Differential diagnosis of the mineralogical composition of urinary stones

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Abstract

BACKGROUND: Urolithiasis is a common chronic disease with a high tendency to recurrence. The high rate of stone recurrence determines the clinical importance of metaphylaxis, which requires precise knowledge of the chemical composition of the calculi.

AIM: This work aimed to develop an optimal algorithm for mathematical processing of infrared spectra and differential diagnostic profiles of various mineralogical types of kidney stones.

METHODS: The object of the study comprised 115 kidney stones obtained during surgical treatment of patients with urolithiasis. Reference samples of the corresponding salts constituting kidney stones were used as standards. Pure reference substances were ground in an agate mortar with potassium bromide (KBr) crystals; the resulting mixture was compressed into transparent pellets, and infrared spectra were recorded using a Fourier-transform infrared spectrometer (Shimadzu IR Prestige 21, Japan). In the infrared spectra of the reference standards, the most frequently occurring and most intense absorption bands were selected (34 maxima).

RESULTS: For chemical compounds commonly present in urinary stones, two differential diagnostic profiles were constructed for each compound based on infrared spectral data. Visual comparison of the differential diagnostic profiles of urinary stones with the reference profiles allowed accurate identification of the chemical composition of the calculi in all cases.

CONCLUSION: Differential diagnostic profiles represent individual characteristics of each stone type and can be used to determine its chemical composition and to develop a personalized approach to the metaphylaxis of urolithiasis.

About the authors

Aleksandr S. Gordetsov

Privolzhsky Research Medical University

Email: algordetsov@yandex.ru
ORCID iD: 0000-0002-4767-9108
SPIN-code: 4976-7049

Dr. Sci. (Chemistry), Professor

Russian Federation, Nizhny Novgorod

Olga V. Krasnikova

Privolzhsky Research Medical University

Email: lala-g@yandex.ru
ORCID iD: 0000-0002-4425-1819
SPIN-code: 6752-5470

Cand. Sci. (Biology), Assistant Professor

Russian Federation, Nizhny Novgorod

Olga S. Streltsova

Privolzhsky Research Medical University

Email: strelzova_uro@mail.ru
ORCID iD: 0000-0002-9097-0267
SPIN-code: 9674-0382

MD, Dr. Sci. (Medicine), Professor

Russian Federation, Nizhny Novgorod

Larisa V. Boyarinova

N.A. Semashko Nizhny Novgorod Regional Clinical Hospital

Email: lboyar@yandex.ru
ORCID iD: 0000-0002-3167-795X
SPIN-code: 4334-1674

MD, Dr. Sci. (Biology)

Russian Federation, Nizhny Novgorod

Dmitrii P. Роchtin

N.A. Semashko Nizhny Novgorod Regional Clinical Hospital

Author for correspondence.
Email: dpochtin@mail.ru
ORCID iD: 0000-0003-4634-408X

MD

Russian Federation, Nizhny Novgorod

Valentin N. Krupin

Privolzhsky Research Medical University

Email: vn.krupin@mail.ru
ORCID iD: 0000-0002-4887-4888
SPIN-code: 8892-7661

MD, Dr. Sci. (Medicine), Professor

Russian Federation, Nizhny Novgorod

References

  1. Kaprin AD, Apolikhin OI, Sivkov AV, et al. The incidence of urolithiasis in the Russian Federation from 2005 to 2020. Experimental and Clinical Urology. 2022;15(2):10–17. doi: 10.29188/2222-8543-2022-15-2-10-17 EDN: EATILC
  2. Rule AD, Lieske JC, Li X, et al. The ROKS nomogram for predicting a second symptomatic stone episode. J Am Soc Nephrol. 2014;25(12): 2878–2886. doi: 10.1681/ASN.2013091011
  3. Ferraro PM, Curhan GC, D’Addessi A, Gambaro G. Risk of recurrence of idiopathic calcium kidney stones: analysis of data from the literature. J Nephrol. 2017;30(2):227–233. doi: 10.1007/s40620-016-0283-8 EDN: DSZFFY
  4. Malkhasyan VA, Gazimiev MA, Martov AG, et al. Current state of metaphylaxis of urinary stones in Russian Federation. Urologiia. 2022;(5):46–53. doi: 10.18565/urology.2022.5.46-52 EDN: UXBROY
  5. Chechina IN, Neimark AI, Neimark BA. Pathogenic calculi formation in kidneys and salivary glands. Experimental and Clinical Urology. 2010;(4):30–31. EDN: OPHBFH
  6. Nuraj P, Beqiri A. The pathomorphology of urolithiasis and the chemical analysis of the stones by X-ray diffraction and infrared spectroscopy. Urologiia. 2021;(6):30–34. doi: 10.18565/urology.2021.6.30-34 EDN: AIFIJJ
  7. Gordetsov AS, Krasnikova OV, Streltsova OS, et al. Application of infrared spectroscopy in the diagnosis of urolithiasis. Current Problems in Science and Education. 2020;(6):175. doi: 10.17513/spno.30420 EDN: PZPTQV
  8. Gordetsov AS. Infrared spectroscopy of biological fluids and tissues. Modern Technologies in Medicine. 2010;(1):85–98. EDN: LDHLUH
  9. Golovanov SA. Clinical-biochemical and physicochemical criteria for the course and prognosis of urolithiasis: [dissertation]. Moscow, 2002. 253 p. Available from: https://www.dissercat.com/content/kliniko-biokhimicheskie-i-fiziko-khimicheskie-kriterii-techeniya-i-prognoza-mochekamennoi-bo (In Russ.)
  10. Vinyarskaya IV, Gordetsov AS, Lukushkina EF, et al. The use of infrared spectroscopy in the diagnosis of myocardial diseases in children. Nizhny Novgorod Medical Journal. 2001;(2):47–52.
  11. Krasnov VV, Gordetsov AS. Infrared spectral analysis of a blood serum as a reflection of the metabolic process disturbance level at infectious pathology in children. Modern Technologies in Medicine. 2009;(1):39–43. EDN: KWEBFR
  12. Patent RU No. 2117289/10.08.1998. Gordetsov AS, Ilicheva KV, Tsybusov SN, et al. Method for diagnosing malignant neoplasm formations. EDN: BJWIEL
  13. Kogan LP, Kislitsyn ID, Krasnikova OV, et al. Diagnosis of a disease using the values of statistical functionals calculated from infrared spectroscopic parameters of blood. Modern Technologies in Medicine. 2017;9(4):25–35. doi: 10.17691/stm2017.9.4.03 EDN: VTXJDV
  14. Kogan LP, Fedorov SA, Volvach AE, et al. Prediction of the development of pulmonary embolism in patients with a new coronavirus infection. The Bulletin of Bakoulev Center. Cardiovascular Diseases. 2022;23(3): 322–332. doi: 10.24022/1810-0694-2022-23-3-322-332 EDN: YPGYLL

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