Bibliographic record
Abstract
Fifty years ago, Canadian neurologist J. Clifford Richardson described five patients with supranuclear vertical gaze palsy, pseudobulbar palsy, axial rigidity-in-extension and cognitive impairment.[1] He along with Olszewski and Steele described the neuro-pathological findings showing loss of nerve cells and gliosis in the pallidum, subthalamic and red nucleus, substantia nigra and locus coeruleus, the superior colliculi, periaqueductal grey matter, and pretectal regions, the vestibular nuclei, various nuclei of the reticular formation and the dentate nuclei. In these regions neurofibrillary tangles without senile plaques were present. Granulovacuolar changes were seen in the red nucleus and nuclei pontis. PSP is a neuro-degenerative disease which is 4R tauopathy.[2] The National Institute of Neurological Disorders and Stroke (NINDS-SPSP) [3] criteria have specificity of 96–100% but sensitivity is low.[456] Since the description of NINDS-SPSP criteria, clinical heterogeneity of PSP has been described with autopsy proven PSP pathology.[57891011] This prompted MDS to setup the task force on PSP which was mandated to provide all inclusive, yet robust, and highly sensitive and specific clinical diagnostic criteria for PSP. Ideally, diagnostic investigations should be added to the clinical diagnostic criteria of PSP to increase both specificity and sensitivity. The positive predictive value of a clinical diagnosis of PSP in life in a patient with the Richardson's syndrome, especially with falls in the first year of life (fulfilling NINDS-SPSP clinical diagnostic criteria is quite high although many patients with the pathological changes of PSP are missed (i.e. low sensitivity). The MDS in the new diagnostic criteria,[12] included four core clinical domains (ocular motor dysfunction [O], postural instability [P], akinesia [A], and cognitive dysfunction [C]. In each domain, they proposed three characteristic core clinical feature. Supportive features to indicate the presence of sporadic, adult-onset, gradually progressive neurodegenerative disease. Mandatory exclusion criteria to rule out PSP should be applied only in patients presenting with suggestive, unusual clinical features justifying further investigation. As in the NINDS-SPSP criteria three certainty levels are included in the MDS diagnostic criteria. They are definite which is the neuropathological gold standard proved at autopsy, regardless of its clinical presentation. Probable PSP is diagnosed in the presence of a combination of clinical features with high specificity. Possible PSP is diagnosed in the presence of clinical features considered to substantially increase the sensitivity for PSP. PREDOMINANT TYPES OF PSP Clinical predominance types are determined based on the combination of clinical features (These include PSP-RS (Richardson), PSP-OM (oculo-motor), PSP-PI (postural instability), PSP-P (parkinsonism), PSP-F (Frontal dysfunction), PSP-PGF (gait freezing), PSP-CBS (corticobasal), and PSP-SL (speech and language).[13] The importance of making a correct diagnosis of PSP, will become critical with the development of effective disease modifying therapies that are specifically directed at the influence of tau aggregation in the pathogenesis of the disorder. Efforts by several authors have been made to identify several phenotypic variants based on autopsy studies. They have shown PSP-RS to form the major proportion, followed by PSP-P, PSP-OM, PSP-PIGF followed by the rest. In this issue an article from a tertiary care teaching hospital categorized 334 PSP patients collected from 1996 to 2017, diagnosis based on NINDS-SPSP criteria, were re-classified according to MDS PSP criteria. Though the study lacks supporting evidence of autopsy, it is still a major landmark study.[14]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.026 | 0.028 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".