| Literature DB >> 32025876 |
Martina Hamböck1, Arthur Hosmann2, Rudolf Seemann3, Harald Wolf4, Florian Schachinger4, Stefan Hajdu4, Harald Widhalm5.
Abstract
BACKGROUND: Secondary cranioplasty (CP) is considered to support the neurological recovery of patients after decompressive craniectomy (DC), but the treatment success might be limited by complications associated to confounders, which are not yet fully characterized. The aim of this study was to identify the most relevant factors based on the necessity to perform revision surgeries.Entities:
Keywords: Decompressive craniectomy; Implant material; Long-term outcome; Secondary cranioplasty; Traumatic brain injury
Mesh:
Substances:
Year: 2020 PMID: 32025876 PMCID: PMC7066309 DOI: 10.1007/s00701-020-04243-7
Source DB: PubMed Journal: Acta Neurochir (Wien) ISSN: 0001-6268 Impact factor: 2.216
Fig. 1Three-dimensional cranial computed tomography reconstruction images showing examples of bone graft resorption graded as a mild: less than 50% of the graft circumference affected, b moderate: more than 50% of the graft circumference affected, and c severe: more than 50% of the original bone flap volume affected
Fig. 2Flow chart illustrating the patient selection and cohort arrangement of patients who received secondary cranioplasty (CP) using autologous calvarial bone (ACB) or polymethylmethacrylate (PMMA) after decompressive craniectomy (DC) for severe traumatic brain injury (TBI) at the department of trauma surgery or neurosurgery between 1984 and 2015
Overview of patient characteristics stratified by the implant material used for secondary cranioplasty
| Characteristic | All patients ( | ACB ( | PMMA ( |
|---|---|---|---|
| Age, years, median (IQR) | 41.8 (26.1–55.2) | 42.4 (28.1–55.4) | 40.4 (21.8–54.9) |
| Age categories, years, | |||
| 18–65 | 121 (77.6) | 91 (76.5) | 30 (81.1) |
| < 18 | 17 (10.9) | 12 (10.1) | 5 (13.5) |
| > 65 | 18 (11.5) | 16 (13.4) | 2 (5.4) |
| Male gender, | 129 (82.7) | 98 (82.4) | 31 (83.8) |
| Initial diagnosisa, | |||
| SDH | 107 (68.6) | 85 (71.4) | 22 (59.5) |
| EDH | 45 (28.8) | 32 (26.9) | 13 (35.1) |
| ICH | 45 (28.8) | 35 (29.4) | 10 (27.0) |
| SAH | 22 (14.1) | 18 (15.1) | 4 (10.8) |
| Edema | 10 (6.4) | 8 (6.7) | 2 (5.4) |
| Fracture | 9 (5.8) | 5 (4.2) | 4 (10.8) |
| Initial GCS score, median (IQR) | 5.5 (3.0–14.0) | 5 (3.0–14.0) | 7 (3.0–14.5) |
| GCS score categories, | |||
| 3–8 | 92 (59.0) | 72 (60.5) | 20 (54.1) |
| 9–15 | 64 (41.0) | 47 (39.5) | 17 (45.9) |
| Cranial defect sizeb, cm2, median (IQR) | 77 (60–99) | 80 (63–108) | 56 (30–72) |
| Defect size categories, cm2, | |||
| < 80 | 69 (51.9) | 48 (44.0) | 21 (87.5) |
| ≥ 80 | 64 (48.1) | 61 (56.0) | 3 (12.5) |
| Date of cranioplasty, | |||
| 1984–1999 | 23 (14.7) | 9 (7.6) | 14 (37.8) |
| 2000–2015 | 133 (85.3) | 110 (92.4) | 23 (62.2) |
| Reconstruction interval, months, median (IQR) | 5.8 (2.6–8.9) | 4.6 (2.2–7.1) | 9.5 (6.7–16.3) |
| 1984–1999 | 9.0 (5.8–13.6) | 5.8 (3.4–10.0) | 12.9 (8.3–14.2) |
| 2000–2015 | 5.3 (2.3–7.7) | 4.4 (2.2–6.7) | 8.9 (4.8–17.9) |
| Reconstruction interval categories, months, | |||
| 0–3 | 45 (28.8) | 40 (33.6) | 5 (13.5) |
| > 3 | 111 (71.2) | 79 (66.4) | 32 (86.5) |
| Complications, | |||
| Resorptionc | 26 (16.7) | 26 (21.8) | – |
| Mild | 3 (1.9) | 3 (2.5) | – |
| Moderate | 8 (5.1) | 8 (6.7) | – |
| Severe | 15 (9.6) | 15 (12.6) | – |
| Hematoma | 7 (4.5) | 5 (4.2) | 2 (5.4) |
| Infection | 5 (3.2) | 5 (4.2) | 0 (0.0) |
| Secondary dislocation | 3 (1.9) | 2 (1.7) | 1 (2.7) |
| Revision surgery, | 28 (17.9) | 26 (21.8) | 2 (5.4) |
| Follow-up, years, median (IQR) | 0.9 (0.0–3.8) | 0.9 (0.1–3.3) | 0.4 (0.0–7.9) |
ACB autologous calvarial bone, EDH epidural hematoma, GCS Glasgow Coma Scale, ICH intracerebral hemorrhage, IQR interquartile range, PMMA polymethylmethacrylate, SAB subarachnoid hemorrhage, SDH subdural hematoma
aMore than one initial diagnosis is possible
bData were only available for 133 patients
cOnly occurs in autologous calvarial bone implants
Univariate and multivariate Cox proportional hazards regression models of variables suggested to influence the frequency of revision surgeries
| Variable | Univariate Cox regression | Multivariate Cox regressiona | ||
|---|---|---|---|---|
| HR (95% CI) | HR (95% CI) | |||
| Implant material | ||||
| ACB | 1 | 1 | ||
| PMMA | 0.3 (0.1–1.1) | 0.06 | 0.2 (0.1–1.0) | 0.04 |
| Age, years | ||||
| < 18 or > 65 | 1 | 1 | ||
| 18–65 | 0.4 (0.2–0.9) | 0.03 | 0.4 (0.2–0.9) | 0.02 |
| Gender | ||||
| Male | 1 | |||
| Female | 0.9 (0.4–2.4) | 0.88 | ||
| Reconstruction interval, months | ||||
| 0–3 | 1 | |||
| > 3 | 0.8 (0.3–1.8) | 0.53 | ||
| Initial GCS score | ||||
| 3–8 | 1 | |||
| 9–15 | 0.9 (0.4–2.0) | 0.86 | ||
| Cranial defect sizeb, cm2 | ||||
| < 80 | 1 | |||
| ≥ 80 | 1.8 (0.8–4.0) | 0.16 | ||
| Date of cranioplasty | ||||
| 1984–1999 | 1 | |||
| 2000–2015 | 1.3 (0.4–4.4) | 0.63 | ||
ACB autologous calvarial bone, CI confidence interval, GCS Glasgow Coma Scale, HR hazard ratio, PMMA polymethylmethacrylate
aOnly variables with p < 0.1 in the univariate analysis were entered into the multivariate Cox regression model
bData were only available for 133 patients
Fig. 3Kaplan-Meier curves estimating the time spent free from revision surgery at 10 years according to a the implant material, b the patient age, c the gender, d the reconstruction interval, e the initial Glasgow Coma Scale (GCS) score at hospital admission, and f the date of secondary cranioplasty