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Record W2943871023 · doi:10.1097/cm9.0000000000000285

Alzheimer's disease identified in a patient with bullous pemphigoid by dementia screening scales

2019· article· en· W2943871023 on OpenAlexaboutno aff
Wenling Zhao, Yiman Wang, Jing Yuan, Yueping Zeng, Li Li

Bibliographic record

VenueChinese Medical Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicAutoimmune Bullous Skin Diseases
Canadian institutionsnot available
FundersPeking Union Medical CollegeNational Natural Science Foundation of ChinaMilstein Medical Asian American Partnership Foundation
KeywordsDementiaBullous pemphigoidMedicineMontreal Cognitive AssessmentFamily historyTrunkPathologyDermatologyInternal medicineDiseaseAntibodyImmunology

Abstract

fetched live from OpenAlex

To the Editor: A 73-year-old man presented with erythemas on his trunk and limbs with significant itching, which he had experienced for 11 months [Figure 1A and 1B]. Histological examination of his skin biopsy revealed sub-epidermal blister formation with eosinophilic and lymphocytic infiltration in the dermis. Direct immunofluorescence revealed the presence of a linear deposition along the basement membrane zone (BMZ). Indirect immunofluorescence revealed that the patient's serum was positive (titer ≥1:320) for anti-BMZ antibodies. Anti-BP180 antibody was 102 U/mL. Based on these findings, a diagnosis of bullous pemphigoid (BP) was established.Figure 1: Clinical features of the patient with BP and the T2-weighted magnetic resonance imaging of brain. (A and B) Erythemas were seen on his trunk and limbs, along with blisters on his hands. (C) Mild hippocampal atrophy. BP: Bullous pemphigoid.The patient was admitted to our hospital on September 21, 2017. During his hospitalization, we noticed that he exhibited bluntness and impaired short-term memory. Further investigation revealed a history of about 2 years of memory decline and a positive family history of dementia; both his father and sister had had dementia. Screening tests for dementia revealed an impaired cognition, as revealed by a score of 25 on the mini-mental state examination (MMSE) and a score of 19 on the montreal cognitive assessment (MoCA). A detailed neuropsychological test battery was implemented by a neurologist at our hospital, and the results demonstrated cognitive deficits in multiple domains, including memory, executive function, and visuospatial abilities. His apolipoprotein E (ApoE) genotype was ε4/ε4, which has been shown to be directly correlated with Alzheimer's disease (AD).[1] Electroencephalogram was mildly abnormal. The T2-weighted magnetic resonance imaging of brain showed mild hippocampal atrophy [Figure 1C] and high-signal intensities in periventricular white matter. The patient was diagnosed with AD by the neurologist, who then prescribed him with vitamin B6 (10 mg/day), folic acid (5 mg/day), and cobalamin (0.5 mg/day). This patient was treated with methylprednisolone (48 mg/day) and tripterygium glycosides (60 mg/day). He was reminded to visit a neurologist regularly for his AD control and had no recurrence of BP after 18 months of follow-up. In recent decades, BP has been shown to be associated with neurological disease (ND). AD is the most common ND associated with BP, and usually progress gradually, such that it can go undiagnosed for years. Indeed, dermatologists are sometimes the first to discover neurological abnormities in patients with BP.[2] Diagnosing ND earlier would result in more effective health care and a better quality of life. Early-stage dementia is associated with relatively mild symptoms and is thus often overlooked in clinical practice. Comprehensive diagnosis of dementia requires multiple evaluations performed by neurologists, including cognitive functioning tests and brain imaging. In this case, the neurologist diagnosed AD based on clinical appearance, various imaging examinations, laboratory tests, and the results of dementia screening scales. This allowed us to intervene and medicate the patient in a timely way, which might improve his prognosis. MMSE and MoCA are widely used scales for screening dementia, and are adopted around the world. Studies have shown that while the MMSE could effectively distinguish between normal patients and those with dementia, it is less able to differentiate between normal patients and those with mild cognitive impairment (MCI).[3] The MoCA can go some way to make up for this, since it has a higher sensitivity in the diagnosis of MCI than does the MMSE.[4] This case study suggests that, when identifying a patient with BP and suspected mental disorders, clinicians should be aware of the possibility of ND. We recommend the combined use of the MMSE and MoCA to examine this, as these are sensitive tools for cognitive impairment screening. Declaration of patient consent The authors certify that they obtained all appropriate patient consent forms. The patient also provided consent for his images and other clinical information to be reported in the journal. The patient understands that his name and initials will not be published and all efforts will be made to conceal his identity, but anonymity cannot be guaranteed. Funding This study was supported by grants from the Milstein Medical Asian American Partnership Foundation (2017, Dermatology), the National Natural Science Foundation of China (No. 81371731), and the Education Reform Projects of Peking Union Medical College (No. 2016zlgc0106). Conflicts of interest None.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.250
Teacher spread0.244 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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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Citations2
Published2019
Admission routes1
Has abstractyes

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