Biofluid Biomarkers in the Prognosis of Chronic Subdural Hematoma: A Systematic Scoping Review
Abstract
:1. Introduction
2. Materials and Methods
3. Results
3.1. Study and Population Characteristics
3.2. Biofluids and Biomarker Types
3.3. Biomarker Findings
3.3.1. Immune- and/or Circulatory-System-Associated Cellular Populations
3.3.2. Cytokines
3.3.3. Fibrinolysis-/Coagulation-Associated Molecules/Complexes, Products and Assays
3.3.4. Other/Miscellaneous
Author, Year [Ref. Number] | Study Type | Sample Size, Recurrence % | Biofluids Utilized | Biomarkers Analyzed | Significant Biomarker Findings (Recurrence/Outcome) |
---|---|---|---|---|---|
Κönig et al., 2003 [12] | Prospective Cohort | 114, 17.5% | Blood and plasma | PLTs, INR, APTT, fibrinogen, FXIII | ↓ PLTs in recurrence |
Frati et al., 2004 [21] | Prospective Cohort | 35, 14.3% | Serum and hematoma | IL-6, IL-8 | ↑ Hematoma IL-6 and IL-8 in recurrence |
Katano et al., 2006 [23] | Prospective Cohort | 60, 8.1% | Serum and hematoma | Plasminogen, antiplasmin, TPA, PIC, HGF, VEGF, bFGF | ↑ Hematoma TPA in recurrence |
Kristof et al., 2008 [9] | Prospective Cohort | 75, 22.7% | Serum, hematoma and hygroma | β-TP | ↑ β-TP of hematoma and hygroma in recurrence |
Hong et al., 2009 [6] | Prospective Cohort | 66, 21.21% | Hematoma | IL-6, VEGF, bFGF | ↑ IL-6 in recurrence |
Song et al., 2013 [20] | Prospective Cohort | 30, 20% | Blood | RBCs, WBCs, PLTs, Hb, PT, APTT, INR, TT, EPCs | ↓ EPCs in recurrence |
Bosche et al., 2013 [24] | Prospective Cohort | 18, 33.3% | Plasma | INR, PTT, PLTs, fibrinogen, FXIII | FXIII activity 68.5% (cut-off) → recurrence (100% sensitivity, 75% specificity) |
Pripp et al., 2014 [22] | Prospective Cohort | 57, 12.5% | Blood and hematoma | TNF-a, IL-1b, IL-2, IL-2R, IL-6, IL-7, IL-12, IL-15, IL-17, CCL2, CXCL8, CXCL9, CXCL1 and IL-1RA, IL-4, IL-5, IL-10 and IL-13 | ↑ Hematoma anti-inflammatory activity (IL-4, IL-5, IL-10, IL-1 RA, IL-13) → ↓ recurrence |
Pripp et al., 2017 [10] | Retrospective Cohort | 93, 17.2% | Hematoma | IL-1-IL-17, TNF-a, IFN-g, CXCL8, GM-CSF, VEGF | ↑ CXCL8 (IL8), CXCL10, IL-5, IL-13, IFN-γ → ↓ recurrence ↑ CCL5 (RANTES) → ↑ recurrence |
Hori et al., 2018 [27] | Retrospective Cohort | 92, NR | Serum | FDP, APTT, PT, D-dimer, PLTs, INR, Hb | FDP > 5 μg/mL = independent recurrence risk factor |
Wang et al., 2020 [25] | Prospective Cohort | 653, 14.7% | Serum | Glucose, Cr, leukocytes, neutrophils, lymphocytes, erythrocytes, Hg, PLTs, PT, INR, fibrinogen, BUN | ↓ Serum leukocytes, neutrophils, PLTs, fibrinogen in recurrence BUN > 6.4 mmol/L = independent recurrence risk factor |
Suero-Molina et al., 2020 [13] | Retrospective Cohort | 148, 23.6% | Blood | PLTs | ↓ PLTs in recurrence |
Liu et al., 2021 [29] | Retrospective Cohort | 274, 84.67% | Serum | TG, total cholesterol, LDL, HDL | ↑ Serum TG in recurrence Low HDL = independent recurrence risk factor (HDL > 37.5 mg/dL, ↓ risk) |
Martinez-Perez et al., 2021 [26] | Retrospective Cohort | 90, 18.9% | Blood | PLTs, Hb, PT | ↑ PT = independent recurrence risk factor |
Chihi et al., 2021 [28] | Prospective Cohort | 119, 13.3% | Plasma | BNP-1 | BNP-1 = independent predictor for functional outcome |
Hirai et al., 2021 [14] | Retrospective Cohort | 307, 10.6% | Blood | PLTs, ABO type | ↓ PLTs = independent recurrence risk factor; blood type A = independent recurrence risk factor (64.9% sensitivity, 58.8% specificity) |
De Oliveira et al., 2022 [19] | Retrospective Cohort | 160, 22.5% | Blood | Neutrophils, NLR | Absolute neutrophil count = independent recurrence risk factor; NLR ≥ 1 = independent recurrence risk factor (77.8% sensitivity, 66.7% specificity); validation on independent sample |
Idowu et al., 2022 [17] | Prospective Cohort | 61, NR | Blood | INR, PT, APTT, NLR, CRP, ESR, PLR | ↑ APTT, ↑ PT, ↑ INR, ↓ PLR → worse outcome |
Mainka et al., 2022 [30] | Retrospective Cohort | 256, 32% | Serum | U/CR | U/Cr > 80 = independent recurrence risk factor |
Chen et al., 2022 [16] | Retrospective Cohort | 258, 14.3% | Blood | WBCs, PLTs, basophils, eosinophils | Eosinophils < 0.15 × 109 = independent recurrence risk factor |
Guresir et al., 2022 [18] | Retrospective Cohort | 297, 12.5% | Blood | CRP, Hb, WBC, PLTs, RDW, RPR | RPR ≥ 0.0568 = independent recurrence risk factor (70.3% sensitivity, 56.2% specificity); low RPR → higher Karnofsky at 3 months |
Matsubara et al., 2023 [15] | Retrospective Cohort | 466, 9.3% | Blood | Eosinophils, PLTs | ↓ PLTs and eosinophils ≥ 100/µL = independent recurrence risk factors |
Puccio et al., 2023 [11] | Prospective Cohort | 20, 42% (21% requiring reoperation) | Hematoma | CXCL9, MCP-1, G-CSF, IL-6, VEGF-A, IL-8, PDGF-AB/BB, PDGF-AA, MDC, IL-1α, IP-10, IL-5, RANTES, IL-10, IL-1β, IL-1 Ra, M-CSF | ↑ IL-5 → ↑ GOS-E RANTES < 1649.24 pg/mL → ↑ recurrence |
4. Discussion
4.1. Biomarker Study Characteristics/Designs and Time Trends
4.2. Biomarkers in Recurrence Prediction
4.3. Biomarkers in Neurological/Functional Outcome Prognosis
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
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Georgountzos, G.; Gkalonakis, I.; Anastasopoulos, L.; Stranjalis, G.; Κalamatianos, T. Biofluid Biomarkers in the Prognosis of Chronic Subdural Hematoma: A Systematic Scoping Review. Diagnostics 2023, 13, 2449. https://doi.org/10.3390/diagnostics13142449
Georgountzos G, Gkalonakis I, Anastasopoulos L, Stranjalis G, Κalamatianos T. Biofluid Biomarkers in the Prognosis of Chronic Subdural Hematoma: A Systematic Scoping Review. Diagnostics. 2023; 13(14):2449. https://doi.org/10.3390/diagnostics13142449
Chicago/Turabian StyleGeorgountzos, Georgios, Ioannis Gkalonakis, Lykourgos Anastasopoulos, George Stranjalis, and Theodosis Κalamatianos. 2023. "Biofluid Biomarkers in the Prognosis of Chronic Subdural Hematoma: A Systematic Scoping Review" Diagnostics 13, no. 14: 2449. https://doi.org/10.3390/diagnostics13142449