A risk score based on pediatric sequential organ failure assessment predicts 90-day mortality in children with Klebsiella pneumoniae bloodstream infection

Abstract Background: Klebsiella pneumoniae bloodstream infection (Kp-BSI) is a serious threat to pediatric patients. The objective of this study was to explore the risk factors for mortality, validate the prediction efficiency of pediatric sequential organ failure assessment (SOFA) and establish better specific early predictors. Methods: All children diagnosed with Kp-BSI were included in this retrospective cohort study from January 2009 to June 2019. Basic characteristics, symptoms and physical examinations, laboratory statistics, and SOFA at the onset of Kp-BSI were recorded. The Cox proportional hazard model and the receiver operating characteristic curves were used to assess the association of the variables with the 90-day mortality and their predictive values. The DeLong's test of receiver operating characteristic curves and integrated discrimination improvement index were calculated to investigate predictive improvement of the modified SOFA models. A predictive score was developed using multivariate logistic regression. Results: Of the 146 children enrolled, 33 (22.6%) died within 90 days. Hospitalization within the previous six months, intra-abdominal source of bloodstream infection, presence of organ failures, and blood biomarkers including the C-reactive protein, albumin, and lactate were identified as significant risk factors for the 90-day mortality. The area under the curve (AUC) of SOFA for predicting 90-day mortality was 0.80 (95% CI 0.71–0.89). We further found a better combined model when adding hospitalization within the previous six months and intra-abdominal source of bloodstream infection into the SOFA score (AUC = 0.89, 95% CI 0.82–0.96, sensitivity = 0.86, specificity = 0.84). According to this novel risk model, we defined three statistically different groups: low-risk, medium-risk and high-risk groups, with an observed 90-day mortality of 5.4%, 35.7%, and 72.0%, respectively. With the reference of the low-risk group, the medium-risk and high-risk groups had a higher mortality, with hazard ratios of 8.36 (95% CI 3.60–27.83) and 20.27 (95% CI 7.47–54.95), respectively. Conclusions: The modified SOFA model may better predict the 90-day mortality of Kp-BSI. Future perspective studies will be required to validate this novel scoring system in external cohorts.

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A risk score based on pediatric sequential organ failure assessment predicts 90-day mortality in children with Klebsiella pneumoniae bloodstream infection

BMC Infectious Diseases ◽

10.1186/s12879-020-05644-w ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Shuang Li ◽

Jingxian Liu ◽

Feng Chen ◽

Kang Cai ◽

Jintong Tan ◽

...

Keyword(s):

Risk Factors ◽

High Risk ◽

Organ Failure ◽

Operating Characteristic ◽

Pediatric Patients ◽

Risk Groups ◽

Receiver Operating Characteristic Curves ◽

Source Of Infection ◽

Failure Assessment ◽

Medium Risk

Abstract Background Klebsiella pneumoniae bloodstream infection (Kp-BSI) is a serious threat to pediatric patients. The objective of this study was to explore the risk factors, validate the prediction efficiency of pediatric Sequential Organ Failure Assessment (SOFA) and establish better early predictors of mortality in pediatric patients with Kp-BSI. Methods All children diagnosed with Kp-BSI were included in this retrospective cohort study from January 2009 to June 2019. Basic characteristics, symptoms and physical examinations, treatments, laboratory statistics, and SOFA at the onset of Kp-BSI were recorded. The Cox proportional hazard model and receiver operating characteristic curves were used to assess the association between the variables and the 90-day mortality and their predictive value. DeLong’s test of receiver operating characteristic curves and integrated discrimination improvement index were used to determine the improvement in predictive capacity of the modified SOFA models. A predictive score was developed using multivariate logistic regression. Results Of the 146 children enrolled, 33 (22.6%) patients died within 90 days. Hospitalization in the last 6 months, intra-abdominal source of infection, presence of organ failure, and altered levels of blood biomarkers, including C-reactive protein, albumin, and lactate were significant risk factors for 90-day mortality. The area under the curve (AUC) of SOFA for predicting 90-day mortality was 0.80 (95% CI 0.71–0.89). Moreover, we found that a prediction model combining SOFA with two other parameters, namely hospitalization in the last 6 months and intra-abdominal source of infection, was better at predicting mortality (AUC = 0.89, 95% CI 0.82–0.96; sensitivity = 0.86; specificity = 0.84). According to this novel risk model, we defined three statistically different groups: low-risk, medium-risk and high-risk groups, with an observed 90-day mortality of 5.4, 35.7, and 72.0%, respectively. With reference to the low-risk patients, the medium-risk and high-risk groups had a higher mortality, with hazard ratios of 8.36 (95% CI 3.60–27.83) and 20.27 (95% CI 7.47–54.95), respectively. Conclusions The modified SOFA may be better than the original score to predict 90-day mortality in pediatric patients with Kp-BSI. Future prospective studies are required to validate this novel scoring system in external cohorts.

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A risk score based on pediatric Sequential Organ Failure Assessment predicts 90-day mortality in children with Klebsiella pneumoniae bloodstream infection

10.21203/rs.2.23350/v4 ◽

2020 ◽

Author(s):

Shuang Li ◽

Jingxian Liu ◽

Feng Chen ◽

Kang Cai ◽

Jintong Tan ◽

...

Keyword(s):

Risk Factors ◽

High Risk ◽

Organ Failure ◽

Operating Characteristic ◽

Pediatric Patients ◽

Risk Groups ◽

Receiver Operating Characteristic Curves ◽

Source Of Infection ◽

Failure Assessment ◽

Medium Risk

Abstract Background: Klebsiella pneumoniae bloodstream infection (Kp-BSI) is a serious threat to pediatric patients. The objective of this study was to explore the risk factors, validate the prediction efficiency of pediatric Sequential Organ Failure Assessment (SOFA) and establish better early predictors of mortality in pediatric patients with Kp-BSI.Methods: All children diagnosed with Kp-BSI were included in this retrospective cohort study from January 2009 to June 2019. Basic characteristics, symptoms and physical examinations, treatments, laboratory statistics, and SOFA at the onset of Kp-BSI were recorded. The Cox proportional hazard model and receiver operating characteristic curves were used to assess the association between the variables and the 90-day mortality and their predictive value. DeLong’s test of receiver operating characteristic curves and integrated discrimination improvement index were used to determine the improvement in predictive capacity of the modified SOFA models. A predictive score was developed using multivariate logistic regression.Results: Of the 146 children enrolled, 33 (22.6%) patients died within 90 days. Hospitalization in the last six months, intra-abdominal source of infection, presence of organ failure, and altered levels of blood biomarkers, including C-reactive protein, albumin, and lactate were significant risk factors for 90-day mortality. The area under the curve (AUC) of SOFA for predicting 90-day mortality was 0.80 (95% CI 0.71–0.89). Moreover, we found that a prediction model combining SOFA with two other parameters, namely hospitalization in the last six months and intra-abdominal source of infection, was better at predicting mortality (AUC = 0.89, 95% CI 0.82–0.96; sensitivity = 0.86; specificity = 0.84). According to this novel risk model, we defined three statistically different groups: low-risk, medium-risk and high-risk groups, with an observed 90-day mortality of 5.4%, 35.7%, and 72.0%, respectively. With reference to the low-risk patients, the medium-risk and high-risk groups had a higher mortality, with hazard ratios of 8.36 (95% CI 3.60–27.83) and 20.27 (95% CI 7.47–54.95), respectively.Conclusions: The modified SOFA may be better than the original score to predict 90-day mortality in pediatric patients with Kp-BSI. Future prospective studies are required to validate this novel scoring system in external cohorts.

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A risk score based on pediatric Sequential Organ Failure Assessment predicts 90-day mortality in children with Klebsiella pneumoniae bloodstream infection

10.21203/rs.2.23350/v3 ◽

2020 ◽

Author(s):

Shuang Li ◽

Jingxian Liu ◽

Feng Chen ◽

Kang Cai ◽

Jintong Tan ◽

...

Keyword(s):

Risk Factors ◽

High Risk ◽

Organ Failure ◽

Operating Characteristic ◽

Pediatric Patients ◽

Risk Groups ◽

Receiver Operating Characteristic Curves ◽

Source Of Infection ◽

Failure Assessment ◽

Medium Risk

Abstract Background: Klebsiella pneumoniae bloodstream infection (Kp-BSI) is a serious threat to pediatric patients. The objective of this study was to explore the risk factors, validate the prediction efficiency of pediatric Sequential Organ Failure Assessment (SOFA) and establish better early predictors of mortality in pediatric patients with Kp-BSI.Methods: All children diagnosed with Kp-BSI were included in this retrospective cohort study from January 2009 to June 2019. Basic characteristics, symptoms and physical examinations, treatments, laboratory statistics, and SOFA at the onset of Kp-BSI were recorded. The Cox proportional hazard model and receiver operating characteristic curves were used to assess the association between the variables and the 90-day mortality and their predictive value. DeLong’s test of receiver operating characteristic curves and integrated discrimination improvement index were used to determine the improvement in predictive capacity of the modified SOFA models. A predictive score was developed using multivariate logistic regression.Results: Of the 146 children enrolled, 33 (22.6%) patients died within 90 days. Hospitalization in the last six months, intra-abdominal source of infection, presence of organ failure, and altered levels of blood biomarkers, including C-reactive protein, albumin, and lactate were significant risk factors for 90-day mortality. The area under the curve (AUC) of SOFA for predicting 90-day mortality was 0.80 (95% CI 0.71–0.89). Moreover, we found that a prediction model combining SOFA with two other parameters, namely hospitalization in the last six months and intra-abdominal source of infection, was better at predicting mortality (AUC = 0.89, 95% CI 0.82–0.96; sensitivity = 0.86; specificity = 0.84). According to this novel risk model, we defined three statistically different groups: low-risk, medium-risk and high-risk groups, with an observed 90-day mortality of 5.4%, 35.7%, and 72.0%, respectively. With reference to the low-risk patients, the medium-risk and high-risk groups had a higher mortality, with hazard ratios of 8.36 (95% CI 3.60–27.83) and 20.27 (95% CI 7.47–54.95), respectively.Conclusions: The modified SOFA may be better than the original score to predict 90-day mortality in pediatric patients with Kp-BSI. Future prospective studies are required to validate this novel scoring system in external cohorts.

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A risk score based on pediatric Sequential Organ Failure Assessment predicts 90-day mortality in children with Klebsiella pneumoniae bloodstream infection

10.21203/rs.2.23350/v2 ◽

2020 ◽

Author(s):

Shuang Li ◽

Jingxian Liu ◽

Feng Chen ◽

Kang Cai ◽

Jintong Tan ◽

...

Keyword(s):

Risk Factors ◽

High Risk ◽

Organ Failure ◽

Operating Characteristic ◽

Pediatric Patients ◽

Risk Groups ◽

Receiver Operating Characteristic Curves ◽

Source Of Infection ◽

Failure Assessment ◽

Medium Risk

Abstract Background: Klebsiella pneumoniae bloodstream infection (Kp-BSI) is a serious threat to pediatric patients. The objective of this study was to explore the risk factors, validate the prediction efficiency of pediatric Sequential Organ Failure Assessment (SOFA) and establish better early predictors of mortality in pediatric patients with Kp-BSI. Methods: All children diagnosed with Kp-BSI were included in this retrospective cohort study from January 2009 to June 2019. Basic characteristics, symptoms and physical examinations, treatments, laboratory statistics, and SOFA at the onset of Kp-BSI were recorded. The Cox proportional hazard model and receiver operating characteristic curves were used to assess the association between the variables and the 90-day mortality and their predictive value. DeLong's test of receiver operating characteristic curves and integrated discrimination improvement index were used to determine the improvement in predictive capacity of the modified SOFA models. A predictive score was developed using multivariate logistic regression. Results: Of the 146 children enrolled, 33 (22.6%) patients died within 90 days. Hospitalization in the last six months, intra-abdominal source of infection, presence of organ failure, and altered levels of blood biomarkers, including C-reactive protein, albumin, and lactate were significant risk factors for 90-day mortality. The area under the curve (AUC) of SOFA for predicting 90-day mortality was 0.80 (95% CI 0.71–0.89). Moreover, we found that a prediction model combining SOFA with two other parameters, namely hospitalization in the last six months and intra-abdominal source of infection, was better at predicting mortality (AUC = 0.89, 95% CI 0.82–0.96; sensitivity = 0.86; specificity = 0.84). According to this novel risk model, we defined three statistically different groups: low-risk, medium-risk and high-risk groups, with an observed 90-day mortality of 5.4%, 35.7%, and 72.0%, respectively. With reference to the low-risk patients, the medium-risk and high-risk groups had a higher mortality, with hazard ratios of 8.36 (95% CI 3.60–27.83) and 20.27 (95% CI 7.47–54.95), respectively. Conclusions: The modified SOFA may be better than the original score to predict 90-day mortality in pediatric patients with Kp-BSI. Future prospective studies are required to validate this novel scoring system in external cohorts.

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Development and Validation of a Nomogram for Renal Involvement in Primary Sjögren Syndrome Patients: A Retrospective Analysis

Modern Rheumatology ◽

10.1093/mr/roab123 ◽

2021 ◽

Author(s):

Xinshi Huang ◽

Xiaobing Wang ◽

Dinglai Yu

Keyword(s):

Risk Factors ◽

Prediction Model ◽

Receiver Operating Characteristic ◽

Operating Characteristic ◽

Renal Involvement ◽

Calibration Plot ◽

Receiver Operating Characteristic Curves ◽

Logistic Analysis ◽

Validation Set ◽

Multivariate Logistic Analysis

Abstract Objective To establish and validate a nomogram for individualized prediction of renal involvement in pSS patients. Methods A total of 1293 patients with pSS from the First Affiliated Hospital of Wenzhou Medical University between January 2008 to January 2020 were recruited and further analyzed retrospectively. The patients were randomly divided into a development set (70%, n = 910) and a validation set (30%, n = 383). The univariable and multivariate logistic regression were performed to analyze the risk factors of renal involvement in pSS. Based on the regression β coefficients derived from multivariate logistic analysis, an individualized nomogram prediction model was developed. The prediction model of discrimination and calibration was evaluated with the area under the receiver operating characteristic curves and Calibration plot. Results Multivariate logistic analysis showed that hypertension, anemia, albumin, uric acid, anti-Ro52, hematuria and Chisholm-Mason grade were independent risk factors of renal involvement in pSS. The area under the receiver operating characteristic curves were 0.797 and 0.750 respectively in development set and validation set, indicating the nomogram had a good discrimination capacity. The Calibration plot showed nomogram had a strong concordance performance between the prediction probability and the actual probability. Conclusion The individualized nomogram for pSS patients those who had renal involvement could be used by clinicians to predict the risk of pSS patients developing into renal involvement and improve early screening and intervention.

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Prevalence of HIV in Different High-Risk Groups and Associated Risk Factors in Pakistan. A Systematic Review from 2010 to 2020

Archives of Internal Medicine Research ◽

10.26502/aimr.0076 ◽

2021 ◽

Vol 04 (03) ◽

Author(s):

Aswa Gondal ◽

Mahrukh Rasheed ◽

Sana Ali ◽

Zain Ul Abdin ◽

Omar Rahim ◽

...

Keyword(s):

Risk Factors ◽

Systematic Review ◽

High Risk ◽

Risk Groups ◽

Associated Risk Factors

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Abstract P275: Demographic and Clinical Profile of Patients with Risk Factors for Coronary Heart Disease (CHD) Defined by National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP) III Guidelines

Circulation ◽

10.1161/circ.129.suppl_1.p275 ◽

2014 ◽

Vol 129 (suppl_1) ◽

Author(s):

David M Kern ◽

Sanjeev Balu ◽

Ozgur Tunceli ◽

Swetha Raparla ◽

Deborah Anzalone

Keyword(s):

Risk Factors ◽

High Risk ◽

Risk Groups ◽

Lipid Lowering ◽

High Risk Patients ◽

Low Hdl ◽

Risk Patients ◽

Artery Disease ◽

Very High ◽

Statin Use

Introduction: This study aimed to compare the demographic and clinical characteristics of patients with different risk factors for CHD as defined by NCEP ATP III guidelines. Methods: Dyslipidemia patients (≥1 medical claim for dyslipidemia, ≥1 pharmacy claim for a statin, or ≥1 LDL-C value ≥100 mg/dL [index date]) aged ≥18 y were identified from the HealthCore Integrated Research Environment from 1/1/2007-7/31/2012. Patients were classified as low risk (0 or 1 risk factor): hypertension, age ≥45 y [men] or ≥55 y [women], or low HDL-C), moderate/moderately high risk (≥2 risk factors), high risk (having CHD or CHD risk equivalent), or very high risk (having ACS or other established cardiovascular disease plus diabetes or metabolic syndrome). Demographics, comorbidities, medication use and lipid levels during the 12 months prior, and statin use during the 6 months post-index date were compared across risk groups (very high vs each other risk group). Results: There were 1,524,351 low-risk (mean age: 47 y; 45% men), 242,357 moderate-risk (mean age: 58 y; 59% men), 188,222 high-risk (mean age: 57 y; 52% men), and 57,469 very-high-risk (mean age: 63 y; 61% men) patients identified. Mean Deyo-Charlson comorbidity score differed greatly across risk strata: 0.20, 0.33, 1.26, and 2.22 from low to very high risk (p<.0001 for each). Compared with high-risk patients, very-high-risk patients had a higher rate of ischemic stroke: 5.4% vs 4.1%; peripheral artery disease: 17.1% vs 11.6%; coronary artery disease: 8.5% vs 8.2%; and abdominal aortic aneurysm: 2.3% vs 2.0% (p<.05 for each). Less than 1% of the total population had a prior prescription for each non-statin lipid-lowering medication (bile acid sequestrants, fibrates, ezetimibe, niacin, and omega-3). Very-high-risk patients had lower total cholesterol (very-high-risk mean: 194 mg/dL vs 207, 205, and 198 mg/dL for low-, moderate-/moderately-high-, and high-risk patients, respectively) and LDL-C (very-high-risk mean: 110 mg/dL vs 126, 126, and 116 mg/dL for the other risk groups; p<.0001 for each); higher triglycerides (TG) (very-high-risk mean: 206 mg/dL vs 123, 177, and 167 mg/dL for the other groups; p<.0001 for each); and lower HDL-C (very-high-risk mean: 45 mg/dL vs 57 [p<.0001], 45 [p=.006], and 51 mg/dL [p<.0001]). Statin use was low overall (15%), but higher in the very-high-risk group (45%) vs the high- (29%), moderate-/moderately-high- (18%), and low- (12%) risk groups (p<.0001 for each). Conclusions: Despite a large proportion of patients having high lipid levels, statin use after a dyslipidemia diagnosis was low: ≥80% of all patients (and more than half at very high risk) failed to receive a statin, indicating a potentially large population of patients who could benefit from statin treatment. Prior use of non-statin lipid-lowering medications was also low considering the high TG and low HDL-C levels among high-risk patients.

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Postoperative PET/CT for detection of early recurrence (ER) after surgery for squamous cell carcinomas (SCC) of the oral cavity (OC).

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.6060 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 6060-6060

Author(s):

Yao Yu ◽

Heiko Schöder ◽

Jung Kang ◽

Sean Matthew McBride ◽

C. Jillian Tsai ◽

...

Keyword(s):

Risk Factors ◽

Overall Survival ◽

High Risk ◽

Postoperative Radiotherapy ◽

Prospective Trial ◽

Disease Free Survival ◽

Distant Metastases ◽

Risk Groups ◽

Free Survival ◽

Pet Ct

6060 Background: Patients with ER after surgery and prior to postoperative radiation (RT) for SCC of the OC have aggressive biology and poor prognosis. After the introduction of a PET/CT simulator in our department, we incorporated post-operative PET/CT as part of RT planning. We hypothesized PET/CT would improve detection of macroscopic disease before postoperative RT. Methods: We reviewed the medical records of patients treated with postoperative radiotherapy between 2005 and 2019 for OC SCC. Clinicopathologic risk factors were recorded. Intermediate risk factors (IRFs) included pT3-4 disease, nodal disease, perineural invasion (PNI), lymphovascular invasion (LVI), and close ( < 5mm) surgical margins (SM); extranodal extension (ENE) and positive SM were considered high-risk factors (HRF). Patients were stratified into risk groups based upon the number and type of risk factors: 0-1 IRFs, 2 IRFs, ≥3 IRFs, and any HRF. Patients were considered to have ER if they had biopsy confirmed recurrence, or if the imaging or exam was sufficiently suspicious, after discussion with the head and neck team, to warrant treatment to definitive doses of RT (70 Gy). Results: Our cohort included 391 patients with SCC of the OCC who were treated with postoperative radiotherapy. 61% of patients were male, 35% had pT3-4 disease, 36% had pN2a-3 disease, 53% had PNI, 20% had LVI, 30% had ENE, and 14% had positive SM. The most common sites were oral tongue (46%), alveolar ridge (18%), and buccal mucosa (13%). 237 (61%) patients underwent postoperative PET/CT planning, and 165 patients (41%) were planned with CT only. Patients screened with post-operative PET/CT were more likely to be diagnosed with ER (46/237, 19.4%) than those simulated with CT only (6/154, 3.9%, p < 0.0001). Among patients simulated with PET/CT, 7%, 9%, 14%, and 35% of patients were diagnosed with ER for patients with 0-1 IRFs, 2 IRFs, ≥3 IRFs, and any HRF, respectively. Median follow-up was 4.1 years (95% CI 3.6 – 4.5). Among 52 patients with ER, 24 (49.0%) had local, 41 (83.7%) had regional, and 5 (10.2%) had distant recurrence. 17 (33%) of ER were biopsy proven. For patients with ER, 3-year freedom from locoregional recurrence, distant-metastasis free survival, and overall survival were 45.2% (95% CI 32% - 64%), 55% (95% CI 42% – 72%), and 43% (95% CI 30% - 61%), respectively. For patients without ER, use of postoperative PET/CT was associated with improved disease-free survival (HR 0.68, 95% CI 0.46 – 0.98, p = 0.041) and overall survival (HR 0.59, 95% CI 0.38 – 0.91, p = 0.019). Conclusions: Postoperative PET/CT may increase detection ER compared to CT simulation alone and improve risk stratification. Patients with ER are at high risk of locoregional failure, distant metastases, and mortality, despite salvage therapy. A prospective trial is underway at our institution to systemically study the role of PET/CT for detection of ER.

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Machine Learning Algorithms to Predict the Mortality of Carbapenem Resistant Klebsiella Pneumoniae bacteremia

10.21203/rs.2.18733/v1 ◽

2019 ◽

Author(s):

Qiqiang Liang ◽

Fang Qian ◽

Yibing Chen ◽

Zhijun Xu ◽

Zhijiang Xu ◽

...

Keyword(s):

Machine Learning ◽

Risk Factors ◽

Septic Shock ◽

High Risk ◽

Klebsiella Pneumoniae ◽

Severe Thrombocytopenia ◽

Acute Renal Injury ◽

High Risk Factors ◽

Carbapenem Resistant ◽

Logical Regression

Abstract Purpose To establish mortality prediction models in 14 days of Carbapenem-Resistant Klebsiella Pneumoniae bacteremia using Machine learning.Materials and Methods It is a single-center retrospective study. We collect the relevant clinical information of all patients with Carbapenem-Resistant Klebsiella Pneumoniae (CRKP) bacteremia in the past 5 years using the local database. Data analysis and verification are carried out by multiple logical regression, decision tree, random forest, support vector machine (SVM), and XGBoost.Result This study includes 187 patients with 40 related variables. In multiple logical regression, acute renal injury (P=0.003), Apache II score (P=0.036), immunodeficiency (P=0.025), severe thrombocytopenia (P=0.025) and septic shock (P=0.044) are the high-risk factors for 14 days mortality of CRKP bloodstream infections. According to the importance of those parameters, risk scoring is established to predict the survival rate of CRKP bacteremia. The analysis of the five models, with 70% training set and 30% test set, show the comprehensive performance of random forest (AUROC=0.953, precision=91.85%) is slightly better than that of XGBoost (AUROC=0.912, precision=86.41%) and SVM (AUROC=0.936, precision=79.89%) in predicting 14-day mortality of CRKP bacteremia. The multiple logical regression model (AUROC=0.825, precision=81.52%) is the second, and the decision tree model (AUROC=0.712, precision=79.89%) is not very ideal.Conclusion Machine learning has good performances in predicting 14-day mortality of CRKP bacteremia than multiple logical regression. Acute renal injury, severe thrombocytopenia, and septic shock are the high-risk factors of CRKP bacteremia mortality.

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