The Impact of Hidradenitis Suppurativa on Work Productivity and Performance: a Systematic Review and Meta-Analysis.

BACKGROUND: Hidradenitis suppurativa (HS) is a chronic inflammatory skin disorder affecting the skinfold regions. There is growing appreciation of the need for socioeconomic factors to be included in multidisciplinary assessments of HS. However, knowledge regarding HS and workplace function is limited. OBJECTIVES: To assess the relationship between HS and workplace function. METHODS: Cinahl, Embase, MedLine, PsycInfo and PubMed were systematically searched to collect data from studies in which validated surveys of workplace function were administered to HS patients. RESULTS: Out of 1,932 publications, twelve studies were included in this review and seven reported sufficient data for meta-analysis. Included studies encompassed 5,187 HS patients and no controls. All studies employed the Work Productivity and Activity Impairment questionnaire, reporting percentage scores for absenteeism, presenteeism, total work productivity impairment (TWPI) and total activity impairment (TAI). Pooled mean scores for HS were calculated as 10.17% (95%CI 8.68-11.66) for absenteeism, 31.13% (95%CI 25.02-37.23) for presenteeism, 34.25% (95%CI 29.37-39.14) for TWPI, and 42.23% (95%CI 38.56-45.89) for TAI. Significant heterogeneity was identified and most studies were of 'poor' to 'fair' quality. CONCLUSIONS: Current evidence suggests considerable impairment of workplace functioning in HS patients. Our findings point to a significant unmet treatment need with respect to improving working capability in HS. The extant literature is inadequate to reliably assess the mechanisms underlying this effect or to comparatively assess the capabilities of HS therapies to improve workplace function.

The Risk of Meningitis After Cochlear Implantation: A Systematic Review and Meta-Analysis.

OBJECTIVE: This study aims to estimate the rate of postoperative meningitis (both immediate and long-term) in patients following cochlear implants (CIs). It aims to do so through a systematic review and meta-analysis of published studies tracking complications after CIs. DATA SOURCES: MEDLINE, Embase, and Cochrane Library. REVIEW METHODS: This review was performed in line with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Studies tracking complications following CIs in patients were included. Exclusion criteria included non-English language studies and case series reporting <10 patients. Bias risk was evaluated using the Newcastle-Ottawa Scale. Meta-analysis was performed through DerSimonian and Laird random-effects models. RESULTS: A total of 116/1931 studies met the inclusion criteria and were included in the meta-analysis. Overall, there were 112 cases of meningitis in 58,940 patients after CIs. Meta-analysis estimated an overall rate of postoperative meningitis of 0.07% (95% confidence interval [CIs], 0.03%-0.1%; I2 = 55%). Subgroup meta-analysis showed this rate had 95% CIs crossing 0% in implanted patients who received the pneumococcal vaccine, antibiotic prophylaxis, those with postoperative acute otitis media (AOM), and those implanted less than 5 years. CONCLUSION: Meningitis is a rare complication following CIs. Our estimated rates of meningitis after CIs appear lower than prior estimates based on epidemiological studies in the early 2000s. However, the rate still appears higher than the baseline rate in the general population. The risk was very low in implanted patients who received the pneumococcal vaccine, antibiotic prophylaxis, received unilateral or bilateral implantations, developed AOM, those implanted with a round window or cochleostomy techniques, and those under 5 years.

Ethics Principles for Artificial Intelligence-Based Telemedicine for Public Health.

The use of artificial intelligence (AI) in the field of telemedicine has grown exponentially over the past decade, along with the adoption of AI-based telemedicine to support public health systems. Although AI-based telemedicine can open up novel opportunities for the delivery of clinical health and care and become a strong aid to public health systems worldwide, it also comes with ethical risks that should be detected, prevented, or mitigated for the responsible use of AI-based telemedicine in and for public health. However, despite the current proliferation of AI ethics frameworks, thus far, none have been developed for the design of AI-based telemedicine, especially for the adoption of AI-based telemedicine in and for public health. We aimed to fill this gap by mapping the most relevant AI ethics principles for AI-based telemedicine for public health and by showing the need to revise them via major ethical themes emerging from bioethics, medical ethics, and public health ethics toward the definition of a unified set of 6 AI ethics principles for the implementation of AI-based telemedicine. (Am J Public Health. 2023;113(5):577-584. https://doi.org/10.2105/AJPH.2023.307225).