Mathematical Model and Software for Prognosis the of Probability of the Lethal Outcome of Oncosurgical Patients Exposed to Radiation Exposure in the Conditions of Production

2018 ◽  
Vol 63 (2) ◽  
pp. 25-32
Author(s):  
Ю. Удалов ◽  
Yu. Udalov ◽  
Ирина Васильева ◽  
Irina Vasil'eva ◽  
А. Гордиенко ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mathematical Model ◽  
Logistic Regression ◽  
Surgical Treatment ◽  
Ionizing Radiation ◽  
Mathematical Models ◽  
Prognostic Model ◽  
Fisher Criterion ◽  
Lethal Outcome ◽  
Risk Of Death

Purpose: Identification of risk factors that influence the outcome of the patient, their ranking on the contribution to the outcome of treatment, as well as determining the possibility of their additional diagnostic evaluation and correction in the deviation at the preoperative preparation stage with the subsequent construction of a prognostic model. Material and methods: The study included patients who received treatment in the surgical department in A. I. Burnasyan Federal Medical Biophysical Center from January 2009 to July 2017, including workers of nuclear facilities that are exposed to ionizing radiation in professional conditions. The study was conducted in 112 patients, 42 of whom (37.5 %) were men and 70 (62.5 %) women aged 25 to 85 years (59.6 ± 13.2). Among the persons included in the study, 25 men and 26 women were exposed to long-term exposure to ionizing radiation from external sources under production conditions during labor activity within the limits of annual maximum permissible doses, averaged 124.6 ± 10.7 mSv. The work experience under conditions of exposure to ionizing radiation ranged from 5 to 35 years, an average of 24 years. The mean age was 59.1 ± 13.4 years. At the end of hospitalization after surgical treatment, 51 patients were discharged (45.5 %), and 61 (54.5 %) died. In all patients, the parameters of the functioning of various organs and systems were collected, including taking into account the anamnestic data of oncological patients, with differentiation in the final outcome of surgical treatment. To determine the leading risk factors for the lethal outcome of the oncosurgical patient, the Fisher criterion χ2 was used. Based on the leading risk factors for constructing mathematical models, the logistic regression equation was used. The mathematical models were analyzed by researching the area under the ROC curves. Results: Using the Fisher criterion χ2, factors were determined by which the groups of survivors and died patients differ: patient age, body mass index, history of heart rhythm disorders, fraction of cardiac output, Hb level in the blood, presence of protein in urine, INR indicator in coagulograms. Based on the identified factors, twelve mathematical models were constructed using the binary logistic regression method, allowing patients to be divided into groups with the outcomes of hospitalization died / survived after surgery. A mathematical model with the best discriminating ability was chosen. Based on the prognostic model, a decision rule was designed that allows to rank patients into three groups: green (patients with a minimal risk of death), yellow (patients who need preoperative correction), red (patients with the maximum risk of death, decision about surgery is necessary to be solved on a consultation).

scholarly journals Prediction of Death After Multiple Wasp Stings with a Clinical Prognostic Model

2021 ◽  
Author(s):  
Maohe Wang ◽  
Mei Qin ◽  
Amanda Y Wang ◽  
Jia Wei Zhao ◽  
Fei Deng ◽  
...  
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Prognostic Model ◽  
Research Subjects ◽  
Predictive Tool ◽  
Wasp Sting ◽  
Risk Of Death ◽  
Severity Classification ◽  
Wasp Stings ◽  
Independent Risk Factors

Abstract Background: We aimed to assess the utility of the poisoning severity score (PSS) as early prognostic predictors in patients with wasp stings, and to explore a reliable and simple predictive tool for short-term outcomes.Methods: From January 2016 to December 2018, 363 patients with wasp stings in Suining Central Hospital were taken as research subjects. In the first 24h of hospital admission, the PSS and Chinese expert consensus on standardized diagnosis and treatment of wasp stings (CECC) were used as the criterion for severity classification, and their correlation was analyzed. The patients were divided into survival and death groups according to the state of discharge. The factors that affect outcome were analyzed by logistic regression analysis. A clinical prognostic model of death was constructed according to the risk factors, and 1000 times repeated sampling was done to include the data to verify the model internally.Results: The mortality of wasp sting patients was 3.9%. There was a correlation between PSS and CECC (r=0.435, P<0.001) for severity classification. Sex, age, number of stings, and PSS were independent risk factors for death. Based on the 4 independent risk factors screened by the above regression analysis, a nomogram model was constructed to predict the risk of death in wasp sting patients. The predicted value C-index was 0.962, and the internally verified AUC was 0.962(95%C.I. 0.936-0.988, P<0.001).Conclusions: PSS is helpful in the early classification of the severity of wasp stings. Sex, age, number of stings, and PSS were independent risk factors for death in wasp sting patients. The nomogram model established in this study can accurately predict the occurrence of the risk of death.

scholarly journals Clinical Risk Factors and Prognostic Model for Idiopathic Inflammatory Demyelinating Diseases after Haploidentical Hematopoietic Stem Cell Transplantation in Patients with Hematological Malignancies

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 2902-2902
Author(s):  
Rui-Xin Deng ◽  
Yun He ◽  
Xiao-Lu Zhu ◽  
Hai-Xia Fu ◽  
Xiao-Dong Mo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Prognostic Model ◽  
Validation Cohort ◽  
Regression Coefficient ◽  
Risk Group ◽  
Area Under The Curve ◽  
Demyelinating Diseases ◽  
Decision Curve Analysis ◽  
Derivation Cohort ◽  
Risk Of Death

Abstract Introduction As a neurological complication following haploidentical haematopoietic stem cell transplantation (haplo-HSCT), immune-mediated demyelinating diseases (IIDDs) of the central nervous system (CNS) are rare, but they seriously affect a patient's quality of life (J Neurooncol, 2012). Although several reports have demonstrated that IIDDs have a high mortality rate and a poor prognosis (J Neurooncol, 2012; Neurology 2013), a method to predict the outcome of CNS IIDDs after haplo-HSCT is not currently available. Here, we reported the largest research on CNS IIDDs post haplo-HSCT, and we developed and validated a prognostic model for predicting the outcome of CNS IIDDs after haplo-HSCT. Methods We retrospectively evaluated 184 consecutive CNS IIDD patients who had undergone haplo-HSCT at a single center between 2008 and 2019. The derivation cohort included 124 patients receiving haplo-HSCT from 2014 to 2019, and the validation cohort included 60 patients receiving haplo-HSCT from 2008 to 2013. The diagnosis of CNS IIDDs was based on the clinical manifestations and exclusion of other aetiologies, including infection, neurotoxicity, metabolic encephalopathy, ischaemic demyelinating disorders, and tumor infiltration. The final prognostic model selection was performed by backward stepwise logistic regression using the Akaike information criterion. The final model was internally and externally validated using the bootstrap method with 1000 repetitions. We assessed the prognostic model performance by evaluating the discrimination [area under the curve (AUC)], calibration (calibration plot), and net benefit [decision curve analysis (DCA)]. Results In total, 184 of 4532 patients (4.1%) were diagnosed with CNS IIDDs after transplantation. Among them, 120 patients had MS, 53 patients had NMO, 7 patients had ADEM, 3 patients had Schilder's disease, and 1 patient had Marburg disease. Grades II to IV acute graft-versus-host disease (aGVHD) (p&lt;0.001) and chronic GVHD (cGVHD) (p&lt;0.001) were identified as risk factors for developing IIDDs after haplo-HSCT. We also tested immune reconstitution by measuring the following parameters 30, 60, and 90 days after haplo-HSCT: proportions of CD19+ B cells, CD3+ T cells and CD4+ T cells; counts of lymphocytes and monocytes; and levels of immunoglobulins A, G, and M. These parameters showed no significant differences between patients with and without IIDD. CNS IIDDs were significantly associated with higher mortality and a poor prognosis (p＜0.001). In a/the multivariate logistic analysis of the derivation cohort, four candidate predictors were entered into the final prognostic model: cytomegalovirus (CMV) infection, Epstein-Barr virus (EBV) infection, the cerebrospinal fluid (CSF) IgG synthesis index (IgG-Syn), and spinal cord lesions. The value assignment was completed according to the regression coefficient of each identified independent prognostic factor for CNS IIDDs in the derivation cohort to establish the CELS risk score model. According to the regression coefficient, point values were given to each factor based on the log scale, and 1 point was awarded for each variable. These 4 factors determined the total risk score, ranging from 0 to 4. There was a higher risk of death in IIDD patients with higher CELS scores and we, therefore, defined three levels of risk of death in IIDD patients: a low-risk group for patients with a score of 0, a medium-risk group for patients with a total score of 1 or 2, and a high-risk group for patients with a total score of 3 or 4. The prognostic model had an area under the curve of 0.864 (95% CI: 0.803-0.925) in the internal validation cohort and 0.871 (95% CI: 0.806-0.931) in the external validation cohort. The calibration plots showed a high agreement between the predicted and observed outcomes. Decision curve analysis indicated that IIDD patients could benefit from the clinical application of the prognostic model. Conclusion s We identified the risk factors for IIDD onset after haplo-HSCT, and we also developed and validated a reliable prediction model, namely, the CELS, to accurately assess the outcome of IIDD patients after haplo-HSCT. Identifying IIDD patients who are at a high risk of death can help physicians treat them in advance, which will improve patient survival and prognosis. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

scholarly journals Analysis of risk factors for different types of anesthetic support of newborns and infants with surgical pathology

2020 ◽  
pp. 28-34
Author(s):  
V.I. Snisar ◽  
◽  
O.O. Vlasov ◽  
I.A. Makedonskyy ◽  
◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Logistic Regression ◽  
Surgical Treatment ◽  
Postoperative Period ◽  
Congenital Malformations ◽  
Fatal Case ◽  
The Body ◽  
Surgical Correction ◽  
Simple Logistic

High-quality anesthetic support during surgical correction of congenital malformations of internal organs and the postoperative period in newborns and infants is complicated by concomitant diseases, significantly affects the processes of metabolism, gas exchange, homeostasis, cerebral, peripheral hemodynamics, etc. before, during and after the surgical intervention. Purpose — to identify the leading risk factors associated with death in various types of anesthetic support for newborns and infants during surgical correction of congenital malformations. Materials and methods. The retrospective study included newborns with congenital malformations of the surgical profile, as well as infants who received and continued stepwise surgical treatment for congenital malformations, depending on the chosen combined anesthetic accompaniment (inhalation + regional anesthesia and inhalation + intravenous anesthesia). The study was carried out in the following stages: 1) to conduct surgical treatment and anesthetic support, 2) introduction of the child into anesthesia, 3) the traumatic stage of the operation, 4) within 1 hour after the operation, 5) 24 hours after the operation. Risk factors were determined by simple logistic regression with the calculation of the odds ratio, 95% confidence interval (95% CI). Results. Among the functional indicators of the vital functions of the body of children with congenital disorders before, during, immediately and 24 hours after surgery against the background of combined anesthesia, with a simple logistic regression analysis, the chance of a fatal case increases with deviations from the norm of peripheral saturation — at all stages of surgical support (7.8–15.0 times); cerebral oxygenation of the child — at the moments of induction into anesthesia and in the postoperative period (10.8 at the stage 2, 72.0 times at the stage 4); increased diastolic blood pressure at the stage of induction of the child into anesthesia (1.6 times). Conclusions. To prevent the chances of death under various types of anesthesia for children with congenital malformations during surgical treatment, it is advisable to more closely monitor blood pressure, cerebral, peripheral oximetry and promptly correct the impaired condition of the child. The research was carried out in accordance with the principles of the Helsinki Declaration. The study protocol was approved by the Local Ethics Committee of these Institutes. The informed consent of the patient was obtained for conducting the studies. No conflict of interest was declared by the authors. Key words: newborns, infants, congenital malformations, anesthesia, risk factors.

scholarly journals Lactate Albumin Ratio is Associated with Mortality in Patients with Moderate to Severe Traumatic Brain Injury

2020 ◽  
Author(s):  
Ruoran Wang ◽  
Min He ◽  
Xiaofeng Ou ◽  
Xiaoqi Xie ◽  
Yan Kang
Keyword(s):  
Risk Factors ◽  
Traumatic Brain Injury ◽  
Logistic Regression ◽  
Brain Injury ◽  
Hospital Mortality ◽  
Prognostic Model ◽  
Multivariate Logistic Regression ◽  
Albumin Ratio ◽  
Severe Tbi ◽  
Auc Value

Abstract Background: Traumatic brain injury (TBI) is a serious public health issue all over the world. This study was designed to evaluate the prognostic value of lactate to albumin ratio (LAR) on moderate to severe traumatic brain injury.Methods: Clinical data of 273 moderate to severe TBI patients hospitalized in West China Hospital between May 2015 and January 2018 were collected. Multivariate logistic regression analyses were used to explore risk factors and construct prognostic model of in-hospital mortality in this cohort. Nomogram was drawn to visualize the prognostic model. Receiver operating characteristic (ROC) curve and calibration curve were respectively drawn to evaluate discriminative ability and stability of this model.Results: Non-survivors had higher LAR than survivors (1.0870 vs 0.5286, p<0.001). Results of multivariate logistic regression analysis showed that GCS (OR=0.818, p=0.008), blood glucose (OR=1.232, p<0.001), LAR (OR=1.883, p=0.012), and red blood cell distribution (RDW)-SD (OR=1.179, p=0.004) were independent risk factors of in-hospital mortality in included patients. These four factors were utilized to construct prognostic model. The area under the ROC curve (AUC) value of single lactate and LAR were 0.733 (95%Cl; 0.673-0.794) and 0.780 (95%Cl; 0.725-0.835), respectively. The AUC value of the prognostic model was 0.868 (95%Cl; 0.826-0.909), which was higher than that of LAR (Z=2.5143, p<0.05).Conclusions: LAR is a readily available prognostic marker of moderate to severe TBI patients. Prognostic model incorporating LAR is beneficial for clinicians to evaluate possible progression and make treatment decisions in these patients.

scholarly journals COVID-19 pneumonia in Galicia (Spain): Impact of prognostic factors and therapies on mortality and need for mechanical ventilation

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253465
Author(s):  
Luis Pérez-de-Llano ◽  
Eva María Romay-Lema ◽  
Adolfo Baloira-Villar ◽  
Christian Anchorena ◽  
María Luisa Torres-Durán ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mechanical Ventilation ◽  
Logistic Regression ◽  
Therapeutic Interventions ◽  
Outcome Variable ◽  
Multivariable Logistic Regression Analysis ◽  
Composite Outcome ◽  
Multicenter Observational Study ◽  
Risk Of Death ◽  
Hospital Beds

Introduction This study was aimed to identify risk factors associated with unfavorable outcomes (composite outcome variable: mortality and need for mechanical ventilation) in patients hospitalized in Galicia with COVID-19 pneumonia. Methods Retrospective, multicenter, observational study carried out in the 8 Galician tertiary hospitals. All Patients admitted with confirmed COVID-19 pneumonia from 1st of March to April 24th, 2020 were included. A multivariable logistic regression analysis was performed in order to identify the relationship between risk factors, therapeutic interventions and the composite outcome variable. Results A total of 1292 patients (56.1% male) were included. Two hundred and twenty-five (17.4%) died and 327 (25.3%) reached the main outcome variable. Age [odds ratio (OR) = 1.03 (95% confidence interval (CI): 1.01–1.04)], CRP quartiles 3 and 4 [OR = 2.24 (95% CI: 1.39–3.63)] and [OR = 3.04 (95% CI: 1.88–4.92)], respectively, Charlson index [OR = 1.16 (95%CI: 1.06–1.26)], SaO2 upon admission [OR = 0.93 (95% CI: 0.91–0.95)], hydroxychloroquine prescription [OR = 0.22 (95%CI: 0.12–0.37)], systemic corticosteroids prescription [OR = 1.99 (95%CI: 1.45–2.75)], and tocilizumab prescription [OR = 3.39 (95%CI: 2.15–5.36)], significantly impacted the outcome. Sensitivity analysis using different alternative logistic regression models identified consistently the ratio admissions/hospital beds as a predictor of the outcome [OR = 1.06 (95% CI: 1.02–1.11)]. Conclusion These findings may help to identify patients at hospital admission with a higher risk of death and may urge healthcare authorities to implement policies aimed at reducing deaths by increasing the availability of hospital beds.

Switching to centrifugal pumps may decrease hemolysis rates among pediatric ECMO patients

Perfusion ◽  
2021 ◽  
pp. 026765912098257
Author(s):  
Kevin N Johnson ◽  
Benjamin Carr ◽  
George B Mychaliska ◽  
Ronald B Hirschl ◽  
Samir K Gadepalli
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Centrifugal Pumps ◽  
Single Center ◽  
Free Hemoglobin ◽  
Risk Of Death ◽  
Multivariable Logistic Regression ◽  
Increased Risk ◽  
The Impact ◽  
Significant Factors

Recent advances in ECLS technology have led to the adoption of centrifugal pumps for the majority of patients worldwide. Despite several advantages of centrifugal pumps, they remain controversial because a number of studies have shown increased rates of hemolysis. The aim of this study was to assess the impact of transitioning from roller to centrifugal pumps on hemolysis rates at our center. A retrospective analysis of all pediatric ECMO patients at a single center between 2005 and 2017 was undertaken. Hemolysis was defined as a plasma free hemoglobin >50 mg/dL. Multivariable logistic regression was performed correcting for several factors to determine risk factors for hemolysis and analyze outcomes among patients with hemolysis. Significant findings were those with p < 0.05. A total of 590 patients were identified during the study period. Multivariable logistic regression for risk factors for hemolysis showed roller pumps (OR 1.92, CI 1.11–3.33) and ECMO duration (OR 1.002 per hour, CI 1.00–1.01) to be significant factors. Rates of hemolysis significantly improved following conversion from roller to centrifugal pumps, with significantly lower rates of hemolysis in 2012, 2015, 2016, and 2017 when compared to the historical average with roller pumps from 2005 to 2009 (34.7%). Additionally, hemolysis was associated with an increased risk of death (OR 3.59, CI 2.05–6.29) when correcting for other factors. These data suggest decreasing rates of hemolysis with centrifugal pumps compared to roller pumps. Since hemolysis was also associated with increased risk of death, these data support the switch from roller to centrifugal pumps at ECMO centers.

scholarly journals Risk Factors for In-Hospital Mortality from COVID-19 Among Nursing Home Patients—An Urban Center Experience

2021 ◽  
Vol 1 (S1) ◽  
pp. s48-s48
Author(s):  
Amit Vahia ◽  
Mamta Sharma ◽  
Leonard Johnson ◽  
Ashish Bhargava ◽  
Louis Saravolatz ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Nursing Home ◽  
Hospital Mortality ◽  
Multivariable Analysis ◽  
Case Fatality ◽  
Severe Infection ◽  
Robust Immune Response ◽  
Risk Of Death ◽  
Nursing Home Patients

Background: As the COVID-19 pandemic continues, special attention is focused on high-risk patients. In this study, we assessed the risk factors for COVID-19 mortality in nursing home patients. Methods: In this retrospective cohort study, we reviewed the electronic medical records of SARS-COV-2 PCR–positive nursing-home patients between March 8 and June 14, 2020. The primary outcome was in-hospital mortality. Risk factors were compared between those who were discharged or died using the Student t test, the Mann-Whitney U test, χ2 analysis, and logistic regression. Results: Among 169 hospitalized nursing-home patients, the case fatality rate was 43.2%. The mean age was 72.3 ± 13.8 years; 92 patients (54.4%) were male; and 112 patients (66.3%) were black. Within the first day of hospitalization, 83 (49%) patients developed fever. On admission, 24 (14.2%) patients were hypotensive. Leukopenia, lymphopenia, and thrombocytopenia were present in 20 (12%), 91 (53%), and 40 (23.7%) patients, respectively. Among the inflammatory markers, elevations in CRP and ferritin levels occurred in 79% and 24%, respectively. Intensive care admission was needed for 40 patients (23.7%). Septic shock occurred in 25 patients (14.8%). Patients over the age of 70 were more likely to die than younger patients (OR, 2.2; 95% CI, 1.2– 4.1; P = .20). Patients with a fever on admission were more likely to die than those who were afebrile (OR, 2.03; 95% CI, 1.08–3.8; P = .03). Also, 66.7% hypotensive patients died compared to 39.3% normotensive patients (OR, 3.1; 95% CI, 1.2–7.7 P = .01). Intubated patients died more often than those not intubated, 78.4% versus 33.3%, respectively (OR=7.3, p < 0.001, CI 3.1, 17.2) Factors significantly associated with death included higher mean qSofa (p < 0.001), higher median Charlson scores (0.02), thrombocytopenia (p = 0.04) and lymphocytopenia (0.04). From multivariable logistic regression, independent factors associated with death were Charlson score (OR=1.2, p=0.05), qSofa (OR=2.0, p=0.004), thrombocytopenia (OR = 3.0, p = 0.01) and BMI less than 25 (OR = 3.5, p=0.002). Conclusions: Our multivariable analysis revealed that patients with a greater burden of comorbidities, lower BMI, higher qSOFA sepsis score, and thrombocytopenia had a higher risk of death, perhaps because of severe infection despite a robust immune response.Funding: NoDisclosures: None

scholarly journals Prediction of death after multiple wasp stings with a clinical prognostic model

2021 ◽  
Author(s):  
Maohe Wang ◽  
Mei Qin ◽  
Amanda Y Wang ◽  
Jia Wei Zhao ◽  
Fei Deng ◽  
...  
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Prognostic Model ◽  
Research Subjects ◽  
Predictive Tool ◽  
Wasp Sting ◽  
Risk Of Death ◽  
Severity Classification ◽  
Wasp Stings ◽  
Independent Risk Factors

Abstract Background We aimed to assess the utility of the poisoning severity score (PSS) as early prognostic predictors in patients with wasp stings, and to explore a reliable and simple predictive tool for short-term outcomes. Methods From January 2016 to December 2018, 363 patients with wasp stings in Suining Central Hospital were taken as research subjects. In the first 24h of hospital admission, the PSS and Chinese expert consensus on standardized diagnosis and treatment of wasp stings (CECC) were used as the criterion for severity classification, and their correlation was analyzed. The patients were divided into survival and death groups according to the state of discharge. The factors that affect outcome were analyzed by logistic regression analysis. A clinical prognostic model of death was constructed according to the risk factors, and 1000 times repeated sampling was done to include the data to verify the model internally. Results The mortality of wasp sting patients was 3.9%. There was a correlation between PSS and CECC (r=0.435, P<0.001) for severity classification. Sex, age, number of stings, and PSS were independent risk factors for death. Based on the 4 independent risk factors screened by the above regression analysis, a nomogram model was constructed to predict the risk of death in wasp sting patients. The predicted value C-index was 0.962, and the internally verified AUC was 0.962(95%C.I. 0.936-0.988, P<0.001). Conclusions PSS is helpful in the early classification of the severity of wasp stings. Sex, age, number of stings, and PSS were independent risk factors for death in wasp sting patients. The nomogram model established in this study can accurately predict the occurrence of the risk of death.

scholarly journals HYPERPLASTIC PROCESSES OF ENDOMETRIUM IN WOMEN OF PERIMENOPAUSAL AGE: CLINICAL ASPECTS OF THE PROBLEM

2017 ◽  
Vol 4 (4) ◽  
pp. 201-207
Author(s):  
Dmitry V. Baburin ◽  
A. L Unanyan ◽  
I. S Sidorova ◽  
E. A Kudrina ◽  
A. I Ishchenko
Keyword(s):  
Risk Factors ◽  
Mathematical Model ◽  
Logistic Regression ◽  
Endometrial Cancer ◽  
Malignant Transformation ◽  
Polycystic Ovary ◽  
Treatment Plan ◽  
Significant Risk ◽  
Binary Logistic Regression ◽  
Clinical Aspects

The aim of the study is to identify the most significant clinical and anamnestic risk factors for the onset and progression of endometrial hyperplastic processes and the development of malignant transformation of endometrium in women of perimenopausal age, with taking into account their importance on the basis of statistical analysis. Methods. Based on Spearman’s correlation analysis and determination the degree of dependence of the development of endometrial cancer (from 0 to 1) on clinical-anamnestic and diagnostic risk factors (risk ratio (RR) in groups), there were obtained coefficients for a mathematical model allowing with the use of the binary logistic regression method predict the risk of the appearance of endometrial cancer. Results. The most clinically and statistically significant risk factors for the progression of the pathological process of the endometrium, having a high RR (greater than 1) and a confidence interval of 95% (p < 0.05), are (in the order of significance): recurrence of the endometrial hyperplastic process, obesity, the pronounced blood flow in Ultrasound with color Doppler mapping, polycystic ovary syndrome, abnormal ovarian formations, infertility (primary and secondary), type 2 diabetes mellitus, combined uterine pathology (myoma and/or adenomyosis), hereditary predisposition to cancer development, hypertension, age of 50 years and older. Conclusion. The tactics of the management and treatment of patients with hyperplastic endometrial processes should be based on the detection of the degree of the risk of the progression of pathological processes and the development of the malignant transformation of the endometrium. The study of the individual prognosis of endometrial cancer in patients with hyperplastic endometrial processes currently is becoming increasingly important due to the need to construct a rational treatment plan of the management and performing the follow-up dispensary observation on the basis of a scientifically justified forecast. Results obtained during our work allowed us identify statistically significant risk factors for the development of endometrial cancer. There were obtained coefficients for the creation a reliable mathematical model. With the use of the method of binary logistic regression, it is possible to calculate the risk of developing cancer and choose an effective management tactic for patients with hyperplastic endometrial processes at the perimenopausal age.

scholarly journals Comparative evaluation of different types of anesthesia in surgical treatment of children with congenital defects

2021 ◽  
Vol 26 (1) ◽  
pp. 115-121
Author(s):  
О.О. Vlasov
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Surgical Treatment ◽  
Predictive Model ◽  
Regional Anesthesia ◽  
Surgical Intervention ◽  
Congenital Defects ◽  
Intravenous Anesthesia ◽  
Surgical Interventions ◽  
Combined Anesthesia

In pediatric anesthesiology in surgical interventions various methods of combined anesthesia with a combination of inhalation, regional, and intravenous anesthesia are used. The provision of high-quality anesthetic support in newborns and infants during surgical treatment of congenital defects is complicated by risk factors, concomitant diseases and different pathology conditions. The study of risk factors and their influence on the functional indices of the child's vital activity in prescribing anesthesia at all stages of the surgical intervention will help prevent complications and deaths in children. Aim – to сonduct a comparative assessment of various types of anesthesia for surgical correction of congenital defects in children and create a predictive model of the association of risk factors and deaths in the selected methods of anesthetic support. The retrospective study included 150 newborns and infants with congenital defects of the surgical profile depending on anesthesia (inhalation + regional anesthesia; inhalation + intravenous anesthesia and total intravenous). After identifying and evaluating prognostic variables by simple logistic regression with calculating the odds ratio, stepwise multiple logistic regression analysis was performed and a predictive model of the association of risk factors and deaths with various types of anesthetic management was created. In thoracic operations a combined anesthesia with sevoran and fentanyl was most often used – 20.4%. In abdominal operations, in total anesthetic support with sevoran and regional anesthesia was used– 69.4%, while in urological operations combined total intravenous anesthesia with 2 drugs – 18.4% ranked first. No significant diffe­ren­ces were found between the types of anesthesia in various surgical interventions for congenital pathologies, between the types of surgery and deaths (p = 0.863). To prevent fatalities in various types of surgical intervention and options for anesthetic support of newborns and infants with congenital defects, it is advisable to more closely monitor the cerebral and peripheral oximetry indicators at all stages of treatment and timely correct the impaired condition of the child.

Sign in / Sign up

Export Citation Format

Share Document