Dataset Information

Development of a patient-report pressure algometer for the quantification of abdominal examination.

ABSTRACT:

Background

Abdominal examination (AE), one of the primary diagnostic tools used in traditional Korean medicine (TKM), has a limitation of being subjective due to depending on individual practitioner's experience. Therefore, we devised a novel patient-report pressure algometer (PA) and performed a clinical trial to investigate its validity.

Methods

In total, 44 participants with functional dyspepsia and 44 healthy participants completed the study. The participants were allocated into one of two groups according to the existence of abdominal stiffness at 5 acupoints or abdominal tenderness at 12 acupoints diagnosed by TKM doctors. The pressure depth and pressure pain threshold (PPT) were evaluated using the PA at the same acupoints. We assessed the validity (sensitivity and specificity) of PA and calculated the area under the curve (AUC) and optimal cutoff value of the test variables (pressure depth and PPT) to criterion standards (abdominal stiffness and tenderness).

Results

Pressure depth and PPT assessed by PA showed high sensitivity and specificity in diagnosing abdominal stiffness and tenderness. The validity at CV-14 of diagnosing abdominal tenderness with PPT by PA had a sensitivity of 73.1%, specificity of 77.8%, and an AUC of 0.807 with a P value of < 0.001.

Conclusion

This study may provide evidence of standardization and quantification of AE through PA.

SUBMITTER: Ko SJ

PROVIDER: S-EPMC8185239 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Publications

Development of a patient-report pressure algometer for the quantification of abdominal examination.

Ko Seok-Jae SJ Kim Keun Ho KH Lee Sang Hun SH Yim Mi Hong MH Park Jae-Woo JW

Integrative medicine research 20210524 4

<h4>Background</h4>Abdominal examination (AE), one of the primary diagnostic tools used in traditional Korean medicine (TKM), has a limitation of being subjective due to depending on individual practitioner's experience. Therefore, we devised a novel patient-report pressure algometer (PA) and performed a clinical trial to investigate its validity.<h4>Methods</h4>In total, 44 participants with functional dyspepsia and 44 healthy participants completed the study. The participants were allocated in ...[more]

PMID: 34141577

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Project description:ObjectivesTo present software for automated adipose tissue quantification of abdominal magnetic resonance imaging (MRI) data using fully convolutional networks (FCN) and to evaluate its overall performance-accuracy, reliability, processing effort, and time-in comparison with an interactive reference method.Materials and methodsSingle-center data of patients with obesity were analyzed retrospectively with institutional review board approval. Ground truth for subcutaneous (SAT) and visceral adipose tissue (VAT) segmentation was provided by semiautomated region-of-interest (ROI) histogram thresholding of 331 full abdominal image series. Automated analyses were implemented using UNet-based FCN architectures and data augmentation techniques. Cross-validation was performed on hold-out data using standard similarity and error measures.ResultsThe FCN models reached Dice coefficients of up to 0.954 for SAT and 0.889 for VAT segmentation during cross-validation. Volumetric SAT (VAT) assessment resulted in a Pearson correlation coefficient of 0.999 (0.997), relative bias of 0.7% (0.8%), and standard deviation of 1.2% (3.1%). Intraclass correlation (coefficient of variation) within the same cohort was 0.999 (1.4%) for SAT and 0.996 (3.1%) for VAT.ConclusionThe presented methods for automated adipose-tissue quantification showed substantial improvements over common semiautomated approaches (no reader dependence, less effort) and thus provide a promising option for adipose tissue quantification.Clinical relevance statementDeep learning techniques will likely enable image-based body composition analyses on a routine basis. The presented fully convolutional network models are well suited for full abdominopelvic adipose tissue quantification in patients with obesity.Key points• This work compared the performance of different deep-learning approaches for adipose tissue quantification in patients with obesity. • Supervised deep learning-based methods using fully convolutional networks were suited best. • Measures of accuracy were equal to or better than the operator-driven approach.

Project description:AimTo provide a comprehensive overview on emerging direct and alternative methods for intra-abdominal pressure (IAP) measurement techniques.MethodsThis was a scoping review study following Arksey and Malley's framework. The PubMed, EMBASE, Web of Science, EBSCO, Scopus and ProQuest databases were searched, and we only considered studies published from 2000 as we have extended the data from two previous reviews. Original studies that reported on the development, feasibility and credibility of IAP measurement techniques were included.ResultsForty-two of 9954 screened articles were included. IAP measurement techniques include three major categories: direct, indirect and less invasive measurement techniques. Agreement analyses were performed in most studies, and some explored the safety, time expenditure and reproducibility of IAP measurement techniques.ConclusionsClinical data assessing the validation of new IAP measurement techniques or the reliability of established measurement techniques remain lacking. Considering the cost and invasiveness, direct measurement is not recommended as a routine method for IAP measurement and should be preserved for critically ill patients where standard techniques are contraindicated or could be inaccurate. The measurement accuracy, reliability and sensitivity of the transrectal and transfemoral vein methods remain insufficient and cannot be recommended as surrogate IAP measures. Transvesical measurement is the most widely used method, which is the potentially most easy applicable technique and can be used as a reliable method for continuous and intermittent IAP measurement. Wireless transvaginal method facilitates the quantitative IAP measurement during exercise and activity, which laying the foundations for monitoring IAP outside of the clinic environment, but the accuracy of this technique in measuring absolute IAP cannot be determined at present. Less invasive technology will become a new trend to measure IAP and has substantial potential to replace traditional IAP measurement technologies, but further validation and standardization are still needed. Medical professionals should choose appropriate measurement tools based on the advantages and disadvantages of each IAP technique in combination with assessing specific clinical situations.

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Dataset Information

Development of a patient-report pressure algometer for the quantification of abdominal examination.

Background

Methods

Results

Conclusion

Publications

Development of a patient-report pressure algometer for the quantification of abdominal examination.

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