Evidence map›Paper›PMID 37674993›Full record

ArticleFrontiers in nephrology2022

Modifiable Risk Factors Are Important Predictors of COVID-19-Related Mortality in Patients on Hemodialysis.

Jeroen Peter Kooman, Paola Carioni, Vratislava Kovarova, Otto Arkossy, Anke Winter, Yan Zhang, Francesco Bellocchio, Peter Kotanko, Hanjie Zhang, Len Usvyat and 3 more

Open access · diamondAbstract read
In one paragraph

Article in Frontiers in nephrology, 2022. 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
0.5field-weighted citation impact, top 36% 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, 5 citations in OpenAlex.

  1. Article
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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

13 authors at 5 institutions in 3 countries.

Jeroen Peter KoomanDepartment of Internal Medicine, University Hospital Maastricht, Maastricht, Netherlands.
Paola CarioniFresenius Medical Care Italia SpA, Palazzo Pignano, Italy.
Vratislava KovarovaFresenius Medical Care Deutschland GmbH, Bad Homburg, Germany.
Otto ArkossyFresenius Medical Care Deutschland GmbH, Bad Homburg, Germany.
Anke WinterFresenius Medical Care Deutschland GmbH, Bad Homburg, Germany.
Yan ZhangFresenius Medical Care Deutschland GmbH, Bad Homburg, Germany.
Francesco BellocchioFresenius Medical Care Italia SpA, Palazzo Pignano, Italy.
Peter KotankoRenal Research Institute, New York, NY, United States.
Hanjie ZhangRenal Research Institute, New York, NY, United States.
Len UsvyatFresenius Medical Care, Waltham, MA, United States.
John LarkinFresenius Medical Care, Waltham, MA, United States.
Stefano StuardFresenius Medical Care Deutschland GmbH, Bad Homburg, Germany.
Luca NeriFresenius Medical Care Italia SpA, Palazzo Pignano, Italy.
Fresenius Medical Care (Germany) · DEFresenius Medical Care (United States) · USIcahn School of Medicine at Mount Sinai · USMaastricht University Medical Centre · NLRenal Research Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Patients with end-stage kidney disease face a higher risk of severe outcomes from SARS-CoV-2 infection. Moreover, it is not well known to what extent potentially modifiable risk factors contribute to mortality risk. In this historical cohort study, we investigated the incidence and risk factors for 30-day mortality among hemodialysis patients with SARS-CoV-2 infection treated in the European Fresenius Medical Care NephroCare network using conventional and machine learning techniques. Methods: We included adult hemodialysis patients with the first documented SARS-CoV-2 infection between February 1, 2020, and March 31, 2021, registered in the clinical database. The index date for the analysis was the first SARS-CoV-2 suspicion date. Patients were followed for up to 30 days until April 30, 2021. Demographics, comorbidities, and various modifiable risk factors, expressed as continuous parameters and as key performance indicators (KPIs), were considered to tap multiple dimensions including hemodynamic control, nutritional state, and mineral metabolism in the 6 months before the index date. We used logistic regression (LR) and XGBoost models to assess risk factors for 30-day mortality. Results: We included 9,211 patients (age 65.4 ± 13.7 years, dialysis vintage 4.2 ± 3.7 years) eligible for the study. The 30-day mortality rate was 20.8%. In LR models, several potentially modifiable factors were associated with higher mortality: body mass index (BMI) 30-40 kg/m Conclusion: Both conventional and machine learning techniques showed that KPIs and modifiable risk factors in different dimensions ascertained 6 months before the COVID-19 suspicion date were associated with 30-day COVID-19-related mortality. Our results suggest that adequate dialysis and achieving KPI targets remain of major importance during the COVID-19 pandemic as well.

Indexed as

chronic kidney diseaseCOVID-19end-stage kidney diseasehemodialysismortalityoutcomesSARS-CoV-2

Identifiers

PMID37674993
PMCPMC10479683
OpenAlexW4286008943

What OpenQuestion holds

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LicenceCC BY
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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.