Evidence map›Paper›PMID 40481359›Full record

ArticleNeurosurgical review2025

Volumetric changes in the bone flap at one year follow up in patients undergoing craniotomy.

Harshit Arora, Sourabh Boruah, Alexander G Yearley, Kaasinath Balagurunath, Advait Patil, Hanfeng Huang, Sulaiman Sajed, John L Kilgallon, Jakob V E Gerstl, Christopher S Hong and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Neurosurgical review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Harshit AroraDepartment of Neurosurgery, Computational Neurosciences Outcomes Center (CNOC), Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
Sourabh BoruahRevBio, Inc., 600 Suffolk Street, Lowell, MA, USA.
Alexander G YearleyDepartment of Neurosurgery, Computational Neurosciences Outcomes Center (CNOC), Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
Kaasinath BalagurunathDepartment of Neurosurgery, Computational Neurosciences Outcomes Center (CNOC), Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
Advait PatilDepartment of Neurosurgery, Computational Neurosciences Outcomes Center (CNOC), Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
Hanfeng HuangDepartment of Neurosurgery, Computational Neurosciences Outcomes Center (CNOC), Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
Sulaiman SajedDepartment of Neurosurgery, Computational Neurosciences Outcomes Center (CNOC), Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
John L KilgallonDepartment of Neurosurgery, Computational Neurosciences Outcomes Center (CNOC), Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
Jakob V E GerstlDepartment of Neurosurgery, Computational Neurosciences Outcomes Center (CNOC), Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
Christopher S HongDepartment of Neurosurgery, Computational Neurosciences Outcomes Center (CNOC), Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
Timothy R SmithDepartment of Neurosurgery, Computational Neurosciences Outcomes Center (CNOC), Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA. trsmith@bwh.harvard.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although bone resorption has been extensively reported following craniectomy, bone resorption and fusion rates following craniotomy remains unexplored. The aim of the present study was to conduct a volumetric assessment of craniotomy resorption and fusion rates at one year following the index surgery. Adult patients who had a computed tomography scan immediately after craniotomy and at one year follow up were included in the study. Various baseline demographic variables and reason for craniotomy, method of fixation, and post-operative complications were recorded. 3D-Slicer was used to demarcate the bone flap segments - central flap, flap edge, kerf, burr-holes, and periphery and the volumes of both computed tomography scans were compared. 34 patients with a mean age of 59.29 ± 17.77 years were included in the study. Tumors were the most common indication of craniotomy. Four patients reported significant pain related to their hardware and one patient reported postoperative cerebrospinal fluid leakage. The mean follow-up period was 357.4 ± 62.67 days. An overall increase in the bone volume was observed in the kerf (+ 8.46%) and burr-hole regions (+ 12.92%) while the central flap (-1.55%), flap edge (-4.48%) and periphery (-3.5%) depicted bone resorption. The increase in volume in the kerf space represents at an average less than 10% bridging of the gap and is far from fusion. On multivariable regression, a negative correlation was observed between the change in peripheral bone volume and patient age and a positive correlation between male sex and flap edge volume change. Cranial flap bone loss in patients who underwent craniotomy was quantified in this study while an overall increase in bone volume was observed in the regions of the kerf and the burr-holes one-year postoperatively, less than 10% of the kerf space was bridged by bone. Clinical Trial Number: Not Applicable.

Indexed as

Bone ResorptionCraniotomyPostoperative ComplicationsSurgical FlapsAdultAgedFemaleFollow-Up StudiesHumansMaleMiddle AgedTomography, X-Ray ComputedBone Flap RemodelingBone ResorptionComputed TomographyCraniotomyCritical CareTrauma

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.