Evidence map›Paper›PMID 42104501›Full record

Observational studyHemodialysis international. International Symposium on Home Hemodialysis2026

Impact of Noise Levels of the Dialysis Machine Alarm on Patient Anxiety.

Biplab Bera, P Hemanth

Abstract readObservational Study
In one paragraph

Observational study in Hemodialysis international. International Symposium on Home Hemodialysis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Biplab BeraUnit of Renal Dialysis Technology, Yenepoya School of Allied Health Sciences, Yenepoya University, Mangalore, Karnataka, India.ORCID https://orcid.org/0009-0009-4004-9160
P HemanthUnit of Renal Dialysis Technology, Yenepoya School of Allied Health Sciences, Yenepoya University, Mangalore, Karnataka, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

INTRODUCTION AND

backgroundHemodialysis machine alarms are warning noises, which are essential for patient safety, but the psychological impact of these alarms is often overlooked. This study aims to assess the relationship between hemodialysis machine alarm noise levels and anxiety among patients undergoing thrice weekly hemodialysis.

methodsThis observational, cross-sectional, analytical study was conducted on 53 participants who were undergoing hemodialysis. A Benetech GM1351 digital sound-level meter was used to measure the noise level of hemodialysis machine alarms. Socio-demographic data and Hamilton Anxiety Rating Scale (HAM-A) were used for data collection.

resultsThe range of noise level of hemodialysis machine alarms was detected from 48.5 to 77.8 dB(A). The study findings revealed that hemodialysis patients who are exposed to high intensity of the hemodialysis machine alarm have a negative impact on anxiety level in the hemodialysis unit. Females and participants with a higher level of education have higher anxiety levels.

conclusionHigher hemodialysis machine alarm noise had a significant impact on hemodialysis patients' anxiety. In addition, sex and educational status became predictors of anxiety. Future interventional research, such as alarm management protocols and tailored education programs to reduce anxiety among dialysis patients due to alarms, can provide meaningful insights.

Indexed as

AnxietyClinical AlarmsNoiseRenal DialysisAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedanxietyHamilton anxiety rating scale (HAM‐A)hemodialysis machine alarmhemodialysis patientsintensity of hemodialysis machine alarm

Identifiers

PMID42104501
PMCPMC13350551

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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.