Blood Count-Derived Inflammatory Markers Correlate with Lengthier Hospital Stay and Are Predictors of Pneumothorax Risk in Thoracic Trauma Patients.
Vlad VunvuleaRăzvan Marian MelinteKlara BrinzaniucBogdan Andrei SuciuAdrian Dumitru IvănescuIoana HălmaciuZsuzsanna Incze-BarthaYlenia PastorelloCristian TrâmbițașLucian MărgineanRéka KallerAhmad KassasTimur HogeaPublished in: Diagnostics (Basel, Switzerland) (2023)
(1) Background: Trauma is one of the leading causes of death worldwide, with the chest being the third most frequent body part injured after abdominal and head trauma. Identifying and predicting injuries related to the trauma mechanism is the initial step in managing significant thoracic trauma. The purpose of this study is to assess the predictive capabilities of blood count-derived inflammatory markers at admission. (2) Materials and Methods: The current study was designed as an observational, analytical, retrospective cohort study. It included all patients over the age of 18 diagnosed with thoracic trauma, confirmed with a CT scan, and admitted to the Clinical Emergency Hospital of Targu Mureş, Romania. (3) Results: The occurrence of posttraumatic pneumothorax is highly linked to age ( p = 0.002), tobacco use ( p = 0.01), and obesity ( p = 0.01). Furthermore, high values of all hematological ratios, such as the NLR, MLR, PLR, SII, SIRI, and AISI, are directly associated with the occurrence of pneumothorax ( p < 0.001). Furthermore, increased values of the NLR, SII, SIRI, and AISI at admission predict a lengthier hospitalization ( p = 0.003). (4) Conclusions: Increased neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic inflammatory index (SII), aggregate inflammatory systemic index (AISI), and systemic inflammatory response index (SIRI) levels at admission highly predict the occurrence of pneumothorax, according to our data.
Keyphrases
- trauma patients
- emergency department
- inflammatory response
- peripheral blood
- risk assessment
- spinal cord
- healthcare
- computed tomography
- end stage renal disease
- oxidative stress
- metabolic syndrome
- type diabetes
- public health
- chronic kidney disease
- insulin resistance
- adipose tissue
- adverse drug
- electronic health record
- peritoneal dialysis
- spinal cord injury
- skeletal muscle
- image quality
- machine learning
- mass spectrometry
- drug induced
- deep learning
- big data
- weight gain
- positron emission tomography
- data analysis
- liquid chromatography