Evidence map›Paper›PMID 36793023›Full record

ArticleBMC pulmonary medicine2023

Optimization of sniff nasal inspiratory pressure (SNIP) measurement methodology in healthy subjects.

R J Wilding, M Thynne, M M F Subhan

Open access · goldAbstract read
In one paragraph

Article in BMC pulmonary medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.1field-weighted citation impact, top 25% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. 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

3 authors at 2 institutions in 1 country.

R J WildingUniversity Hospitals Plymouth NHS Trust, Plymouth, PL6 8DH, UK.ORCID http://orcid.org/0000-0002-1545-9995
M ThynneChest Clinic, University Hospitals Plymouth NHS Trust, Plymouth, PL6 8DH, UK.
M M F SubhanSchool of Biomedical Sciences, Faculty of Health, University of Plymouth, C507, Portland Square, Drake Circus, Plymouth, PL4 8AA, UK. feisal.subhan@plymouth.ac.uk.
University Hospitals Plymouth NHS Trust · GBUniversity of Plymouth · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMaximal inspiratory pressure (MIP) is currently the most commonly used measure for respiratory muscle strength (RMS) estimation, however, requires significant effort. Falsely low values are therefore common, especially in fatigue-prone subjects, such as neuromuscular disorder patients. In contrast, sniff nasal inspiratory pressure (SNIP) requires a short, sharp sniff; this is a natural manoeuvre, decreasing required effort. Consequently, it has been suggested that use of SNIP could confirm the accuracy of MIP measurements. However, no recent guidelines regarding the optimal method of SNIP measurement exist, and varied approaches have been described.

objectivesWe compared SNIP values from three conditions, namely with 30, 60 or 90 s time intervals between repeats, the right (SNIP

method52 healthy subjects (23 males) were recruited for this study, of which a subset of 10 subjects (5 males) completed tests comparing the time interval between repeats. SNIP was measured from functional residual capacity via a probe in one nostril, while MIP was measured from residual volume.

resultsThere was no significant difference in SNIP depending on the interval between repeats (P = 0.98); subjects preferred the 30 s. SNIP

conclusionsWe conclude that SNIP

Indexed as

Nasal CavityFunctional Residual CapacityHealthy VolunteersHumansMalePressureRespiratory Function TestsHealthy subjectsReproducibilityRespiratory muscle strengthSNIP

Identifiers

PMID36793023
PMCPMC9930287
OpenAlexW4321002113

What OpenQuestion holds

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LicenceCC BY
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.