Nationwide retrospective study of critically ill adults with sickle cell disease in France.
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ABSTRACT:
SUBMITTER: Agbakou M
PROVIDER: S-EPMC8632921 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood could be discovered that would: 1) determine which patients with systemic inflammation had sepsis; 2) be robust across independent patient cohorts; 3) be insensitive to disease severity; and 4) provide diagnostic utility. The overall goal of this study was to identify and validate such a molecular classifier. Methods and Findings: We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte® Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyte® Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood possible) gave an AUC of 0.89 (95% CI: 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyte® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyte® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyte® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyte® Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation. SIRS and Sepsis ICU patients, admission samples Retrospective, mutli-site sutdy using retrospective physician adjudication as a comparator
2015-10-24 | E-GEOD-74224 | biostudies-arrayexpress
Project description:BACKGROUND:Sickle cell disease (SCD) is a genetic disorder of the red blood cells, resulting in multiple acute and chronic complications, including pain episodes, stroke, and kidney disease. Patients with SCD develop chronic organ dysfunction, which may progress to organ failure during disease exacerbations. Early detection of acute physiological deterioration leading to organ failure is not always attainable. Machine learning techniques that allow for prediction of organ failure may enable early identification and treatment and potentially reduce mortality. OBJECTIVE:The aim of this study was to test the hypothesis that machine learning physiomarkers can predict the development of organ dysfunction in a sample of adult patients with SCD admitted to intensive care units (ICUs). METHODS:We applied diverse machine learning methods, statistical methods, and data visualization techniques to develop classification models to distinguish SCD from controls. RESULTS:We studied 63 sequential SCD patients admitted to ICUs with 163 patient encounters (mean age 30.7 years, SD 9.8 years). A subset of these patient encounters, 22.7% (37/163), met the sequential organ failure assessment criteria. The other 126 SCD patient encounters served as controls. A set of signal processing features (such as fast Fourier transform, energy, and continuous wavelet transform) derived from heart rate, blood pressure, and respiratory rate was identified to distinguish patients with SCD who developed acute physiological deterioration leading to organ failure from patients with SCD who did not meet the criteria. A multilayer perceptron model accurately predicted organ failure up to 6 hours before onset, with an average sensitivity and specificity of 96% and 98%, respectively. CONCLUSIONS:This retrospective study demonstrated the viability of using machine learning to predict acute organ failure among hospitalized adults with SCD. The discovery of salient physiomarkers through machine learning techniques has the potential to further accelerate the development and implementation of innovative care delivery protocols and strategies for medically vulnerable patients.
| S-EPMC7254279 | biostudies-literature
Project description:Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood could be discovered that would: 1) determine which patients with systemic inflammation had sepsis; 2) be robust across independent patient cohorts; 3) be insensitive to disease severity; and 4) provide diagnostic utility. The overall goal of this study was to identify and validate such a molecular classifier. Methods and Findings: We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte® Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyte® Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood possible) gave an AUC of 0.89 (95% CI: 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyte® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyte® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyte® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyte® Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation. SIRS and Sepsis ICU patients, admission samples
2015-10-24 | GSE74224 | GEO
Project description:ContextSickle cell disease (SCD) is a severe hematological disorder. The most common acute complication of SCD is vaso-occlusive crisis (VOC), but SCD is a systemic disease potentially involving all organs. SCD prevalence estimates rely mostly on extrapolations from incidence-based newborn screening programs, although recent improvements in survival may have led to an increase in prevalence, and immigration could account for a substantial number of prevalent patients in Europe. The primary objective of this study was to estimate SCD prevalence in France.MethodsA cross-sectional observational study was conducted using a representative sample of national health insurance data. SCD patients followed up in France between 2006 and 2011 were captured through hydroxyurea reimbursement and with the International Classification of Diseases (ICD-10) SCD specific code D570.1.2, excluding code D573 (which corresponds to sickle cell trait (SCT)). Nevertheless, we assumed that ICD-10 diagnosis coding for inpatient stays could be imperfect, with the possibility of SCT being miscoded as SCD. Therefore, prevalence was analyzed in two groups of patients [with at least one (G1) or two (G2) inpatient stay] based on the number of SCD-related inpatient stays in the six-year study period, assuming that SCT patients are rarely rehospitalized compared to SCD. The prevalence of SCD in the sample, which was considered to be representative of the French population, was then extrapolated to the general population. The rate of vaso-occlusive crisis (VOC) events was estimated based on hospitalizations, emergencies, opioid reimbursements, transfusions, and sick leave.ResultsBased on the number of patients identified for G1 and G2, the 2016 French prevalence was estimated to be between 48.6 per 100,000 (G1) or 32,400 patients and 29.7 per 100,000 (G2) or 19,800 patients. An average of 1.51 VOC events per year were identified, with an increase frequency of 15 to 24 years of age. The average annual number of hospitalizations was between 0.70 (G1) and 1.11 (G2) per patient. Intensive care was observed in 7.6% of VOC-related hospitalizations. Fewer than 34% of SCD patients in our sample received hydroxyurea at any point in their follow-up. The annual average cost of SCD care is €5,528.70 (G1) to €6,643.80 (G2), with most costs arising from hospitalization and lab testing.ConclusionOur study estimates SCD prevalence in France at between 19,800 and 32,400 patients in 2016, higher than previously published. This study highlights the significant disease burden associated with vaso-occlusive events.
| S-EPMC8270152 | biostudies-literature
Project description:BackgroundCoronavirus disease 2019 (COVID-19) is often accompanied by secondary infections, such as invasive aspergillosis. In this study, risk factors for developing COVID-19-associated pulmonary aspergillosis (CAPA) and their clinical outcomes were evaluated.MethodsThis multicenter retrospective cohort study included critically ill COVID-19 patients from July 2020 through March 2021. Critically ill patients were defined as patients requiring high-flow respiratory support or mechanical ventilation. CAPA was defined based on the 2020 European Confederation of Medical Mycology and the International Society for Human and Animal Mycology consensus criteria. Factors associated with CAPA were analyzed, and their clinical outcomes were adjusted by a propensity score-matched model.ResultsAmong 187 eligible patients, 17 (9.1%) developed CAPA, which is equal to 33.10 per 10,000 patient-days. Sixteen patients received voriconazole-based antifungal treatment. In addition, 82.4% and 53.5% of patients with CAPA and without CAPA, respectively, received early high-dose corticosteroids (P = 0.022). In multivariable analysis, initial 10-day cumulative steroid dose > 60 mg of dexamethasone or dexamethasone equivalent dose) (adjusted odds ratio [OR], 3.77; 95% confidence interval [CI], 1.03-13.79) and chronic pulmonary disease (adjusted OR, 4.20; 95% CI, 1.26-14.02) were independently associated with CAPA. Tendencies of higher 90-day overall mortality (54.3% vs. 35.2%, P = 0.346) and lower respiratory support-free rate were observed in patients with CAPA (76.3% vs. 54.9%, P = 0.089).ConclusionOur study showed that the dose of corticosteroid use might be a risk factor for CAPA development and the possibility of CAPA contributing to adverse outcomes in critically ill COVID-19 patients.
| S-EPMC9091428 | biostudies-literature
Project description:Introduction: Risk factors for neurological complications in sickle cell disease differ in the adult and pediatric populations. Here, we focused on neurological complications in adults with sickle cell disease. Methods: Patients were selected using the audit data from the St George's Hospital Red Cell Database. The genotyping, demographics, clinical data, and investigation findings were collected. Results: A total of 303 patients were enrolled in the study: hemoglobin S homozygosity (HbSS) genotype 56%, hemoglobin S and C coinheritance (HbSC) genotype 35%, and hemoglobin S and β-thalassemia coinheritance (HbSβ) thalassemia genotype 9%; the mean age was 38.8 years (±13.5 SD) with 46% males. The most common neurological complication was cerebrovascular disease (n = 37, 12%) including those with ischemic stroke (10%), cerebral vasculopathy (3%), and intracranial hemorrhage (1%). Ischemic stroke was common among the HbSS genotype compared with other genotypes (8 vs. 1.6%, p = 0.001). Comparing the patients with sickle cell disease who had suffered a stroke to those who had not, there was a higher proportion of intracranial vasculopathy (p = 0.001, in particular, Moyamoya) and cognitive dysfunction (p < 0.0001). Conclusion: Our cohort supports previous reports that the most common neurological complication in adult sickle cell patients is cerebrovascular disease. Strategies to prevent cerebral vasculopathy and cognitive impairment should be explored.
| S-EPMC8714798 | biostudies-literature
Project description:Background: Liver injury commonly occurs in patients with COVID-19. There is limited data describing the course of liver injury occurrence in patients with different disease severity, and the causes and risk factors are unknown. We aim to investigate the incidence, characteristics, risk factors, and clinical outcomes of liver injury in patients with COVID-19. Methods: This retrospective observational study was conducted in three hospitals (Zhejiang, China). From January 19, 2020 to February 20, 2020, patients confirmed with COVID-19 (≥18 years) and without liver injury were enrolled and divided into non-critically ill and critically ill groups. The incidence and characteristics of liver injury were compared between the two groups. Demographics, clinical characteristics, treatments, and treatment outcomes between patients with or without liver injury were compared within each group. The multivariable logistic regression model was used to explore the risk factors for liver injury. Results: The mean age of 131 enrolled patients was 51.2 years (standard deviation [SD]: 16.1 years), and 70 (53.4%) patients were male. A total of 76 patients developed liver injury (mild, 40.5%; moderate, 15.3%; severe, 2.3%) with a median occurrence time of 10.0 days. Critically ill patients had higher and earlier occurrence (81.5 vs. 51.9%, 12.0 vs. 5.0 days; p < 0.001), greater injury severity (p < 0.001), and slower recovery (50.0 vs. 61.1%) of liver function than non-critically ill patients. Multivariable regression showed that the number of concomitant medications (odds ratio [OR]: 1.12, 95% confidence interval [CI]: 1.05-1.21) and the combination treatment of lopinavir/ritonavir and arbidol (OR: 3.58, 95% CI: 1.44-9.52) were risk factors for liver injury in non-critically ill patients. The metabolism of arbidol can be significantly inhibited by lopinavir/ritonavir in vitro (p < 0.005), which may be the underlying cause of drug-related liver injury. Liver injury was related to increased length of hospital stay (mean difference [MD]: 3.2, 95% CI: 1.3-5.2) and viral shedding duration (MD: 3.0, 95% CI: 1.0-4.9). Conclusions: Critically ill patients with COVID-19 suffered earlier occurrence, greater injury severity, and slower recovery from liver injury than non-critically ill patients. Drug factors were related to liver injury in non-critically ill patients. Liver injury was related to prolonged hospital stay and viral shedding duration in patients with COVID-19. Clinical Trial Registration: World Health Organization International Clinical Trials Registry Platform, ChiCTR2000030593. Registered March 8, 2020.
| S-EPMC7324794 | biostudies-literature
Project description:The PREVAIL study was a Phase II/III randomized controlled trial examining the use of lactoferrin to prevent nosocomial infections in critically ill patients undergoing mechanical ventilation. Gene expression data was generated from a consecutive subset of patients at the lead study site. We used the Affymetrix PrimeView array to generate expression data at various time points during the ICU stay.
2018-08-22 | GSE118657 | GEO
Project description:BackgroundCoronavirus disease 2019 (COVID-19) may be associated with cardiac arrhythmias in hospitalized patients, but data from the ICU setting are limited. We aimed to describe the epidemiology of cardiac arrhythmias in ICU patients with COVID-19.MethodsWe conducted a multicenter, retrospective cohort study including all ICU patients with an airway sample positive for severe acute respiratory syndrome corona-virus 2 from March 1st to June 1st in the Capital Region of Denmark (1.8 million inhabitants). We registered cardiac arrhythmias in ICU, potential risk factors, interventions used in ICU and outcomes.ResultsFrom the seven ICUs we included 155 patients with COVID-19. The incidence of cardiac arrhythmias in the ICU was 57/155 (37%, 95% confidence interval 30-45), and 39/57 (68%) of these patients had this as new-onset arrhythmia. Previous history of tachyarrhythmias and higher disease severity at ICU admission were associated with cardiac arrhythmias in the adjusted analysis. Fifty-four of the 57 (95%) patients had supraventricular origin of the arrhythmia, 39/57 (68%) received at least one intervention against arrhythmia (eg amiodarone, IV fluid or magnesium) and 38/57 (67%) had recurrent episodes of arrhythmia in ICU. Patients with arrhythmias in ICU had higher 60-day mortality (63%) as compared to those without arrhythmias (39%).ConclusionNew-onset supraventricular arrhythmias were frequent in ICU patients with COVID-19 and were related to previous history of tachyarrhythmias and severity of the acute disease. The mortality was high in these patients despite the frequent use of interventions against arrhythmias.
| S-EPMC8014528 | biostudies-literature
Project description:BackgroundCoronavirus disease 2019 (COVID-19) has resulted in high hospitalization rates worldwide. Acute kidney injury (AKI) in patients hospitalized for COVID-19 is frequent and associated with disease severity and poor outcome. The aim of this study was to investigate the incidence of kidney replacement therapy (KRT) in critically ill patients with COVID-19 and its implication on outcome.MethodsWe retrospectively analyzed all COVID-19 patients admitted to the Department of Intensive Care Medicine at the University Medical Center Hamburg-Eppendorf (Germany) between 1 March 2020 and 31 July 2021. Demographics, clinical parameters, type of organ support, length of intensive care unit (ICU) stay, mortality and severity scores were assessed.ResultsThree-hundred critically ill patients with COVID-19 were included. The median age of the study population was 61 (IQR 51-71) years and 66% (n = 198) were male. 73% (n = 219) of patients required invasive mechanical ventilation. Overall, 68% (n = 204) of patients suffered from acute respiratory distress syndrome and 30% (n = 91) required extracorporeal membrane oxygenation (ECMO). We found that 46% (n = 139) of patients required KRT. Septic shock (OR 11.818, 95% CI: 5.941-23.506, p < 0.001), higher simplified acute physiology scores (SAPS II) (OR 1.048, 95% CI: 1.014-1.084, p = 0.006) and vasopressor therapy (OR 5.475, 95% CI: 1.127-26.589, p = 0.035) were independently associated with the initiation of KRT. 61% (n = 85) of patients with and 18% (n = 29) without KRT died in the ICU (p < 0.001). Cox regression found that KRT was independently associated with mortality (HR 2.075, 95% CI: 1.342-3.208, p = 0.001) after adjusting for confounders.ConclusionCritically ill patients with COVID-19 are at high risk of acute kidney injury with about half of patients requiring KRT. The initiation of KRT was associated with high mortality.
| S-EPMC9630840 | biostudies-literature