Changes in neutrophil-to-lymphocyte ratios in postcardiac arrest patients treated with targeted temperature management

Baser, Kazim; Baş, Hatice; Attaluri, Pavan; Rodrigues, Terrance; Nichols, Jacob; Nugen, Kennetht

doi:10.14744/anatoljcardiol.2017.7716

Cited by 6 publications

(8 citation statements)

References 26 publications

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“…Because a widely inflammatory process is triggered in patients with CA, previous studies have frequently investigated the importance of inflammatory markers. [16][17][18][19][20] NLR, a cheap and an easily detectable marker from CBC, is a combination of two independent markers of systemic inflammation. 5 It was demonstrated that NLR was a stronger parameter than other white blood cell subtypes for evaluating the inflammatory process.…”

Section: Discussionmentioning

confidence: 99%

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Prognostic value of C‐reactive protein to albumin ratio in patients resuscitated from out‐of‐hospital cardiac arrest

et al. 2021

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Background: Despite major advances in basic and advanced life supports, patients who survived from out-of-hospital cardiac arrest (OHCA) have still poor prognosis.Several inflammatory parameters have been used to determine early and long-term prognosis in patients with OHCA. C-reactive protein-to-albumin ratio (CAR) is also a novel marker of systemic inflammation. To our knowledge, there is no study evaluating the clinical importance of CAR in OHCA patients. Aims:To evaluate the effect of CAR on in-hospital mortality in patients with OHCA.Methods: A total of 102 patients with OHCA were included in this study. The study population was divided into two groups as survivour (n = 43) and non-survivour (n = 59) during follow-up. Complete blood cell counts, biochemical and blood gas analyses were recorded for all patients. Neutrophil to lymphocyte ratio (NLR) was calculated as the ratio of neutrophil to lymphocyte. CAR was calculated as the ratio of C-reactive protein to the albumin.Results: NLR (P = .012), CAR (P < .001) and serum lactate level (P = .002) were significantly higher whereas lymphocyte (P = .008) and serum albumin (P < .001) were significantly lower in the non-survivour group compared with the survivour group.Multivariate logistic regression analysis showed that NLR (odds ratio [OR]: 1.044,

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Section: Discussionmentioning

confidence: 99%

“…Because a widely inflammatory process is triggered in patients with CA, previous studies have frequently investigated the importance of inflammatory markers 16‐20 . NLR, a cheap and an easily detectable marker from CBC, is a combination of two independent markers of systemic inflammation 5 .…”

Section: Discussionmentioning

confidence: 99%

Prognostic value of C‐reactive protein to albumin ratio in patients resuscitated from out‐of‐hospital cardiac arrest

et al. 2021

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“…Recently, the relationship between lymphopenia in the acute phase and prognosis of PCAS patients was reported. One study showed that the neutrophil–lymphocyte ratio (NLR) is associated with mortality in cardiac arrest patients at admission . Another study showed that lymphopenia occurs in PCAS patients at admission and is associated with neurological recovery in out‐of‐hospital cardiac arrest patients .…”

Section: Introductionmentioning

confidence: 99%

Association between lymphocyte count and neurological outcomes in post‐cardiac arrest patients treated with mild therapeutic hypothermia

Miyatake

Fujino

Tanaka

et al. 2018

Acute Medicine & Surgery

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AimTo examine lymphocyte counts as a predictive prognostic marker in patients with coma after cardiac arrest.MethodsWe retrospectively evaluated patients with coma after cardiac arrest admitted to the intensive care unit of Shiga University of Medical Science (Otsu, Japan). Lymphocyte counts were measured for 6 days from admission. Neurological outcome was assessed as favorable or unfavorable using cerebral performance categories. Associations between lymphocyte count and prognosis were investigated using multivariate logistic regression analysis and receiver operating characteristic curves.ResultsForty‐six patients were assessed from February 2012 to December 2016. Survivors had significantly higher lymphocyte counts than non‐survivors on days 2 and 5. Multivariate analysis showed that lymphocyte count was not associated with 90‐day mortality. Patients with favorable neurological outcome at discharge had significantly higher lymphocyte counts on days 2–6 than patients with unfavorable outcomes. Multivariate logistic regression analysis, including possible confounders, showed that lymphocyte counts on days 2–4 and 6 were associated with neurological outcome (day 2: odds ratio [OR] = 0.75, 95% confidence interval [CI] = 0.58–0.97, P = 0.029; day 3: OR = 0.68, 95% CI = 0.47–0.98, P = 0.04; day 4: OR = 0.4, 95% CI = 0.16–1.00, P = 0.05; day 6: OR = 0.69, 95% CI = 0.48–0.99, P = 0.046). Receiver operating characteristic curve analysis indicated high accuracy for predicting neurological outcome for each lymphocyte count on days 2–6 using the area under the curve, day 4 values being most accurate (day 2: 0.776, day 3: 0.787, day 4: 0.909, day 5: 0.774, day 6: 0.839).ConclusionLymphocyte counts on days 2–4 and 6 after cardiac arrest are associated with neurological outcome; counts on day 4 most accurately predict neurological outcome.

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“…Baser et al [61] investigated the relationship between neutrophil cells and mortality risk prediction and emphasized that vasopressors are used in patients who survive.…”

Section: Discussionmentioning

confidence: 99%

An enhanced random forest approach using CoClust clustering: MIMIC-III and SMS spam collection application

2023

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The random forest algorithm could be enhanced and produce better results with a well-designed and organized feature selection phase. The dependency structure between the variables is considered to be the most important criterion behind selecting the variables to be used in the algorithm during the feature selection phase. As the dependency structure is mostly nonlinear, making use of a tool that considers nonlinearity would be a more beneficial approach. Copula-Based Clustering technique (CoClust) clusters variables with copulas according to nonlinear dependency. We show that it is possible to achieve a remarkable improvement in CPU times and accuracy by adding the CoClust-based feature selection step to the random forest technique. We work with two different large datasets, namely, the MIMIC-III Sepsis Dataset and the SMS Spam Collection Dataset. The first dataset is large in terms of rows referring to individual IDs, while the latter is an example of longer column length data with many variables to be considered. In the proposed approach, first, random forest is employed without adding the CoClust step. Then, random forest is repeated in the clusters obtained with CoClust. The obtained results are compared in terms of CPU time, accuracy and ROC (receiver operating characteristic) curve. CoClust clustering results are compared with K-means and hierarchical clustering techniques. The Random Forest, Gradient Boosting and Logistic Regression results obtained with these clusters and the success of RF and CoClust working together are examined.

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Changes in neutrophil-to-lymphocyte ratios in postcardiac arrest patients treated with targeted temperature management

Cited by 6 publications

References 26 publications

Prognostic value of C‐reactive protein to albumin ratio in patients resuscitated from out‐of‐hospital cardiac arrest

Prognostic value of C‐reactive protein to albumin ratio in patients resuscitated from out‐of‐hospital cardiac arrest

Association between lymphocyte count and neurological outcomes in post‐cardiac arrest patients treated with mild therapeutic hypothermia

An enhanced random forest approach using CoClust clustering: MIMIC-III and SMS spam collection application

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