Upper extremity thromboses in medical-surgical critically ill patients
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ABSTRACT:
SUBMITTER: Zytaruk N
PROVIDER: S-EPMC3061652 | biostudies-literature | 2011 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundPrevious studies have suggested that prediction models for mortality should be adjusted for additional risk factors beyond the Acute Physiology and Chronic Health Evaluation (APACHE) score. Our objective was to identify risk factors independent of APACHE II score and construct a prediction model to improve the predictive accuracy for hospital and intensive care unit (ICU) mortality.MethodsWe used data from a multicenter randomized controlled trial (PROTECT, Prophylaxis for Thromboembolism in Critical Care Trial) to build a new prediction model for hospital and ICU mortality. Our primary outcome was all-cause 60-day hospital mortality, and the secondary outcome was all-cause 60-day ICU mortality.ResultsWe included 3746 critically ill non-trauma medical-surgical patients receiving heparin thromboprophylaxis (43.3 % females) in this study. The new model predicting 60-day hospital mortality incorporated APACHE II score (main effect: hazard ratio (HR) = 0.97 for per-point increase), body mass index (BMI) (main effect: HR = 0.92 for per-point increase), medical admission versus surgical (HR = 1.67), use of inotropes or vasopressors (HR = 1.34), acetylsalicylic acid or clopidogrel (HR = 1.27) and the interaction term between APACHE II score and BMI (HR = 1.002 for per-point increase). This model had a good fit to the data and was well calibrated and internally validated. However, the discriminative ability of the prediction model was unsatisfactory (C index < 0.65). Sensitivity analyses supported the robustness of these findings. Similar results were observed in the new prediction model for 60-day ICU mortality which included APACHE II score, BMI, medical admission and invasive mechanical ventilation.ConclusionCompared with the APACHE II score alone, the new prediction model increases data collection, is more complex but does not substantially improve discriminative ability.Trial registrationClinicalTrials.gov Identifier: NCT00182143.
| S-EPMC4769241 | biostudies-literature
Project description:BackgroundSuboptimal triage of critically ill patients with surgical sepsis may contribute to adverse outcomes. Patients transferred to a tertiary care center after spending 24 hours or longer at an outside facility were compared with patients who had early triage to a tertiary care center with the null hypothesis that management parameters and outcomes would be similar between groups.MethodsThis prospective observational cohort study included 308 patients treated for surgical sepsis in a surgical intensive care unit at a tertiary care center. Patients transferred after spending more than 24 hours at an outside facility (n = 69) were compared with patients who were directly admitted or transferred within 24 hours (n = 239). Patient characteristics, management parameters, and outcomes were compared between groups. This study was registered at ClinicalTrials.gov (NCT02276066).ResultsAverage outside facility length of stay in the delayed transfer group was 43 hours. Delayed transfer patients had higher sequential organ failure assessment (7 vs. 5, p = 0.003) and APACHE II scores (19 vs. 16, p = 0.007) on admission. The interval between admission and source control was significantly longer in the delayed transfer group (12.1 hours vs. 1.0 hours, p = 0.009). The incidence of nosocomial infection was significantly higher in the delayed transfer group (41% vs. 23%, p = 0.005). Delayed transfer was independently associated with a 10-day increase in hospital length of stay. Delayed transfer patients were less likely to be discharged home (22% vs. 59%, p < 0.001) and suffered twofold higher in-hospital mortality (14.5% vs. 7.1%, p = 0.056).ConclusionPatients with surgical sepsis who spent more than 24 hours at an outside facility prior to transfer had greater initial illness severity, longer intervals between admission and source control, and more nosocomial infections compared with patients who had early triage to a tertiary care center.Level of evidenceCare management/therapeutic, Level IV; Epidemiologic/prognostic, Level III.
| S-EPMC6927529 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2022-02-28 | GSE197259 | GEO
Project description:Failure to recognize the presence of competing risk or to account for it may result in misleading conclusions. We aimed to perform a competing risk analysis to assess the efficacy of the low molecular weight heparin dalteparin versus unfractionated heparin (UFH) in venous thromboembolism (VTE) in medical-surgical critically ill patients, taking death as a competing risk.This was a secondary analysis of a prospective randomized study of the Prophylaxis for Thromboembolism in Critical Care Trial (PROTECT) database. A total of 3746 medical-surgical critically ill patients from 67 intensive care units (ICUs) in 6 countries receiving either subcutaneous UFH 5000 IU twice daily (n = 1873) or dalteparin 5000 IU once daily plus once-daily placebo (n = 1873) were included for analysis.A total of 205 incident proximal leg deep vein thromboses (PLDVT) were reported during follow-up, among which 96 were in the dalteparin group and 109 were in the UFH group. No significant treatment effect of dalteparin on PLDVT compared with UFH was observed in either the competing risk analysis or standard survival analysis (also known as cause-specific analysis) using multivariable models adjusted for APACHE II score, history of VTE, need for vasopressors, and end-stage renal disease: sub-hazard ratio (SHR) = 0.92, 95% confidence interval (CI): 0.70-1.21, P-value = 0.56 for the competing risk analysis; hazard ratio (HR) = 0.92, 95% CI: 0.68-1.23, P-value = 0.57 for cause-specific analysis. Dalteparin was associated with a significant reduction in risk of pulmonary embolism (PE): SHR = 0.54, 95% CI: 0.31-0.94, P-value = 0.02 for the competing risk analysis; HR = 0.51, 95% CI: 0.30-0.88, P-value = 0.01 for the cause-specific analysis. Two additional sensitivity analyses using the treatment variable as a time-dependent covariate and using as-treated and per-protocol approaches demonstrated similar findings.This competing risk analysis yields no significant treatment effect on PLDVT but a superior effect of dalteparin on PE compared with UFH in medical-surgical critically ill patients. The findings from the competing risk method are in accordance with results from the cause-specific analysis.clinicaltrials.gov Identifier: NCT00182143.
| S-EPMC4616653 | biostudies-literature
Project description:BackgroundThere has been a global increase in the incidence of acute kidney injury (AKI), including among critically-ill surgical patients. AKI prediction score provides an opportunity for early detection of patients who are at risk of AKI; however, most of the AKI prediction scores were derived from cardiothoracic surgery. Therefore, we aimed to develop an AKI prediction score for major non-cardiothoracic surgery patients who were admitted to the intensive care unit (ICU).MethodsThe data of critically-ill patients from non-cardiothoracic operations in the Thai Surgical Intensive Care Unit (THAI-SICU) study were used to develop an AKI prediction score. Independent prognostic factors from regression analysis were included as predictors in the model. The outcome of interest was AKI within 7 days after the ICU admission. The AKI diagnosis was made according to the Kidney Disease Improving Global Outcomes (KDIGO)-2012 serum creatinine criteria. Diagnostic function of the model was determined by area under the Receiver Operating Curve (AuROC). Risk scores were categorized into four risk probability levels: low (0-2.5), moderate (3.0-8.5), high (9.0-11.5), and very high (12.0-16.5) risk. Risk of AKI was presented as likelihood ratios of positive (LH+).ResultsA total of 3474 critically-ill surgical patients were included in the model; 333 (9.6%) developed AKI. Using multivariable logistic regression analysis, older age, high Sequential Organ Failure Assessment (SOFA) non-renal score, emergency surgery, large volume of perioperative blood loss, less urine output, and sepsis were identified as independent predictors for AKI. Then AKI prediction score was created from these predictors. The summation of the score was 16.5 and had a discriminative ability for predicting AKI at AuROC = 0.839 (95% CI 0.825-0.852). LH+ for AKI were: low risk = 0.117 (0.063-0.200); moderate risk = 0.927 (0.745-1.148); high risk = 5.190 (3.881-6.910); and very high risk = 9.892 (6.230-15.695), respectively.ConclusionsThe function of AKI prediction score to predict AKI among critically ill patients who underwent non-cardiothoracic surgery was good. It can aid in early recognition of critically-ill surgical patients who are at risk from ICU admission. The scores could guide decision making for aggressive strategies to prevent AKI during the perioperative period or at ICU admission.Trial registrationTCTR20190408004, registered on April 4, 2019.
| S-EPMC7271390 | biostudies-literature
Project description:Objective: COVID19 is caused by the SARS-CoV-2 virus and has been associated with severe inflammation leading to organ dysfunction and mortality. Our aim was to profile the transcriptome in leukocytes from critically ill ICU patients positive for COVID19 vs. those negative for COVID19 to better understand the COVID19 associated host response. Design: Transcriptome profiling of buffy coat cells via ribonucleic acid sequencing (RNAseq) at the time of admission to the ICU. Setting: Tertiary care ICU and academic laboratory. Subjects: All patients admitted to the ICU suspected of being infected with SARS-CoV-2, using standardized hospital screening methodologies, had blood samples collected at the time of admission to the ICU. Interventions: None. Measurement and Main Results: Age- and sex-matched ICU patients that were either COVID19+ (PCR positive, 2 genes) or COVID19- (PCR negative) were enrolled. Cohorts were well-balanced with the exception that COVID19- patients had significantly higher total white blood cell counts and circulating neutrophils and COVID19+ patients were more likely to suffer bilateral pneumonia compared to COVID19- patients. Further, the mortality rate for this cohort of COVID19+ ICU patients was 29%. Transcriptional analysis revealed that when compared to COVID19- patients, the altered transcriptional responses of leukocytes in critically ill COVID19+ ICU patients appeared to be associated with multiple interrelated outcomes, including but not limited to robust interferon (IFN)-associated transcriptional responses, a marked decrease in the transcriptional activity of genes contributing to protein synthesis and the dysregulated expression of genes that contribute to coagulation, platelet activation, Toll-like receptor activation, neurotrophin signaling, and protein SUMOylation/ubiquitination. Conclusions: COVID19+ patients on day 1 of admission to the ICU display a unique leukocyte transcriptional profile that distinguishes them from COVID19- patients. Identification of this profile provides guidance for future targeted studies exploring novel prognostic/therapeutic aspects of COVID19.
2020-10-01 | GSE154998 | GEO
Project description:BackgroundThe prognostic implication of delirium subtypes in critically ill medical and surgical patients is scarcely investigated. The objective was to determine how delirium subtypes are associated with hospital mortality and other clinical outcomes.MethodsWe performed a secondary analysis on data from a prospective multicenter study aimed at implementation of delirium-oriented measures, conducted between 2012 and 2015 in The Netherlands. We included adults (≥ 18 years) admitted to the medical or surgical intensive care unit (ICU). Exclusion criteria were neurological admission diagnosis, persistent coma or ICU readmissions. Delirium was assessed using the Confusion Assessment Method-ICU or Intensive Care Delirium Screening Checklist, and delirium subtypes (hypoactive, hyperactive, or mixed) were classified using the Richmond Agitation-Sedation Scale. The main outcome was hospital mortality. Secondary outcomes were ICU mortality, ICU length of stay, coma, mechanical ventilation, and use of antipsychotics, sedatives, benzodiazepines and opioids.ResultsDelirium occurred in 381 (24.4%) of 1564 patients (52.5% hypoactive, 39.1% mixed, 7.3% hyperactive). After case-mix adjustment, patients with mixed delirium had higher hospital mortality than non-delirious patients (OR 3.09, 95%CI 1.79-5.33, p = 0.001), whereas hypoactive patients did not (OR 1.34, 95%CI 0.71-2.55, p = 0.37). Similar results were found for ICU mortality. Compared to non-delirious patients, both subtypes had longer ICU stay, more coma, increased mechanical ventilation frequency and duration, and received more antipsychotics, sedatives, benzodiazepines and opioids. Except for coma and benzodiazepine use, the most unfavourable outcomes were observed in patients with mixed delirium.ConclusionsPatients with mixed delirium had the most unfavourable outcomes, including higher mortality, compared with no delirium. These differences argue for distinguishing delirium subtypes in clinical practice and future research. Trial registration ClinicalTrials.gov NCT01952899.
| S-EPMC9764534 | biostudies-literature
Project description:The upper respiratory tract (URT) microbiome can contribute to the acquisition and severity of respiratory viral infections. The described associations between URT microbiota and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are limited at microbiota genus level and by the lack of functional interpretation. Our study, therefore, characterized the URT bacterial microbiome at species level and their encoded pathways in patients with COVID-19 and correlated these to clinical outcomes. Whole metagenome sequencing was performed on nasopharyngeal samples from hospitalized patients with critical COVID-19 (n = 37) and SARS-CoV-2-negative individuals (n = 20). Decreased bacterial diversity, a reduction in commensal bacteria, and high abundance of pathogenic bacteria were observed in patients compared to negative controls. Several bacterial species and metabolic pathways were associated with better respiratory status and lower inflammation. Strong correlations were found between species biomarkers and metabolic pathways associated with better clinical outcome, especially Moraxella lincolnii and pathways of vitamin K2 biosynthesis. Our study demonstrates correlations between the URT microbiome and COVID-19 patient outcomes; further studies are warranted to validate these findings and to explore the causal roles of the identified microbiome biomarkers in COVID-19 pathogenesis.
| S-EPMC9138573 | biostudies-literature
Project description:Hyperglycemia frequently occurs with acute medical illness, especially among patients with cardiovascular disease, and has been linked to increased morbidity and mortality in critically ill patients. Even patients who are normoglycemic can develop hyperglycemia in response to acute metabolic stress. An expanding body of literature describes the benefits of normalizing hyperglycemia with insulin therapy in hospitalized patients. As a result, both the American Diabetes Association and the American College of Endocrinology have developed guidelines for optimal control of hyperglycemia, specifically targeting critically ill, hospitalized patients. Conventional blood glucose values of 140-180 mg/dL are considered desirable and safely achievable in most patients. More aggressive control to <110 mg/dL remains controversial, but has shown benefits in certain patients, such as those in surgical intensive care. Intravenous infusion is often used for initial insulin administration, which can then be transitioned to subcutaneous insulin therapy in those patients who require continued insulin maintenance. This article reviews the data establishing the link between hyperglycemia and its risks of morbidity and mortality, and describes strategies that have proven effective in maintaining glycemic control in high-risk hospitalized patients.
| S-EPMC3004512 | biostudies-other
Project description:Hyperglycemia is common in critically ill patients and can be caused by various mechanisms, including nutrition, medications, and insufficient insulin. In the past, hyperglycemia was thought to be an adaptive response to stress, but hyperglycemia is no longer considered a benign condition in patients with critical illnesses. Indeed, hyperglycemia can increase morbidity and mortality in critically ill patients. Correction of hyperglycemia may improve clinical outcomes. To date, a definite answer with regard to glucose management in general intensive care unit patients, including treatment thresholds and glucose target is undetermined. Meta-analyses of randomized controlled trials suggested no survival benefit of tight glycemic control and a significantly increased incidence of hypoglycemia. Studies have shown a J- or U-shaped relationship between average glucose values and mortality; maintaining glucose levels between 100 and 150 mg/dL was likely to be associated with the lowest mortality rates. Recent studies have shown glycemic control < 180 mg/dL is not inferior to near-normal glycemia in critically ill patients and is clearly safer. Glycemic variability is also an important aspect of glucose management in the critically ill patients. Higher glycemic variability may increase the mortality rate, even in patients with the same mean glucose level. Decreasing glucose variability is an important issue for glycemic control in critically ill patients. Continuous measurements with automatic closed-loop systems could be considered to ensure that blood glucose levels are controlled within a specific range and with minimal variability.
| S-EPMC3956063 | biostudies-other