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2 SIDES OF LUPUS: CASE REPORT

2025· article· en· W4410715786 on OpenAlexvenueno aff
Ana Alwina Stan, Gener Ismail

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSystemic lupus erythematosusDermatologyLupus erythematosusInternal medicineImmunologyDiseaseAntibody

Abstract

fetched live from OpenAlex

PV294 / #139 Case Report Poster Topic: AS19 - Patient-Reported Outcome Measures Introduction Systemic lupus erythematosus (SLE) is a complex disease, often described as the “disease with 1000 faces.” Its impact on the various organs and systems has been thoroughly described, however we believe that it is important to assess the impact it has on patients that are also physicians-on their professional activity, quality of life and relation toward fellow patients. Case Presentation With Investigation My first symptoms, consisting of lower limb rash, fatigue and pancytopenia, appeared around the age of 16. Subsequent investigations suggested an autoimmune disease and although there was no clear diagnosis I received intensive immunosuppression (high-dose oral steroids, IV cyclophosphamide and mycophenolate) which only partially improved the symptoms and caused significant side effects (nausea, vomiting, diarrhea, frequent upper respiratory and urinary infections, menstrual cycle abnormalities), thus leading to educational deficits and isolation from peers. Over the next few years treatment was reassessed, maintaining only low-dose prednisone and hydroxychloroquine (HCQ), which was enough at that point to control the disease and enabling me to start studying medicine. The first 5 years were mostly uneventful, except for the occasional rash, lower limb edema and intense itching from HCQ. Afterwards I started experiencing joint pain (hips, knees, Costo-vertebral, fingers) as well as myalgia and muscle spasms, which lead to extensive use of NSAIDS. Finally in 2012 (the year I graduated) I received the definitive diagnosis of SLE due to positive serology. In addition to steroids and HCQ I was started on azathioprine, which seemed to improve symptoms during the first few months but then was less effective as I started working night shifts as an internal medicine resident. In my second year of residency, I quit these shifts and took part in a study on Belimumab (Benlysta)- being effective both on symptoms and laboratory results. After the study ended, I continued on azathioprine, unfortunately leading to severe neutropenia. For the next 2 years I took only oral vitamin D until a severe flare in 2017 when I was started on sc methotrexate, which lead to anal fissures and a very poor quality of life. Next year (my first as a specialist physician) consisted of extensive joint involvement not controlled by low-dose prednisone. In 2019 Benlysta was finally approved in Romania and I started infusions, finally obtaining remission of symptoms. Unfortunately, my kidney function began deteriorating, biopsy showing class III lupus nephritis. With add-on mycophenolate, HCQ and ACE inhibitor, creatinine and proteinuria decreased, having stable values to the present time. This also determined me to pursue nephrology as a second specialty. Literature Review No relevant information. Discussion Dealing with SLE from both perspectives (patient and doctor) allowed me to better understand all the implications of this disease-on one’s career, family and relationships, self-esteem and overall quality of life, helping me to have a more holistic approach of each case and offer a qualitative care for my patients.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0030.001
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0220.006

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 head0.023
GPT teacher head0.333
Teacher spread0.310 · 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 designCase report
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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Citations1
Published2025
Admission routes1
Has abstractyes

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