Bibliographic record
Abstract
clinical state became serious with lethargy, aspontaneity, disinhibition and executive dysfunction.Biological features were abnormal with elevated creatinine phosphokinase (3415 UI/l), increased C-reactive protein (3.7 mg/ dl) and hepatic cytolysis.Her treatment consisted of cyclophosphamide and methylprednisolone, and the introduction of a titrating-dose (up to 600 mg) of quetiapine for the psychiatric symptoms was decided upon.Her creatinine phosphokinase levels returned progressively to normal, and no signs of neuroleptic malignant syndrome were observed.Six weeks after continuing this treatment, biological and clinical features were normalised.This case illustrates the importance of differentiating delirium caused by a neuropsychiatric systemic lupus erythematosus, a steroid-induced delirium 1 (which was not the case here as the patient had not been receiving any steroids when she developed the second psychotic episode) and an alteration in the consciousness level due to neuroleptic malignant syndrome, which was the case here.Although there are no guidelines for the treatment of the psychiatric manifestations of systemic lupus erythematosus, it usually includes immunosuppressants associated with secondgeneration antipsychotics.3 The diagnosis of neuroleptic malignant syndrome is based on muscle rigidity, hyperthermia, delirium and autonomic disturbances.4 The dopaminergic hypothesis of the syndrome is well documented.5 Neuroleptic malignant syndrome is not an absolute contraindication for further antipsychotic treatment and some factors can reduce that risk: avoiding the long-term use of antipsychotics, using low-potency agents, adjunctive treatments and slow titration.2 In this case, we suggest that the introduction of quetiapine -a lower D 2 -affinity antipsychotic -was an interesting alternative.
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 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 | 0.004 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.033 | 0.034 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".