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

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.

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

10.21203/rs.3.rs-877961/v1 ◽

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.

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A Prognostic Model for Patients With Gastric Signet Ring Cell Carcinoma

Technology in Cancer Research & Treatment ◽

10.1177/15330338211027912 ◽

2021 ◽

Vol 20 ◽

pp. 153303382110279

Author(s):

Qinping Guo ◽

Yinquan Wang ◽

Jie An ◽

Siben Wang ◽

Xiushan Dong ◽

...

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Cox Regression ◽

Signet Ring Cell Carcinoma ◽

Signet Ring Cell ◽

Training Set ◽

Cox Regression Analysis ◽

Signet Ring ◽

Ring Cell ◽

Independent Risk Factors

Background: The aim of our study was to develop a nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with gastric signet ring cell carcinoma (GSRC). Methods: GSRC patients from 2004 to 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database and randomly assigned to the training and validation sets. Multivariate Cox regression analyses screened for OS and CSS independent risk factors and nomograms were constructed. Results: A total of 7,149 eligible GSRC patients were identified, including 4,766 in the training set and 2,383 in the validation set. Multivariate Cox regression analysis showed that gender, marital status, race, AJCC stage, TNM stage, surgery and chemotherapy were independent risk factors for both OS and CSS. Based on the results of the multivariate Cox regression analysis, prognostic nomograms were constructed for OS and CSS. In the training set, the C-index was 0.754 (95% CI = 0.746-0.762) for the OS nomogram and 0.762 (95% CI: 0.753-0.771) for the CSS nomogram. In the internal validation, the C-index for the OS nomogram was 0.758 (95% CI: 0.746-0.770), while the C-index for the CSS nomogram was 0.762 (95% CI: 0.749-0.775). Compared with TNM stage and SEER stage, the nomogram had better predictive ability. In addition, the calibration curves also showed good consistency between the predicted and actual 3-year and 5-year OS and CSS. Conclusion: The nomogram can effectively predict OS and CSS in patients with GSRC, which may help clinicians to personalize prognostic assessments and clinical decisions.

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Preoperative risk factors for postoperative blood transfusion after hip fracture surgery: establishment of a nomogram

Journal of Orthopaedic Surgery and Research ◽

10.1186/s13018-021-02557-5 ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Fu Cheng Bian ◽

Xiao Kang Cheng ◽

Yong Sheng An

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Hip Fracture ◽

Blood Transfusion ◽

Multivariate Logistic Regression ◽

Preoperative Risk ◽

Hip Fracture Surgery ◽

Preoperative Risk Factors ◽

Independent Risk Factors ◽

Fracture Surgery

Abstract Background This study aimed to explore the preoperative risk factors related to blood transfusion after hip fracture operations and to establish a nomogram prediction model. The application of this model will likely reduce unnecessary transfusions and avoid wasting blood products. Methods This was a retrospective analysis of all patients undergoing hip fracture surgery from January 2013 to January 2020. Univariate and multivariate logistic regression analyses were used to evaluate the association between preoperative risk factors and blood transfusion after hip fracture operations. Finally, the risk factors obtained from the multivariate regression analysis were used to establish the nomogram model. The validation of the nomogram was assessed by the concordance index (C-index), the receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and calibration curves. Results A total of 820 patients were included in the present study for evaluation. Multivariate logistic regression analysis demonstrated that low preoperative hemoglobin (Hb), general anesthesia (GA), non-use of tranexamic acid (TXA), and older age were independent risk factors for blood transfusion after hip fracture operation. The C-index of this model was 0.86 (95% CI, 0.83–0.89). Internal validation proved the nomogram model’s adequacy and accuracy, and the results showed that the predicted value agreed well with the actual values. Conclusions A nomogram model was developed based on independent risk factors for blood transfusion after hip fracture surgery. Preoperative intervention can effectively reduce the incidence of blood transfusion after hip fracture operations.

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Monocytes as an Early Predictor for Patients with Acute Paraquat Poisoning: A Retrospective Analysis

BioMed Research International ◽

10.1155/2019/6360459 ◽

2019 ◽

Vol 2019 ◽

pp. 1-7

Author(s):

Yong Zhao ◽

Ya Qi Song ◽

Jie Gao ◽

Shun Yi Feng ◽

Yong Li

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Receiver Operator Characteristic ◽

Monocyte Count ◽

Central Hospital ◽

Predictive Values ◽

Kaplan Meier ◽

Independent Risk Factors ◽

Early Predictor

Background. The predictive values of monocytes in the prognosis of patients with acute paraquat (PQ) poisoning are unclear. This retrospective study investigated the predictive values of monocytes in the prognosis of patients with acute PQ poisoning. Methods. Adult patients who suffered from acute PQ poisoning in the emergency care unit of Cangzhou Central Hospital from May 2012 to December 2018 were enrolled. The patients were divided into groups, namely, survival and nonsurvival, according to a 90-day prognosis. Moreover, correlation, logistic regression, receiver-operator characteristic (ROC), and Kaplan–Meier curve analyses were applied to evaluate the monocyte values used to predict the prognosis of patients with acute PQ poisoning. Result. Among the 109 patients, 45 survived within 90 days after the poisoning, resulting in a 41.28% survival rate. The monocyte count of the nonsurvivors was significantly higher than that of the survivors (P< 0.001). Correlation analysis showed that monocyte count positively correlated with plasma PQ concentration (r= 0.413; P< 0.001) and negatively correlated with survival time (r= 0.512; P< 0.001) and 90-day survival (r= 0.503; P< 0.001). Logistic regression analysis showed that elevated monocytes were the independent risk factors for the 90-day survival. The area under the ROC curve of the monocyte count used to predict the 90-day survival was 0.826 (95% CI: 0.751–0.904), the optimal cut-off was 0.51×109/L, sensitivity was 73.4%, and specificity was 86.7%. Conclusion. This study demonstrated that elevated monocyte count is a useful early predictor of 90-day survival in patients with acute PQ poisoning. However, further studies are warranted to draw firm conclusions.

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Development of Predictive Nomograms for Clinical Use to Quantify the Risk of Amputation in Patients with Diabetic Foot Ulcer

Journal of Diabetes Research ◽

10.1155/2021/6621035 ◽

2021 ◽

Vol 2021 ◽

pp. 1-9

Author(s):

Bocheng Peng ◽

Rui Min ◽

Yiqin Liao ◽

Aixi Yu

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Prediction Model ◽

Predictive Factors ◽

Diabetic Foot ◽

Univariate Analysis ◽

Foot Ulcer ◽

Diabetic Foot Ulcer ◽

Single Factor ◽

Independent Risk Factors

Objective. To determine the novel proposed nomogram model accuracy in the prediction of the lower-extremity amputations (LEA) risk in diabetic foot ulcer (DFU). Methods and Materials. In this retrospective study, data of 125 patients with diabetic foot ulcer who met the research criteria in Zhongnan Hospital of Wuhan University from January 2015 to December 2019 were collected by filling in the clinical investigation case report form. Firstly, univariate analysis was used to find the primary predictive factors of amputation in patients with diabetic foot ulcer. Secondly, single factor and multiple factor logistic regression analysis were employed to screen the independent influencing factors of amputation introducing the primary predictive factors selected from the univariate analysis. Thirdly, the independent influencing factors were applied to build a prediction model of amputation risk in patients with diabetic foot ulcer by using R4.3; then, the nomogram was established according to the selected variables visually. Finally, the performance of the prediction model was evaluated and verified by receiver working characteristic (ROC) curve, corrected calibration curve, and clinical decision curve. Results. 7 primary predictive factors were selected by univariate analysis from 21 variables, including the course of diabetes, peripheral angiopathy of diabetic (PAD), glycosylated hemoglobin A1c (HbA1c), white blood cells (WBC), albumin (ALB), blood uric acid (BUA), and fibrinogen (FIB); single factor logistic regression analysis showed that albumin was a protective factor for amputation in patients with diabetic foot ulcer, and the other six factors were risk factors. Multivariate logical regression analysis illustrated that only five factors (the course of diabetes, PAD, HbA1c, WBC, and FIB) were independent risk factors for amputation in patients with diabetic foot ulcer. According to the area under curve (AUC) of ROC was 0.876 and corrected calibration curve of the nomogram displayed good fitting ability, the model established by these 5 independent risk factors exhibited good ability to predict the risk of amputation. The decision analysis curve (DCA) indicated that the nomogram model was more practical and accurate when the risk threshold was between 6% and 91%. Conclusion. Our novel proposed nomogram showed that the course of diabetes, PAD, HbA1c, WBC, and FIB are the independent risk factors of amputation in patients with DFU. This prediction model was well developed and behaved a great accurate value for LEA so as to provide a useful tool for screening LEA risk and preventing DFU from developing into amputation.

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Nomogram for Predicting COVID-19 Disease Progression Based on Single-Center Data: Observational Study and Model Development (Preprint)

10.2196/preprints.19588 ◽

2020 ◽

Author(s):

Tao Fan ◽

Bo Hao ◽

Shuo Yang ◽

Bo Shen ◽

Zhixin Huang ◽

...

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Clinical Characteristics ◽

Cox Regression ◽

Disease Onset ◽

Lasso Regression ◽

Prediction Ability ◽

Calibration Curves ◽

Independent Risk Factors ◽

Critical Patients

BACKGROUND In late December 2019, a pneumonia caused by SARS-CoV-2 was first reported in Wuhan and spread worldwide rapidly. Currently, no specific medicine is available to treat infection with COVID-19. OBJECTIVE The aims of this study were to summarize the epidemiological and clinical characteristics of 175 patients with SARS-CoV-2 infection who were hospitalized in Renmin Hospital of Wuhan University from January 1 to January 31, 2020, and to establish a tool to identify potential critical patients with COVID-19 and help clinical physicians prevent progression of this disease. METHODS In this retrospective study, clinical characteristics of 175 confirmed COVID-19 cases were collected and analyzed. Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were used to select variables. Multivariate analysis was applied to identify independent risk factors in COVID-19 progression. We established a nomogram to evaluate the probability of progression of the condition of a patient with COVID-19 to severe within three weeks of disease onset. The nomogram was verified using calibration curves and receiver operating characteristic curves. RESULTS A total of 18 variables were considered to be risk factors after the univariate regression analysis of the laboratory parameters (P<.05), and LASSO regression analysis screened out 10 risk factors for further study. The six independent risk factors revealed by multivariate Cox regression were age (OR 1.035, 95% CI 1.017-1.054; P<.001), CK level (OR 1.002, 95% CI 1.0003-1.0039; P=.02), CD4 count (OR 0.995, 95% CI 0.992-0.998; P=.002), CD8 % (OR 1.007, 95% CI 1.004-1.012, P<.001), CD8 count (OR 0.881, 95% CI 0.835-0.931; P<.001), and C3 count (OR 6.93, 95% CI 1.945-24.691; P=.003). The areas under the curve of the prediction model for 0.5-week, 1-week, 2-week and 3-week nonsevere probability were 0.721, 0.742, 0.87, and 0.832, respectively. The calibration curves showed that the model had good prediction ability within three weeks of disease onset. CONCLUSIONS This study presents a predictive nomogram of critical patients with COVID-19 based on LASSO and Cox regression analysis. Clinical use of the nomogram may enable timely detection of potential critical patients with COVID-19 and instruct clinicians to administer early intervention to these patients to prevent the disease from worsening.

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Risk factors affecting the 1-year outcomes of minor ischemic stroke: results from Xi’an stroke registry study of China[1]

10.21203/rs.3.rs-38303/v2 ◽

2020 ◽

Author(s):

Zhongzhong Liu ◽

Wenjuan Lin ◽

Qingli Lu ◽

Jing Wang ◽

Pei Liu ◽

...

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Ischemic Stroke ◽

Multivariate Logistic Regression Analysis ◽

Stroke Recurrence ◽

Multivariate Logistic Regression ◽

Factors Affecting ◽

Nihss Score ◽

Minor Ischemic Stroke ◽

Independent Risk Factors

Abstract Background: The incidences of stroke recurrence, disability, and all-cause death of patients with minor ischemic stroke (MIS) remain problematic. The aim of the present was to identify risk factors associated with adverse outcomes at 1-year after MIS in the Xi’an region of China. Methods: The cohort of this prospective cohort study included MIS patients aged 18–97 years with a National Institutes of Health Stroke Scale (NIHSS) score of ≤ 3 who were treated in any of four hospitals in Xi’an region of China between January and December 2015. The 1-year percentage of stroke recurrence, disability, and all-cause death were evaluated. Multivariate logistic regression analysis was performed to assess the association between the identified risk factors and clinical outcomes. Results: Among the 1,121 patients included for analysis, the percentage of stroke recurrence, disability, and all-cause death at 1 year after MIS were 3.4% (38/1121), 9.3% (104/1121), and 3.3% (37/1121), respectively. Multivariate logistic regression analysis identified age, current smoking, and pneumonia as independent risk factors for stroke recurrence. Age, pneumonia, and alkaline phosphatase were independent risk factors for all-cause death. Independent risk factors for disability were age, pneumonia, NIHSS score on admission, and leukocyte count. Conclusions: The 1-year outcomes of MIS is not optimistic in the Xi’an region of China, especially high percentage of disability. In this study, we found the risk factors affecting 1-year stroke recurrence, disability and, all-cause death which need further verification in the subsequent studies.

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Low serum albumin, aspartate aminotransferase, and body mass are risk factors for frailty in elderly people with diabetes: possible mechanistic role of dehydroepiandrosterone sulfate – a cross-sectional study

10.21203/rs.2.22681/v1 ◽

2020 ◽

Author(s):

Toshihiko Yanase ◽

Ikumi Yanagita ◽

Yuya Fujihara ◽

Chikayo Iwaya ◽

Yuichi Kitajima ◽

...

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Serum Albumin ◽

Body Mass ◽

Aspartate Aminotransferase ◽

Dehydroepiandrosterone Sulfate ◽

Cross Sectional Study ◽

Sectional Study ◽

Cross Sectional ◽

Independent Risk Factors

Abstract Background: Relatively low dehydroepiandrosterone sulfate (DHEA-S) and high cortisol/DHEA ratio have been suggested to be associated with frailty, evaluated using a physical scale. However, the significance of these two hormones for frailty in elderly patients with type 2 diabetes mellitus (T2DM) has not been assessed using a wider range of measures of frailty, including physical, mental, and social indices. Methods: We performed a cross-sectional study to investigate the significance of these two hormones for frailty in elderly T2DM patients (n=148; ≥65 years), using a broad assessment, the clinical frailty scale, and to reevaluate the risk factors for frailty in elderly T2DM patients. We compared parameters between the non-frail and frail groups using the unpaired t and Mann-Whitney U tests. The Jonckheere-Therpstra test was used to identify relationships with the severity of frailty and risk factors were identified using binary regression analysis. Results: Simple regression analysis identified a number of significant risk factors for frailty, including DHEAS <70 µg/dL and cortisol/DHEA-S ratio ≥0.2. Multiple regression analysis showed that low albumin (<4.0 g/dl) (odds ratio [OR]=5.79, p <0.001), low aspartate aminotransferase (AST) activity (<25 IU/L) (OR=4.34, p =0.009), and low body mass (BM) (<53 kg) (OR=3.85, p =0.012) were independent risk factors for frailty. A significant decrease in DHEA-S and a significant increase in the cortisol/DHEA-S ratio occurred alongside increases in the severity of frailty. DHEA-S concentration positively correlated with both serum albumin and BM. Conclusions: Hypoalbuminemia, low AST, and low BM are independent risk factors for frailty in elderly T2DM patients, strongly implying relative malnutrition in these frail patients. DHEA-S may be important for the maintenance of liver function and BM. A decrease in DHEA-S and an increase in the cortisol/DHEAS ratio may be involved in the mechanism of the effect of malnutrition in elderly T2DM patients.

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Risk Factors for Silent Cerebral Infarcts in a Pediatric Sickle Cell Anemia (SCA) Cohort

Blood ◽

10.1182/blood.v112.11.2487.2487 ◽

2008 ◽

Vol 112 (11) ◽

pp. 2487-2487 ◽

Cited By ~ 1

Author(s):

Francoise Bernaudin ◽

Suzanne Verlhac ◽

Annie Kamdem ◽

Cécile Arnaud ◽

Lena Coïc ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Risk Factor ◽

Logistic Regression Analysis ◽

G6pd Deficiency ◽

Significant Risk ◽

Significant Risk Factor ◽

History Of ◽

Independent Risk Factors

Abstract Background Silent infarcts are associated with impaired cognitive functioning and have been shown to be predictors of stroke (Miller ST J Pediatr 2001). Until now, reported risk factors for silent infarcts were low pain event rate, history of seizures, high leukocyte count and Sen bS haplotype (Kinney TR Pediatrics 1999). Here, we seek to define the prevalence and risk factors of silent infarcts in the Créteil SCA pediatric cohort comprising patients assessed at least yearly by transcranial doppler (TCD) since 1992, and by MRI/MRA. Methods This study retrospectively analyzed data from the Créteil cohort stroke-free SS/Sb0 children (280; 134 F, 146 M), according to institutional review board. Time-averaged mean of maximum velocities higher than 200 cm/sec were considered as abnormal, resulting in initiation of a transfusion program (TP). A switch to hydroxyurea was proposed to patients with normalized velocities (< 170 cm/sec) and normal MRA on TP, although TP was re-initiated in case of abnormal velocities recurrence. Patients with “conditional” velocities (170–199 cm/sec) were assessed by TCD 4 times yearly. Alpha genes and beta-globin haplotypes were determined. Baseline biological parameters (G6PD activity; WBC, PMN, Reticulocytes, Platelets counts; Hemoglobin, Hematocrit, HbF, LDH levels; MCV; SpO2) were obtained a minimum of 3 months away from a transfusion, one month from a painful episode, after 12 months of age, before the first TCD, and always before therapy intensification. Results. Patients were followed for a total of 2139 patient-years. Alpha-Thal was present in 114/254 patients (45%) and 27/241 (11.2%) had G6PD deficiency. Beta genotype, available in 240 patients, was BaBa in 102 (42.5%), BeBe in 54 (22.5%), SeSe in 19 (7.9%) and “other” in 65 (27.1%); TCD was abnormal in 52 of 280 patients (18.6%). MRA showed stenoses in 30 of 226 evaluated patients (13.3%) while MRI demonstrated presence of silent infarcts in 81/280 patients (28.9%). Abnormal TCD (p<0.001), G6PD deficiency (p=0.008), high LDH (p=0.03), and low Hb (p=0.026) were significant risk factors for stenoses by univariate analysis while multivariate analysis retained only abnormal TCD as a significant risk factor for stenoses ([OR= 10.6, 95% CI (4.6–24.4)]; p<0.001). Univariate logistic regression analysis showed that the risk of silent infarcts was not related to alpha-Thal, beta genotype, abnormal TCD, WBC, PMN, platelets, reticulocyte counts, MCV, LDH level, HbF %, pain or ACS rates but was significantly associated with stenoses detected by MRA (p<0.001), gender (male; p=0.04), G6PD deficiency (p=0.05), low Hb (p=0.016) and Hct (p=0.012). Multivariate logistic regression analysis showed that gender ([OR= 2.1, 95% CI (1.03–4.27)]; p=0.042), low Hb ([OR= 1.4, 95% CI (1.0–1.1)]; p=0.05) and stenoses ([OR= 4.8, 95% CI (1.88–12.28)]; p=0.001) were all significant independent risk factors for silent infarcts. The presence of stenoses was the only significant risk factor for silent infarcts in patients with a history of abnormal TCD ([OR= 5.9, 95% CI (1.6–21.7)]; p=0.008). Conclusion We recently showed that G6PD deficiency, absence of alpha-Thal, and hemolysis are independent significant risk factors for abnormal TCD in stroke-free SCA patients (Bernaudin et al, Blood, 2008, in press). Here, we report that an abnormal TCD is the most significant risk factor for stenoses and, expanding previous studies, we demonstrate that stenoses, low Hb and gender are significant independent risk factors for silent infarcts.

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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

Medical Radiology and radiation safety ◽

10.12737/article_5ac61d88969a97.33709654 ◽

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).

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