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ORIGINAL RESEARCH article

Front. Neurol., 04 December 2025

Sec. Neurotrauma

Volume 16 - 2025 | https://doi.org/10.3389/fneur.2025.1674327

Factors associated with progression and sex-specific patterns in chronic subdural hematoma: a single-centre retrospective study

Weijian Yang,,,,&#x;Weijian Yang1,2,3,4,5Zhuoying Du,,,,&#x;Zhuoying Du1,2,3,4,5Qifang Chen,,,,&#x;Qifang Chen1,2,3,4,6Qiang Yuan,,,,Qiang Yuan1,2,3,4,5Pengfei Fu,,,,Pengfei Fu1,2,3,4,5Jiang Fang,,,,Jiang Fang1,2,3,4,5Jin Hu,,,,
Jin Hu1,2,3,4,5*Gang Wu,,,,
Gang Wu1,2,3,4,5*
  • 1Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
  • 2National Center for Neurological Disorders, Shanghai, China
  • 3Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, China
  • 4Neurosurgical Institute of Fudan University, Shanghai, China
  • 5Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China
  • 6Department of Nursing, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China

Objective: This study aims to identify determinants of chronic subdural hematoma (CSDH) progression and to evaluate potential sex-related differences.

Methods: Patients with unilateral CSDH were retrospectively enrolled between January 2018 and December 2024. Data on demographics, clinical characteristics, hematoma density, hematological parameters and coagulation function were collected. Multivariable logistic regression was used to identify independent predictors. Patients were randomly divided into training and validation cohorts in a 7:3 ratio to identify factors associated with hematoma progression. Subsequently, logistic regression models were applied to both cohorts to confirm the factors influencing progression.

Results: This retrospective study enrolled 1,142 patients, who were categorized into progression (n = 773, 67.69%) and recovery (n = 369, 32.31%) groups. Multivariate regression analysis revealed that international normalized ratio (INR) (OR 7.39, 95% CI 2.79–19.55), hypertension (OR 5.35, 95% CI 2.80–10.25), diabetes (OR 4.68, 95% CI 1.74–12.60), neutrophil to lymphocyte ratio (NLR) (OR 2.14, 95% CI 1.46–3.13), white blood cell count (WBC) (OR 1.16, 95% CI 1.02–1.31), and maximum hematoma density (MaHD) (OR 1.02, 95% CI 1.01–1.03) were independent risk factors for hematoma progression, whereas female gender (OR 0.61, 95% CI 0.40–0.95) was identified as a protective factor against CSDH progression. Subgroup analysis stratified by sex revealed statistically significant differences between female and male patients in hemoglobin concentration, serum albumin level, and platelet count. Nevertheless, all values remained within the respective sex-specific reference intervals.

Conclusion: Elevated INR, hypertension, diabetes, NLR, WBC, and MaHD were independently associated with CSDH progression. Female sex conferred a protective effect. These findings require prospective validation.

1 Introduction

Chronic subdural hematoma (CSDH), defined as an encapsulated accumulation of blood products located within the subdural space, is a common neurosurgical condition among older adults (1). Population-based studies report an annual incidence of 1.7–20.6 per 100,000 person-years (2). Population ageing is projected to increase the burden of CSDH substantially on both neurosurgical services and wider healthcare systems (3). Clinical manifestations span from incidental neuroimaging findings to overt impairment of consciousness. Absence of high-level evidence underpins marked inter-hospital and international heterogeneity in management strategies (4). Asymptomatic or minimally symptomatic patients may be managed conservatively with serial clinical review and interval imaging as clinically indicated (5).

The current body of literature identifies a limited number of factors that influence the progression of hematomas. Studies have demonstrated that hematoma volume and the presence of hypodense hematoma types are significant contributors to the efficacy of conservative treatment for CSDH (5, 6). Additionally, emerging evidence indicates that the pathogenesis and progression of CSDH are closely associated with inflammatory cascades (79). Furthermore, coagulation profiles play a crucial role in influencing the dynamics of the disease (10, 11). Recent investigations also suggest the presence of gender disparities within CSDH populations, with female patients exhibiting distinct clinical manifestations, laboratory profiles, and therapeutic responses when compared to their male counterparts (12, 13). Nevertheless, research focusing on sex-specific differences remains limited, and the underlying mechanisms that drive these variations are not yet fully understood.

In the absence of these parameters, clinicians face considerable challenges in formulating a “wait-and-watch” strategy. This study sought to evaluate the efficacy of initial conservative treatment at the levels of the patient, coagulation, inflammatory markers, and hematoma. Furthermore, it aimed to identify factors associated with the progression of CSDH in a large, consecutive cohort of patients with unilateral CSDH. Additionally, a gender-based analysis of the disease was conducted.

2 Materials and methods

2.1 Participants and study settings

This research was conducted in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Ethical approval was waived by the Ethics Committee of the Evaluation of Biomedical Research Projects of Huashan Hospital in view of the retrospective nature of the study and all the procedures being performed were part of the routine care. All patient information was de-identified, and patient consent to participate or publish was waived by the ethics committee. The study conducted a comprehensive evaluation of all inpatients and outpatients diagnosed with CSDH at Huashan Hospital, an academic teaching hospital affiliated with Fudan University, over the period from January 2018 to December 2024. The inclusion criteria encompassed: (1) patients diagnosed with primary unilateral CSDH via computed tomography (CT); and (2) individuals aged 18 years or older. The exclusion criteria included: (1) patients with a medical history of tumors, intracerebral arteriovenous malformations, arachnoid cysts, ventriculoperitoneal shunts, immunodeficiency, coagulation disorders, or chronic inflammation; (2) patients receiving immunosuppressive or anti-inflammatory treatment upon admission; and (3) patients who were lost to follow-up or had incomplete data. The study cohort was divided into two groups: progression and recovery. Recovery was defined as the resolution of CSDH on CT imaging without the need for surgical intervention. Hematoma progression was characterized by a notable decline in neurological function, including exacerbating headaches, progressive limb paralysis, or altered levels of consciousness, as well as the enlargement of the hematoma and/or midline shift observed on follow-up CT scans. The follow-up period for patients extended over six months.

2.2 Data collection

The study systematically gathered extensive data on patients, encompassing both demographic and clinical information. Demographic data included gender and age, while disease-related variables comprised etiology, clinical symptoms, medical history, and treatment records. Hematological parameters were assessed, including albumin levels, hemoglobin (Hb), white blood cell count (WBC), absolute neutrophil count (NEUT #), absolute lymphocyte count (LYMPH #), platelet count (PLT), neutrophil-to-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR). Indicators of coagulation function were also evaluated, such as prothrombin time (PT), international normalized ratio (INR), activated partial thromboplastin time (APTT), thrombin time (TT), fibrinogen (FIB), D-dimer (DDI), and fibrin degradation products (FDP). Additionally, CT findings were recorded.

The initial CT data were collected at the time of diagnosis, including measurements of initial midline shift (MS), initial hematoma thickness (HT), minimum hematoma density (MiHD), and maximum hematoma density (MaHD). MS and HT were quantified in millimeters (mm), while CT density values were expressed in Hounsfield units (Hu). MS was defined as the line extending from the septum pellucidum, perpendicular to the midline, between the most anterior and posterior aspects of the falx cerebri. HT was measured from the brain surface, perpendicular to the tangent line of the inner compact bone. The hematoma density difference (HDD) was calculated as the difference between MaHD and MiHD. To ensure accuracy, three university-affiliated neurosurgeons verified all radiological findings, and the clinical data were anonymized using the picture archiving and communication system (PACS). The methodology for CT data measurement is illustrated in Figure 1.

Figure 1
CT scans of a brain in four panels labeled A, B, C, and D. Panel A depicts a linear measurement of 13.51 millimeters. Panel B shows three linear measurements: 23.73 mm, 24.71 mm, and 24.24 mm. Panel C and D display measurements of hematoma density parameters within three circular areas, such as the minimum density, maximum density, and mean values.

Figure 1. The data measurement method on CT. (A–D) show the measurement method of MS (A), HT (B), and hematoma density (C,D), separately. MS, midline shift; HT, maximal hematoma thickness.

2.3 Statistical analysis

In the univariate analysis, the distributions of variables were compared between the surgical and conservative groups, as well as between female and male participants. Categorical variables were analyzed using the chi-squared (χ2) test, while continuous variables were assessed using t-tests or Mann–Whitney U tests. Variables that were significant at p < 0.1 in the univariate analysis were included in a multivariable logistic regression model, employing a backward stepwise method based on the Akaike Information Criterion (AIC). Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Patients were randomly divided into training and validation cohorts in a 7:3 ratio to identify factors associated with hematoma progression. Subsequently, logistic regression models were applied to both cohorts to confirm the factors influencing progression. Internal validation was conducted using the Hosmer-Lemeshow test for goodness-of-fit, calculation of the area under the receiver operating characteristic curve (AUC), assessment of model calibration, and decision curve analysis. Multicollinearity was assessed and deemed absent when the variance inflation factor (VIF) was below 5. Data processing and analysis were conducted using R version 4.3.3, in conjunction with Zstats 1.01 (Accessed on July 27, 2025).

3 Results

3.1 Demographic and clinical characteristics of the study cohort

The study encompassed a total of 1,142 patients, among whom 924 (80.91%) were male (Table 1). The mean age of the participants was 68.19 years, with a standard deviation of 12.62 years. A significant proportion, 760 patients (66.55%), were within the age range of 61 to 80 years. The most frequently reported symptom was headache, occurring in 460 cases (40.28%), followed closely by dyskinesia, which was reported in 449 cases (39.32%). Additionally, 782 patients (68.48%) had a history of head trauma, and 118 patients (10.33%) reported the use of antithrombotic therapy. Hypertension was reported by 172 individuals (15.06%), while 79 individuals (6.92%) had a history of diabetes. Conservative treatment was effective for 369 patients (32.31%), whereas 773 patients (67.69%) who experienced disease progression underwent surgical intervention.

Table 1
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Table 1. Demographic and clinical characteristics of patients.

3.2 Characteristics of patients in progression and recovery group

A total of 369 patients (32.31%) were successfully managed with conservative treatment and were classified into the recovery group, whereas 773 patients (67.69%) demonstrated disease progression and were categorized into the progression group. Patients in the recovery group exhibited significantly lower rates of anti-thrombotic drug use, hypertension, and diabetes compared to those in the progression group (p < 0.05).

Significant differences were observed in levels of albumin, Hb, NEUT (#), Lymph (#), NLR, and PLR between the progression and recovery groups (p < 0.05). Notably, only the progression group exhibited NEUT (#) and NLR levels above the normal reference ranges. Regarding coagulation function, significant differences were identified in PT, INR, and FIB levels between the progression and recovery groups (p < 0.05), with only the INR value in the progression group exceeding the normal reference range. Additionally, statistically significant differences were found in MiHD, MaHD, and HDD between the progression and recovery groups, with higher values of MiHD and MaHD observed in the progression group (p < 0.05). Further details can be found in Table 2.

Table 2
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Table 2. Characteristics of patients in progression and recovery group.

3.3 Multivariable regression analysis of CSDH progression

In a multivariable regression analysis, the coagulation parameter INR emerged as the most significant factor associated with hematoma progression (OR 7.39, 95% CI 2.79–19.55). Additionally, both hypertension (OR 5.35, 95% CI 2.80–10.25) and diabetes (OR 4.68, 95% CI 1.74–12.60) were found to be associated with hematoma progression. Inflammatory markers, such as the NLR (OR 2.14, 95% CI 1.46–3.13) and WBC (OR 1.16, 95% CI 1.02–1.31), also demonstrated significant associations with hematoma progression. Furthermore, the CT value of the hematoma, as measured by MaHD, was significantly correlated with hematoma progression (OR 1.02, 95% CI 1.01–1.03). Notably, female patients were more likely to achieve successful outcomes with conservative treatment (OR 0.61, 95% CI 0.40–0.95). Additional details can be found in Table 3.

Table 3
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Table 3. Multivariable logistic regression analysis of CSDH progression.

3.4 Internal validation, calibration, and decision curve analysis

To further investigate factors associated with hematoma progression, patients were randomly divided into training and validation cohorts in a 7:3 ratio. The receiver operating characteristic (ROC) curves for the factors associated with hematoma progression revealed AUC values of 0.93 (95% CI: 0.91–0.95) in the training cohort and 0.89 (95% CI: 0.85–0.93) in the validation cohort, as illustrated in Figures 2A,B. Furthermore, the calibration curves indicated a strong concordance between the observed outcomes and the predicted probabilities (Figures 2C,D). Additionally, the decision curve analysis (DCA) results demonstrated substantial clinical utility of the factors (Figures 2E,F).

Figure 2
Six-panel figure displaying performance metrics of predictive models. Panel A and B are ROC curves with AUCs of 0.93 and 0.89, respectively, indicating model accuracy. Panels C and D are calibration plots showing apparent, bias-corrected, and ideal prediction lines with Hosmer-Lemeshow p-values of 1.000 and 0.138, examining model fit. Panels E and F present decision curve analysis graphs, illustrating net benefits at various risk thresholds for two models.

Figure 2. Logistic regression models for training and validation cohorts (A,B) ROC curves for training and validation cohorts, respectively. (C,D) Calibration plots for training and validation cohorts, respectively. (E,F) Decision curves analysis for training and validation cohorts, respectively. ROC, receiver operating characteristic; AUC, area under the curve.

3.5 Gender disparity analysis

Overall, the Hb concentration was significantly elevated in males compared to females, as presented in Table 4. A more detailed stratified analysis indicated that within the progression group, males exhibited a significantly higher Hb level than females (Table 5). In the recovery group, males demonstrated a significantly higher albumin concentration compared to females. Conversely, in the same group, females had a significantly higher platelet count than males (Table 6). It is noteworthy that, despite the statistically significant differences observed across various comparative analyses, all measured values remained within the established normal reference range.

Table 4
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Table 4. Characteristics of male and female patients.

Table 5
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Table 5. Characteristics of male and female patients in progression group.

Table 6
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Table 6. Characteristics of male and female patients in recovery group.

4 Discussion

This retrospective study aimed to investigate the factors associated with the progression of CSDH. The cohort comprised 1,142 patients, of whom 19.09% were female. Multivariable regression analysis identified that INR, hypertension, diabetes, NLR, WBC, and MaHD were independently associated with CSDH progression. Notably, female sex emerged as a protective factor against hematoma progression. Further subgroup analysis revealed statistically significant differences between female and male patients in Hb levels, albumin concentrations, and platelet counts, although all values remained within the normal reference range.

CSDH predominantly affects the elderly population, with our findings indicating that individuals aged 61 to 80 years constitute 66.55% of the cases. As the global population continues to age, the prevalence of CSDH is anticipated to increase, potentially imposing substantial burdens on healthcare systems and families (14). Treatment options for CSDH include conservative management for asymptomatic patients with small hematomas and surgical intervention for more severe cases. The risk of treatment failure with both strategies ranges from 5 to 50%, often resulting in persistence or worsening of the condition (15). Therefore, identifying factors associated with CSDH progression could provide valuable insights for neurologists in developing effective follow-up and management strategies.

The increasing use of antithrombotic medications appears to contribute to the development of CSDH (16). Meta-analyses indicate that approximately 17.33% of CSDH patients are receiving antithrombotic therapy at the time of presentation (17). In our study, 10.33% of patients were undergoing antithrombotic therapy. A case–control study demonstrated that the use of antithrombotic drugs is associated with a higher risk of subdural hematoma (10). It is well-established that the INR reflects the coagulation function in patients. Research indicates that when INR values in patients with CSDH exceed 1.25, the condition may deteriorate or even result in mortality (18). Our study indicates that the mean INR in the progression group is 1.25, which exceeds the normal range, whereas in the recovery group, it is 1.07, falling within the normal range. Multivariate analysis identifies INR as a significant factor associated with hematoma progression.

The trauma-induced inflammatory response facilitates hematoma expansion by increasing vascular permeability, promoting capillary formation, enhancing fibrinolytic activity, and recruiting immune cells (19). Both hypertension and diabetes potentially exert pro-inflammatory effects. Chronic hypertension induces inflammatory alterations in arterial vessels, ultimately resulting in endothelial damage and vascular stiffness (20). Diabetes mellitus is characterized by elevated tissue levels of inflammatory markers (21). A national study has identified hypertension and diabetes as risk factors for the occurrence and progression of CSDH (8). Our multivariate analysis further corroborates that hypertension and diabetes are risk factors for CSDH progression, with odds ratios of 5.35 and 4.68, respectively. The NLR serves as an indicator of the dynamic interplay between the innate immune response, represented by neutrophils, and the adaptive cellular immune response, represented by lymphocytes, during illness and various pathological conditions. Research indicates that patients with CSDH exhibit significantly higher NLR values compared to healthy controls (22). Further studies have established a correlation between elevated postoperative NLR and an increased risk of recurrence (23). In our cohort, patients experiencing progression had mean NLR values exceeding the normal range, which were significantly higher than those observed in patients undergoing recovery. Multivariate regression analysis identified NLR as a risk factor for hematoma progression, with an odds ratio of 2.14.

CSDH is marked by blood products older than two to three weeks (24). As these blood products degrade over time, the hematoma undergoes liquefaction and becomes encapsulated by a fibrous membrane. In the absence of recent hemorrhage, CSDH typically manifests as a homogeneously hypodense lesion (25). According to Zhang et al., hypodense hematomas are independent predictors of a “wait and watch” management strategy (26). Foppen et al. identified hematoma volume and hypodense hematoma type were associated with successful conservative treatment outcomes (5). The underlying theory posits that hypodense hematomas lack active bleeding components (5). The high density observed within SDH may be attributed to the acute hemorrhage of existing CSDH (27). Our research indicates that MaHD is a contributing factor to hematoma progression.

Our multivariate analysis identified female sex as a protective factor against CSDH progression, a finding that warrants further discussion regarding potential underlying mechanisms. The observed sex disparity may be attributed to a combination of biological and socio-behavioral factors. From a biological perspective, the influence of sex hormones, particularly estrogen, is a leading hypothesis. Estrogen has been demonstrated to possess neuroprotective, anti-inflammatory, and pro-angiogenic properties (28). It may attenuate the inflammatory cascade and promote more stable vascular repair within the neo membranes of CSDH, thereby reducing the propensity for hematoma expansion and progression. In contrast, testosterone in males has been linked to a more pronounced pro-inflammatory state, which could exacerbate the local pathology (29). Furthermore, well-established physiological differences, such as generally lower levels of blood pressure and a potentially different vascular reactivity profile in pre-menopausal women, might contribute to a less favorable environment for hematoma progression (30). From a socio-behavioral standpoint, epidemiological studies consistently report that male sex is a risk factor for traumatic brain injury, the primary etiology of CSDH (12). This is often linked to higher rates of risk-taking behaviors, occupational hazards, and a greater incidence of falls in elderly males. Consequently, the initial insult and the subsequent pathophysiological response might differ between sexes.

While our subgroup analysis revealed significant differences in hemoglobin, albumin, and platelet counts between sexes, all values remained within normal limits, suggesting that these common clinical parameters may not fully explain the protective effect. The mechanisms are likely multifactorial and rooted in deeper hormonal and molecular pathways. Future prospective studies incorporating dedicated biomarker analyses are essential to validate these hypotheses and elucidate the precise causes of the sex-specific disparities observed in CSDH outcomes.

This study has several important limitations. Its retrospective, single-center design inherently limits causal inference and may introduce selection bias and unmeasured confounding. Moreover, as the data were derived from a single institution, the generalizability of our findings to other populations or healthcare settings remains uncertain. Another limitation is the lack of subgroup analyses comparing different surgical techniques or conservative management strategies. Future studies should adopt multicenter, prospective designs that incorporate broader outcome measures and stratify patients based on specific clinical, radiological, and treatment variables—such as the number of burr holes or timing of intervention. Such rigorously designed research would be essential for validating the factors associated with CSDH progression and sex-specific disparities, ultimately helping to refine personalized treatment approaches.

5 Conclusion

This study examined the risk factors contributing to the progression of CSDH and emphasized the significance of sex-specific variations. The factors identified as being associated with CSDH progression included INR, hypertension, diabetes, NLR, WBC, and MaHD. Additionally, female sex was found to be a protective factor against hematoma progression.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by Ethics Committee of the Evaluation of Biomedical Research Projects of Huashan Hospital. The studies were conducted in accordance with the local legislation and institutional requirements. The ethics committee/institutional review board waived the requirement of written informed consent for participation from the participants or the participants’ legal guardians/next of kin because this is a retrospective observational study.

Author contributions

WY: Data curation, Funding acquisition, Writing – original draft, Writing – review & editing. ZD: Data curation, Writing – original draft, Writing – review & editing. QC: Data curation, Writing – original draft, Writing – review & editing. QY: Formal analysis, Writing – review & editing. PF: Formal analysis, Writing – review & editing. JF: Formal analysis, Writing – review & editing. JH: Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Writing – review & editing. GW: Conceptualization, Methodology, Project administration, Supervision, Writing – review & editing.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This study was funded by the National Natural Science Foundation of China (grant nos. 82401618, 82471407, 82171382) and Research Foundation of Huashan Hospital, affiliated to Fudan University (2021QD026).

Acknowledgments

We thank all the staffs in the Department of Radiology, Neurosurgery and Medical Record for their kind help.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Footnotes

References

1. Svedung Wettervik, T, Lindblad, C, Axelsson, F, Chidiac, C, Gonzalez-Ortiz, F, Blennow, K, et al. Blood biomarkers for brain injury in chronic subdural hematomas: postoperative dynamics and relation to long-term outcome. J Neurosurg. (2025) 143:479–89. doi: 10.3171/2025.1.JNS242942

PubMed Abstract | Crossref Full Text | Google Scholar

2. Gajjar, AA, Ramachandran, N, Prabhala, T, Chen, JY, Custozzo, A, and Paul, AR. Impact of frailty on surgical outcomes in nonacute subdural hematomas: a Nationwide analysis of 251,597 patients over 20 years. J Clin Med. (2025) 14:3176. doi: 10.3390/jcm14093176

PubMed Abstract | Crossref Full Text | Google Scholar

3. Zolnourian, A, Manivannan, S, Edwards, B, Chua, A, Arora, M, Akhigbe, T, et al. Factors affecting outcomes following burr hole drainage of chronic subdural hematoma: a single-center retrospective study. J Neurosurg. (2025) 142:1606–15. doi: 10.3171/2024.9.JNS24370

PubMed Abstract | Crossref Full Text | Google Scholar

4. Kan, P, Fiorella, D, Dabus, G, Samaniego, EA, Lanzino, G, Siddiqui, AH, et al. Arise I consensus statement on the management of chronic subdural hematoma. Stroke. (2024) 55:1438–48. doi: 10.1161/STROKEAHA.123.044129

PubMed Abstract | Crossref Full Text | Google Scholar

5. Foppen, M, Lodewijkx, R, Bandral, HV, Yah, K, Slot, KM, Vandertop, W, et al. Factors associated with success of conservative therapy in chronic subdural hematoma: a single-center retrospective analysis. J Neurol. (2024) 271:3586–94. doi: 10.1007/s00415-024-12307-2

PubMed Abstract | Crossref Full Text | Google Scholar

6. Foppen, M, Bandral, HV, Slot, KM, Vandertop, WP, and Verbaan, D. Success of conservative therapy for chronic subdural hematoma patients: a systematic review. Front Neurol. (2023) 14:1249332. doi: 10.3389/fneur.2023.1249332

PubMed Abstract | Crossref Full Text | Google Scholar

7. Yagi, K, Kanda, E, Hijikata, Y, Tao, Y, and Hishikawa, T. Eosinophil-platelet ratio as a predictive marker of the postoperative recurrence of a chronic subdural hematoma. Neurosurgery. (2025) 96:1301–6. doi: 10.1227/neu.0000000000003229

PubMed Abstract | Crossref Full Text | Google Scholar

8. Jensen, TSR, Thiesson, EM, Fugleholm, K, Wohlfahrt, J, and Munch, TN. Inflammatory risk factors for chronic subdural hematoma in a Nationwide cohort. J Inflamm Res. (2024) 17:8261–70. doi: 10.2147/JIR.S472849

PubMed Abstract | Crossref Full Text | Google Scholar

9. Matsubara, M, Yagi, K, Minami, Y, Kanda, E, Sunada, Y, Tao, Y, et al. Preoperative elevated eosinophils in peripheral blood for prediction of postoperative recurrence of chronic subdural hematoma. J Neurosurg. (2023) 139:708–13. doi: 10.3171/2022.12.JNS222432

PubMed Abstract | Crossref Full Text | Google Scholar

10. Gaist, D, García Rodríguez, LA, Hellfritzsch, M, Poulsen, FR, Halle, B, Hallas, J, et al. Association of Antithrombotic Drug use with Subdural Hematoma Risk. JAMA. (2017) 317:836–46. doi: 10.1001/jama.2017.0639

PubMed Abstract | Crossref Full Text | Google Scholar

11. Bao, Z, Xu, S, Cui, G, Qu, JM, and Liang, TY. The relationship between serum coagulation parameters and the recurrence of chronic subdural hematoma. Mol Cell Biochem. (2025) 480:1055–61. doi: 10.1007/s11010-024-05019-8

PubMed Abstract | Crossref Full Text | Google Scholar

12. Hotta, K, Sorimachi, T, Honda, Y, and Matsumae, M. Chronic subdural hematoma in women. World Neurosurg. (2017) 105:47–52. doi: 10.1016/j.wneu.2017.05.105

PubMed Abstract | Crossref Full Text | Google Scholar

13. Ou, Y, Fan, W, Yu, X, Wu, L, and Liu, W. A single-Center analysis of sex differences in patients with chronic subdural hematoma in China. Front Neurol. (2022) 13:888526. doi: 10.3389/fneur.2022.888526

PubMed Abstract | Crossref Full Text | Google Scholar

14. Chen, H, Colasurdo, M, Malhotra, A, Gandhi, D, and Bodanapally, UK. Advances in chronic subdural hematoma and membrane imaging. Front Neurol. (2024) 15:1366238. doi: 10.3389/fneur.2024.1366238

PubMed Abstract | Crossref Full Text | Google Scholar

15. Kasem, RA, Venegas, JM, Ibrahim, A, Hubbard, ZS, Essibayi, MA, Aldamouni, M, et al. Can antithrombotic therapy be safely resumed after middle meningeal artery embolization with or without surgery for chronic subdural hematoma? A systematic review and meta-analysis. Acta Neurochir. (2025) 167:183. doi: 10.1007/s00701-025-06600-w

PubMed Abstract | Crossref Full Text | Google Scholar

16. Hamou, HA, Clusmann, H, Schulz, JB, Wiesmann, M, Altiok, E, and Höllig, A. Chronic subdural hematoma. Dtsch Arztebl Int. (2022) 119:208–13. doi: 10.3238/arztebl.m2022.0144

PubMed Abstract | Crossref Full Text | Google Scholar

17. Wang, H, Zhang, M, Zheng, H, Xia, X, Luo, K, Guo, F, et al. The effects of antithrombotic drugs on the recurrence and mortality in patients with chronic subdural hematoma: a meta-analysis. Medicine (Baltimore). (2019) 98:e13972. doi: 10.1097/MD.0000000000013972

PubMed Abstract | Crossref Full Text | Google Scholar

18. Wang, S, Ma, Y, Zhao, X, Yang, C, Gu, J, Weng, W, et al. Risk factors of hospital mortality in chronic subdural hematoma: a retrospective analysis of 1117 patients, a single institute experience. J Clin Neurosci. (2019) 67:46–51. doi: 10.1016/j.jocn.2019.06.026

PubMed Abstract | Crossref Full Text | Google Scholar

19. Yi, X, Yue, J, Yue, S, Li, J, Zhang, X, Zhao, G, et al. The evolution and recurrence of chronic subdural hematoma was associated with different distribution of macrophage M1/M2 polarization. Inflammation. (2025). doi: 10.1007/s10753-025-02318-0

Crossref Full Text | Google Scholar

20. Franco, C, Sciatti, E, Favero, G, Bonomini, F, Vizzardi, E, and Rezzani, R. Essential hypertension and oxidative stress: novel future perspectives. Int J Mol Sci. (2022) 23:14489. doi: 10.3390/ijms232214489

PubMed Abstract | Crossref Full Text | Google Scholar

21. Delalat, S, Sultana, I, Osman, H, Sieme, M, Zhazykbayeva, S, Herwig, M, et al. Dysregulated inflammation, oxidative stress, and protein quality control in diabetic HFpEF: unraveling mechanisms and therapeutic targets. Cardiovasc Diabetol. (2025) 24:211. doi: 10.1186/s12933-025-02734-4

PubMed Abstract | Crossref Full Text | Google Scholar

22. Zhang, Y, Yang, Y, Long, S, and Li, G. Assessment of peripheral blood cell inflammatory markers in patients with chronic subdural hematoma. Clin Neurol Neurosurg. (2020) 191:105738. doi: 10.1016/j.clineuro.2020.105738

PubMed Abstract | Crossref Full Text | Google Scholar

23. de Oliveira, AJM, Solla, DJF, de Oliveira, KF, Amaral, BS, Andrade, AF, Kolias, AG, et al. Postoperative neutrophil-to-lymphocyte ratio variation is associated with chronic subdural hematoma recurrence. Neurol Sci. (2022) 43:427–34. doi: 10.1007/s10072-021-05241-y

PubMed Abstract | Crossref Full Text | Google Scholar

24. Mehta, V, Harward, SC, Sankey, EW, Nayar, G, and Codd, PJ. Evidence based diagnosis and management of chronic subdural hematoma: a review of the literature. J Clin Neurosci. (2018) 50:7–15. doi: 10.1016/j.jocn.2018.01.050

PubMed Abstract | Crossref Full Text | Google Scholar

25. Carroll, JJ, Lavine, SD, and Meyers, PM. Imaging of subdural hematomas. Neurosurg Clin N Am. (2017) 28:179–203. doi: 10.1016/j.nec.2016.11.001

PubMed Abstract | Crossref Full Text | Google Scholar

26. Zhang, X, Sha, Z, Gao, C, Yuan, J, He, L, Huang, J, et al. Factors influencing wait-and-watch management in mild primary chronic subdural hematoma: a retrospective case-control study. Acta Neurol Belg. (2023) 123:2277–86. doi: 10.1007/s13760-023-02293-z

PubMed Abstract | Crossref Full Text | Google Scholar

27. Devgan, S, and Shankar, J. Imaging for management of chronic subdural hematoma: a review. Can J Neurol Sci. (2024) 52:741–50. doi: 10.1017/cjn.2024.328

Crossref Full Text | Google Scholar

28. Giordano, KR, Rojas-Valencia, LM, Bhargava, V, and Lifshitz, J. Beyond binary: influence of sex and gender on outcome after traumatic brain injury. J Neurotrauma. (2020) 37:2454–9. doi: 10.1089/neu.2020.7230

PubMed Abstract | Crossref Full Text | Google Scholar

29. Yang, W, and Huang, J. Chronic subdural hematoma: epidemiology and natural history. Neurosurg Clin N Am. (2017) 28:205–10. doi: 10.1016/j.nec.2016.11.002

PubMed Abstract | Crossref Full Text | Google Scholar

30. Ge, R, and Shen, J. Gender-specific differences in chronic subdural hematoma. J Craniofac Surg. (2023) 34:e124–8. doi: 10.1097/SCS.0000000000008855

PubMed Abstract | Crossref Full Text | Google Scholar

Keywords: chronic subdural hematoma, sex, coagulation, inflammation, progression

Citation: Yang W, Du Z, Chen Q, Yuan Q, Fu P, Fang J, Hu J and Wu G (2025) Factors associated with progression and sex-specific patterns in chronic subdural hematoma: a single-centre retrospective study. Front. Neurol. 16:1674327. doi: 10.3389/fneur.2025.1674327

Received: 27 July 2025; Revised: 01 October 2025; Accepted: 25 November 2025;
Published: 04 December 2025.

Edited by:

Ferdinand Hui, Johns Hopkins Medicine, United States

Reviewed by:

Luis Alberto Camputaro, University of Buenos Aires, Argentina
Mohamed Arnaout, Zagazig University, Egypt

Copyright © 2025 Yang, Du, Chen, Yuan, Fu, Fang, Hu and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jin Hu, aHVqaW5AZnVkYW4uZWR1LmNu; Gang Wu, d3VnYW5nM0BodWFzaGFuLm9yZy5jbg==

These authors have contributed equally to this work and share first authorship

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.