Prognosis evaluation is crucial for the effective management of patients with acute traumatic brain injury (TBI). However, there is still a lack of routinely available blood indicators for mortality risk in clinical practice. To investigate whether blood red cell distribution width to platelet count ratio (RPR) correlates with hospital mortality of TBI, clinical data of 2220 patients with TBI were extracted from two large intensive care unit cohorts (MIMIC-III and eICU Database), and were integratively analyzed using our developed method named MeDICS. We found that higher RPR can be observed among non-survivors than survivors of TBI (p < 0.001). It had a moderately good prognostic performance for mortality with an area under receiver-operating characteristic curve (AUC) of 0.7367, which was greater than that of Glasgow Coma Scale (GCS; AUC = 0.6022). Besides, the nomogram consisting of RPR, GCS, and other risk factors was developed, where 10-fold cross-validation was performed to protect it against overfitting. A Harrell's C-index of 0.8523 was determined, suggesting an improved prognostic value based on RPR. The in vivo experiments further confirmed the association between RPR and neuro-outcome after TBI. It indicated that the continuous change in RPR post-injury is attributed to the development of inflammation, which emphasized the importance of controlling inflammatory response in clinical treatment. Taken together, RPR is a promising routinely available predictor of mortality for acute TBI. The nomogram generated from it can be used in resource-limited settings, thus be proposed as a prognosis evaluation aid for patients with TBI in all levels of medical system.
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References
1.
RubianoA.M., CarneyN., ChesnutR., and PuyanaJ.C. (2015). Global neurotrauma research challenges and opportunities. Nature, 527, S193–S197.
MurrayG., BrennanP., and TeasdaleG. (2018). Simplifying the use of prognostic information in traumatic brain injury. Part 2: Graphical presentation of probabilities. J. Neurosurg. 128, 1621–1634.
4.
UndénL., CalcagnileO., UndénJ., ReinstrupP., and BazarianJ. (2015). Validation of the Scandinavian guidelines for initial management of minimal, mild and moderate traumatic brain injury in adults. BMC Med. 13, 292.
5.
ShahimP., PolitisA., van der MerweA., MooreB., EkanayakeV., LippaS., ChouY., PhamD., ButmanJ., Diaz-ArrastiaR., ZetterbergH., BlennowK., GillJ., BrodyD., and ChanL. (2020). Time course and diagnostic utility of NfL, tau, GFAP, and UCH-L1 in subacute and chronic TBI. Neurology, 95, e623–e636.
6.
CzeiterE., AmreinK., GravesteijnB., LeckyF., MenonD., MondelloS., NewcombeV., RichterS., SteyerbergE., VyvereT., VerheydenJ., XuH., YangZ., MaasA., WangK., and BükiA. (2020). Blood biomarkers on admission in acute traumatic brain injury: Relations to severity, CT findings and care path in the CENTER-TBI study. EBioMedicine, 56, 102785.
7.
FrankelM., FanL., YeattsS., JerominA., VosP., WagnerA., WolfB., PaulsQ., LunneyM., MerckL., HallC., PaleschY., SilbergleitR., and WrightD. (2019). Association of very early serum levels of S100B, glial fibrillary acidic protein, ubiquitin C-terminal hydrolase-L1, and spectrin breakdown product with outcome in ProTECT III. J. Neurotrauma, 36, 2863–2871.
8.
DolmansR., HulsbergenA., GormleyW., and BroekmanM. (2020). Routine blood tests for severe traumatic brain injury: can they predict outcomes?. World Neurosurg. 136, e60–e67.
9.
SadakaF., DoctorsN., PearsonT., SnydersB., and O'BrienJ. (2018). Does red cell distribution width predict outcome in traumatic brain injury: comparison to corticosteroid randomization after significant head injury. J. Clin. Med. Res. 10, 9–12.
10.
LorenteL., MartínM., RuizC., Abreu-GonzálezP., Pérez-CejasA., González-RiveroA., Ramos-GómezL., ArguesoM., Solé-ViolánJ., CáceresJ., JiménezA., and García-MarínV. (2020). Red blood cell distribution width as mortality biomarker in patients with traumatic brain injury. Acta Neurol. Belg. 2020 Jun 15; Epub ahead of. print.
11.
Fletcher-SandersjööA., ThelinE., MaegeleM., SvenssonM., and BellanderB. (2020). Time course of hemostatic disruptions after traumatic brain injury: a systematic review of the literature. Neurocrit. Care. 2020 Jun 30; Epub ahead of. print.
12.
YuanQ., YuJ., WuX., SunY., LiZ., DuZ., WuX., and HuJ. (2018). Prognostic value of coagulation tests for in-hospital mortality in patients with traumatic brain injury. Scand. J. Trauma Resusc. Emerg. Med. 26, 3.
13.
SimonD., McGeachyM., BayırH., ClarkR., LoaneD., and KochanekP. (2017). The far-reaching scope of neuroinflammation after traumatic brain injury. Nat. Rev. Neurol. 13, 171–191.
14.
XuX., YinD., RenH., GaoW., LiF., SunD., WuY., ZhouS., LyuL., YangM., XiongJ., HanL., JiangR., and ZhangJ. (2018). Selective NLRP3 inflammasome inhibitor reduces neuroinflammation and improves long-term neurological outcomes in a murine model of traumatic brain injury. Neurobiol. Dis. 117, 15–27.
15.
GeX., LiW., HuangS., YinZ., YangM., HanZ., ChenF., WangH., LeiP., and ZhangJ. (2019). Increased miR-21-3p in injured brain microvascular endothelial cells after traumatic brain injury aggravates blood-brain barrier damage by promoting cellular apoptosis and inflammation through targeting MAT2B. J. Neurotrauma, 36, 1291–1305.
16.
GeX., LiW., HuangS., YinZ., XuX., ChenF., KongX., WangH., ZhangJ., and LeiP. (2018). The pathological role of NLRs and AIM2 inflammasome-mediated pyroptosis in damaged blood-brain barrier after traumatic brain injury. Brain Res. 10–20.
17.
HuangS., GeX., YuJ., HanZ., YinZ., LiY., ChenF., WangH., ZhangJ., and LeiP. (2018). Increased miR-124-3p in microglial exosomes following traumatic brain injury inhibits neuronal inflammation and contributes to neurite outgrowth via their transfer into neurons. FASEB J. 32, 512–528.
18.
GeX., YuJ., HuangS., YinZ., HanZ., ChenF., WangZ., ZhangJ., and LeiP. (2018). A novel repetitive mild traumatic brain injury mouse model for chronic traumatic encephalopathy research. J. Neurosci. Methods, 308, 162–172.
19.
LegerM., QuiedevilleA., BouetV., HaelewynB., BoulouardM., Schumann-BardP., and FreretT. (2013). Object recognition test in mice. Nat. Protoc. 8, 2531–2537.
20.
ZhangY., KimM.S., JiaB., YanJ., Zuniga-HertzJ.P., HanC., and CaiD. (2017). Hypothalamic stem cells control ageing speed partly through exosomal miRNAs. Nature, 548, 52–57.
21.
ZhangJ., ZhangF., and DongJ. (2018). Coagulopathy induced by traumatic brain injury: systemic manifestation of a localized injury. Blood, 131, 2001–2006.
22.
LippiG., SalvagnoG.L., and GuidiG.C. (2014). Red blood cell distribution width is significantly associated with aging and gender. Clin. Chem. Lab. Med. 52, e197–e199.
23.
SalvagnoG.L., Sanchis-GomarF., PicanzaA., and LippiG. (2015). Red blood cell distribution width: a simple parameter with multiple clinical applications. Crit. Rev. Clin. Lab. Sci. 52, 86–105.
24.
GhaffariS. (2008). Oxidative stress in the regulation of normal and neoplastic hematopoiesis. Antioxid. Redox. Signal, 10, 1923–1940.
25.
SunP., ZhangF., ChenC., BiX., YangH., AnX., WangF., and JiangW. (2016). The ratio of hemoglobin to red cell distribution width as a novel prognostic parameter in esophageal squamous cell carcinoma: a retrospective study from southern China. Oncotarget, 7, 42650–42660.
AssingerA., SchrottmaierW., SalzmannM., and RayesJ. (2019). Platelets in sepsis: an update on experimental models and clinical data. Front. Immunol. 10, 1687.
28.
RipocheJ. (2011). Blood platelets and inflammation: their relationship with liver and digestive diseases. Clin. Res. Hepatol. Gastroenterol. 35, 353–357.
29.
GuoF., WangX., HuanJ., LiangX., ChenB., TangJ., and GaoC. (2012). Association of platelet counts decline and mortality in severely burnt patients. J. Crit. Care 27, 529. e521–e527.
30.
DingY., TaoZ., WangH., LiaoZ., ZhuX., XuW., JinF., and LiuH. (2019). Predictive value of the red blood cell distribution width-to-platelet ratio for hepatic fibrosis. Scand. J. Gastroenterol. 54, 81–86.
31.
TaefiA., HuangC., KolliK., EbrahimiS., and PatelM. (2015). Red cell distribution width to platelet ratio, a useful indicator of liver fibrosis in chronic hepatitis patients. Hepatol. Int. 9, 454–460.
32.
CetinkayaE., SenolK., SaylamB., and TezM. (2014). Red cell distribution width to platelet ratio: new and promising prognostic marker in acute pancreatitis. World J. Gastroenterol. 20, 14450–14454.
33.
TekinY.K. and TekinG. (2020). Mean platelet volume-to-platelet count ratio, mean platelet volume-to-lymphocyte ratio, and red blood cell distribution width-platelet count ratio as markers of inflammation in patients with ascending thoracic aortic aneurysm. Brazilian J. Cardiovasc. Surg. 35, 175–180.
34.
CelikT., BaltaS., DemirM., YildirimA.O., KayaM.G., OzturkC., DemirkolS., UnluM., KilicS., AydinI., and IyisoyA. (2016). Predictive value of admission red cell distribution width-platelet ratio for no-reflow phenomenon in acute ST segment elevation myocardial infarction undergoing primary percutaneous coronary intervention. Cardiol. J. 23, 84–92.
35.
QiuL., ChenC., LiS.J., WangC., GuoF., PeszelA., LiuS., WangF., SunY.X., WangY.J., and ChenX.L. (2017). Prognostic values of red blood cell distribution width, platelet count, and red cell distribution width-to-platelet ratio for severe burn injury. Sci. Rep. 7, 13720.
36.
XieS. and ChenX. (2018). Red blood cell distribution width-to-platelet ratio as a disease activity-associated factor in systemic lupus erythematosus. Medicine, 97, e12342.
37.
GeX., HuangS., GaoH., HanZ., ChenF., ZhangS., WangZ., KangC., JiangR., YueS., LeiP., and ZhangJ. (2016). miR-21-5p alleviates leakage of injured brain microvascular endothelial barrier in vitro through suppressing inflammation and apoptosis. Brain Res. 1650, 31–40.
GeX., LiW., HuangS., YinZ., XuX., ChenF., KongX., WangH., ZhangJ., and LeiP. (2018). The pathological role of NLRs and AIM2 inflammasome-mediated pyroptosis in damaged blood-brain barrier after traumatic brain injury. Brain Res. 1697, 10–20.
40.
ShiK., ZhangJ., DongJ.F., and ShiF.D. (2019). Dissemination of brain inflammation in traumatic brain injury. Cell. Mol. Immunol. 16, 523–530.
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