Evidence map›Paper›PMID 31325123›Full record

ArticleLasers in medical science2020

Detecting creatine excreted in the urine of swimming athletes by means of Raman spectroscopy.

Letícia Parada Moreira, Débora Dias Ferraretto Moura Rocco, Alexandre Galvão da Silva, Marcos Tadeu Tavares Pacheco, Landulfo Silveira

Abstract read
PubMed Publisher
In one paragraph

Article in Lasers in medical science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 37% 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

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
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

5 authors at 2 institutions in 1 country.

Letícia Parada MoreiraUniversidade Santa Cecília - UNISANTA, Rua Oswaldo Cruz, 277, Santos, SP, 11045-907, Brazil.
Débora Dias Ferraretto Moura RoccoUniversidade Santa Cecília - UNISANTA, Rua Oswaldo Cruz, 277, Santos, SP, 11045-907, Brazil.
Alexandre Galvão da SilvaUniversidade Santa Cecília - UNISANTA, Rua Oswaldo Cruz, 277, Santos, SP, 11045-907, Brazil.
Marcos Tadeu Tavares PachecoUniversidade Santa Cecília - UNISANTA, Rua Oswaldo Cruz, 277, Santos, SP, 11045-907, Brazil.
Landulfo SilveiraUniversidade Santa Cecília - UNISANTA, Rua Oswaldo Cruz, 277, Santos, SP, 11045-907, Brazil. landulfo.silveira@gmail.com.ORCID http://orcid.org/0000-0002-6616-3334
Universidade Santa Cecília · BRAnhembi Morumbi University · BR

Funding

Fundação de Amparo à Pesquisa do Estado de São Paulo 2009/01788-5
6 · The paper itself

Abstract

High-level sport requires analysis of athletes' metabolic conditions in order to improve the training. Raman spectroscopy can be used to assess urinary composition advantageously when compared to conventional methods of urinalysis. In this work, Raman spectroscopy has been employed to detect creatine in urine of professional swimmers before and after training compared to sedentaries. It has been collected urine samples from five swimmers before and immediately after 150 min of swimming and submitted to Raman spectroscopy (830 nm excitation, 350 mW laser power, 20 s integration time) and compared to the urine from a control group (14 sedentary subjects). The Raman spectra of urine from four swimmers after training showed peaks related to creatine at 829, 915, 1049, and 1397 cm

Indexed as

AthletesSpectrum Analysis, RamanAdultCreatineCreatinineFemaleHumansKetone BodiesMalePrincipal Component AnalysisSedentary BehaviorSwimmingYoung AdultCreatineCreatinineKetone BodiesCreatinePhysical exerciseRaman spectroscopySwimming athletesUrine metabolite

Identifiers

PMID31325123
OpenAlexW2963261498

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.