Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Going Electric: Expert Survey on the Future of Battery Technologies for Electric Vehicles

The paper describes the results of a survey, carried out with leading EU experts, on the capacity of both fully electric and plug-in hybrid vehicles to reach commercial success in the next twenty years. The success of electric transport is hampered by a combination of low range, scarce efficiency and high costs of batteries. Costs are expected to decrease in response to increasing sales volume and technical improvements, and advances would result from adequate investments in research, development and demonstration (RD&D). Experts' judgements are collected to shed light on the inherently uncertain relationship between RD&D efforts and consequent technical progress, and to assess the complex dynamics that will hinder or support the widespread diffusion of electric vehicles. The analysis of the experts' data results in a number of important policy recommendations to guide future RD&D choices and target commitments both for the EU and its member states

A genetic algorithm for the design of job rotation schedules considering ergonomic and competence criteria

Job rotation is an organizational strategy increasingly used in manufacturing systems as it provides benefits to both workers and management in an organization. Job rotation prevents musculoskeletal disorders, eliminates boredom and increases job satisfaction and morale. As a result, the company gains a skilled and motivated workforce, which leads to increases in productivity, employee loyalty and decreases in employee turnover. A multi-criteria genetic algorithm is employed to generate job rotation schedules, with considering the most adequate employee-job assignments to prevent musculoskeletal disorders caused by accumulation of fatigue. The algorithm provides the best adequacy available between workers and the competences needed for performing the tasks. The design of the rotation schedules is based not only on ergonomic criteria but also on issues related to product quality and employee satisfaction. The model includes the workers' competences as a measure for the goodness of solutions. © 2011 Springer-Verlag.We thank the Universidad Politecnica de Valencia for its support of this research through its Research and Development Program 2009 and financing through the project PAID-06-09/2902. The Universidad Politecnica de Valencia has funded the translation of this work.Asensio Cuesta, S.; Diego Más, JA.; Canós Darós, L.; Andrés Romano, C. (2012). A genetic algorithm for the design of job rotation schedules considering ergonomic and competence criteria. International Journal of Advanced Manufacturing Technology. 60(9-12):1161-1174. doi:10.1007/s00170-011-3672-0S11611174609-12Podniece Z (2008) Work-related musculoskeletal disorders: prevention report. European Agency for Safety and Health at Work, BelgiumBernard B, Sauter S, Fine LJ, Petersen I, Hales T (1994) Job task and psychosocial risk factors for work-related musculoskeletal disorders among new paper employees. Scand J Work Environ Health 20:417–426Emodi T, Zhang WJ, Lang SYT, Bi ZM (2007) A framework for modeling and analysis of human repetitive operations in a production assembly line. International SAE Digital Human Modeling for Design and Engineering Conference And Exhibition, University District Seattle, Washington, USAHuang HJ (1999) Job rotation from the employees’ point of view. Res Hum R M 7:75–85Eriksson T, Ortega J (2006) The adoption of job rotation: testing the theories. Ind Labor Relat Rev 59:653–666Azizi N, Zolfaghari S, Liang M (2010) Modeling job rotation in manufacturing systems: the study of employee’s boredom and skill variations. Int J Prod Econ 123:69–85Cunningham BJ, Eberle T (1990) A guide to job enrichment and redesign. Personnel 67:56–61Rissen D, Melin B, Sandsjö L, Dohns I, Lundberg U (2002) Psychophysiological stress reactions, trapezius muscle activity, and neck and shoulder pain among female cashiers before and after introduction of job rotation. Work Stress 16:127–137Jonsson B (1988) Electromyographic studies of job rotation. Scand J Work Environ Health 14:108–109Hazzard L, Mautz J, Wrightsman D (1992) Job rotation cuts cumulative trauma cases. Personnel 71:29–32Papadimitriou CH, Steiglitz K (1982) Combinatorial optimization: algorithms and complexity. Dover, New YorkCarnahan BJ, Redfern MS, Norman B (2000) Designing safe job rotation schedules using optimization and heuristic search. Ergonomics 43:543–560Tharmmaphornphilas W, Norman B (2004) A quantitative method for determining proper job rotation intervals. Ann Oper Res 128:251–266Yaoyuenyong S, Nanthavanij S (2006) Hybrid procedure to determine optimal workforce without noise hazard exposure. Comput Ind Eng 51:743–764Costa AM, Miralles C (2009) Job rotation in assembly lines employing disabled workers. Int J Prod Econ 120:625–632Aryanezhad MB, Kheirkhah V, Deljoo V, Mirzapour Al-e-hashem SMJ (2009) Designing safe job rotation schedules based upon workers skills. Int J Adv Manuf Technol 41:193–199Tharmmaphornphilas W, Norman BA (2007) A methodology to create robust job rotation schedules. Ann Oper Res 155:339–360Nanthavanij S, Kullpattaranirun T (2001) A genetic algorithm approach to determine minimax work assignments. Int J Ind Eng Theor 8:176–185Kullpattaranirun T, Nanthavanij S (2005) A heuristic genetic algorithm for solving complex safety-based work assignment problems. Int J Ind Eng Theor 12:45–57Diego-Mas JA, Asensio-Cuesta S, Sanchez-Romero MA, Artacho-Ramirez MA (2009) A multi-criteria genetic algorithm for the generation of job rotation schedules. Int J Ind Ergon 39:23–33Seçkiner SU, Kurt M (2007) A simulated annealing approach to the solution of job rotation scheduling problems. Appl Math Comput 188:31–45Seçkiner SU, Kurt M (2008) Ant colony optimization for the job rotation scheduling problem. Appl Math Comput 201:149–160Spencer L, Spencer S (1993) Competence at work: models for superior performance. Wiley, New YorkAshkanasy NM, Hartel CEJ, Daus CS (2002) Diversity and emotion: the new frontiers in organizational behavior and research. J Manag 28:307–338Triggs DD, King PM (2000) Job rotation: an administrative strategy for hazard control. Prof Saf 45:32–34Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor, MichiganEmodi T, Zhang WJ (2008) Injury analysis in assembly and production lines: a state of the art review. Int J Ergon Hum Factors 30:11–38Glover F (1986) Future paths for integer programming and links to artificial intelligence. Comput Oper Res 13:533–549Chambers LD (1995) Practical handbook of genetic algorithms: new frontiers, 1st edn. CRC, Boca Raton, FloridaChambers LD (1998) Practical handbook of genetic algorithms: complex coding system, 1st edn. CRC, Boca Raton, FloridaChambers LD (2000) Practical handbook of genetic algorithms: applications, 2nd edn. CRC, Boca Raton, FloridaDavis L (1991) Handbook of genetic algorithms. Van Nostrand Reinhold, New YorkGoldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison-Wesley, MassachusettsRodgers SH (1986) Ergonomic design for people at work. Van Nostrand Reinhold, New YorkRodgers SH (1992) A functional job analysis technique. Occup Med State Art 7:679–711Waters TR, Putz-Anderson V, Garg A, Fine LJ (1993) Revised NIOSH equation for the design and evaluation of manual lifting tasks. Ergonomics 7:749–776McAtamney L, Corlett EN (1993) RULA: A survey method for the investigation of work-related upper limb disorders. Appl Ergon 24:91–9