Letter: Cranial Chordoma: A New Preoperative Grading System
Notice bibliographique
Résumé
To the Editor: We read with great interest the scoring system, Sekhar Grading System for Cranial Chordomas (SGSCC), devised by the group headed by the senior author Sekhar.1 Not to downplay the immense work of the skull base surgeons in evolving this preoperative score, the idea of this letter is to compare similar parallel scoring systems in surgical neurology and allied specialties and see if bits and pieces of these can be put together. Challenges involved in the incorporation of advanced pathological parameters have been brilliantly highlighted in the comments of the article itself. Scoring systems can be applied at pre-, intra-, and postoperative levels. Many trainee surgeons apply scoring systems via an app in their smartphones. A Simple Example First on Scoring Systems: Banking Sector-Credit Score and Smartphones A domestic example being a bad credit score (banking sector). Most scores are based on logistic regression model (nonlinear). But, there is a lot of difference between someone who defaults on his major bank home-loan payment (major problem) vs someone who removes a silly monthly phone-call direct debit payment from his bank's standing orders especially after completing, say, a 2-yr contract (sometimes the primary phone call providers are so manipulative, that it is very difficult to negotiate even finishing a contract, let alone the monetary loss of terminating a contract in the middle). Head Injury Genomics and proteomics are emerging tools in neuropathology. They are usually postoperative parameters, but can be a very important preoperative parameter if a biopsy has already been done. Like genomics and proteomes, there are “interactomes,” which will summate and tell us if a series of subcellular interactions of molecules will produce epilepsy or not in a head injury patient.2 Incorporation for Arteriovenous Malformation Grading The initial Spetzler–Martin grading was supplemented by Lawton Young and was then revised by adding more parameters in the AVICH (arteriovenous malformation [AVM]-related intracerebral haemorrhage) score. It was found that the AVICH score predicts outcome of cerebral AVM more than either of the former scores.3 Anatomic Compartments and Subcompartments: We understand a scoring system evolves from a simple classification (anatomic classification for example), then is tested in group of patients, and later validated in larger patient groups. Some evolution has already occurred in clival chordoma grading as clearly discussed in the article1 (Al Mefty [compartmental] scoring and Gui [endoscopic] scoring systems for clival chordomas). Endoscopically, Gui et al4 classified the chordomas as anterior skull base, upper, upper-middle, middle-inferior, lower, total clivus, and extensive types. Although it might appear that this classification will help in approach selection, additional bone needs to be drilled and removed around the tumor for total excision. Hence, it may not be of good value. We know from Professor Rhoton's cadaveric pictures and videos that the vertebral artery is close to cranial nerves 11 and 12, while PICA (the posterior inferior cerebellar artery) is close to 9 and 10.5 We also know that usually the vertebral artery is larger than PICA unless there are some anomalies. Subcompartments are also important. For example, the jugular foramen has 3 compartments: petrous, intrajugular (neural), and sigmoid. Even within the intrajugular compartment there are separate tiny orifices for the ninth and the tenth. These form separate perforations in the intrajugular dura. This compartmentalization will be useful in the endoscopic removal of tiny bits and pieces. Figure 1 shows the infratemporal view of the jugular foramen.FIGURE 1.: In the infratemporal upside down view of the skull base, showing the occipital condyle top most, followed by hypoglossal canal and then jugular foramen, the lateral pterygoid plate is to the left. This is only an anatomic view. This view will be especially useful if an infratemporal approach is used for a tumor in the clivus.Intraoperative Neuromonitoring Intraoperative neuromonitoring during microvascular decompression of the facial nerve for hemifacial spasm, in the form of brainstem auditory evoked potential, can provide a correlative evidence to postoperative clinical hearing loss (World Health Organization grade).6 Incorporating Advanced Neuropathology Parameters: Experimental and advanced/newer treatment parameters cannot be applied without revising the score. Aggressive surgery, preserving the key structures and post-op radiotherapy is the norm in chordoma. As appropriately commented by Professor Goel in the SGSCC grading article,1 genomics and proteomics for skull base chordoma cannot be included. The reason being they are not widely available and are being used only in experimental centers. Cannot be Uniformly Applied in All Centers Diagnostic classifications, like The Diagnostic and Statistical Manual of Mental Disorders (DSM) classification for psychiatric illnesses, can be considered like a scoring system. Only medically intractable cases come to psychosurgery. Again, although in this case, DSM classification is encouraged, the same cannot be made mandatory in all centers considering the fundamental nature of psychiatric diseases and the cultural flavor attached to it.7 Incorporating Examples in American Society of Anesthesiologists Grade The anesthesiologist's American Society of Anesthesiologists (ASA) grade has been significantly modified to include an “E” for emergency and a “P” for pregnancy. Even including clinical examples within the above ASA grade can significantly improve clarity in assigning correct grade to patients.8 Improvising Existing Medical Research Council (MRC) Grading Scores: Another simple example is the MRC grading for muscle weakness, which has been respectfully modified (for muscle disorders by neurologists) by “adding” the following: 0-paralysis, 1-severe weakness, 2-mild weakness, and 3-normal strength. A Rasch statistical analysis was performed to get a “summed” score.9 The Rasch analysis is used to incorporate interval parameters into an ordinal score. Understand and Evaluate Pathogenesis in Trigeminal Neuralgia Preoperative scoring10 of vascular contact of trigeminal neuralgia into no contact, simple contact, and severe (with nerve displacement) contact is an important step in the understanding the pathogenesis of trigeminal neuralgia. We already know, from Professors Jannetta and Ramesh,11 that not all vascular contact produces demyelination in the trigeminal nerve. We also know that demyelination alone without vascular contact produces trigeminal neuralgia. Prevent Bad Outcomes The SGSCC score will certainly prevent bad outcomes from happening. As rightly stated in the grading system discussion, it will help surgeons identify difficult areas and areas that will need further therapy like carbon-ion therapy. But it cannot account for and should not be solely based on an exceptionally good surgeon–physician's results. In such a surgeon's hands, even a poor grade lesion will have a very good outcome. Predict Mortality In 1998, it was analyzed that the “Portsmouth” modification of Physiological and Operative Severity Scoring system for enUmeration of Mortality (P-POSSUM) score audits predicted mortality accurately12. It incorporates physiological score and operative severity score. The P-POSSUM equation is as follows: Ln [R (1–R)] = –9.065 + (0.1692 × physiological score) + (0.1550 × operative severity score). R is the predicted risk of mortality. It was widely used in vascular and general surgery. Elective cranial surgeries were only later included. It was not yet validated for spine, peripheral nerve, and acute cranial procedures. Then the West Australian Categorization of Operative Severity (WA classification) emerged for use in neurosurgery. But when these 2 equations were combined as the WA P-POSSUM score, the prediction of mortality in neurosurgery was more accurate than either of them.13 ASPECTS (Alberta Stroke Program Early Computer Tomography Score) Application This quantitative score with a maximum of 10 points, including caudate, internal capsule, lentiform nucleus, insular ribbon, and 6 middle cerebral artery territories, was significantly modified and utilized when applying diffusion-weighted imaging. Although it was initially considered systematic, reproducible, and practical, a clear low score cut-off cannot be given. This will hinder certain aspects of newer treatment protocols, for example “pushing the limits” protocols to include lower scores in mechanical thrombectomy.14 Information Technology (IT)—Practicality, Effectiveness, Economization, and Educational For example, information technology (IT)-based clinical pathway is in effect a scoring system, with a sequence. Such a clinical pathway helps in making treatment of spondylodiscitis effective, economical, and educative. This is especially so for newer employees entering an organization with especially high turn-over of employees.15 CONCLUSION Not all scoring systems serve all purposes. Some systems are good for assessing outcome and some for assessing cost. Some scores predict mortality, while others will add cost effectiveness. The question remains if future analysis should include and summate all similar scoring systems for clival chordomas. Bits and pieces of scores from each of the examples above can be included and “summated” into a scoring system (for example, an IT-based clinical pathway). It will obviously become complex. Anesthesiologist's and intensivist's parameters like Elective/emergency procedure can be defined at a preoperative assessment level. Intraoperatively, there are other monitoring devices that can provide additional parameters. Neuropathology/oncology parameters can be included to further subcellularly grade the benign chordoma postoperatively. All of these contribute to the advantages and disadvantages of a scoring system (Figure 2).FIGURE 2.: Line diagram showing the flow chart for modifying a score after application.Disclosure The authors have no personal, financial, or institutional interest in any of the drugs, materials, or devices described in this article.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,003 | 0,005 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,014 | 0,020 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,004 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».