Assessing the Correlation of At-Home Audio Testing and In-office Uroflowmetry: Moving Towards a New Gold-Standard

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This study evaluated whether at-home audio-based uroflowmetry using the Emano Flow phone application correlates with in-office uroflowmetry among 32 adult men with lower urinary tract symptoms, who performed both assessments and provided urine void data over one week. Using Pearson correlation, the authors found no significant relationship between conventional in-clinic Qmax and the mean at-home Qmax before adjusting for void volume, but a significant correlation after residualizing for void volume. The paper’s key limitation is that differences in void volume and at least one uncharacteristically low in-clinic void likely affected the unadjusted comparison. Relevance to endometriosis: the paper focuses on LUTS and uroflowmetry in men, and it does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Objectives The incidence of lower urinary tract symptoms (LUTS) increases with age. Uroflowmetry, a diagnostic tool for LUTS, requires that patients travel to their urologist’s office. As audio-based uroflowmetry is being developed in the field, research is needed to evaluate whether it is equivalent to the gold standard, in-clinic uroflowmetry. Methods Men over age 18 with a chief complaint of LUTS conducted a standard in-office uroflowmetry and used the Emano Flow phone application for one week to conduct audio-based uroflowmetry. Pearson correlation coefficient (PCC) was utilized to assess the relationship between conventional and the mean of audio-based Qmax after adjusting for the effect of void volume by performing residualization. Results Thirty-two participants were recruited. On average, a patient’s home volume was 2.18x (SD 1.67) higher than their clinic volume. Prior to adjusting for void volume, conventional and the mean of multiple at-home maximum flow rates were not correlated (PCC=0.21, p=0.31). After adjusting for void volume, conventional and mean of multiple at-home Qmax were significantly correlated (PCC=0.41, p = 0.04). Conclusion Prior to adjusting for void volume, conventional and at-home maximum flow rates were not correlated. This can be explained, in part, by patients having one uncharacteristically low in-clinic on-demand void. Once we adjusted for void volume, office and at-home Qmax were correlated. As office Qmax may not accurately capture a patient’s natural voiding patterns, our findings underscore the potential value of at-home testing. Further work is needed to improve the tools that we use for diagnosing and evaluating LUTS.
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Abstract

Objectives The incidence of lower urinary tract symptoms (LUTS) increases with age. Uroflowmetry, a diagnostic tool for LUTS, requires that patients travel to their urologist’s office. As audio-based uroflowmetry is being developed in the field, research is needed to evaluate whether it is equivalent to the gold standard, in-clinic uroflowmetry.

Methods

Men over age 18 with a chief complaint of LUTS conducted a standard in-office uroflowmetry and used the Emano Flow phone application for one week to conduct audio-based uroflowmetry. Pearson correlation coefficient (PCC) was utilized to assess the relationship between conventional and the mean of audio-based Qmax after adjusting for the effect of void volume by performing residualization.

Results

Thirty-two participants were recruited. On average, a patient’s home volume was 2.18x (SD 1.67) higher than their clinic volume. Prior to adjusting for void volume, conventional and the mean of multiple at-home maximum flow rates were not correlated (PCC=0.21, p=0.31). After adjusting for void volume, conventional and mean of multiple at-home Qmax were significantly correlated (PCC=0.41, p = 0.04).

Conclusion

Prior to adjusting for void volume, conventional and at-home maximum flow rates were not correlated. This can be explained, in part, by patients having one uncharacteristically low in-clinic on-demand void. Once we adjusted for void volume, office and at-home Qmax were correlated. As office Qmax may not accurately capture a patient’s natural voiding patterns, our findings underscore the potential value of at-home testing. Further work is needed to improve the tools that we use for diagnosing and evaluating LUTS. Competing Interest Statement The authors have declared no competing interest. Funding Statement This study was funded by the Winston Research Grants Fund. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was approved by the University of California Los Angeles Institutional Review Board (23-1068-CR-001). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Footnotes Author Emails: Raeven S. Grant, BS - rsgrant{at}mednet.ucla.edu Kymora B. Scotland, MD PhD - kscotland{at}mednet.ucla.edu Karan N. Thaker, BS - karan.thaker{at}ucla.edu Camille Watson, BS - cmwatson{at}mednet.ucla.edu Yash Motwani, BS – ymotwani{at}mednet.ucla.edu Myung-Shin Sim, PhD – msim{at}mednet.ucla.edu Abigail Lavold, BS – alavold{at}mmednet.ucla.edu David F. Yao, MD -dyao{at}mednet.ucla.edu Stephanie Pannell, MD - spannell{at}mednet.ucla.edu Disclosures: None Data Availability All data produced in the present study are available upon reasonable request to the author.

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