Diagnostic accuracy of mercury versus digital blood pressure measuring devices: a systematic review and meta-analysis

This systematic review was conducted based on the Preferred Reporting Items for a Systematic Review and Meta-Analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA)9 (Additional annex). The protocol of this systematic review has been registered on PROSPERO, the international prospective register of systematic reviews (registration number CRD42019118822).

Sources of information

A comprehensive literature search was undertaken in search engines which included PubMed, Cochrane, EBSCO, EMBASE and Google Scholar.

Search Strategy

The search terms used to retrieve published information specifically for each database are provided in Supplementary Table A1. The number of articles obtained and further filtering according to the eligibility criteria are provided in Table A1.

PICO-elements

PICO

The PICO criteria for the systematic review are shown in Supplementary Table A2.

Population

Studies performed in the over 18 age group.

Intervention trial

Digital blood pressure monitoring devices.

Comparator test

A mercury sphygmomanometer was used manually.

Results

The sensitivity and specificity of digital and mercury sphygmomanometer-based blood pressure measurements.

Eligibility criteria

Types of studies

Cross-sectional and observational cohort studies assessing the diagnostic accuracy of blood pressure measured by mercury sphygmomanometer and digital devices.

Language and period

Journal articles published in English between January 1, 2000 and April 3, 2021 with full-text accessibility were included.

Reference standard

A mercury sphygmomanometer was used as a reference standard.

Exclusion criteria

Diagnostic accuracy studies that considered digital blood pressure monitoring devices using a standard mercury-free sphygmomanometer as a comparator, and studies in children, special populations, and specific disease groups were excluded.

Study selection process

Studies were reviewed individually by two reviewers, and any discrepancies raised in the selection process were resolved with the third reviewer. Duplicates were removed from shortlisted studies after title and abstract selection. A full selection of articles was performed for the pre-selected studies. Studies that did not meet the selection criteria did not have relevant information for inclusion and required data were excluded. The remaining eligible studies were included in the review.

Quality and risk assessment

The quality of the included studies was assessed using the QUADAS-2 questionnaire (Table A3 in supplement)ten, a standard tool used for quality assessment of diagnostic accuracy studies. This questionnaire measures risk of bias and applicability issues.

Index test and standard

The index test studied was a digital blood pressure monitor, which is a cuff-based device used to measure blood pressure by oneself or by trained personnel. The cutoff used for hypertension or high blood pressure was ≥140 for systolic blood pressure and ≥90 for diastolic blood pressure or as defined by the included studies. A mercury sphygmomanometer was the gold standard test used.

Data Extraction

Data were extracted from included studies using the data extraction form. We collected information on the screening instrument used, the reference standard employed, indices of diagnostic accuracy, statistical and methodological considerations. Data on study characteristics such as year, setting, population, design, comparator, and sample size were also collected.

Data synthesis and analysis

The data collected was entered into the Microsoft Excel spreadsheet. We qualitatively described the characteristics of the studies included in the review. Diagnostic accuracy indices, including true positive, true negative, false positive, false negative, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, sensitivity, and specificity were calculated. The diagnostic odds ratio (DOR) and the 95% confidence interval were estimated. For quantitative meta-analysis, RevMan (version 5.4) and R studio software were used. A forest plot was used to represent pooled estimates for DOR, sensitivity, and specificity. The heterogeneity of the included studies was also assessed by the I2 statistics for all the parameters evaluated.

About Mark A. Tomlin

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