. 2019 Jul;105[14]:1063-9.
125. Scatteia A, Pascale CE, Gallo P, Pezzullo S, America R, Cappelletti AM, et al. Abnormal Papillary Muscle Signal on Cine MRI As a Typical Feature of Mitral Valve Prolapse. Sci Rep. 2020 Jun 8;10[1] :9166.
126. Han H-C, Parsons SA, Teh AW, Sanders P, Neil C, Leong T, et al. Characteristic Histopathological Findings and Cardiac Arrest Rhythm in Isolated Mitral Valve Prolapse and Sudden Cardiac Death. J Am Heart Assoc. 2020 Apr 7;9[7]:e015587.
127. Tonchev I, Luria D, Orenstein D, Lotan C, Biton Y. For Whom the Bell Tolls : Refining Risk Assessment for Sudden Cardiac Death. Curr Cardiol Rep. 2019 Aug 2;21[9]:106.
128. Basso C, Perazzolo Marra M, Rizzo S, De Lazzari M, Giorgi B, Cipriani A, et al. Arrhythmic Mitral Valve Prolapse and Sudden Cardiac Death. Circulation. 2015 Aug 18;132[7]:556-66.
129. Durst R, Gilon D. Imaging of Mitral Valve Prolapse: What Can We Learn from Imaging about the Mechanism of the Disease? J Cardiovasc Dev Dis. 2015 Jul 10;2[3]:165-75.
130. Wunderlich NC, Ho SY, Flint N, Siegel RJ. Myxomatous Mitral Valve Disease with Mitral Valve Prolapse and Mitral Annular Disjunction: Clinical and Functional Significance of the Coincidence. J Cardiovasc Dev Dis. 2021 Jan 24;8[2].
131. Fernández-Friera L, Salguero R, Vannini L, Argüelles AF, Arribas F, Solís J. Mechanistic insights of the left ventricle structure and fibrosis in the ar-rhythmogenic mitral valve prolapse. Glob Cardiol Sci Pract. 2018 Mar 14;2018[1]:4.
132. Çelik SF. Early Impairment Left Ventricular Mechanics in Children With Mitral Valve Prolapse. Am J Cardiol. 2019 Jun 15;123[12]:1992-8.
133. Fukuda S, Song J-K, Mahara K, Kuwaki H, Jang JY, Takeuchi M, et al. Basal Left Ventricular Dilatation and Reduced Contraction in Patients With Mitral Valve Prolapse Can Be Secondary to Annular Dilatation: Preoperative and Postoperative Speckle-Tracking Echocardiography Study on Left Ventricle and Mitral Valve Annulus Interaction. Circ Cardiovasc Imaging. 2016 0ct;9[10].
134. Huttin O, Pierre S, Venner C, Voilliot D, Sellal J-M, Aliot E, et al. Interactions between mitral valve and left ventricle analysed by 2D speckle tracking in patients with mitral valve prolapse: one more piece to the puzzle. Eur Heart J Cardiovasc Imaging. 2017 Mar 1;18[3]:323—31.
135. Khodaei S, Fatouraee N, Nabaei M. Numerical simulation of mitral valve prolapse considering the effect of left ventricle. Math Biosci. 2017 Mar;285:75-80.
136. Osovska NY, Datsyuk OI, Shaprynskyi YV, Shamrai VA, Hruhorenko AM, Chechuha SB, et al. Specific characteristics of intracardiac hemodynamics and vegetative regulation in healthy young individuals with normal heart geometry and concentric remodeling of left ventricle. Wiad Lek. 2017;70[6 pt 1]:1051-6.
137. Saji M, Rossi AM, Ailawadi G, Dent J, Ragosta M, Lim DS. Adjunctive intracardiac echocardiography imaging from the left ventricle to guide percutaneous mitral valve repair with the MitraClip in patients with failed prior surgical rings. Catheter Cardio-vasc Interv. 2016 Feb 1;87[2]:E75-82.
138. Mikashinovich ZI, Urazovskaia EV, Ko-valenko TD. [Peptide-bound oxyproline and the activity of alkaline phosphatase in the serum of women with onychodystrophy]. Klin Lab Diagn. 2009 Jul;[7]:12-4.
139. Askerova TA, Iusifova NA, Gasanova GT, Kerimova AR. [Diagnostic value of the determination of free oxyproline in hereditary and acquired colla-genoses]. Klin Lab Diagn. 2009 Sep;[9]:15-7.
140. Srivastava AK, Khare P, Nagar HK, Raghuwanshi N, Srivastava R. Hydroxyproline: A Potential Biochemical Marker and Its Role in the Patho-genesis of Different Diseases. Curr Protein Pept Sci. 2016;17[6]:596-602.
141. Islam MS, Khunkar SJ, Nakashima S, Sadr A, Nikaido T, Tagami J. Comparative study of demin-eralized collagen degradation determined by hydroxy-proline assay and microscopic depth measurement. J Dent. 2016 Apr;47:94-7.
142. Krane SM. The importance of proline residues in the structure, stability and susceptibility to proteolytic degradation of collagens. Amino Acids. 2008 Nov;35[4]:703-10.
143. Qiu B, Wei F, Sun X, Wang X, Duan B, Shi C, et al. Measurement of hydroxyproline in collagen with three different methods. Mol Med Rep. 2014 Aug;10[2]:1157-63.
144. Rappu P, Salo AM, Myllyharju J, Heino J. Role of prolyl hydroxylation in the molecular interactions of collagens. Essays Biochem. 2019 Sep 13;63[3]:325-35.
145. Gjaltema RAF, Bank RA. Molecular insights into prolyl and lysyl hydroxylation of fibrillar collagens in health and disease. Crit Rev Biochem Mol Biol. 2017 Feb;52[1]:74-95.
146. Perret S, Eble JA, Siljander PR-M, Merle C, Farndale RW, Theisen M, et al. Prolyl hydroxylation of collagen type I is required for efficient binding to integ-rin alpha 1 beta 1 and platelet glycoprotein VI but not to alpha 2 beta 1. J Biol Chem. 2003 Aug 8;278[32]:29873-9.
147. Shi J, Ma X, Gao Y, Fan D, Zhu C, Mi Y, et al. Hydroxylation of Human Type III Collagen Alpha Chain by Recombinant Coexpression with a Viral Prolyl 4-Hydroxylase in Escherichia coli. Protein J. 2017 Aug;36[4]:322-31.
148. Bailey AJ, Kent MJ. Non-enzymatic glyco-sylation of fibrous and basement membrane collagens. Prog Clin Biol Res. 1989;304:109-22.
149. Hennet T. Collagen glycosylation. Curr Opin Struct Biol. 2019 Jun;56:131-8.
150. West CM, van der Wel H, Blader IJ. Detection of cytoplasmic glycosylation associated with hy-droxyproline. Methods Enzymol. 2006;417:389-404.
151. Surazynski A, Miltyk W, Palka J, Phang JM. Prolidase-dependent regulation of collagen biosynthesis. Amino Acids. 2008 Nov;35[4]:731-8.
152. Andreassen BS, Veronesi F, Gerard O, Solberg AHS, Samset E. Mitral Annulus Segmentation Using Deep Learning in 3-D Transesophageal Echocardi-ography. IEEE J Biomed Health Inform. 2020 Apr;24 [4] :994-1003.
153. Ellahham S. Artificial Intelligence: The Future for Diabetes Care. Am J Med. 2020 Aug;133[8]:895-900.
154. Gargeya R, Leng T. Automated Identification of Diabetic Retinopathy Using Deep Learning. Ophthalmology. 2017 Jul;124[7]:962-9.
155. Kokol P, Mernik M, Zavrsnik J, Kancler K, Malcic I. Decision trees based on automatic learning and their use in cardiology. J Med Syst. 1994 Aug;18[4]:201-6.
156. Long H, Liao B, Xu X, Yang J. A Hybrid Deep Learning Model for Predicting Protein Hydrox-ylation Sites. Int J Mol Sci. 2018 Sep 18;19[9].
157. Zavrsnik J, Kokol P, Maleiae I, Kancler K, Mernik M, Bigec M. ROSE: decision trees, automatic learning and their applications in cardiac medicine. Me-dinfo. 1995;8 Pt 2:1688.
158. Zhu T, Li K, Herrero P, Georgiou P. Deep Learning for Diabetes: A Systematic Review. IEEE J Biomed Health Inform. 2020 Nov 24;PP.
FACTORS OF FACIAL DEFECTS RECONSTRUCTIVE SURGERY EFFICIENCY
Valikhnovskyi R.
Surgeon, MD, PhD, Clinic 311 LLC, Kyiv, Ukraine ORCID: 0000-0002-6037-3752
Abstract
The problem of reconstructive surgery for facial defects, its social and economic aspects remain on the agenda in Ukraine and around the world. The study of the factors of effectiveness of reconstructive surgery of facial defects is an urgent problem of plastic surgery, and the implementation of appropriate systematic review allows to determine the status and future prospects and priorities of research in this area. Identification of the main clusters of factors of efficiency of reconstructive surgery of facial defects by conducting a systematic review of the scientific literature on this issue. The systematic review includes the following types of studies: systematic reviews, randomized clinical trials, cohort studies, case-control studies, sectional studies, case studies, case series. Publications that contain data on reconstructive plastic surgery of facial defects. The search was conducted in the following databases: PubMed, Cochrane Library, Scopus, Web of Science. Excel and R software were used for analysis.
According to the inclusion criteria, publications devoted to certain aspects of determining the factors of effectiveness of reconstructive surgery for facial defects were selected. There is a significant predominance (p <0.01) of type studies, in descending order: description of individual cases, series of cases, sectional, "case-control". Factors for the effectiveness of reconstructive surgery of facial defects relate to medical and biological (congenital, acquired) aspects of each individual, environmental factors of natural, man-made nature, organizational and administrative issues, qualifications of medical professionals and technological equipment, as well as psychological status and psychological microclimate etc. The prospect of further research is to conduct an appropriate phase of meta-analysis of data selected at the current stage.
Keywords: reconstructive surgery, plastic surgery, face defects, efficacy, factors.
Background. The problem of reconstructive surgery of facial defects, its social and economic aspects remain on the agenda in Ukraine and around the world [1]. Appearance, especially - the face itself, has a significant impact on everyday life, its quality, professional career of people [2]. For this reason, any change in body image perception can lead to social losses, such as loss of job, status and role, as well as loss of beauty and attractiveness [3, 4]. The perception of the body image is a reflection in the mind of the body image and all the feelings associated with the body. When a person experiences any deformation of appearance or any dysfunction, he experiences an internal conflict between the perceived image of the body at that moment and the expected pattern. Cognitive processes, effectiveness
and response to the concept of self-control change, and self-confidence is lost along with changes in body image perception. Thus, it is important to improve the perception of body image and its deformation and dysfunction in the formation of image perception and self-esteem. Surgical reconstructive treatment of facial defects increases self-confidence and affects the quality of life [5-7].
The face has a symbolic meaning in social and personal relations and is a kind of "window" of the individual into the world. As a result, any dysfunction or deformity of the face adversely affects the appearance and psychology of the individual and leads to concerns about their appearance [8, 9]. Facial interventions in
