Diagnostic Algorithm Research Articles

Disorders of secondary peristalsis are associated with the development of esophagitis.

Disorders of primary peristalsis are associated with a higher percent time pH <4 in the esophagus suggesting poor acid clearance. However, there are no studies of secondary peristalsis and its relationship to microscopic or erosive esophagitis. The goal of this study was to determine the relationship between secondary peristalsis using functional luminal imaging probes (EndoFLIP) and the presence or absence of esophagitis. We reviewed the endoscopic and EndoFLIP 2.0 tracings for 103 consecutive patients including those with a history of upper gastrointestinal surgery undergoing upper endoscopy. Esophagogastric junction (EGJ) distensibility and diameter, repetitive antegrade contraction (RACs) presence and frequency, and occlusive diameters were measured. Measurements were then compared between patients with and without microscopic and/or erosive esophagitis. Means were compared using t-tests. Proportions were compared using Chi-Squared analyses. One hundred and three patients were included (mean age: 14.4 + 6.4 years). Ten patients had erosive esophagitis and 28 patients had microscopic esophagitis. Erosive and microscopic esophagitis were associated with abnormal or absent of RACs (p < 0.001). Occlusive diameters were higher in patients with esophagitis compared to those without (p < 0.001). There was no relationship between EGJ distensibility and the presence of erosive or microscopic esophagitis (p = 0.4). The absence of RACs was the only independent predictor of esophagitis (erosive and microscopic), after controlling for age, proton pump inhibitors (PPI) use and EGJ distensibility (p < 0.001). Abnormal secondary peristalsis is associated with microscopic and gross esophagitis, suggesting that EndoFLIP should be part of the diagnostic algorithm for esophagitis.

Exploring stakeholder perceptions about using artificial intelligence for the diagnosis of rare and atypical infections.

To evaluate critical care provider perspectives about diagnostic practices for rare and atypical infections and the potential for using artificial intelligence (AI) as a decision-support system (DSS). We conducted an anonymous web-based survey among critical care providers at Mayo Clinic Rochester between 11/25/2023 and 1/15/2024, to evaluate their experience with rare and atypical infection diagnostic processes and AI-based DSSs. We also assessed the perceived usefulness of AI-based DSSs, their potential impact on improving diagnostic practices for rare and atypical infections, and the perceived risks and benefits of their use. A total of 47/143 providers completed the survey. 38/47 agreed that there was a delay in diagnosing rare and atypical infections. Among those who agreed, limited assessment of specific patient factors and failure to consider them were the most frequently cited important contributing factors (33/38). 38/47 reported familiarity with the AI-based DSS applications available to critical care providers. Less than half (18/38) thought AI-based DSSs often provided valuable insights for patient care, but almost three quarters (34/47) thought AI-based DDSs often provided valuable insight when specifically asked about their ability to improve the diagnosis of rare and atypical infections. All respondents rated reliability as important in enhancing the perceived utility of AI-based DSSs (47/47) and almost all rated interpretability and integration into the workflow as important (45/47). The primary concern about implementing an AI-based DSS in this context was alert fatigue (44/47). Most critical care providers perceived that there are delays in diagnosing rare infections, indicating inadequate assessment and consideration of the diagnosis as the major contributors. Reliability, interpretability, workflow integration, and alert fatigue emerged as key factors impacting usability of AI-based DSS. These findings will inform the development and implementation of an AI-based diagnostic algorithm to aid in identifying rare and atypical infections.

Guidelines for Rigorous and Reproducible Research on Other Specified Feeding or Eating Disorder: Commentary on Dang et al. (2024).

Dang et al.'s review concludes that atypical anorexia nervosa (atypical AN), purging disorder (PD), and night eating syndrome (NES) are clinically significant and severe eating disorders (EDs). However, findings are unlikely to alter their status in future editions of the DSM due to limitations in the literature to date. Guidelines are offered to promote rigorous and reproducible research on other specified feeding or eating disorder OSFED. First, published research diagnostic criteria for atypical AN, PD, and NES should be consistently used to ensure findings across studies reflect the same conditions. Second, operational definitions are recommended for "recurrent" as at least twice within a 3-month period, minimum duration as at least 1 month, and "significant weight loss" as >5% BMI reduction within 1 month. Third, Thomas's and Gydus's trumping scheme for differential diagnosis of OSFED subcategories is endorsed but should prioritize identifying treatment targets based on medical morbidity over mirroring existing diagnostic algorithms. Fourth, a systematic approach for establishing clinical significance is recommended that explicitly notes medical risk associated with malnutrition, purging and nonpurging behaviors, and relevance of marked distress related to binge eating and body image disturbance. Adoption of these guidelines will facilitate necessary research on clinical utility.

Алгоритмы диагностики дилатации проксимальной грудной аорты в педиатрической практике

Aortic dilation may manifest in childhood subsequently resulting in the formation of an intramural hematoma or dissection. The asymptomatic nature of the disease and the absence of unified echocardiographic algorithms for its detection contribute to its underestimation and the inability to implement timely monitoring of patients. The purpose of this research was to develop algorithms for diagnosing dilation of various parts of the thoracic aorta in children using cardiac ultrasound - echocardiography (ECHO). Materials and methods used: a single-center cross-sectional study had been carried out on the basis of the cardiological department of the Z.A. Bashlyaeva Children’s City Clinical Hospital of the Moscow Department of Healthcare (Moscow, Russia): 11,516 primary ECHO protocols in patients aged 7 and up to 18 y/o, 7.5% (869) of which had records regarding aortic dilation, were identified. 572 with hemodynamically significant CHD were excluded from the study therefore the remaining 297 (76.8% (228) boys) with a median age of 14.2 (11.3; 16.4) y/o were studied for the parameters as follows: internal diameters of the aorta at the level of the sinuses of the Valsalva (SV), sinotubular junction (STJ) and ascending aorta (AAo) in systole. Aortic dilation was defined as a size exceeding 2z at any level, and an aneurysm was defined as exceeding 3z. Results: a total of 116 had a bicuspid aortic valve (BAV), 181 demonstrated a tricuspid valve (TAV) without significant concomitant heart pathology (“idiopathic dilation” (IDAo)). Dilation and AAo aneurysm were more prevalent than in the SV region (73.4% v 28%, р&lt;0.001 and 25.2% v 3.7%, р&lt;0.001, respectively). The presence of BAV was identified as a significant risk factor, in which AAo dilation occurred more frequently than in TAV (1.96 times higher, 95% CI 1.12-3.44, p=0.017) and AAo aneurysm occurred with a 3.07 times higher frequency (95% CI 1.79-5.25 р&lt;0.001). Conclusion: the structure of aortic pathology in children is dominated by AAo dilation. ECHO requires visualization of the entire proximal aorta, not merely the aortic valve and SV that are typically assessed in outpatient practice. Authors represent a diagnostic algorithm and methodological guidelines for assessing the condition of the aorta in children.

Review of Treatment Algorithms in Mycosis Fungoides and Sezary Syndrome

Review of Treatment Algorithms in Mycosis Fungoides and Sezary Syndrome

Treatment of lower-risk myelodysplastic syndromes.

Myelodysplastic neoplasms (MDS) involve clonal hematopoiesis and cellular dysplasia, driven by genetic and epigenetic alterations. Spliceosome mutations and epigenetic dysregulation underscore the intricate pathogenesis of MDS. The bone marrow microenvironment, stromal dysfunction, chronic inflammation, and immune dysregulation contribute to disease progression. This complex pathogenesis underscores the necessity for targeted therapies, offering a personalized medicine approach, particularly in lower-risk patients. The development of risk scores like the International Prognostic Scoring System (PISS), its revision IPSS-R, and the incorporation of molecular genetics in IPSS-M have refined the diagnostic and prognostic framework of MDS. These scoring systems facilitate tailored treatment strategies and better prognostication, especially for lower-risk MDS patients. The progression from IPSS to IPSS-R and now to IPSS-M epitomizes the shift towards personalized medicine in MDS management. In this review we discuss recent developments and positive phase III studies in lower-risk MDS. The review concludes by proposing a treatment algorithm for LR-MDS and highlighting ongoing trials in this heterogeneous patient population.

Improving Diagnostic Yield in Patients with Pulsatile Tinnitus: A Ten-Year Analysis.

To determine the yield of a comprehensive diagnostic algorithm for patients with pulsatile tinnitus (PT) and to review the common etiologies and present clinical pears for their diagnosis. Retrospective chart review of patients with PT from 2013 to 2023. Charts were reviewed for demographic data (age, sex, BMI), side of PT (or bilateral), specialty clinic of initial evaluation, coexistent symptoms in addition to PT, and final diagnosis (or non-diagnosis). Clinical, audiometric, laboratory, and radiographic data were collected. Putative chart diagnoses were reviewed by the authors and deemed likely or unlikely to be the source of the patient's PT. Those with "unlikely" were grouped in the "idiopathic" cohort. The diagnostic algorithm is presented in detail. Two hundred and 90 patients were included for analysis. The overall diagnostic yield was 90.7% for all patients and 95.6% for those patients who completed the recommended workup - a substantial improvement over published rates. Twenty-nine etiologies were identified with the most common etiology was idiopathic intracranial hypertension (IIH). Twenty-one diagnoses comprised no more than 5% of patients. Seventy-three patients (25.2%) had more than one pathology as a potential source for their PT. PT can present a diagnostic challenge to the clinician. The findings of this study, however, reveal that proper evaluation based on obtaining a thorough history, performing a physical examination, coupled with properly directed imaging studies and blood testing can accomplish a high diagnostic yield of at least one potential etiology. 4 Laryngoscope, 2024.

Enhanced QSVM with elitist non‐dominated sorting genetic optimisation algorithm for breast cancer diagnosis

AbstractMachine learning has emerged as a promising method for predicting breast cancer using quantum computation techniques. Quantum machine learning algorithms, such as quantum support vector machines (QSVMs), are demonstrating superior efficiency and economy in tackling complex problems compared to traditional machine learning methods. When compared with classical support vector machine, the quantum machine produces remarkably accurate results. The suggested quantum SVM model in this study effectively resolved the binary classification problem for diagnosing malignant breast cancer. This work introduces an enhanced approach to breast cancer diagnosis by integrating QSVM with elitist non‐dominated sorting genetic optimization (ENSGA), leveraging the strengths of both techniques to achieve more accurate and efficient classification results. ENSGA plays a crucial role in optimising QSVM parameters, ensuring that the model attains the best possible classification accuracy while considering multiple objectives simultaneously. Moreover, the quantum kernel estimation method demonstrated exceptional performance by achieving high accuracy within an impressive execution time of 0.14 in the IBM QSVM simulator. The seamless integration of quantum computation techniques with optimisation strategies such as ENSGA highlights the potential of quantum machine learning in revolutionising the field of healthcare, particularly in the domain of breast cancer diagnosis.

Liver Transplantation for the Cure of Neuroendocrine Liver Metastasis: A Systematic Review with Particular Attention to the Risk Factors of Death and Recurrence

Background/Objectives: Neuroendocrine neoplasms (NEN) are heterogeneous entities. Despite considerable advancement in the field, almost 50% of patients have metastatic disease, when liver transplantation (LT) is one of the possible treatments offering a cure in well-selected patients. Methods: The present study aims to systematically review all the literature from 2000 onwards on using LT for patients with NEN-LM, with particular attention to the risk factors of death and recurrence. Results: LT offers 5-year OS ranging from 52 to 74% and 5-year TFS rates ranging from 39 to 62%, with even better results published from 2009 onwards. The main risk factors for patient deaths are related to unfavorable primary tumor pathology, higher liver involvement, and simultaneous LT and primary resection. Similarly, recurrence is higher related to poor tumor grade and differentiation, and in the case of an older recipient age. Conclusions: Applying uniform criteria and a more in-depth understanding of the relevant prognostic factors contribute to a better selection of candidates for curative LT due to NEN metastases. LT for unresectable or liver-restricted NENs has a relevant place in the treatment algorithm and has achieved excellent results in recent decades, but more international efforts are needed to further improve outcomes.

Evaluation of a Physiologic-Driven Closed-Loop Resuscitation Algorithm in an Animal Model of Hemorrhagic Shock.

Appropriate resuscitation from hemorrhagic shock is critical to restore tissue perfusion and to avoid over-resuscitation. The objective of this study was to test the ability of a closed-loop diagnosis and resuscitation algorithm called resuscitation from shock using functional hemodynamic monitoring using invasive monitoring (ReFit1) and minimally invasive monitoring (ReFit2) to identify, treat, and stabilize a porcine model of severe hemorrhagic shock. We created a ReFit algorithm using dynamic hemodynamic parameters of pulse pressure variation (PPV), stroke volume variation (SVV), dynamic arterial elastance (Eadyn = PPV/SVV), driven by mean arterial pressure (MAP), mixed venous oxygen saturation, and heart rate targets to define the need for fluids, vasopressors, and inotropes. University-based animal laboratory. Twenty-seven female pigs. Anesthetized, intubated, and ventilated (8 mL/kg) pigs were bled at 10 mL/min until a MAP of less than 40 mm Hg, held for 30 minutes, then resuscitated. The ReFit algorithm used the above dynamic parameters to drive computer-controlled infusion pumps to deliver blood, lactated Ringer's solution, norepinephrine, and in ReFit1 dobutamine. In four animals, after initial resuscitation from hemorrhagic shock, the ability of the ReFit1 algorithm to treat acute air embolism-induced pulmonary hypertension and right heart failure was also tested. In 10 ReFit1 and 17 ReFit2 animals, the time to stabilization from shock was not dissimilar to open controlled resuscitation performed by an expert physician (52 ± 12, 50 ± 13, and 60 ± 15 min, respectively) with similar amounts of fluids and norepinephrine needed. In four ReFit1 animals after initial stabilization, the algorithm successfully resuscitated the animals after inducing an acute air embolism right heart failure, with all animals recovering stability within 30 minutes. Our physiologically based functional hemodynamic monitoring-centered closed-loop resuscitation system can effectively diagnose and treat cardiovascular shock due to hemorrhage and air embolism.

Aneurism of the left portal vein branch in a teenager - a rare clinical case

The authors presented their own clinical observation of an aneurysm of the left portal vein branch in a teenager with a long-term asymptomatic course. Reduced serum concentrations of ceruloplasmin and α-1-antitrpsin made diagnostic search difficult, which could lead to incorrect therapeutic decisions. However, the results of imaging methods allowed us to establish the root cause of liver damage and its cirrhotic transformation. Vascular aneurysms of the portal vein system are a very rare pathology, and it should be taken into account in the differential diagnostic algorithm while excluding other, more obvious causes of liver pathology.

Challenges in the diagnostics of mantle cell lymphoma in an elderly comorbid patient

We present a case of a rare lymphoproliferative disease diagnosed while differentiating between the causes of exudative-constrictive pericarditis. An 83-year old man was hospitalized with shortness of breath, edema and newly diagnosed atrial fibrillation (AF). Initially, the signs and symptoms were interpreted as manifestations of heart failure due to old myocardial infarction, arterial hypertension and AF. However, no significant systolic or diastolic dysfunction of the left ventricle and valve disease were identified and natriuretic peptide level was normal. Despite treatment, dyspnea and edema persisted, and pleural effusion (requiring drainage) and pericardial effusion increased. Repeated echocardiography showed signs of exudative-constrictive pericarditis. We consequently excluded the infectious (tuberculosis) and non-infectious (electrolyte disorders, hypothyroidism, solid tumors) etiologies of effusion. Taking into account the long-standing mediastinal lymphadenopathy (the patient had been previously examined, but the cause not identified), anemia, episodes of low-grade fever, weight loss, and polyneuropathy, a lymphoproliferative disease was suspected. Serum protein electrophoresis identified an M spike in the gamma globulin region. Immunophenotyping of peripheral blood lymphocytes and immunohistochemical examination of bone marrow confirmed the diagnosis of mantle cell lymphoma. The patient was referred for specialized treatment. At 5 months of the follow-up, the therapy was successful, the patient was stable with no cardiac complaints, no edema, and no new AF episodes. The case demonstrates the need to strictly follow differential diagnostic algorithms to identify the causes of nonspecific symptoms beyond one medical specialty.

A Non-Contact AI-Based Approach to Multi-Failure Detection in Avionic Systems

The increasing electrification and integration of advanced controls in modern aircraft designs have significantly raised the number and complexity of installed printed circuit boards (PCBs), posing new challenges for efficient maintenance and rapid failure detection. Despite self-diagnostic features in current avionics systems, circuit damage and multiple simultaneous failures may arise, compromising safety and diagnostic accuracy. To address these challenges, this paper aims to develop a fast, accurate, and non-destructive, multi-failure diagnosis algorithm for PCBs. The proposed method combines a self-attention mechanism with an adaptive graph convolutional neural network to enhance diagnostic precision. A convolutional neural network with residual connections extracts features from scalar magnetic field data, ensuring robust input diversity. The model was tested on a typical dual-phase amplitude boosting circuit with up to four different simultaneous failures, achieving the experimental results of 99.08%, 98.50%, 98.78%, 98.01%, 98.93%, 98.25%, 97.03%, and 99.77% across metrics including overall precision, per-class precision, overall recall, per-class recall, overall F1 measure, and per-class F1 measure. The results demonstrated its effectiveness and feasibility in diagnosing complex PCBs with multiple failures, indicating the algorithm’s potential to improve failure diagnosis performance and offer a promising PCB diagnosis solution in aerospace applications.

Intelligent Diagnosis of Bearing Failures Based on Recurrence Quantification and Energy Difference

Bearing health is key for maintaining good performance and safety in rotating machinery. As the diagnosis of mechanical faults develops toward intelligence and automation, accurate and systematic fault diagnosis algorithms are imperative. Focusing on the diagnosis of rolling bearing failures, this study utilizes a sliding time window to extract essential data segments. A series of signal processing techniques, including filtering, amplitude–frequency analysis, Hilbert envelope analysis, and energy analysis, is applied to establish a comprehensive dataset. For extraction of the hidden properties of the data, the recurrence quantity spectrum is defined for the input of the neural network. The goal is to obtain a cleaner dataset with enhanced features. A convolution neural network is constructed. Different activation functions in the activation layer are compared for better fault diagnosis algorithms. The established feature matrices are specifically defined to accurately identify the subtlest defects of bearings, thereby facilitating early detection. The proposed procedure distinguishes various fault modes. As for the multidimensional complexities of fault signals, this study carries out a comprehensive comparison of energies, recurrence quantification, and amplitude–frequency characteristics of bearing fault detection to assess the accuracy, computational efficiency, and robustness of bearing fault diagnosis. The proposed method and bearing fault detection procedures have potential in practical applications.

A Novel Diagnosis Algorithm of Open Phase Fault in Grid-Connected Transformer for Energy Storage System

A Novel Diagnosis Algorithm of Open Phase Fault in Grid-Connected Transformer for Energy Storage System

Development and Validation of a Diagnostic Algorithm for Down Syndrome Using Birth Certificate and International Classification of Diseases Codes.

We aimed to develop an algorithm that accurately identifies children with Down syndrome (DS) using administrative data. We identified a cohort of children born between 2000 and 2017, enrolled in the Tennessee Medicaid Program (TennCare), who either had DS coded on their birth certificate or had a diagnosis listed using an International Classification of Diseases (ICD) code (suspected DS), and who received care at Vanderbilt University Medical Center, a comprehensive academic medical center, in the United States. Children with suspected DS were defined as having DS if they had (a) karyotype-confirmed DS indicated on their birth certificate; (b) karyotype-pending DS indicated on their birth certificate (or just DS if test type was not specified) and at least two healthcare encounters for DS during the first 6 years of life; or (c) at least three healthcare encounters for DS, with the first and last encounter separated by at least 30 days, during the first six years of life. The positive predictive value (PPV) of the algorithm and 95% confidence interval (CI) were reported. Of the 411 children with suspected DS, 354 (86.1%) were defined as having DS by the algorithm. According to medical chart review, the algorithm correctly identified 347 children with DS (PPV = 98%, 95%CI: 96.0-99.0%). Of the 57 children the algorithm defined as not having DS, 50 (97.7%, 95%CI: 76.8-93.9%) were confirmed as not having DS by medical chart review. An algorithm that accurately identifies individuals with DS using birth certificate data and/or ICD codes provides a valuable tool to study DS using administrative data.

Respiratory sarcopenia: aspects of pathogenesis, approaches to diagnosis

The severe course of infectious and inflammatory diseases of the respiratory system, high rates of morbidity and mortality among the elderly and senile aged people may be associated with respiratory sarcopenia, a new nosological form that describes age-related changes in the strength and structure of the respiratory muscles. The aim of the review is to update the data of open access scientific sources on aspects of pathogenesis and diagnostic approaches to respiratory sarcopenia. Foreign and domestic scientific publications on this topic were analyzed from 2019 to the present. The mechanisms of respiratory sarcopenia pahogenesis were assessed in the light of its relationship with whole body sarcopenia, age-related mechanisms of aging of the respiratory system as a whole, risk factors and lifestyle aspects of the elderly. The currently proposed diagnostic algorithm for respiratory sarcopenia is considered in detail. Conclusion. Age-related changes in muscle tissue also affect the respiratory muscles. Whole-body sarcopenia, according to some authors, may be accompanied by respiratory sarcopenia. The proposed terminology and algorithm for diagnosing this pathology require additional data accumulation and further discussion.

Surgical treatment algorithm for thoracic and lumbar hyperkyphosis in pediatric population.

There is no standardized and universally accepted surgical treatment for thoracic and lumbar hyperkyphosis in children. A surgical treatment algorithm was developed to aid in the choice of the appropriate corrective technique. A retrospective analysis was conducted of patients younger than 18years who underwent primary correction surgery and posterior fusion for thoracic and lumbar hyperkyphosis. Patients were categorized according to the classification of Rajasekaran et al. and divided into 2 groups: a posterior column osteotomies (PCO) group and a three-column osteotomies (3CO) group. We analyzed the angularity and flexibility of the curve, global sagittal balance, and preoperative neurological status of the patient. Forty-nine patients were included. The mean age was 12.8years (1-18) and the mean preoperative kyphosis was 93.5° (40°-175°). In the PCO group (N = 30), the sagittal deformity angular ratio (DAR) was less than 16.5 in 26 patients (86.6%), while in the 3CO group (N = 19), sagittal DAR was greater than 16.5 in 17 patients (89.4%). In the PCO group (N = 28), the T1-Pelvic angle (TPA) was less than 17° in 19 patients (67.8%), while in the 3CO group (N = 15), TPA was greater than 17° in 10 patients (66.6%). Five patients (10.2%) had recent-onset or progressive neurological alteration, all of them (100%) required 3CO. An algorithm for kyphosis was developed based on the classification by Rajasekaran et al., preoperative analysis of the angularity and flexibility of the curve, global sagittal balance and neurological status of the patient, to aid in the choice of the appropriate corrective osteotomy. IV.

Safety and efficacy of tisotumab vedotin with cervical cancers: A systematic review and meta-analysis.

Tisotumab vedotin (TV) holds promise for treating recurrence or metastatic cervical cancer (r/mCC), with recent FDA approval for second-line use in recurrent or metastatic cases. Our research aims to evaluate TV's efficacy and safety in these patients, focusing on overall survival (OS) and progression-free survival (PFS) outcomes. We searched five electronic databases in February 2024, retrieved articles, screened them based on inclusion and exclusion criteria, and assessed their quality. A meta-analysis of the extracted data was performed and applied a random-effects model for our analysis. The search identified 86 articles, with six meeting the inclusion criteria. Meta-analysis revealed 80.8% and 48.0% OS at 6 and 12 months, and a 29.9% PFS at 6 months. Combined treatment with carboplatin or pembrolizumab showed 33.0% PFS at 1 year and 15.1% at 2 years. The objective response rate (ORR) was 21.0%, reaching 43.3% with combined treatment. Confirmed disease control rate (CDCR) was 70.0% overall and in combination. The median duration of response (DOR) was 6.1 months, increasing to 9.5 months in combined treatment, with a consistent time to response (TTR) of 1.4 months. Adverse events included ocular issues (conjunctivitis 30.3%, dry eye 18.7%) and common side effects (nausea 38.4%, epistaxis 35.7%). This systematic review and meta-analysis highlights the potential of TV as a treatment option for r/mCC patients. However, healthcare providers must communicate safety profiles and recommend prophylactic measures for optimal patient outcomes. Further studies, particularly assessing combination treatments, are needed to clarify TV's role in treatment algorithms and improve clinical outcomes.

Biomarkers of renal parenhimal damage in young children with congenital hydronephrosis (literature review).

Enlargement of the fetal renal cavity system occurs in 1-5% of cases during prenatal ultrasound examination and can be caused by congenital hydronephrosis as having pelvi-ureteric junction obstruction, which is one of the most common nosologies in the structure of obstructive uropathy in childhood. The high risk of decreased renal function at the preclinical stage of disease development dictates the need to create highly informative diagnostic programs and treatment algorithms aimed at preventing the development of complications. In this review, we discuss the results of studies on the diagnostic and prognostic value of cytokine biomarkers that are of greatest interest in congenital hydronephrosis in young children, these include: KIM-1, VEGF-A, MCP-1, NGAL, IL-1. The literature search for writing this review was carried out using the Web of Science, PubMed, RSCI, CyberLeninka, Scopus databases.