scholarly journals Analysis of Prognostic Risk Factors of Sepsis Patients in Intensive Care Unit Based on Data Analysis

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Lina Yao ◽  
Lei Zhang ◽  
Chengjie Zhou
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Intensive Care ◽  
Data Analysis ◽  
Quantitative Data ◽  
Lactate Clearance ◽  
Single Factor ◽  
Prognostic Risk Factors

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.

scholarly journals Risk Factors and Outcomes of Acute Kidney Injury in Critically Ill Patients with Coronavirus Disease 2019

2020 ◽  
pp. 1-9
Author(s):  
Yichun Cheng ◽  
Nanhui Zhang ◽  
Ran Luo ◽  
Meng Zhang ◽  
Zhixiang Wang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Acute Kidney Injury ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Kidney Injury ◽  
Stage 1

<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.

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 ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Nephrotic Syndrome ◽  
Intensive Care ◽  
Venous Thromboembolism ◽  
Streptococcus Pneumoniae ◽  
Hospitalized Children ◽  
Median Hospital

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.

scholarly journals Risk Factors and Outcomes of Acute Kidney Injury in Critically Ill Patients With Coronavirus Disease 2019

2020 ◽  
Author(s):  
Yichun Cheng ◽  
Nanhui Zhang ◽  
Ran Luo ◽  
Meng Zhang ◽  
Zhixiang Wang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Acute Kidney Injury ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Kidney Injury ◽  
Stage 1

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.

Risk factor identification and predictive models for central line requirements for patients on vasopressors

2021 ◽  
pp. 0310057X2110242
Author(s):  
Adrian D Haimovich ◽  
Ruoyi Jiang ◽  
Richard A Taylor ◽  
Justin B Belsky
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Logistic Regression ◽  
Intensive Care ◽  
Central Venous Catheter ◽  
Single Agent ◽  
Composite Endpoint ◽  
Venous Catheter ◽  
Central Venous Catheters ◽  
Central Venous

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.

scholarly journals Effect of Sleep Disorder on Delirium in Post-Cardiac Surgery Patients

2020 ◽  
Vol 47 (5) ◽  
pp. 627-633 ◽  
Author(s):  
Hongbai Wang ◽  
Liang Zhang ◽  
Qipeng Luo ◽  
Yinan Li ◽  
Fuxia Yan
Keyword(s):  
Intensive Care Unit ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cardiac Surgery ◽  
Intensive Care ◽  
Sleep Quality ◽  
Sleep Disorder ◽  
Logistic Regression Analysis ◽  
Univariate Analysis ◽  
Post Cardiac Surgery

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.

Minimally invasive surfactant therapy failure: risk factors and outcome

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 ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Intensive Care ◽  
Minimally Invasive ◽  
Logistic Regression Analysis ◽  
Neonatal Intensive Care ◽  
Multivariate Logistic Regression Analysis ◽  
Surfactant Therapy ◽  
Multivariate Logistic Regression

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.

scholarly journals Influence of Tigecycline on Liver Function in Adult Patients in the Intensive Care Unit

2021 ◽  
Author(s):  
Jingnan Song ◽  
Pan Chen ◽  
Zhaoxia Tang ◽  
Yifan Zheng ◽  
Xiao Chen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Regression Analysis ◽  
Intensive Care ◽  
Liver Disease ◽  
Liver Injury ◽  
Liver Function ◽  
Adult Patients ◽  
Apache Ii Score ◽  
Cox Regression Analysis

Abstract Background There are few studies investigating TGC-associated hepatotoxicity in ICU patients, and the pathogenesis of hepatotoxicity and identification of risk factors are limited. Objectives To analyze the influence of tigecycline (TGC) on liver function in adult patients in the Intensive Care Unit to identify potential risk factors for tigecycline-induced liver injury (TILI). Methods Patients receiving tigecycline treatment in ICU during January 2019 to October 2020 were retrospectively enrolled. The liver function parameters before and after tigecycline treatment were collected, and risk factors associated with TILI was identified by logistic regression analysis. The probability of 28-day mortality was determined in Cox regression analysis. Results A total of 242 patients were enrolled, and TILI was identified in 24 patients (9.92%), of whom 75.0% had grade 1 liver injury, and 16.67%, 4.17%, 4.17% had grade 2 to 4 liver injury, respectively. The pattern of hepatotoxicity was hepatocellular in 16 patients (66.67%), cholestatic in 4 patients (16.67%), and mixed in 4 patients (16.67%). The median time from tigecycline start to symptoms was only 5 days (IQR, 3-7 days). Multivariate analysis identified tigecycline dose ≥ 200mg/day, longer course of treatment and preexisting liver disease tend to be independently associated with TILI. In addition, APACHE II score > 15, higher dose of tigecycline and TILI were independent risk factors of 28-day mortality, while longer course of tigecycline reduced this risk despite its association with TILI. Conclusions The maintenance dose and course of tigecycline, as well as liver disease is considered as risk factors of hepatotoxicity. 28-day mortality tended to be higher in TILI patients. The relationships among tigecycline dose and course, TILI and mortality should be further investigated.

scholarly journals Neonatal Mortality and Its Associated Factors among Neonates Admitted to Wollega University Referral Hospital Neonatal Intensive Care Unit, East Wollega, Ethiopia

2021 ◽  
Vol 8 ◽  
pp. 2333794X2110301
Author(s):  
Tesfaye Abera ◽  
Lami Bayisa ◽  
Teshome Bekele ◽  
Mulugeta Dessalegn ◽  
Diriba Mulisa ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Intensive Care ◽  
Neonatal Intensive Care Unit ◽  
Neonatal Mortality ◽  
Logistic Regression Analysis ◽  
Neonatal Intensive Care ◽  
Multiple Logistic Regression Analysis ◽  
Birth Asphyxia

Ethiopia has a high neonatal mortality rate in spite of dearth of study. Therefore we aimed to assess magnitude and associated factors of neonatal mortality among neonates admitted to neonatal intensive care units of Wollega University Referral Hospital. Accordingly, a facility based cross-sectional study was conducted on 289 by reviewing medical records of neonates admitted to neonatal intensive care unit. The collected data were entered in to Epi data version 3.1 and Stata version 14 used for analysis. Variables with P-value  < 0.25 at with 95% confidence interval in binary logistic regression analysis were taken to the multiple logistic regression analysis. Finally, variables with Likewise, variable with P-value < 0.05 at 95% confidence interval in multiple logistic regression analysis were considered as statistically significant. Among 289 neonates admitted to neonatal intensive care unit, 53 (18.34 %) were died. Majority 42(79.25%) of those deaths occurred at ≤ 7 days of birth. Preterm [AOR 4.15, 95% CI (1.67-10.33)], neonates faced birth asphyxia [AOR 3.26, 95% CI (1.33-7.98)], neonates who developed sepsis [AOR 2.29 95% CI (1.01-5.20)] and neonates encountered with jaundice [(AOR 11.08, 95% CI (1.03-119.59)] were more at risk to die. In general, the magnitude of neonatal mortality among neonates admitted to neonatal intensive care unit was high. Gestational age (maturity of new born), birth asphyxia, neonatal sepsis and neonatal jaundice were predictors of neonatal mortality. Neonates admitted to neonatal intensive care unit with sepsis, jaundice, and birth asphyxia demand special attention to reduce neonatal mortality.

scholarly journals Applicability of Paediatric Index of Mortality 2 Score to Predict Outcome in Children Admitted to Paediatric Intensive Care Unit

2018 ◽  
Vol 38 (3) ◽  
pp. 149-152
Author(s):  
Shrikiran Aroor ◽  
Sandeep Kumar ◽  
Pushpa Kini ◽  
Suneel Mundkur
Keyword(s):  
Intensive Care Unit ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Intensive Care ◽  
Logistic Regression Analysis ◽  
Paediatric Intensive Care Unit ◽  
Death Rate ◽  
Paediatric Intensive Care ◽  
P Value ◽  
The Mean

Introduction: Research on critically ill children admitted to the intensive care unit has shown the usefulness of Paediatric Index of Mortality 2 (PIM2) score at admission to predict outcome. This study was conducted to estimate PIM2 score in children admitted to Paediatric Intensive Care Unit and its correlation with clinical outcome. Methods: This prospective observational study was conducted in children of age group one month to 18 years admitted to the paediatric intensive care unit of a tertiary care hospital. Data including demographics, diagnostic categories, duration of hospital stay, predicted death rate (PDR) measured by PIM2 score was compared between survivors and non survivors. Logistic regression analysis was performed to arrive at a risk adjusted relationship between the different predictor variables and the probability of death. Results: Consecutive 130 children admitted to PICU during the study period were enrolled. The mean PDR (%) of the total study population was 22.4 ± 10.60. The mean PDR in survivors was 12.4 ± 7.80 while the PDR in non survivors was 44.2 ± 12.62 (p value < 0.001). Children with PDR < 1% had a mortality rate of 2.4% when compared to 71.4% in children with PDR > 5% (p value < 0.001). PDR by PIM2 score and the presence of hypo-albuminemia remained significant even after adjusting for age in multivariate logistic regression analysis. Conclusion: PDR measured by PIM2 score differentiated well between survivors and non survivors in PICU. The predicted death rate was less than the observed death rate. PIM2 score is a useful tool to assess the severity of illness and predict outcome.

Sign in / Sign up

Export Citation Format

Share Document