Evidence map›Paper›PMID 38036813›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

High-Throughput Quantitative LC-MS/MS Analysis of Barbiturates in Human Urine.

Putuma P Gqamana, Y Victoria Zhang

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Interpol review of forensic drug chemistry, 2022-2025.Forensic science international. Synergy · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Putuma P GqamanaDepartment of Pathology and Laboratory Medicine, University of Rochester Medical Center, Rochester, NY, USA.
Y Victoria ZhangDepartment of Pathology and Laboratory Medicine, University of Rochester Medical Center, Rochester, NY, USA. Victoria_Zhang@URMC.Rochester.edu.
University of Rochester Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We hereby present a fast, high-throughput, and clinical LC-MS/MS assay for the simultaneous analysis of barbiturates in human urine. It is deployed as a quantitative assay for phenobarbital, butalbital, pentobarbital/amobarbital, and secobarbital, as well as for confirmations following positive immunoassay drug screens in patient urine. Briefly, urine specimens are processed via dilute and shoot, i.e., by mixing the sample with 20 times volume of internal standard reagent and injecting 50 μL of that mixture into the analytical instrument. Chromatographic separation is performed using a reversed-phase C18 column in a mobile-phase system doped with <1 mM ammonium fluoride. Mass spectrometric detection occurs via negative-mode electrospray ionization multiple reaction monitoring in the TSQ Quantiva triple-quadrupole instrument. All the analytes in the mixture are detected and quantified simultaneously with respect to internal calibration in the range 20-2500 ng/mL. However, the assay cannot distinguish pentobarbital from amobarbital, which are isobaric analytes. Nonetheless, the assay is sensitive, robust, and amenable to harmonization with other assays that employ barbiturate cutoffs in the range of 20-150 ng/mL.

Indexed as

AmobarbitalPentobarbitalBarbituratesChromatography, High Pressure LiquidChromatography, LiquidHumansReproducibility of ResultsTandem Mass SpectrometryAmobarbitalBarbituratesPentobarbitalBarbituratesHigh-throughput LC-MS/MSMultiple reaction monitoring (MRM)Multiplex HPLCNegative-mode electrospray ionization (ESI)

Identifiers

PMID38036813
OpenAlexW4389209045

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.