Object The COVID-19 pandemic has disrupted all aspects of society globally. As healthcare resources had to be preserved for infected patients, and the risk of in-hospital procedures escalated for uninfected patients and staff, neurosurgeons around the world have had to postpone non-emergent procedures. Under these unprecedented conditions, the decision to defer cases became increasingly difficult as COVID-19 cases skyrocketed. Methods Data was collected by self-reporting surveys during two discrete periods: the principal survey accrued responses during 2 weeks at the peak of the global pandemic, and the supplemental survey accrued responses after that to detect changes in opinions and circumstances. Nine hypothetical surgical scenarios were used to query neurosurgeons' opinion on the risk of postponement and the urgency to re-schedule the procedures. An acuity index was generated for each scenario, and this was used to rank the nine cases. Results There were 494 respondents to the principal survey from 60 countries. 258 (52.5%) reported that all elective cases and clinics have been shut down by their main hospital. A total of 226 respondents (46.1%) reported that their operative volume had dropped more than 50%. For the countries most affected by COVID-19, this proportion was 54.7%. There was a high degree of agreement among our respondents that fast-evolving neuro-oncological cases are non-emergent cases that nonetheless have the highest risk in postponement, and selected vascular cases may have high acuity as well. Conclusion We report on the impact of COVID-19 on neurosurgeons around the world. From their ranking of the nine case scenarios, we deduced a strategic scheme that can serve as a guideline to triage non-emergent neurosurgical procedures during the pandemic. With it, hopefully, neurosurgeons can continue to serve their patients without endangering them either neurologically or risking their exposure to the deadly virus.
Both endoscopic and microsurgical approaches for TSR of growth hormone-secreting adenomas are viable treatment options for patients with acromegaly, and yield similarly high rates of remission under the most current consensus criteria.
Middle meningeal artery (MMA) embolization has been proposed as a minimally invasive treatment for chronic subdural hematoma (cSDH). The aim of this systematic review and meta-analysis is to compare outcomes after MMA embolization versus conventional management for cSDH. We performed a systematic review of PubMed, Embase, Oxford Journal, Cochrane, and Google Scholar databases from April 1987 to October 2020 in accordance with PRISMA guidelines. Studies reporting outcomes after MMA embolization for ≥3 patients with cSDH were included. A meta-analysis comparing MMA embolization with conventional management was performed. The analysis comprised 20 studies with 1416 patients, including 718 and 698 patients in the MMA embolization and conventional management cohorts, respectively. The pooled recurrence, surgical rescue, and in-hospital complication rates in the MMA embolization cohort were 4.8% (95% CI 3.2% to 6.5%), 4.4% (2.8% to 5.9%), and 1.7% (0.8% to 2.6%), respectively. The pooled recurrence, surgical rescue, and in-hospital complication rates in the conventional management cohort were 21.5% (0.6% to 42.4%), 16.4% (5.9% to 27.0%), and 4.9% (2.8% to 7.1%), respectively. Compared with conservative management, MMA embolization was associated with lower rates of cSDH recurrence (OR=0.15 (95% CI 0.03 to 0.75), p=0.02) and surgical rescue (OR=0.21 (0.07 to 0.58), p=0.003). In-hospital complication rates were comparable between the two cohorts (OR=0.78 (0.34 to 1.76), p=0.55). MMA embolization is a promising minimally invasive therapy that may reduce the need for surgical intervention in appropriately selected patients with cSDH. Additional prospective studies are warranted to determine the long-term durability of MMA embolization, refine eligibility criteria, and establish this endovascular approach as a viable definitive treatment for cSDH.
In our cohort, early, profound hypocortisolemia could be used as a clinical prediction tool for durable remission. Achievement of hypocortisolemia ≤2 µg/dL before 21 post-operative hours appeared to accurately predict durable remission in the intermediate term.
Background and Purpose—
Hematoma volume measurements influence prognosis and treatment decisions in patients with spontaneous intracerebral hemorrhage (ICH). The aims of this study are to derive and validate a fully automated segmentation algorithm for ICH volumetric analysis using deep learning methods.
Methods—
In-patient computed tomography scans of 300 consecutive adults (age ≥18 years) with spontaneous, supratentorial ICH who were enrolled in the ICHOP (Intracerebral Hemorrhage Outcomes Project; 2009–2018) were separated into training (n=260) and test (n=40) datasets. A fully automated segmentation algorithm was derived using convolutional neural networks, and it was trained on manual segmentations from the training dataset. The algorithm’s performance was assessed against manual and semiautomated segmentation methods in the test dataset.
Results—
The mean volumetric Dice similarity coefficients for the fully automated segmentation algorithm when tested against manual and semiautomated segmentation methods were 0.894±0.264 and 0.905±0.254, respectively. ICH volumes derived from fully automated versus manual (
R
2
=0.981;
P
<0.0001), fully automated versus semiautomated (
R
2
=0.978;
P
<0.0001), and semiautomated versus manual (
R
2
=0.990;
P
<0001) segmentation methods had strong between-group correlations. The fully automated segmentation algorithm (mean 12.0±2.7 s/scan) was significantly faster than both of the manual (mean 201.5±92.2 s/scan;
P
<0.001) and semiautomated (mean 288.58±160.3 s/scan;
P
<0.001) segmentation methods.
Conclusions—
The fully automated segmentation algorithm quantified hematoma volumes from computed tomography scans of supratentorial ICH patients with similar accuracy and substantially greater efficiency compared with manual and semiautomated segmentation methods. External validation of the fully automated segmentation algorithm is warranted.
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