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Record W1991510272 · doi:10.1002/hup.467

Use of paroxetine for the treatment of depression and anxiety disorders in the elderly: a review

2002· review· en· W1991510272 on OpenAlexaff
Michel Bourin

Bibliographic record

VenueHuman Psychopharmacology Clinical and Experimental · 2002
Typereview
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsParoxetinePanic disorderAnxietyGeneralized anxiety disorderPsychiatryAnxiety disorderPanicDepression (economics)PsychologyTolerabilitySocial anxietyAdverse effectAntidepressantMedicineInternal medicine

Abstract

fetched live from OpenAlex

Paroxetine is a potent selective serotonin reuptake inhibitor (SSRI) with indications for the treatment of depression, obsessive- compulsive disorder, panic disorder and social phobia. It is also used in the treatment of generalized anxiety disorder, post-traumatic stress disorder, premenstrual dysphoric disorder and chronic headache. There is wide interindividual variation in the pharmacokinetics of paroxetine in adults as well as in the elderly with higher plasma concentrations and slower elimination noted in the latter. Elimination is also reduced in severe renal and hepatic impairment, however, serious adverse events are extremely rare even in overdose. A Pub Med search was used to collect information on the efficacy and tolerability in elderly patients. There are few studies of depression in the elderly and only one study in the old-old. In anxiety disorders including general anxiety disorder, panic disorder, obsessive-compulsive disorder and social anxiety, there are no studies at all in the elderly. However, the safety of the drug allows its prescription in the elderly. In summary, paroxetine is well tolerated in the treatment of depression in those between the ages of 65 and 75, although few studies have examined its use in those of 75 and older.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.221
GPT teacher head0.523
Teacher spread0.302 · 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 designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations24
Published2002
Admission routes1
Has abstractyes

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