scholarly journals Subphenotypes of Cardiac Arrest Patients Admitted to Intensive Care Unit: a latent profile analysis of a large critical care database

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Zhongheng Zhang ◽  
Min Yao ◽  
Kwok M. Ho ◽  
Yucai Hong
Keyword(s):  
Intensive Care Unit ◽  
Cardiac Arrest ◽  
Intensive Care ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Laboratory Data ◽  
Elevated Serum ◽  
Multiple Organ ◽  
Risk Of Death ◽  
Latent Profile

Abstract Cardiac arrest (CA) may occur due to a variety of causes with heterogeneity in their clinical presentation and outcomes. This study aimed to identify clinical patterns or subphenotypes of CA patients admitted to the intensive care unit (ICU). The clinical and laboratory data of CA patients in a large electronic healthcare database were analyzed by latent profile analysis (LPA) to identify whether subphenotypes existed. Multivariable Logistic regression was used to assess whether mortality outcome was different between subphenotypes. A total of 1,352 CA patients fulfilled the eligibility criteria were included. The LPA identified three distinct subphenotypes: Profile 1 (13%) was characterized by evidence of significant neurological injury (low GCS). Profile 2 (15%) was characterized by multiple organ dysfunction with evidence of coagulopathy (prolonged aPTT and INR, decreased platelet count), hepatic injury (high bilirubin), circulatory shock (low mean blood pressure and elevated serum lactate); Profile 3 was the largest proportion (72%) of all CA patients without substantial derangement in major organ function. Profile 2 was associated with a significantly higher risk of death (OR: 2.09; 95% CI: 1.30 to 3.38) whilst the mortality rates of Profiles 3 was not significantly different from Profile 1 in multivariable model. LPA using routinely collected clinical data could identify three distinct subphenotypes of CA; those with multiple organ failure were associated with a significantly higher risk of mortality than other subphenotypes. LPA profiling may help researchers to identify the most appropriate subphenotypes of CA patients for testing effectiveness of a new intervention in a clinical trial.

scholarly journals Increased Risk of Death, in the Hospital and Outside the Intensive Care Unit, for Patients With Cirrhosis After Cardiac Arrest

2017 ◽  
Vol 15 (11) ◽  
pp. 1808-1810 ◽  
Author(s):  
Megan E. Reinders ◽  
Gabriel Wardi ◽  
Ricki Bettencourt ◽  
Daniel Bouland ◽  
Jessica Bazick ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Cardiac Arrest ◽  
Intensive Care ◽  
Risk Of Death ◽  
Increased Risk

scholarly journals Risk factors for death in patients with severe COVID-19 admitted to an intensive care unit

2021 ◽  
Vol 6 (4) ◽  
pp. 22-44
Author(s):  
N. Yu. Osyaev ◽  
N. V. Ivannikova ◽  
G. V. Vavin ◽  
V. G. Moses ◽  
O. V. Gruzdeva ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Complete Blood Count ◽  
Fasting Blood Glucose ◽  
Elevated Serum ◽  
Multiple Organ ◽  
Blood Oxygen Saturation ◽  
Significant Deterioration ◽  
And Gender

Aim. Severe COVID-19 is accompanied by reduced blood oxygen saturation, systemic inflammatory response syndrome and multiple organ failure, all causing a significant deterioration of homeostasis associated with death. Here we aimed to study the risk factors for death in patients with severe COVID-19 who have been admitted to an intensive care unit.Materials and Methods. The study included 144 consecutive patients with severe COVID-19 who have been admitted to an intensive care unit of Kuzbass Clinical Hospital from August to December 2020. Groups of survivors and non-survivors were equal in number (n = 72) and matched by gender (36 men and women) and age (median age 64 years, interquartile range 56-70 years in survivors and 58-69 years in non-survivors). Complete blood count, urinalysis, biochemical analysis, coagulation testing, and measurement of anti-SARS-CoV-2 IgM/IgG were carried out in all patients immediately upon the admission to intensive care unit.Results. Risk factors for death in severe COVID-19 at the admission to intensive care unit were arterial hypertension, chronic heart failure, peripheral atherosclerosis, impaired renal homeostasis (reduced glomerular filtration rate, elevated serum creatinine and urea, proteinuria, hematuria), augmented fasting blood glucose and lactate, neutrophilia (in men), lymphopenia and increased neutrophil-to-lymphocyte ratio (in women), and decreased IgM/IgG to SARS-CoV-2 (in women).Conclusion. We found both independent and gender-specific risk factors for death due to COVID-19.

scholarly journals A UK nationwide study of people with type 1 diabetes admitted to hospital with COVID-19 infection

Diabetologia ◽  
2021 ◽  
Author(s):  
Yue Ruan ◽  
◽  
Robert E. J. Ryder ◽  
Parijat De ◽  
Benjamin C. T. Field ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Type 1 Diabetes ◽  
Intensive Care ◽  
Primary Outcome ◽  
Microvascular Complications ◽  
Laboratory Data ◽  
Macrovascular Disease ◽  
Risk Of Death ◽  
The Uk

Abstract Aims/hypothesis The aim of this work was to describe the clinical characteristics of adults with type 1 diabetes admitted to hospital and the risk factors associated with severe coronavirus disease-2019 (COVID-19) in the UK. Methods A retrospective cohort study was performed using data collected through a nationwide audit of people admitted to hospital with diabetes and COVID-19, conducted by the Association of British Clinical Diabetologists from March to October 2020. Prespecified demographic, clinical, medication and laboratory data were collected from the electronic and paper medical record systems of the participating hospitals by local clinicians. The primary outcome of the study, severe COVID-19, was defined as death in hospital and/or admission to the adult intensive care unit (AICU). Logistic regression models were used to generate age-adjusted ORs. Results Forty UK centres submitted data. The final dataset included 196 adults who were admitted to hospital and had both type 1 diabetes and COVID-19 on admission (male sex 55%, white 70%, with mean [SD] age 62 [19] years, BMI 28.3 [7.3] kg/m2 and last recorded HbA1c 76 [31] mmol/mol [9.1 (5.0)%]). The prevalence of pre-existing microvascular disease and macrovascular disease was 56% and 39%, respectively. The prevalence of diabetic ketoacidosis on admission was 29%. A total of 68 patients (35%) died or were admitted to AICU. The proportions of people that died were 7%, 38% and 38% of those aged <55, 55–74 and ≥75 years, respectively. BMI, serum creatinine levels and having one or more microvascular complications were positively associated with the primary outcome after adjusting for age. Conclusions/interpretation In people with type 1 diabetes and COVID-19 who were admitted to hospital in the UK, higher BMI, poorer renal function and presence of microvascular complications were associated with greater risk of death and/or admission to AICU. Risk of severe COVID-19 is reassuringly very low in people with type 1 diabetes who are under 55 years of age without microvascular or macrovascular disease. In people with Type 1 diabetes and COVID-19 admitted to hospital in the UK, BMI and one or more microvascular complications had a positive association and low serum creatine levels had a negative association with death/admission to intensive care unit after adjusting for age.

scholarly journals Latent transition analysis of cardiac arrest patients treated in the intensive care unit

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0252318
Author(s):  
Lifeng Xing ◽  
Min Yao ◽  
Hemant Goyal ◽  
Yucai Hong ◽  
Zhongheng Zhang
Keyword(s):  
Intensive Care Unit ◽  
Logistic Regression ◽  
Cardiac Arrest ◽  
Intensive Care ◽  
Multiple Organ ◽  
Survival Outcome ◽  
Latent Transition Analysis ◽  
Transition Analysis ◽  
Icu Admission ◽  
Latent Transition

Background and objective Post-cardiac arrest (CA) syndrome is heterogenous in their clinical presentations and outcomes. This study aimed to explore the transition and stability of subphenotypes (profiles) of CA treated in the intensive care unit (ICU). Patients and methods Clinical features of CA patients on day 1 and 3 after ICU admission were modeled by latent transition analysis (LTA) to explore the transition between subphenotypes over time. The association between different transition patterns and mortality outcome was explored using multivariable logistic regression. Results We identified 848 eligible patients from the database. The LPA identified three distinct subphenotypes: Profile 1 accounted for the largest proportion (73%) and was considered as the baseline subphenotype. Profile 2 (13%) was characterized by brain injury and profile 3 (14%) was characterized by multiple organ dysfunctions. The same three subphenotypes were identified on day 3. The LTA showed consistent subphenotypes. A majority of patients in profile 2 (72%) and 3 (82%) on day 1 switched to profile 1 on day 3. In the logistic regression model, patients in profile 1 on day 1 transitioned to profile 3 had worse survival outcome than those continue to remain in profile 1 (OR: 20.64; 95% CI: 6.01 to 70.94; p < 0.001) and transitioned to profile 2 (OR: 8.42; 95% CI: 2.22 to 31.97; p = 0.002) on day 3. Conclusion The study identified three subphenotypes of CA, which was consistent on day 1 and 3 after ICU admission. Patients who transitioned to profile 3 on day 3 had significantly worse survival outcome than those remained in profile 1 or 2.

scholarly journals Assessment and identification of predictors of performance of early rehabilitation of patients in the general intensive care unit.

2020 ◽  
pp. 33-40
Author(s):  
Sergey A. Andreychenko ◽  
M. V Bychinin ◽  
T. V Klypa
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Critical Illness ◽  
Laboratory Data ◽  
Functional Independence ◽  
Multiple Organ ◽  
Early Rehabilitation ◽  
Rehabilitation Potential ◽  
Negative Effect

Introduction. Currently, there are no universal criteria for assessing the volume of predicted functional recovery of patients during rehabilitation in intensive care units. Objective. To identify independent predictors of efficiency of rehabilitation of patients after a critical illness. Materials and methods. The study was conducted on the basis of a general ICU in 2017-2019. Patients with a short course of rehabilitation ( 7 days), deep impairment of consciousness ( 7 points on the Glasgow coma scale), decompensated multiple organ failure were excluded from the study. Clinical and laboratory data of 82 patients were retrospectively analyzed, including baseline severity of the condition, degree of functional independence and mobility, assessment of neurological deficit, incidence of depression and delirium, duration of mechanical ventilation and terms of hospitalization. We used a calculated indicator to analyze the effectiveness of rehabilitation - the rehabilitation potential index (RPI). Patients were assigned to the group of effective rehabilitation (ER) or ineffective rehabilitation (IR) depending on the level of RPI. Results. The duration of mechanical ventilation, the frequency of impaired consciousness and the duration of hospitalization were higher in the IR group than in the ER group. Consciousness impairment was found to be an independent predictor of low efficacy of the rehabilitation (odds ratio 4.53; confidence interval 95 % 1.63-12.6; p 0.05). Conclusions. RPI can be used as a tool for assessing the effectiveness of rehabilitation of patients after a critical illness. The duration of mechanical ventilation has a negative effect on the functional outcome at discharge from the intensive care unit. The initial level of consciousness can be a benchmark for predicting the effectiveness of rehabilitation. Further prospective studies are needed to identify predictors of the effectiveness of early rehabilitation.

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