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Record W4401613802 · doi:10.1227/neu.0000000000003093

Is It Neurosurgery?

2024· editorial· en· W4401613802 on OpenAlexaboutno aff
Douglas Kondziolka

Bibliographic record

VenueNeurosurgery · 2024
Typeeditorial
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNeurosurgeryMedical physicsSurgery

Abstract

fetched live from OpenAlex

Learning to be a neurosurgeon is an expansive process. We all know the myriad disciplines involved in the traditional elements of neuroanatomy, neurophysiology, surgical principles, disease states, and therapeutic approaches. Indeed, this expansive universe is a topic I have discussed before. It is truly getting larger. I have mentioned previously that some call time the “principle property of medicine.” We simply do not have the time to learn all of the care elements that affect our patients and are in constant flux. If we did, we would spend time in training at the side of neuroradiologists, learning their approaches to imaging-based diagnosis and study of outcomes, which is at the heart of everything we do. We would spend time at the side of physical medicine and rehabilitation specialists, physical therapists, and pain management experts, who we rely on to help bring our patients through difficult times and periods of restoration to better understand what is possible. We would spend months with neuropathologists to better know our disease states, as I thankfully did in my residency (I even had to do the autopsies). We would spend time with psychiatrists or cognitive neurologists, working to understand the workings of the functional mind (now increasingly prevalent in reports about tractography and surgical outcomes). I could go on and on. A 2-week elective in neuroradiology at the Toronto General Hospital as a fourth-year medical student, sparked my career in some ways, and put me on better ground to more comfortably take in house call by myself even at a young stage. Like most of us still do, we had to read our own scans and report to the chief resident. Later, during my own research in stroke repair and neuronal transplantation, I relied on physical medicine and rehabilitation colleagues to develop tests and programs necessary to “exercise the transplanted neurons.” As part of clinical trial design and conduct, I was opened up to that field in a way I had not been before. In decades past, neurosurgery training had broader exposure to those disciplines, which seemed to go away once we had to learn more and more new techniques. Again, time was the driver. We have certain confines within our journals and of course are dependent upon whatever articles are submitted to us for review and possible acceptance. As part of our editorial board, we do have sections in neurology, neuroscience, neuroradiology, neuropathology, showing interest and outreach to those disciplines. But clearly we can do more. Dan Kelly and colleagues wrote on the neuroscience of psychedelic agents that may have a role in clinical practice.1 Is this neurosurgery? Not yet. But it could be part of a patient or family discussion during recovery from a neurological insult. Are we prepared for that discussion? Our editorial board thought that exposure to the topic in our journal was warranted. At the time of this writing, together with Global Neurosurgery section editor, Gail Rosseau, I was allowed to view a screening of a new documentary on vaccine access called “Shot in the Dark.” This was during United Nations week here in New York as part of an initiative partly supported by the World Health Organization. The physicist and cosmologist Neil DeGrasse Tyson is an executive producer, and we had a chance to chat during the screening. We talked about parallels between neurosurgery and astrophysics and how surgery and our solutions are built increasingly on physics, mathematics, and geometry. Endovascular techniques and devices reflect that well. The film emphasized the cultural basis of vaccine acceptance or denial, and although this branch of medicine is not part of my own practice, it clearly emphasized the cultural elements that reflect on how patients accept our own recommendations, whether they be related to end-of-life care, brain tumor management, blood transfusion, or any perceived ethical conflict. Indeed on the topic of misinformation (the film shows the basis for how autism and vaccines became linked in the minds of some people and how misinformation led to tragic results), we all have our patients and families who read “literature” that seem to argue for or against treatments based on the interpreted writings. I am not speaking about equipoise, but about what some describe as misleading or even fraud. Associate Editor Fred Barker spoke on the topic of “misinformation” in his recent presidential address for the American Academy of Neurological Surgery. He argued that a powerful source of misinformation can be our own literature, misusing statistics which can cloud even articles published in this journal. Despite our efforts to ensure that statistical tests are appropriate, that P values are followed by CIs and that proper conclusions are drawn, we sometimes fall short. Some in the field of scholarly publication think that artificial intelligence techniques may solve some of these concerns, and they may be right. When use of statistics seems even too complex for our peer review editorial panel, we send articles to one of our team of biostatistician reviewers. All this toward the goal of making our message sound. As a member of the Accreditation Council for Graduate Medical Education Review Committee for Neurosurgery, I get to see the breadth of training program designs in the United States. Despite standards, they are not all the same, and some are being wonderfully innovative. As a former Director of the American Board of Neurological Surgery, I had the opportunity to participate in the evaluation of our trainees and program graduates at the individual level. Some of the best oral examination candidates displayed mastery of the classic disciplines in their responses, understanding the fundamentals of anatomy and physiology. Responses were more confident, more multidimensional, more diverse. There are many ways to become a neurosurgeon, with many paths and much to learn. It seems that increasingly there are multiple ways to care for the disorders we treat. It is clear that we can always do better if what we learn is focused on our patients, both medically and holistically. Neurosurgery is not always what we think of within our “traditional” definition. Our journals should remain open to this challenge. Douglas Kondziolka, MD, MSc Editor-in-Chief, Neurosurgery Publications New York, New York, USA

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.006
Scholarly communication0.0080.009
Open science0.0020.003
Research integrity0.0080.013
Insufficient payload (model declined to judge)0.0590.022

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.359
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes1
Has abstractyes

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