Incidence and Predictive Value of Thrombocytopenia in Patients with Severe Community Acquired Pneumonia

2015 ◽  
Vol 15 (1) ◽  
pp. 35-39 ◽  
Author(s):  
Jelena Dunaiceva ◽  
Olegs Sabelnikovs
Keyword(s):  
Intensive Care ◽  
Platelet Count ◽  
Hospital Mortality ◽  
Sofa Score ◽  
Predictive Value ◽  
Community Acquired Pneumonia ◽  
Icu Patients ◽  
Icu Stay ◽  
Severe Community Acquired Pneumonia ◽  
Clinical Records

SummaryIntroduction. Thrombocytopenia is frequently encountered in intensive care unit (ICU) patients. The cause of thrombocytopenia is multifactorial, it develops as a result of infection, inflammation and depletion of coagulation factors. Therefore, thrombocytopenia could potentially serve as an indicator of severity of the illness and an outcome predictor in patients with severe community-acquired pneumonia (CAP).Aim of the study. To determine incidence and predictive value of thrombocytopenia in ICU patients with severe CAP.Material and methods. We carried out a retrospective study based on clinical records from patients admitted to the Pauls Stradins Clinical University Hospital Intensive Care and Reanimation Unit from 2011 to 2014. Thrombocytopenia was defined as platelet count ≤150×109/L.Results. A total of 98 patients were included in this study, 58 (59%) men and 40 (41%) women. The mean (±SD) age of patients was 61±17.9 years, 54% died and 46% survived. 57 patients (58%) developed thrombocytopenia, in 58% it was present at the admission to ICU, and 42% developed thrombocytopenia during their stay in ICU. The lowest platelet count, in survivors was on fifth day in ICU, while in non-survivors on fourth day in ICU. Platelet count on admission to ICU (ROC AUC: 0.610, p=0.095) had lower discriminative power for ICU mortality than SOFA score (ROC AUC: 0.729, p=0.001) and CURB-65 score (ROC AUC: 0.680, p=0.006). Patients with thrombocytopenia at any point of ICU stay had higher hospital mortality in comparison to patients without thrombocytopenia. (36 (63.1%) vs 17 (41.1%), p=0.041). In thrombocytopenic patients non-resolution of thrombocytopenia during the ICU stay was associated with higher mortality (OR 5.5; 95% CI, 1.6-18.7, p=0.006). After adjusting for age, gender and SOFA score, non-resolution of thrombocytopenia remained to be an independent mortality predictor (OR 8, 95% CI 1.7-37, p=0.008)Conclusions. Thrombocytopenia is frequently encountered in patients with severe CAP. Thrombocytopenia at any point of ICU stay is associated with higher hospital mortality. Resolution of thrombocytopenia is associated with better clinical outcome.

Predictive Values of Initial Severity Scores at Intensive Care Unit Admission for Patients With Overnight or Prolonged Stay

2021 ◽  
Author(s):  
Koji Hosokawa ◽  
Nobuaki Shime
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Predictive Value ◽  
Apache Ii ◽  
Icu Patients ◽  
Prolonged Stay ◽  
Saps Ii ◽  
Icu Stay ◽  
Severity Scores

Abstract Background: The predictive value of disease severity scores for intensive care unit (ICU) patients is occasionally inaccurate because ICU patients with mild symptoms are also considered. We, thus, aimed to evaluate the accuracy of severity scores in predicting mortality of patients with complicated conditions admitted for > 24 hours. Methods: Overall, 35,353 adult patients using nationwide ICU data were divided into two groups: (1) overnight ICU stay after elective surgery and alive on discharge within 24 hours and (2) death within 24 hours or prolonged stay. The performance and accuracy of Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation (APACHE) II and III, and Simplified Acute Physiology Score (SAPS) II scores in predicting in-hospital mortality were evaluated. Results: In the overnight stay group, the correlation between SOFA and APACHE III scores or SAPS II was low because many had a SOFA score of 0. In the prolonged stay group, the predictive value of SAPS II and APACHE II and III showed high accuracy but that of SOFA was moderate. Conclusions: When overnight ICU stay patients were not included, the high predictive value for in-hospital mortality of SAPS II and APACHE II and III was evident.

scholarly journals Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Comparative Machine Learning Study (Preprint)

2020 ◽  
Author(s):  
Sujeong Hur ◽  
Ji Young Min ◽  
Junsang Yoo ◽  
Kyunga Kim ◽  
Chi Ryang Chung ◽  
...  
Keyword(s):  
Machine Learning ◽  
Intensive Care Unit ◽  
Patient Safety ◽  
Intensive Care ◽  
Predictive Value ◽  
Prediction Models ◽  
Support Vector ◽  
Unplanned Extubation ◽  
Electronic Health Record Data ◽  
Icu Patients

BACKGROUND Patient safety in the intensive care unit (ICU) is one of the most critical issues, and unplanned extubation (UE) is considered as the most adverse event for patient safety. Prevention and early detection of such an event is an essential but difficult component of quality care. OBJECTIVE This study aimed to develop and validate prediction models for UE in ICU patients using machine learning. METHODS This study was conducted an academic tertiary hospital in Seoul. The hospital had approximately 2,000 inpatient beds and 120 intensive care unit (ICU) beds. The number of patients, on daily basis, was approximately 9,000 for the out-patient. The number of annual ICU admission was approximately 10,000. We conducted a retrospective study between January 1, 2010 and December 31, 2018. A total of 6,914 extubation cases were included. We developed an unplanned extubation prediction model using machine learning algorithms, which included random forest (RF), logistic regression (LR), artificial neural network (ANN), and support vector machine (SVM). For evaluating the model’s performance, we used area under the receiver operator characteristic curve (AUROC). Sensitivity, specificity, positive predictive value negative predictive value, and F1-score were also determined for each model. For performance evaluation, we also used calibration curve, the Brier score, and the Hosmer-Lemeshow goodness-of-fit statistic. RESULTS Among the 6,914 extubation cases, 248 underwent UE. In the UE group, there were more males than females, higher use of physical restraints, and fewer surgeries. The incidence of UE was more likely to occur during the night shift compared to the planned extubation group. The rate of reintubation within 24 hours and hospital mortality was higher in the UE group. The UE prediction algorithm was developed, and the AUROC for RF was 0.787, for LR was 0.762, for ANN was 0.762, and for SVM was 0.740. CONCLUSIONS We successfully developed and validated machine learning-based prediction models to predict UE in ICU patients using electronic health record data. The best AUROC was 0.787, which was obtained using RF. CLINICALTRIAL N/A

Neutrophil-to-lymphocyte Ratio as a Predictor of Mortality in ICU Patients: An Analysis of MIMIC-III Database

2020 ◽  
Author(s):  
Xie Wu ◽  
Zhanhao Su ◽  
Qipeng Luo ◽  
Yinan Li ◽  
Hongbai Wang ◽  
...  
Keyword(s):  
Intensive Care ◽  
Mortality Rate ◽  
Hospital Mortality ◽  
Predictive Power ◽  
Inflammatory Marker ◽  
Survival Group ◽  
Icu Patients ◽  
Lymphocyte Ratio ◽  
Saps Ii ◽  
Death Group

Abstract Background: Identifying high-risk patients in intensive care unit (ICU) is very important because of the high mortality rate. Existing scoring systems are numerous but lack effective inflammatory markers. Our objective was to identify and evaluate a low-cost, easily accessible and effective inflammatory marker that can predict mortality in ICU patients.Methods: We conducted a retrospective study using data from the Medical Information Mart for Intensive Care III database. We first divided the patients into the survival group and the death group based on in-hospital mortality. Receiver operating characteristic analyses were performed to find the best inflammatory marker (i.e. neutrophil-to-lymphocyte ratio, NLR). We then re-divided the patients into three groups based on NLR levels. Univariate and multivariate logistic regression were performed to evaluate the association between NLR and mortality. The area under the curve (AUC), Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) were used to assess whether the incorporate of NLR can improve the predictive power of existing predictive model. Results: A total of 21,822 patients were included in this study, with an in-hospital mortality rate of 14.43%. Among all inflammatory marker in routine blood test results, NLR had the best predictive ability, with a median (interquartile range) NLR of 5.40 (2.95, 10.46) in the survival group and 8.32 (4.25, 14.75) in the death group. We then re-divided the patients into low (≤1), medium (1-6) and high (≥6) groups based on NLR levels. Compared with the median NLR group, the in-hospital mortality rates were significantly higher in the low (odds ratio [OR] = 2.09; 95% confidence interval [CI], 1.64 to 2.66) and high (OR=1.64; 95%CI, 1.50-1.80) NLR groups. The addition of NLR to Simplified Acute Physiology Score II (SAPS II) improved the AUC from 0.789 to 0.798 (P<0.001), with NRI of 16.64% (P<0.001) and IDI of 0.27% (P<0.001).Conclusion: NLR is a good predictor of mortality in ICU patients, both low and high levels of NLR are associated with elevated mortality rate. The inclusion of NLR might improve the predictive power of SAPS II.

scholarly journals Epidemiology and prognosis of anti-infective therapy in the ICU setting during acute pancreatitis: a cohort study

Critical Care ◽  
2019 ◽  
Vol 23 (1) ◽  
Author(s):  
Philippe Montravers ◽  
Elie Kantor ◽  
Jean-Michel Constantin ◽  
Jean-Yves Lefrant ◽  
Thomas Lescot ◽  
...  
Keyword(s):  
Acute Pancreatitis ◽  
Hospital Mortality ◽  
Therapeutic Interventions ◽  
Therapeutic Management ◽  
Pulmonary Infections ◽  
Prescribing Practices ◽  
Icu Patients ◽  
Icu Stay ◽  
Large Heterogeneity ◽  
Length Of Icu Stay

Abstract Background Recent international guidelines for acute pancreatitis (AP) recommend limiting anti-infective therapy (AIT) to cases of suspected necrotizing AP or nosocomial extrapancreatic infection. Limited data are available concerning empirical and documented AIT prescribing practices in patients admitted to the intensive care unit (ICU) for the management of AP. Methods Using a multicentre, retrospective (2009–2014), observational database of ICU patients admitted for AP, our primary objective was to assess the incidence of AIT prescribing practices during the first 30 days following admission. Secondary objectives were to assess the independent impact of centre characteristics on the incidence of AIT and to identify factors associated with crude hospital mortality in a logistic regression model. Results In this cohort of 860 patients, 359 (42%) received AIT on admission. Before day 30, 340/359 (95%) AIT patients and 226/501 (45%) AIT-free patients on admission received additional AIT, mainly for intra-abdominal and lung infections. A large heterogeneity was observed between centres in terms of the incidence of infections, therapeutic management including AIT and prognosis. Administration of AIT on admission or until day 30 was not associated with an increased mortality rate. Patients receiving AIT on admission had increased rates of complications (septic shock, intra-abdominal and pulmonary infections), therapeutic (surgical, percutaneous, endoscopic) interventions and increased length of ICU stay compared to AIT-free patients. Patients receiving delayed AIT after admission and until day 30 had increased rates of complications (respiratory distress syndrome, intra-abdominal and pulmonary infections), therapeutic interventions and increased length of ICU stay compared to those receiving AIT on admission. Risk factors for hospital mortality assessed on admission were age (adjusted odds ratio [95% confidence interval] 1.03 [1.02–1.05]; p < 0.0001), Balthazar score E (2.26 [1.43–3.56]; p < 0.0001), oliguria/anuria (2.18 [1.82–4.33]; p < 0.0001), vasoactive support (2.83 [1.73–4.62]; p < 0.0001) and mechanical ventilation (1.90 [1.15–3.14]; p = 0.011), but not AIT (0.63 [0.40–1.01]; p = 0.057). Conclusions High proportions of ICU patients admitted for AP receive AIT, both on admission and during their ICU stay. A large heterogeneity was observed between centres in terms of incidence of infections, AIT prescribing practices, therapeutic management and outcome. AIT reflects the initial severity and complications of AP, but is not a risk factor for death.

scholarly journals Sequential Organ Failure Assessment Component Score Prediction of In-hospital Mortality From Sepsis

2018 ◽  
Vol 35 (8) ◽  
pp. 810-817 ◽  
Author(s):  
Tushar Gupta ◽  
Michael A. Puskarich ◽  
Elizabeth DeVos ◽  
Adnan Javed ◽  
Carmen Smotherman ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Sequential Organ Failure Assessment ◽  
Organ Failure ◽  
Sofa Score ◽  
Statistical Significance ◽  
Predictive Ability ◽  
Hospital Death ◽  
Icu Stay ◽  
Relative Contribution ◽  
Failure Assessment

Objectives: Early organ dysfunction in sepsis confers a high risk of in-hospital mortality, but the relative contribution of specific types of organ failure to overall mortality is unclear. The objective of this study was to assess the predictive ability of individual types of organ failure to in-hospital mortality or prolonged intensive care. Methods: Retrospective cohort study of adult emergency department patients with sepsis from October 1, 2013, to November 10, 2015. Multivariable regression was used to assess the odds ratios of individual organ failure types for the outcomes of in-hospital death (primary) and in-hospital death or ICU stay ≥ 3 days (secondary). Results: Of 2796 patients, 283 (10%) experienced in-hospital mortality, and 748 (27%) experienced in-hospital mortality or an ICU stay ≥ 3 days. The following components of Sequential Organ Failure Assessment (SOFA) score were most predictive of in-hospital mortality (descending order): coagulation (odds ratio [OR]: 1.60, 95% confidence interval [CI]: 1.32-1.93), hepatic (1.58, 95% CI: 1.32-1.90), respiratory (OR: 1.33, 95% CI: 1.21-1.47), neurologic (OR: 1.20, 95% CI: 1.07-1.35), renal (OR: 1.14, 95% CI: 1.02-1.27), and cardiovascular (OR: 1.13, 95% CI: 1.01-1.25). For mortality or ICU stay ≥3 days, the most predictive SOFA components were respiratory (OR: 1.97, 95% CI: 1.79-2.16), neurologic (OR: 1.72, 95% CI: 1.54-1.92), cardiovascular (OR: 1.38, 95% CI: 1.23-1.54), coagulation (OR: 1.31, 95% CI: 1.10-1.55), and renal (OR: 1.19, 95% CI: 1.08-1.30) while hepatic SOFA (OR: 1.16, 95% CI: 0.98-1.37) did not reach statistical significance ( P = .092). Conclusion: In this retrospective study, SOFA score components demonstrated varying predictive abilities for mortality in sepsis. Elevated coagulation or hepatic SOFA scores were most predictive of in-hospital death, while an elevated respiratory SOFA was most predictive of death or ICU stay >3 days.

Sequential Organ Failure Assessment (SOFA) Score As a Predictor of Outcome in Sepsis in Pediatric Intensive Care Unit

2020 ◽  
Author(s):  
A.V. Lalitha ◽  
J.K. Satish ◽  
Mounika Reddy ◽  
Santu Ghosh ◽  
Jiny George ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Pediatric Intensive Care Unit ◽  
Sofa Score ◽  
Severity Of Illness ◽  
Pediatric Intensive Care ◽  
Inotropic Support ◽  
Discriminative Power ◽  
Failure Assessment

AbstractSequential organ failure assessment (SOFA) score is used as a predictor of outcome of sepsis in the pediatric intensive care unit. The aim of the study is to determine the application of SOFA scores as a predictor of outcome in children admitted to the pediatric intensive care unit with a diagnosis of sepsis. The design involved is prospective observational study. The study took place at the multidisciplinary pediatric intensive care unit (PICU), tertiary care hospital, South India. The patients included are children, aged 1 month to 18 years admitted with a diagnosis of sepsis (suspected/proven) to a single center PICU in India from November 2017 to November 2019. Data collected included the demographic, clinical, laboratory, and outcome-related variables. Severity of illness scores was calculated to include SOFA score day 1 (SF1) and day 3 (SF3) using a pediatric version (pediatric SOFA score or pSOFA) with age-adjusted cutoff variables for organ dysfunction, pediatric risk of mortality III (PRISM III; within 24 hours of admission), and pediatric logistic organ dysfunction-2 or PELOD-2 (days 1, 3, and 5). No intervention was observed during the period of study. A total of 240 patients were admitted to the PICU with septic shock during the study period. The overall mortality rate was 42 of 240 patients (17.5%). The majority (59%) required mechanical ventilation, while only 19% required renal replacement therapy. The PRISM III, PELOD-2, and pSOFA scores correlated well with mortality. All three severity of illness scores were higher among nonsurvivors as compared with survivors (p < 0.001). pSOFA scores on both day 1 (area under the curve or AUC 0.84) and day 3 (AUC 0.87) demonstrated significantly higher discriminative power for in-hospital mortality as compared with PRISM III (AUC, 0.7), and PELOD-2 (day 1, [AUC, 0.73]), and PELOD-2 (day 3, [AUC, 0.81]). Utilizing a cutoff SOFA score of >8, the relative risk of prolonged duration of mechanical ventilation, requirement for vasoactive infusions (vasoactive infusion score), and PICU length of stay were all significantly increased (p < 0.05), on both days 1 and 3. On multiple logistic regression, adjusted odds ratio of mortality was elevated at 8.65 (95% CI: 3.48–21.52) on day 1 and 16.77 (95% confidence interval or CI: 4.7–59.89) on day 3 (p < 0.001) utilizing the same SOFA score cutoff of 8. A positive association was found between the delta SOFA ([Δ] SOFA) from day 1 to day 3 (SF1–SF3) and in-hospital mortality (chi-square for linear trend, p < 0.001). Subjects with a ΔSOFA of ≥2 points had an exponential mortality rate to 50%. Similar association was—observed between ΔSOFA of ≥2 and—longer duration of inotropic support (p = 0.0006) with correlation co-efficient 0.2 (95% CI: 0.15–0.35; p = 0.01). Among children admitted to the PICU with septic shock, SOFA scores on both days 1 and 3, have a greater discriminative power for predicting in-hospital mortality than either PRISM III score (within 24 hours of admission) or PELOD-2 score (days 1 and 3). An increase in ΔSOFA of >2 adds additional prognostic accuracy in determining not only mortality risk but also duration of inotropic support as well.

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