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Effect of montelukast and rupatadine on rituximab infusion time, rate, severity of reactions, and cost of administration.

2019· article· en· W2946833429 on OpenAlexaff
Rouslan Kotchetkov, Jesse McLean, Lauren Gerard, Derek Nay, Sean Hopkins

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsCancer Care OntarioRoyal Victoria Regional Health CentreBarrie Urology Group
Fundersnot available
KeywordsMedicineRituximabDiphenhydramineMontelukastInternal medicineGastroenterologyAnesthesiaAsthmaLymphoma

Abstract

fetched live from OpenAlex

6500 Background: Rituximab is associated with frequent infusion reactions which carry significant burden to patients and health care practitioners. Standard pre-medications (SP) do not prevent reactions sufficiently. Rupatidine (R) and Montelukast (M) are used for symptomatic treatment of urticaria and allergic rhinitis. We assessed addition of R, M and their combination on Rituximab infusion, rate, severity of reactions and cost of administration. Methods: Adult patients with lymphoproliferative disorders treated at our cancer center between Jan 2018 to Jan 2019 were evaluated with Rituximab-containing regiments. Since the majority of reactions occur during the first infusion, our study was limited to the initial Rituximab treatment. Patients received either SP with diphenhydramine/acetaminophen and additional R, M or R+M combination. Comparative analysis of infusion time/rate, severity of infusion reactions, number of rescue medications and cost of Rituximab infusions among groups was performed using one-way ANOVA with Tukey post-hoc or chi-square. The study was approved by our institutional IRB. Results: Patients received either: 1) SP; 2) SP + Rupatadine (R) 10 mg; 3) SP + Montelukast (M) 10 mg; or 4) both (SP+R+M). Patient demographics are shown in the table. Compared to SP, the R, M and R+M groups had greater improvement in Rituximab delivery. Mean infusion time was 306 [range 235-441] min. in SP, 254 [105-390] in M, 265 [193-350] in R and 248 [196-342] in R+M groups, (p=0.0001). Infusion reactions occurred in 92% in SP vs. 38, 45, 33% in M, R and R+M groups (p=0.0001). Median reaction grade was 2 in SP, 1 (M), 0 (R and R+M). Median number of rescue medications was 3 [0-10] in SP vs 0 [0-7] in M, R and R+M groups. Cost of rescue medications (US$) was 38 [0-63] (SP), 11 [0-50] (M), 17 [0-63] (R), 12 [0-58] (R+M) groups (p<0.0001). Mean nursing cost (US$) per patient infusion was calculated as 269 [207-388] in SP vs 222 [92-343] (M), 233 [170-308] (R), 218 [174-301] (R+M) group. Conclusions: Addition of R, M and particularly R+M significantly improved Rituximab delivery, lowered the rate and severity of infusion reactions, and lowered the cost of Rituximab administration. [Table: see text]

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
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)0.0000.000

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 head0.044
GPT teacher head0.441
Teacher spread0.397 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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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Citations1
Published2019
Admission routes1
Has abstractyes

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