Evidence map›Paper›PMID 30997523›Full record

ArticleDer Internist2019

[Laboratory tests for kidney disease].

G M Fiedler, B Vogt

Abstract read
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In one paragraph

Article in Der Internist, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Review
  2. 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

2 authors.

G M FiedlerZentrum für Labormedizin und Universitätsinstitut für Klinische Chemie, Inselspital, Universitätsspital Bern, Universität Bern, 3010, Bern, Schweiz. martin.fiedler@insel.ch.
B VogtUniversitätsklinik für Nephrologie und Hypertonie, Inselspital, Universitätsspital Bern, Universität Bern, 3010, Bern, Schweiz.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kidney diseases are among the most frequently reported diseases with a poor prognosis that are diagnosed too late. According to current Kidney Disease Improving Global Outcomes (KDIGO) guidelines, diagnosis and risk stratification are mainly based on functional markers (creatinine and cystatin C), which are used to determine the estimated glomerular filtration rate (eGFR) and the analysis of urinary albumin excretion as a marker of kidney damage. These methods have limitations that can complicate the interpretation of the results and can lead to a delay of the diagnosis as well as to a misinterpretation of the prognosis. Therefore, new damage markers are required that sensitively and specifically detect kidney damage and enable targeted treatment. Urinalysis complements the laboratory diagnostic spectrum of diseases of the kidneys and urinary tract. It is mainly used for screening and provides important information on localization (renal/postrenal) and differentiation of kidney diseases (glomerular/tubulointerstitial).

Indexed as

BiomarkersCreatinineCystatin CGlomerular Filtration RateHumansKidneyKidney DiseasesKidney Function TestsRenal InsufficiencyUrinalysisBiomarkersCreatinineCystatin CBiomarkersCreatinineCystatin CGlomerular filtration rateUrinalysis

Identifiers

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.