Evidence map›Paper›PMID 36657422›Full record

ArticleBlood purification2023

The Investigation of Kidney Involvement in 430 Hospitalized Patients with Omicron COVID-19 in Tianjin, China.

Lanbo Teng, Wenxiu Chang

Open access · greenAbstract read
In one paragraph

Article in Blood purification, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 28% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

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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 2 institutions in 1 country.

Lanbo TengDepartment of Nephrology, Tianjin First Central Hospital, Tianjin, China.
Wenxiu ChangDepartment of Nephrology, Tianjin First Central Hospital, Tianjin, China.
Tianjin First Center Hospital · CNTianjin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThis study evaluated the incidence, clinical characteristics, and risk factors of kidney involvement in patients with the Omicron variant infection in the post-acute treatment phase in Tianjin, China.

methodsData were collected from 430 patients with Omicron variant infection in Tianjin, China. Demographics, comorbidities, laboratory blood tests, urinalysis, vaccination status, and COVID-19 clinical classification were assessed. Patients were grouped based on kidney involvement, and associated risk factors of kidney involvement were also investigated.

resultsAsymptomatic, mild, ordinary, and severe patients with Omicron COVID-19 variant comprised 1.5%, 49.1%, 48.9%, and 0.5% of the sample population, respectively, without critical illness or death. The incidences of hematuria, proteinuria, and concurrent hematuria and proteinuria were 14.7%, 14.2%, and 5.1%, respectively. Patients with and without kidney involvement differed in age, body mass index (BMI), comorbidity, creatinine levels, estimated glomerular filtration rate, and C-reactive protein (CRP) levels. Age, hypertension, higher CRP levels, and higher BMI were linked with kidney involvement.

conclusionThe majority of the patients suffered from mild or ordinary symptoms of Omicron COVID-19 infection. The primary kidney involvement was hematuria and proteinuria. Proteinuria was significantly associated with Omicron variant infection, and patients with hypertensive comorbidity, higher CRP, and higher creatinine levels were at increased risk of proteinuria after Omicron variant infection.

Indexed as

COVID-19HypertensionChinaCreatinineHematuriaHumansKidneyProteinuriaSARS-CoV-2CreatinineHematuriaKidney involvementOmicronProteinuria

Identifiers

PMID36657422
PMCPMC9893007
OpenAlexW4317467434

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Registered trials

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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.