Neymark Alexander Izrailevich et al., 2023: The use of intelligent analysis (IA) in determining the tactics of treating patients with nephrolithiasis.

Friday, 17 November 2023

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Department of Urology and Nephrology, Altai State Medical University (Federal State Budgetary Educational Institution of Higher Education), Altai Krai, Russia.
FGBOU VO Krasnoyarsk State Medical University, Krasnoyarsk, Russia.
Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia.

Abstract

Introduction: The use of modern information technologies allows to increase confidence in the choice of a surgical treatment method of kidney stones, as well as to improve the quality of treatment due to an adequate combination of therapeutic techniques.

Materials and methods: In our study we analyzed the treatment results of 625 patients with kidney stones. We created a register with the information on more than 50 parameters for each patient. Each example had an output parameter representing a predefined treatment strategy (extracorporeal shock-wave lithotripsy [ESWL]-1, percutaneous nephrolithotomy [PCNL]-2, pyelolithotomy or nephrolithotomy-3). The initial database served as the basis for training the neural network estimation technique. The aim of our study was to assess the possibility of using neural network algorithms in choosing a method for surgical treatment of urolithiasis.

Results: A prospective study was conducted to assess the clinical effectiveness of implementing the recommendations of the system. The average number of sessions in the group using the neural network assessment technique was 1.4. Residual fragments remained at the time of discharge in seven (15.6%) patients: four in the kidney, three in the lower third of the ureter "stone path." Inversion of therapeutic tactics-PCNL-was performed in four cases. The efficiency of the ESWL was 91.1%. The indicators of the ESWL in the comparison groups differed statistically significantly: in the second group, the efficiency was higher due to more stone fragmentation, with lower energy costs (the average number of sessions was 0.4 less).

Conclusion: The presented technique can be of help for a practicing urologist to choose the optimal treatment method for each patient, thereby minimizing the risk of early postoperative complications.

Urologia. 2023 Apr 3:3915603231162881. doi: 10.1177/03915603231162881. Epub ahead of print. PMID: 37006180.

Comments 1

Peter Alken on Friday, 17 November 2023 08:45

An old study - patient material from 2015/2016 - but an interesting paper as it promises to assist the urologist to read the patients future by health forecasting. On this way to a personalized medicine the data of previously treated patients were used to develop a primary set of 50 parameters. The degree of correlation with the outcome “helped to identified 28 selected parameters that had the greatest impact on the choice of surgical treatment. With “a value of above 0.7, the correlation was recognized as equal, at a value of 0.5-0.7 as average. In cases where the correlation coefficient was less than 0.5, the correlation was considered weak”.

“The most important factors (p 0.01) determining the choice of the surgical treatment method were: seeing the stone in the KUB (0.621), stone number (0.549), smooth contour of the stone (0.522), hyperthermia (0.512), glomerular filtration rate (0.471), the number of WBC in the urine sediment (0.450), obturation of the underlying ureter (0.437), pervious procedures (0.420), the presence of clearances in the shadow of the stone according to radiography (0.392), stone density according to MSCT (0.381), leucocytosis in peripheral blood (0.342), the level of left shift (0.380) and the results of ultrasound data, such as the degree of hydronephrosis (0.340).

Less significant (p 0.05) parameters were the presence of cardiovascular and pulmonary pathology, urea and creatinine levels, the degree of development of subcutaneous fat, the results of bacteriological examination of urine, the presence of an inflection of the ureter below the stone.” 150 patients were split in two groups treated either according to the “old scheme” group 1, or based on the predictive parameters, group 2. Unfortunately, it is not shown what the old scheme was. It must have been very old as 7 of 75 group 1 patients were submitted to open surgery. As also 4 of 75 group 2 patients had open surgery it seems that the system is barely valuable for modern standards.

Peter Alken

“The most important factors (p [img]https://www.storzmedical.com/images/blog/sonderzeichen.jpg[/img]  0.01) determining the choice of the surgical treatment method were: seeing the stone in the KUB  (0.621),  stone number (0.549), smooth contour of the stone (0.522), hyperthermia (0.512), glomerular filtration rate (0.471), the number of WBC in the urine sediment (0.450), obturation of the underlying ureter (0.437), pervious procedures (0.420), the presence of clearances in the shadow of the stone according to radiography (0.392), stone density according to MSCT (0.381), leucocytosis in peripheral blood (0.342), the level of left shift (0.380) and the results of ultrasound data, such as the degree of hydronephrosis (0.340).

Less significant (p [img]https://www.storzmedical.com/images/blog/sonderzeichen.jpg[/img]  0.05) parameters were the presence of cardiovascular and pulmonary pathology, urea and creatinine levels, the degree of development of subcutaneous fat, the results of bacteriological examination of urine, the presence of an inflection of the ureter below the stone.” 150 patients were split in two groups treated either according to the “old scheme” group 1, or based on the predictive parameters, group 2. Unfortunately, it is not shown what the old scheme was. It must have been very old as 7 of 75 group 1 patients were submitted to open surgery. As also 4 of 75 group 2 patients had open surgery it seems that the system is barely valuable for modern standards.

Peter Alken

An old study - patient material from 2015/2016 - but an interesting paper as it promises to assist the urologist to read the patients future by health forecasting. On this way to a personalized medicine the data of previously treated patients were used to develop a primary set of 50 parameters. The degree of correlation with the outcome “helped to identified 28 selected parameters that had the greatest impact on the choice of surgical treatment. With “a value of above 0.7, the correlation was recognized as equal, at a value of 0.5-0.7 as average. In cases where the correlation coefficient was less than 0.5, the correlation was considered weak”. “The most important factors (p [img]https://www.storzmedical.com/images/blog/sonderzeichen.jpg[/img] 0.01) determining the choice of the surgical treatment method were: seeing the stone in the KUB (0.621), stone number (0.549), smooth contour of the stone (0.522), hyperthermia (0.512), glomerular filtration rate (0.471), the number of WBC in the urine sediment (0.450), obturation of the underlying ureter (0.437), pervious procedures (0.420), the presence of clearances in the shadow of the stone according to radiography (0.392), stone density according to MSCT (0.381), leucocytosis in peripheral blood (0.342), the level of left shift (0.380) and the results of ultrasound data, such as the degree of hydronephrosis (0.340). Less significant (p [img]https://www.storzmedical.com/images/blog/sonderzeichen.jpg[/img] 0.05) parameters were the presence of cardiovascular and pulmonary pathology, urea and creatinine levels, the degree of development of subcutaneous fat, the results of bacteriological examination of urine, the presence of an inflection of the ureter below the stone.” 150 patients were split in two groups treated either according to the “old scheme” group 1, or based on the predictive parameters, group 2. Unfortunately, it is not shown what the old scheme was. It must have been very old as 7 of 75 group 1 patients were submitted to open surgery. As also 4 of 75 group 2 patients had open surgery it seems that the system is barely valuable for modern standards. Peter Alken

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