Complete Blood Count and Derived Indices: Evolution Pattern and Prognostic Value in Adult Burned Patients

Angulo, Martín; Moreno, Laura; Aramendi, I.; Santos, Gimena dos; Cabrera, Julio; Burghi, Gastón

doi:10.1093/jbcr/iraa091

Cited by 14 publications

(29 citation statements)

References 36 publications

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“…Clinical laboratory results such as creatinine, platelet count, PT, and PLR are significant risk factors in burn patients. This result is consistent with previous studies using classic logistic regression analysis [ 24 , 25 ].…”

Section: Discussionsupporting

confidence: 94%

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Prediction of Mortality after Burn Surgery in Critically Ill Burn Patients Using Machine Learning Models

Park

Cho

Shin

et al. 2022

JPM

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Severe burns may lead to a series of pathophysiological processes that result in death. Machine learning models that demonstrate prognostic performance can be used to build analytical models to predict postoperative mortality. This study aimed to identify machine learning models with the best diagnostic performance for predicting mortality in critically ill burn patients after burn surgery, and then compare them. Clinically important features for predicting mortality in patients after burn surgery were selected using a random forest (RF) regressor. The area under the receiver operating characteristic curve (AUC) and classifier accuracy were evaluated to compare the predictive accuracy of different machine learning algorithms, including RF, adaptive boosting, decision tree, linear support vector machine, and logistic regression. A total of 731 patients met the inclusion and exclusion criteria. The 90-day mortality of the critically ill burn patients after burn surgery was 27.1% (198/731). RF showed the highest AUC (0.922, 95% confidence interval = 0.902–0.942) among the models, with sensitivity and specificity of 66.2% and 93.8%, respectively. The most significant predictors for mortality after burn surgery as per machine learning models were total body surface area burned, red cell distribution width, and age. The RF algorithm showed the best performance for predicting mortality.

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Section: Discussionsupporting

confidence: 94%

“…CBC is a routinely applied laboratory blood test for most patients. The unique components analyzed by CBC are known to be related with inflammation or infection that affects the prognosis of medical conditions [ 24 ]. Of these simple blood biomarkers, RDW is a numerical measurement of the range in the volume and size of the erythrocytes.…”

Section: Discussionmentioning

confidence: 99%

Prediction of Mortality after Burn Surgery in Critically Ill Burn Patients Using Machine Learning Models

Park

Cho

Shin

et al. 2022

JPM

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“…Simple and easily available biomarkers are more popular and accepted by clinicians ( 34 ). PPR, the ratio of PDW to PLT, is derived from CBC parameters ( 35 ). PPR was a simple and cheap parameter, which could be evaluated in routine clinical practice with minimal additional cost, and could help clinicians quickly identify high-risk patients ( 26 , 29 , 36 , 37 ).…”

Section: Discussionmentioning

confidence: 99%

“…They found that the AUC of RPR for adverse outcome prediction on day 3 were 0.712, while 0.750 on day 7. Angulo M et al ( 35 ) found that neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and RPR in the early stage of severe burns could identify patients with increased mortality. In our study, the AUC of PPR for predicting 120-day mortality was 0.816 on day 3, while 0.750 on day 7.…”

Section: Discussionmentioning

confidence: 99%

Prognostic Values of Platelet Distribution Width and Platelet Distribution Width-to-Platelet Ratio in Severe Burns

Lin

Zheng

et al. 2021

Shock

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Background: Platelet distribution width (PDW) and PDW-to-platelet ratio (PPR) have been proven to be good prognostic indicators for many diseases. However, their prognostic values in severe burns have not been reported. Objective: To investigate the early time course of PDW and PPR in severe burn patients and investigate their prognostic values. Methods: This is a 16-year, single-center retrospective study of 590 severe burn patients. The complete blood count parameters on day 1, day 3, and day 7 postburn, including PDW and PPR, were collected. Receiver operating characteristic curves (ROC) analysis, multiple logistic regression analysis and Kaplan-Meier survival analysis were performed to evaluate the prognostic values of PDW and PPR in severe burn patients. Results: According to 120-day follow-up records, 96 patients were nonsurvivors and 494 patients were survivors. ROC and area under the curve (AUC) analysis showed that, for predicting 120-day prognosis, the AUC of PDW (0.782) and PPR (0.816) on day 3 was the highest, followed by the AUC of PDW (0.764) and PPR (0.750) on day 7. The ROC-AUC of PPR (0.816) on day 3 was very close to that of the ABSI score (0.818). Multiple logistic regression analysis showed that the PDW (P ¼ 0.033 and P ¼ 0.009) and PPR (P ¼ 0.052 and P ¼ 0.046) on day 3 and day 7 were all significantly independently positively associated with 120-day mortality. Kaplan-Meier survival analysis showed that high PDW and PPR were both significantly associated with a high 120-day mortality rate on day 3 and day 7. Conclusion: PDW and PPR on day 3 and day 7 were independent risk factors for 120-day mortality in severe burn patients. These objective and readily available prognostic indicators may be more clinically favored.

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“…RPR has been associated with various clinical conditions in medical literature. These conditions include rheumatoid arthritis, autoimmune hepatitis, cardiovascular morbidities, mortality of burned patients and acute pancreatitis [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Red cell distribution width-to-platelet count ratio is a promising predictor of functional bowel disease

Kahveci,

Aktas,

Atak Tel

et al. 2022

fmpcr

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Complete Blood Count and Derived Indices: Evolution Pattern and Prognostic Value in Adult Burned Patients

Cited by 14 publications

References 36 publications

Prediction of Mortality after Burn Surgery in Critically Ill Burn Patients Using Machine Learning Models

Prediction of Mortality after Burn Surgery in Critically Ill Burn Patients Using Machine Learning Models

Prognostic Values of Platelet Distribution Width and Platelet Distribution Width-to-Platelet Ratio in Severe Burns

Red cell distribution width-to-platelet count ratio is a promising predictor of functional bowel disease

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