Infections Are Associated with Higher Risk of Venous Thromboembolism in Hospitalized Children with Nephrotic Syndrome

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3811-3811
Author(s):  
Jennifer Goldman ◽  
Shannon L Carpenter ◽  
Ashley K Sherman ◽  
David Selewski ◽  
Mahmoud Kallash ◽  
...  

Abstract Introduction: Although it is known that children with nephrotic syndrome (NS) are at greater risk for certain complications, the frequency of these complications and predisposing risk factors are poorly defined. In particular, nephrotic syndrome has long been considered a hypercoagulable state. Risk for development of venous thromboembolism (VTE) is known to be increased in the setting of an active infection. The objective of this study was to determine the prevalence of infection and VTE among a cohort of hospitalized children with NS, and the association of these complications on outcomes. Methods: Records of hospitalized children with NS admitted to any of 17 participating pediatric hospitals across North America from 2010-2012 were included. Data including demographics, clinical pattern of NS, renal biopsy results, number of hospitalizations, nephrotoxic medication usage, infection and VTE history were recorded. Descriptive statistics were used to determine prevalence of infection and VTE. Wilcoxon rank sum was used to perform comparisons between groups. Logistic regression analysis was utilized to determine predictors of VTE development. Results: Seven-hundred thirty hospitalizations occurred among 370 children. One-hundred forty-eight children (40%) had at least 1 infection with a total of 211 infectious episodes; 11 (3%) had VTE. Those with infection were more likely to have VTE (p = 0.0457). Infections associated with VTE were C. difficile (1 subject), methicillin sensitive S. Aureus (2), Streptococcus pneumoniae (1), and unknown (3). There were no differences between those with and without infection regarding gender or ethnicity. Those with infection were younger at NS diagnosis (3.0 vs. 4.0 years; p = 0.008), and steroid resistant NS was more highly associated with infection than all other clinical diagnoses (steroid-sensitive NS, steroid-dependent NS, other) (p = 0.003). The most common types of infections encountered included peritonitis (23%), pneumonia (22%), and bacteremia (16%). Bacterial pathogens (Streptococcus pneumoniae 41%, Escherichia coli 16%, Clostridium difficile 10%) were most commonly identified. Children with VTE, infection, or both, also required significantly more days in hospital. The median hospital stay for those without infection was 5 days vs. 10 in those with infection (p< 0.0001). Similarly, median hospital days for those without VTE were 6 days as compared to 22 in those with VTE (p < 0.0001). Of those with infection, 13% had an ICU stay compared with 3.3% of those without. Those with VTE also had a median of 4 days in the intensive care unit as compared to 0 days in those without VTE (p < 0.0001). In a logistic regression analysis, only the number of ICU days was predictive of the presence of VTE (OR 1.074, 95% CI 1.013 - 1.138). Conclusions: Children with NS who are hospitalized have high rates of infection. While the rate of VTE was not high in this cohort, presence of VTE was associated with infection. Both infection and VTE were associated with longer hospitalizations and intensive care unit stays. Streptococcus pneumoniae remains the most commonly identified bacterial pathogen in children with nephrotic syndrome, though methicillin sensitive S. Aureus was identified in 2 of 11 patients with VTE. Further studies are needed to identify potentially modifiable risk factors that could minimize these complications in this already high risk population. Disclosures No relevant conflicts of interest to declare.

2020 ◽  
pp. 1-9
Author(s):  
Yichun Cheng ◽  
Nanhui Zhang ◽  
Ran Luo ◽  
Meng Zhang ◽  
Zhixiang Wang ◽  
...  

<b><i>Background:</i></b> Coronavirus disease 2019 (COVID-19) has emerged as a major global health threat with a great number of deaths worldwide. Acute kidney injury (AKI) is a common complication in patients admitted to the intensive care unit. We aimed to assess the incidence, risk factors and in-hospital outcomes of AKI in COVID-19 patients admitted to the intensive care unit. <b><i>Methods:</i></b> We conducted a retrospective observational study in the intensive care unit of Tongji Hospital, which was assigned responsibility for the treatments of severe COVID-19 patients by the Wuhan government. AKI was defined and staged based on Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Mild AKI was defined as stage 1, and severe AKI was defined as stage 2 or stage 3. Logistic regression analysis was used to evaluate AKI risk factors, and Cox proportional hazards model was used to assess the association between AKI and in-hospital mortality. <b><i>Results:</i></b> A total of 119 patients with COVID-19 were included in our study. The median patient age was 70 years (interquartile range, 59–77) and 61.3% were male. Fifty-one (42.8%) patients developed AKI during hospitalization, corresponding to 14.3% in stage 1, 28.6% in stage 2 and 18.5% in stage 3, respectively. Compared to patients without AKI, patients with AKI had a higher proportion of mechanical ventilation mortality and higher in-hospital mortality. A total of 97.1% of patients with severe AKI received mechanical ventilation and in-hospital mortality was up to 79.4%. Severe AKI was independently associated with high in-hospital mortality (OR: 1.82; 95% CI: 1.06–3.13). Logistic regression analysis demonstrated that high serum interleukin-8 (OR: 4.21; 95% CI: 1.23–14.38), interleukin-10 (OR: 3.32; 95% CI: 1.04–10.59) and interleukin-2 receptor (OR: 4.50; 95% CI: 0.73–6.78) were risk factors for severe AKI development. <b><i>Conclusions:</i></b> Severe AKI was associated with high in-hospital mortality, and inflammatory response may play a role in AKI development in critically ill patients with COVID-19.


2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Lina Yao ◽  
Lei Zhang ◽  
Chengjie Zhou

In this paper, a data-enabled analysis of the prognostic risk factors of sepsis patients in the intensive care unit is presented. For this purpose, we have selected 220 sepsis patients, preferably those admitted to the intensive care unit for treatment in a tertiary a hospital in Tianjin from June 2018 to June 2019 and received complete data as the research objects, to explore the prognostic risk factors of sepsis patients in the intensive care unit. All patients met the SSC sepsis diagnosis guidelines and recorded the patients’ age, gender, underlying disease, and infection site. Laboratory indicators, such as blood routine, electrolytes, arterial blood gas, liver function, and renal function, were collected within 24 hours of admission. Furthermore, the corresponding specimens were cultured for pathogenic microorganisms according to the site of infection. The LAC value was measured at admission and 24 h after admission, and the 24 h lactate clearance rate was calculated. The Acute Physiological and Chronic Health Status Score II (APACHE-II) and SOFA score were calculated, which were based on the worst value of the index within 24 hours after admission. According to the prognosis of patients during hospitalization, they are divided into two groups: (i) survival group and (ii) death group. We entered all the data into Excel and used SPSS21.0 statistical software for data analysis and processing. Quantitative data are tested for normality. Quantitative data for normal distribution are expressed as mean ± standard deviation, and normal distribution and uniform variance are measured. The factors affecting the prognosis of patients with sepsis were first subjected to a single-factor logistic regression analysis, and a multiple logistic regression analysis was performed on the basis of the significance of the single-factor analysis. The results found that the prognosis of patients with sepsis in the ICU is affected by multiple factors such as underlying diseases, infectious microorganisms, comorbidities, and interventional therapy. APACHE-II score, 24 h lactate clearance rate, ARDS, and DIC are independent risk factors that affect the prognosis of ICU patients.


2020 ◽  
Author(s):  
Yichun Cheng ◽  
Nanhui Zhang ◽  
Ran Luo ◽  
Meng Zhang ◽  
Zhixiang Wang ◽  
...  

Abstract Background: Coronavirus disease 2019 (COVID-19) has emerged as a major global health threat with a great number of deaths worldwide. Acute kidney injury (AKI) is a common complication in patients admitted to the intensive care unit. We aimed toassess the incidence, risk factors and in-hospital outcomes of AKI in COVID-19 patients admitted to intensive care unitMethods: we conducted a retrospective observational study in intensive care unit of Tongji hospital, which was assigned responsibility for the treatments of severe COVID-19 patients by Wuhan government. The AKI was defined and staged based onKidney Disease: Improving Global Outcomes (KDIGO) criteria. Mild AKI was defined as stage 1, and severe AKI was defined as stage 2 or stage 3. We used logistic regression analysis to evaluate AKI risk factors and the association between AKI and in-hospital mortality.Results: A total of 150 patients with COVID-19 were included in our study. The median age of patients was 70 (interquartile range, 60-80) years and 62.7% were male. 70 (46.7%) patients developed AKI during hospitalization, corresponding to the 17.3% in stage 1 and 9.3% in stage 2 and 20.0% in stage 3, respectively. Compared to patients without AKI, patients with AKI had higher proportion of mechanical ventilation mortality and higher in-hospital mortality. 95.5% patients with severe AKI received mechanical ventilation and in-hospital mortality was up to 79.5%. Severe AKI was independently associated with high in-hospital mortality (OR: 4.30; 95% CI: 1.83-10.10). Logistic regression analysis demonstrated that high serum interleukin-6 (OR: 2.54; 95%CI: 1.00-6.42) and interleukin-10 (OR: 3.02; 95%CI: 1.17-7.82) were risk factors for severe AKI development.Conclusions: severe AKI was associated with high in-hospital mortality and inflammatory response may play a role in AKI development in critically ill patients with COVID-19.


2021 ◽  
pp. 0310057X2110242
Author(s):  
Adrian D Haimovich ◽  
Ruoyi Jiang ◽  
Richard A Taylor ◽  
Justin B Belsky

Vasopressors are ubiquitous in intensive care units. While central venous catheters are the preferred route of infusion, recent evidence suggests peripheral administration may be safe for short, single-agent courses. Here, we identify risk factors and develop a predictive model for patient central venous catheter requirement using the Medical Information Mart for Intensive Care, a single-centre dataset of patients admitted to an intensive care unit between 2008 and 2019. Using prior literature, a composite endpoint of prolonged single-agent courses (>24 hours) or multi-agent courses of any duration was used to identify likely central venous catheter requirement. From a cohort of 69,619 intensive care unit stays, there were 17,053 vasopressor courses involving one or more vasopressors that met study inclusion criteria. In total, 3807 (22.3%) vasopressor courses involved a single vasopressor for less than six hours, 7952 (46.6%) courses for less than 24 hours and 5757 (33.8%) involved multiple vasopressors of any duration. Of these, 3047 (80.0%) less than six-hour and 6423 (80.8%) less than 24-hour single vasopressor courses used a central venous catheter. Logistic regression models identified associations between the composite endpoint and intubation (odds ratio (OR) 2.36, 95% confidence intervals (CI) 2.16 to 2.58), cardiac diagnosis (OR 0.72, CI 0.65 to 0.80), renal impairment (OR 1.61, CI 1.50 to 1.74), older age (OR 1.002, Cl 1.000 to 1.005) and vital signs in the hour before initiation (heart rate, OR 1.006, CI 1.003 to 1.009; oxygen saturation, OR 0.996, CI 0.993 to 0.999). A logistic regression model predicting the composite endpoint had an area under the receiver operating characteristic curve (standard deviation) of 0.747 (0.013) and an accuracy of 0.691 (0.012). This retrospective study reveals a high prevalence of short vasopressor courses in intensive care unit settings, a majority of which were administered using central venous catheters. We identify several important risk factors that may help guide clinicians deciding between peripheral and central venous catheter administration, and present a predictive model that may inform future prospective trials.


Author(s):  
Hongbai Wang ◽  
Liang Zhang ◽  
Qipeng Luo ◽  
Yinan Li ◽  
Fuxia Yan

ABSTRACT:Background:Post-cardiac surgery patients exhibit a higher incidence of postoperative delirium (PD) compared to non-cardiac surgery patients. Patients with various cardiac diseases suffer from preoperative sleep disorder (SPD) induced by anxiety, depression, breathing disorder, or other factors.Objective:To examine the effect of sleep disorder on delirium in post-cardiac surgery patients.Methods:We prospectively selected 186 patients undergoing selective cardiac valve surgery. Preoperative sleep quality and cognitive function of all eligible participants were assessed through the Pittsburgh Sleep Quality Index (PSQI) and the Montreal Cognitive Assessment, respectively. The Confusion Assessment Method for Intensive Care Unit was used to assess PD from the first to seventh day postoperatively. Patients were divided into two groups according to the PD diagnosis: (1) No PD group and (2) the PD group.Results:Of 186 eligible patients, 29 (15.6%) were diagnosed with PD. A univariate analysis showed that gender (p = 0.040), age (p = 0.009), SPD (p = 0.008), intraoperative infusion volume (p = 0.034), postoperative intubation time (p = 0.001), and intensive care unit stay time (p = 0.009) were associated with PD. A multivariate logistic regression analysis demonstrated that age (odds ratio (OR): 1.106; p = 0.001) and SPD (OR: 3.223; p = 0.047) were independently associated with PD. A receiver operating characteristic curve demonstrated that preoperative PSQI was predictive of PD (area under curve: 0.706; 95% confidence interval: 0.595–0.816). A binomial logistic regression analysis showed that there was a significant association between preoperative 6 and 21 PSQI scores and PD incidence (p = 0.009).Conclusions:Preoperative SPD was significantly associated with PD and a main predictor of PD.


2019 ◽  
Vol 104 (6) ◽  
pp. F636-F642 ◽  
Author(s):  
Lobke CE Janssen ◽  
Jooske Van Der Spil ◽  
Anton H van Kaam ◽  
Jeanne P Dieleman ◽  
Peter Andriessen ◽  
...  

ObjectiveTo evaluate incidence of minimally invasive surfactant therapy (MIST) failure, identify risk factors and assess the impact of MIST failure on neonatal outcome.DesignRetrospective cohort study. MIST failure was defined as need for early mechanical ventilation (<72 hours of life). Multivariate logistic regression analysis was performed to identify risk factors for MIST failure and compare outcomes between groups.SettingTwo tertiary neonatal intensive care centres in the Netherlands.PatientsInfants born between 24 weeks’ and 31 weeks’ gestational age (GA) (n=185) with MIST for respiratory distress syndrome.InterventionsMIST procedure with poractant alfa (100–200 mg/kg).Main outcome measuresContinuous positive airway pressure (CPAP) failure after MIST in the first 72 hours of life.Results30% of the infants failed CPAP after MIST. In a multivariate logistic regression analysis, four risk factors were independently associated with failure: GA <28 weeks, C reactive protein ≥10 mg/L, absence of antenatal corticosteroids and lower surfactant dose. Infants receiving 200 mg/kg surfactant had a failure rate of 14% versus 35% with surfactant dose <200 mg/kg. Mean body temperature was 0.4°C lower at neonatal intensive care unit admission and before the procedure in infants with MIST failure.Furthermore, MIST failure was independently associated with an increased risk of severe intraventricular haemorrhage.ConclusionWe observed moderate MIST failure rates in concordance with the results of earlier studies. Absence of corticosteroids and lower surfactant dose are risk factors for MIST failure that may be modifiable in order to improve MIST success and patient outcome.


Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2313-2313
Author(s):  
Minh Q Tran ◽  
Steven L Shein ◽  
Hong Li ◽  
Sanjay P Ahuja

Abstract Introduction: Venous thromboembolism (VTE) in Pediatric Intensive Care Unit (PICU) patients is associated with central venous catheter (CVC) use. However, risk factors for VTE development in PICU patients with CVCs are not well established. The impact of Hospital-Acquired VTE in the PICU on clinical outcomes needs to be studied in large multicenter databases to identify subjects that may benefit from screening and/or prophylaxis. Method: With IRB approval, the Virtual Pediatric Systems, LLC database was interrogated for children < 18yo admitted between 01/2009-09/2014 who had PICU length of stay (LOS) <1 yr and a CVC present at some point during PICU care. The exact timing of VTE diagnosis was unavailable in the database, so VTE-PICU was defined as an "active" VTE that was not "present at admission". VTE-prior was defined as a VTE that was "resolved," "ongoing" or "present on admission." Variables extracted from the database included demographics, primary diagnosis category, and Pediatric Index of Mortality (PIM2) score. PICU LOS was divided into quintiles. Chi squared and Wilcoxon rank-sum were used to identify variables associated with outcomes, which were then included in multivariate models. Our primary outcome was diagnosis of VTE-PICU and our secondary outcome was PICU mortality. Children with VTE-prior were included in the mortality analyses, but not the VTE-PICU analyses. Data shown as median (IQR) and OR (95% CI). Results: Among 143,524 subjects, the median age was 2.8 (0.47-10.31) years and 55% were male. Almost half (44%) of the subjects were post-operative. The median PIM2 score was -4.11. VTE-prior was observed in 2498 patients (1.78%) and VTE-PICU in 1741 (1.2%). The incidence of VTE-PICU were 852 (1.7%) in patients ≤ 1 year old, 560 (0.9%) in patients 1-12 years old, and 303 (1.1%) in patients ≥ 13 years old (p < 0.0001). In univariate analysis, variables associated with a diagnosis of VTE-PICU were post-operative state, four LOS quintiles (3-7, 7-14, and 14-21 and >21 days) and several primary diagnosis categories: cardiovascular, gastrointestinal, infectious, neurologic, oncologic, genetic, and orthopedic. Multivariate analysis showed increased risk of VTE with cardiovascular diagnosis, infectious disease diagnosis, and LOS > 3 d (Table 1). The odds increased with increasing LOS: 7 d < LOS ≤ 14 d (5.18 [4.27-6.29]), 14 d < LOS ≤ 21 d (7.96 [6.43-9.82]), and LOS > 21 d (20.73 [17.29-24.87]). Mortality rates were 7.1% (VTE-none), 7.2% (VTE-prior), and 10.1% (VTE-PICU) (p < 0.0001). In the multivariate model, VTE-PICU (1.25 [1.05-1.49]) and VTE-prior (1.18 [1.002-1.39]) were associated with death vs. VTE-none. PIM2 score, trauma, and several primary diagnosis categories were also independently associated with death (Table 2). Conclusion: This large, multicenter database study identified several variables that are independently associated with diagnosis of VTE during PICU care of critically ill children with a CVC. Children with primary cardiovascular or infectious diseases, and those with PICU LOS >3 days may represent specific populations that may benefit from VTE screening and/or prophylaxis. Hospital-Acquired VTE in PICU was independently associated with death in our database. Additional analysis of this database, including adding specific diagnoses and secondary diagnoses, may further refine risk factors for Hospital-Acquired VTE among PICU patients with a CVC. Table 1. Multivariate analysis of Factors Associated with VTE-PICU. Factors Odds Ratio 95% Confidence Interval 3d < LOS ≤ 7d vs LOS ≤ 3d 2.19 1.78-2.69 7d < LOS ≤ 14d vs LOS ≤ 3d 5.18 4.27-6.29 14d < LOS ≤ 21d vs LOS ≤ 3d 7.95 6.44-9.82 LOS > 21d vs LOS ≤ 3d 20.73 17.29-24.87 Age 1.00 0.99-1.01 Post-operative 0.89 0.80-0.99 PIM2 Score 1.47 1.01-1.07 Primary Diagnosis: Cardiovascular 1.50 1.31-1.64 Primary Diagnosis: Infectious 1.50 1.27-1.77 Primary Diagnosis: Genetics 0.32 0.13-0.78 Table 2. Multivariate Analysis of Factors Associated with PICU Mortality. Factors Odds Ratio 95% ConfidenceInterval VTE-prior 1.18 1.00-1.39 VTE-PICU 1.25 1.05-1.49 PIM2 Score 2.08 2.05-2.11 Trauma 1.92 1.77-2.07 Post-operative 0.45 0.42-0.47 Primary Diagnosis: Genetic 2.07 1.63-2.63 Primary Diagnosis: Immunologic 2.45 1.51-3.95 Primary Diagnosis: Hematologic 1.63 1.30-2.06 Primary Diagnosis: Metabolic 0.71 0.58-0.87 Primary Diagnosis: Infectious 1.47 1.36-1.59 Primary Diagnosis: Neurologic 1.37 1.27-1.47 Disclosures No relevant conflicts of interest to declare.


Sign in / Sign up

Export Citation Format

Share Document