Evidence map›Paper›PMID 37524062›Full record

ArticleAmerican journal of nephrology2023

Impact of the COVID-19 Pandemic on the Provision of Dialysis Service and Mortality in Veterans Receiving Maintenance Hemodialysis in the VA: An Interrupted Time-Series Analysis.

Samir Patel, Eduardo A Trujillo Rivera, Venkatesh K Raman, Charles Faselis, Virginia Wang, Jeffrey C Fink, Jeffrey M Roseman, Charity J Morgan, Sijian Zhang, Helen M Sheriff and 4 more

Abstract read
In one paragraph

Article in American journal of nephrology, 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
4.0field-weighted citation impact, top 5% 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, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Observational
  4. 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

14 authors at 7 institutions in 2 countries.

Samir PatelCenter for Data Science and Outcomes Research, Veterans Affairs Medical Center, Washington, District of Columbia, USA.
Eduardo A Trujillo RiveraCenter for Data Science and Outcomes Research, Veterans Affairs Medical Center, Washington, District of Columbia, USA.
Venkatesh K RamanCenter for Data Science and Outcomes Research, Veterans Affairs Medical Center, Washington, District of Columbia, USA.
Charles FaselisCenter for Data Science and Outcomes Research, Veterans Affairs Medical Center, Washington, District of Columbia, USA.
Virginia WangCenter of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System, Durham, North Carolina, USA.
Jeffrey C FinkVeterans Affairs Medical Center, Baltimore, Maryland, USA.
Jeffrey M RosemanDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA.
Charity J MorganDepartment of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA.
Sijian ZhangCenter for Data Science and Outcomes Research, Veterans Affairs Medical Center, Washington, District of Columbia, USA.
Helen M SheriffCenter for Data Science and Outcomes Research, Veterans Affairs Medical Center, Washington, District of Columbia, USA.
Michael S HeimallCenter for Data Science and Outcomes Research, Veterans Affairs Medical Center, Washington, District of Columbia, USA.
Wen-Chih WuMedical service, Veterans Affairs Medical Center, Providence, Rhode Island, USA.
Qing Zeng-TreitlerCenter for Data Science and Outcomes Research, Veterans Affairs Medical Center, Washington, District of Columbia, USA.
Ali AhmedCenter for Data Science and Outcomes Research, Veterans Affairs Medical Center, Washington, District of Columbia, USA.
Georgetown University · USGeorge Washington University · USUniversity of Alabama at Birmingham · USBrown University · USDurham VA Health Care System · USUniformed Services University of the Health Sciences · USVeterans Health Administration · US

Funding

Improving Outcomes in Veterans with Heart Failure and Chronic Kidney DiseaseI01HX002422 · VA · U.S. DEPT/VETS AFFAIRS MEDICAL CENTER · PI AHMED, ALI, WU, WEN-CHIH · 2019 to 2025
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HSRD VA I01 HX002422HSRD VA I01 HX003574
6 · The paper itself

Abstract

introductionAccording to the US Renal Data System (USRDS), patients with end-stage kidney disease (ESKD) on maintenance dialysis had higher mortality during early COVID-19 pandemic. Less is known about the effect of the pandemic on the delivery of outpatient maintenance hemodialysis and its impact on death. We examined the effect of pandemic-related disruption on the delivery of dialysis treatment and mortality in patients with ESKD receiving maintenance hemodialysis in the Veterans Health Administration (VHA) facilities, the largest integrated national healthcare system in the USA.

methodsUsing national VHA electronic health records data, we identified 7,302 Veterans with ESKD who received outpatient maintenance hemodialysis in VHA healthcare facilities during the COVID-19 pandemic (February 1, 2020, to December 31, 2021). We estimated the average change in the number of hemodialysis treatments received and deaths per 1,000 patients per month during the pandemic by conducting interrupted time-series analyses. We used seasonal autoregressive moving average (SARMA) models, in which February 2020 was used as the conditional intercept and months thereafter as conditional slope. The models were adjusted for seasonal variations and trends in rates during the pre-pandemic period (January 1, 2007, to January 31, 2020).

resultsThe number (95% CI) of hemodialysis treatments received per 1,000 patients per month during the pre-pandemic and pandemic periods were 12,670 (12,525-12,796) and 12,865 (12,729-13,002), respectively. Respective all-cause mortality rates (95% CI) were 17.1 (16.7-17.5) and 19.6 (18.5-20.7) per 1,000 patients per month. Findings from SARMA models demonstrate that there was no reduction in the dialysis treatments delivered during the pandemic (rate ratio: 0.999; 95% CI: 0.998-1.001), but there was a 2.3% (95% CI: 1.5-3.1%) increase in mortality. During the pandemic, the non-COVID hospitalization rate was 146 (95% CI: 143-149) per 1,000 patients per month, which was lower than the pre-pandemic rate of 175 (95% CI: 173-176). In contrast, there was evidence of higher use of telephone encounters during the pandemic (3,023; 95% CI: 2,957-3,089), compared with the pre-pandemic rate (1,282; 95% CI: 1,241-1,324).

conclusionsWe found no evidence that there was a disruption in the delivery of outpatient maintenance hemodialysis treatment in VHA facilities during the COVID-19 pandemic and that the modest rise in deaths during the pandemic is unlikely to be due to missed dialysis.

Indexed as

COVID-19Kidney Failure, ChronicVeteransHumansPandemicsRenal DialysisRetrospective StudiesCOVID-19DialysisMortalityVeterans Affairs healthcare system

Identifiers

PMID37524062
PMCPMC10959175
OpenAlexW4385442514

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.