Dataset Information

Neutrophil CD64 expression is a predictor of mortality for patients in the intensive care unit.

ABSTRACT:

Background

Neutrophil CD64 has been shown to be a promising biomarker for bacterial infection and sepsis identification. However, the prognostic value of CD64 in predicting the likelihood of survival for patients in intensive care unit (ICU) is unclear.

Methods

A total of 797 patients in the ICU of Xin-Hua Hospital, Shanghai, China were enrolled. We determined the Acute Physiology and Chronic Health Evaluation II (APACHE II) scores from these patients and collected blood samples to measure the levels of neutrophil CD64, thyroid hormone and C-reactive protein (CRP). We assessed the association between APACHE II scores or these biomarkers and mortality of patients in the ICU. Receiver operating characteristic (ROC) curves were generated and the Area Under the Curve (AUC) for each indicator was determined.

Results

The AUC for CD64 was 0.752 ± 0.026, which was higher than that of FT3 (0.696 ± 0.028) and CRP (0.672 ± 0.026). APACHE II scores had the highest AUC (0.872 ± 0.018). The level of neutrophil CD64 expression positively associated with CRP and APACHE II, and negatively correlated with FT3. Multiple regression analysis revealed that APACHE II scores (Standard ? value = 0.183, P < 0.001), CD64 (Standard ? value = 0.518, P < 0.001) or log (CRP) (Standard ? value = 1.203, P < 0.001) independently predicted ICU mortality.

Conclusion

CD64 had the greatest power for predicting ICU mortality other than APACHE II scores. This result indicates that CD64 may be used as a biomarker to in combination with the use of APACHE II scores to improve the accuracy of predicting mortality outcome for patients in the ICU.

SUBMITTER: Chen Q

PROVIDER: S-EPMC4270525 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Neutrophil CD64 expression is a predictor of mortality for patients in the intensive care unit.

Chen Qiqi Q Shi Junfeng J Fei Aihua A Wang Feilong F Pan Shuming S Wang Weiwei W

International journal of clinical and experimental pathology 20141015 11

<h4>Background</h4>Neutrophil CD64 has been shown to be a promising biomarker for bacterial infection and sepsis identification. However, the prognostic value of CD64 in predicting the likelihood of survival for patients in intensive care unit (ICU) is unclear.<h4>Methods</h4>A total of 797 patients in the ICU of Xin-Hua Hospital, Shanghai, China were enrolled. We determined the Acute Physiology and Chronic Health Evaluation II (APACHE II) scores from these patients and collected blood samples t ...[more]

PMID: 25550820

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Project description:ObjectivesIdentifying high-risk patients in the intensive care unit (ICU) is important given the high mortality rate. However, existing scoring systems lack easily accessible, low-cost and effective inflammatory markers. We aimed to identify inflammatory markers in routine blood tests to predict mortality in ICU patients and evaluate their predictive power.DesignRetrospective case-control study.SettingSingle secondary care centre.ParticipantsWe analysed data from the Medical Information Mart for Intensive Care III database. A total of 21 822 ICU patients were enrolled and divided into survival and death groups based on in-hospital mortality.Primary and secondary outcome measuresThe predictive values of potential inflammatory markers were evaluated and compared using receiver operating characteristic curve analysis. After identifying the neutrophil-to-lymphocyte ratio (NLR) as having the best predictive ability, patients were redivided into low (≤1), medium (1-6) and high (>6) NLR groups. Univariate and multivariate logistic regression analyses were performed to evaluate the association between the NLR and mortality. The area under the curve (AUC), net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were used to assess whether incorporating the NLR could improve the predictive power of existing scoring systems.ResultsThe NLR had the best predictive ability (AUC: 0.609; p<0.001). In-hospital mortality rates were significantly higher in the low (OR (OR): 2.09; 95% CI 1.64 to 2.66) and high (OR 1.64; 95% CI 1.50 to 1.80) NLR groups than in the medium NLR group. Adding the NLR to the Simplified Acute Physiology Score II improved the AUC from 0.789 to 0.798, with an NRI and IDI of 16.64% and 0.27%, respectively.ConclusionsThe NLR predicted mortality in ICU patients well. Both low and high NLRs were associated with elevated mortality rates, including the NLR may improve the predictive power of the Simplified Acute Physiology Score II.

Project description:BackgroundAcute kidney injury (AKI) is a common complication in patients during intensive care unit (ICU) admission. AKI is defined as an increase in serum creatinine (SCr) and/or a reduction in urine output. SCr is a marker of renal function with several limitations, which led to the search for biomarkers for earlier AKI detection. Our aim was to study the predictive value of plasma neutrophil gelatinase-associated lipocalin (NGAL) at admission as a biomarker for AKI progression during the first 48 h of ICU admission in an unselected, heterogeneous ICU patient population.MethodsWe conducted a prospective observational study in an academic tertiary referral ICU population. We recorded AKI progression in all ICU patients during the first 48 h of ICU admission in a 6-week period. Plasma NGAL was measured at admission but levels were not reported to the attending clinicians. As possible predictors of AKI progression, pre-existing AKI risk factors were recorded. We examined the association of clinical parameters and plasma NGAL levels at ICU admission with the incidence and progression of AKI within the first 48 h of the ICU stay.ResultsA total of 361 patients were included. Patients without AKI progression during the first 48 h of ICU admission had median NGAL levels at admission of 115 ng/mL [interquartile range (IQR) 81-201]. Patients with AKI progression during the first 48 h of ICU admission had median NGAL levels at admission of 156 ng/mL (IQR 97-267). To predict AKI progression, a multivariant model with age, sex, diabetes mellitus, body mass index, admission type, Acute Physiology and Chronic Health Evaluation score and SCr at admission had an area under the receiver operating characteristics (ROC) curve of 0.765. Adding NGAL to this model showed a small increase in the area under the ROC curve to 0.783 (95% confidence interval 0.714-0.853).ConclusionsNGAL levels at admission were higher in patients with progression of AKI during the first 48 h of ICU admission, but adding NGAL levels at admission to a model predicting this AKI progression showed no significant additive value.

Dataset Information

Neutrophil CD64 expression is a predictor of mortality for patients in the intensive care unit.

Background

Methods

Results

Conclusion

Publications

Neutrophil CD64 expression is a predictor of mortality for patients in the intensive care unit.

Similar Datasets

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