Sustainability through digital transformation is essential for contemporary businesses. Embracing sustainability, micro-, small-, and medium-sized enterprises (MSMEs) can gain a competitive advantage, attracting customers and investors who share these values. Moreover, incorporating sustainable practices empowers MSMEs to drive innovation, reduce costs, and enhance their reputation. This study aims to identify how owners or senior managers of MSMEs can initiate a sustainable digital transformation project. A systematic literature review was carried out, including 59 publications from 2019 to 2023. As a result, this research identifies the first steps owners of MSMEs can take to begin the transition by identifying critical organizational capabilities necessary for successful transformation, explores the technologies that can support MSMEs in their sustainability goals, and emphasizes the significance of stakeholders in achieving a successful digital transformation journey. Firstly, owners or senior managers should change the organizational culture to support decisions and strategies focus on sustainability. Secondly, the leading role of stakeholders is in the innovation process that allows businesses to be more competitive locally and globally. Finally, big data is the technology that can provide the most significant benefit to MSMEs because it will enable analyzing data of all kinds and contributes disruptively to decision-making.

Background: Although 24‐hour blood pressure (BP) variability ( BPV ) is predictive of cardiovascular outcomes independent of absolute BP levels, it is not regularly assessed in clinical practice. One possible limitation to routine BPV assessment is the lack of standardized methods for accurately estimating 24‐hour BPV . We conducted a systematic review to assess the predictive power of reported BPV indexes to address appropriate quantification of 24‐hour BPV , including the average real variability ( ARV ) index. Methods and Results: Studies chosen for review were those that presented data for 24‐hour BPV in adults from meta‐analysis, longitudinal or cross‐sectional design, and examined BPV in terms of the following issues: (1) methods used to calculate and evaluate ARV ; (2) assessment of 24‐hour BPV determined using noninvasive ambulatory BP monitoring; (3) multivariate analysis adjusted for covariates, including some measure of BP; (4) association of 24‐hour BPV with subclinical organ damage; and (5) the predictive value of 24‐hour BPV on target organ damage and rate of cardiovascular events. Of the 19 assessed studies, 17 reported significant associations between high ARV and the presence and progression of subclinical organ damage, as well as the incidence of hard end points, such as cardiovascular events. In all these cases, ARV remained a significant independent predictor ( P <0.05) after adjustment for BP and other clinical factors. In addition, increased ARV in systolic BP was associated with risk of all cardiovascular events (hazard ratio, 1.18; 95% confidence interval, 1.09–1.27). Only 2 cross‐sectional studies did not find that high ARV was a significant risk factor. Conclusions: Current evidence suggests that ARV index adds significant prognostic information to 24‐hour ambulatory BP monitoring and is a useful approach for studying the clinical value of BPV .

Outcome-driven recommendations about time intervals during which ambulatory blood pressure should be measured to diagnose white-coat or masked hypertension are lacking. We cross-classified 8237 untreated participants (mean age, 50.7 years; 48.4% women) enrolled in 12 population studies, using ≥140/≥90, ≥130/≥80, ≥135/≥85, and ≥120/≥70 mm Hg as hypertension thresholds for conventional, 24-hour, daytime, and nighttime blood pressure. White-coat hypertension was hypertension on conventional measurement with ambulatory normotension, the opposite condition being masked hypertension. Intervals used for classification of participants were daytime, nighttime, and 24 hours, first considered separately, and next combined as 24 hours plus daytime or plus nighttime, or plus both. Depending on time intervals chosen, white-coat and masked hypertension frequencies ranged from 6.3% to 12.5% and from 9.7% to 19.6%, respectively. During 91 046 person-years, 729 participants experienced a cardiovascular event. In multivariable analyses with normotension during all intervals of the day as reference, hazard ratios associated with white-coat hypertension progressively weakened considering daytime only (1.38; P =0.033), nighttime only (1.43; P =0.0074), 24 hours only (1.21; P =0.20), 24 hours plus daytime (1.24; P =0.18), 24 hours plus nighttime (1.15; P =0.39), and 24 hours plus daytime and nighttime (1.16; P =0.41). The hazard ratios comparing masked hypertension with normotension were all significant ( P <0.0001), ranging from 1.76 to 2.03. In conclusion, identification of truly low-risk white-coat hypertension requires setting thresholds simultaneously to 24 hours, daytime, and nighttime blood pressure. Although any time interval suffices to diagnose masked hypertension, as proposed in current guidelines, full 24-hour recordings remain standard in clinical practice.

This study presents a sustainable digital transformation framework to integrate sustainable practices into digital transformation initiatives within Small and Medium Enterprises (SMEs). The methodology includes a literature review, a framework creation, and a case study with passive participation. The framework was structured to help industries implement responsible digitalization initiatives in five key stages: setting objectives, fostering stakeholder-focused engagement, defining sustainable objectives and dimensions, creating a sustainable model, and executing the project. Validating the proposal in the context of an SME allowed us to discern the tangible benefits of sustainability practices for the organization, further reinforcing the relevance and applicability of the framework. In conclusion, this research offers valuable information for SMEs considering starting a sustainable digitalization process.

Average real variability (ARV) is a recently proposed index for short-term blood pressure (BP) variability. We aimed to determine the minimum number of BP readings required to compute ARV without loss of prognostic information. ARV was calculated from a discovery dataset that included 24-hour ambulatory BP measurements for 1,254 residents (mean age = 56.6 years; 43.5% women) of Copenhagen, Denmark. Concordance between ARV from full (≥80 BP readings) and randomly reduced 24-hour BP recordings was examined, as was prognostic accuracy. A test dataset that included 5,353 subjects (mean age = 54.0 years; 45.6% women) with at least 48 BP measurements from 11 randomly recruited population cohorts was used to validate the results. In the discovery dataset, a minimum of 48 BP readings allowed an accurate assessment of the association between cardiovascular risk and ARV. In the test dataset, over 10.2 years (median), 806 participants died (335 cardiovascular deaths, 206 cardiac deaths) and 696 experienced a major fatal or nonfatal cardiovascular event. Standardized multivariable-adjusted hazard ratios (HRs) were computed for associations between outcome and BP variability. Higher diastolic ARV in 24-hour ambulatory BP recordings predicted (P < 0.01) total (HR = 1.12), cardiovascular (HR = 1.19), and cardiac (HR = 1.19) mortality and fatal combined with nonfatal cerebrovascular events (HR = 1.16). Higher systolic ARV in 24-hour ambulatory BP recordings predicted (P < 0.01) total (HR = 1.12), cardiovascular (HR = 1.17), and cardiac (HR = 1.24) mortality. Forty-eight BP readings over 24 hours were observed to be adequate to compute ARV without meaningful loss of prognostic information.