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Home  >  Medical Research Archives  >  Issue 149  > Newer Perspectives in Anesthesiology: A Philatelic Based Review
Published in the Medical Research Archives
Jun 2023 Issue

Newer Perspectives in Anesthesiology: A Philatelic Based Review

Published on Jun 26, 2023




Over the past decade, the practice of anesthesiology had become inextricably dependent upon technology. Anesthetics were first discovered, then made increasingly safe, and now, more precise and efficient, all due to tremendous advances in monitoring and delivery technology. Telemedicine has revolutionized medicine and preoperative evaluations and teaching are being done via teleconference and zoom meetings. Patient monitoring has become noninvasive, and closed-loop anesthesia delivery systems are making anesthetic administration very precise and safe. Next-generation technology and innovations will eliminate human errors entirely.

Author info

Chandrasekhar Krishnamurti, Zohra Mehdi, Vijayalakshmi Chandrasekhar


The scope of anesthesia practice has seen a considerable expansion over the past two decades and it has become inextricably dependent upon monitoring and delivery technology. The scope of anesthesia practice has expanded globally, providing anesthesiologists with unique new technological tools to ensure a precise and safer care of surgical patients.


In the 1960s and 1970s, the death related to anesthesia was one in every 10,000 to 20,000 patients. Now, with technological advances, it is in the range of one in every 200,000 patients. Deaths and adverse outcomes continue to decrease significantly due to comprehensive and continuous monitoring and improved vigilance, education, and training. 1,2


Improved image quality as well a significant reduction in price, with handheld devices with intuitive interfaces and AI integration has led to the point-of-care use of ultrasonography to acquire and interpret all images in real time. (Fig 1) This has enabled better and early diagnosis of patient status and rapid, and goal-oriented therapy for better outcome. Bedside lung ultrasound in emergency protocol, fluid administration limited by lung sonography, fast focused assessment with sonography for trauma have facilitated precise and evidence-based patient treatment. 3,4,5,6

Fig 1: Imaging and Point of Care Diagnosis and Treatment


Telemedicine has resulted in a sea change in outpatient medicine and perioperative management. (Fig 2) Preoperative evaluations are now done via teleconferencing and comprehensive patient health data is available at the click of a mouse

Fig 2: Telemedicine : Remote global medicare


Automation applied to the administration of closed-loop anesthesia delivery, artificial intelligence (AI) and machine learning (ML) have transformed the future of health care. All phases of perioperative care from accurate risk prediction to operating room organization has been impacted to improve cost-effectivity, quality care and better outcomes. (Fig 3, 4) Drug designing and development was hampered by complex and huge data from genomics, proteomics, microarray data, and clinical trials. Deep learning (DL) algorithms based on deep, convolutional (CNN), recurrent (RNN) neural and deep auto-encoder (DAEN) networks has facilitated newer drug discovery. Artificial intelligence applied to monitoring drug release, pre-clinical and clinical development, primary and secondary drug screening, biomarker development, pharmaceutical manufacturing, bioactivity identification and physiochemical properties, prediction of toxicity, and identification of mode of action will result in newer, more efficacious and less toxic drugs in the near future. 10,11,12,13,14

Fig 3 & 4: Automation and Artificial Intelligence Application in Medicare


Zoom video conferencing has made person-to- person communication involving anesthesiologists possible through the Covid-19 pandemic. (Fig 5, 6) Almost all anesthesiology related continuing medical education (CME) is being effectively conducted through these newer portals. 15,16

Fig 5 & 6: Zoom learning – the revolution in knowledge updates


Target-controlled infusion (TCI) pumps and depth of anaesthesia monitors have made total intravenous anesthesia (TIVA) easy, safe, and precise. The rapid pharmacokinetics and pharmacodynamics characteristics of newer short acting intravenous designer drugs like ciprofol, remimazolam, remifentanil, dexmedetomidine, and cisatracurium has resulted in good quality of recovery and discharge. These drugs are painless on intravenous injection, and provide better haemodynamic stability and good quality of recovery and early discharge from hospital. 17,18,19 These newer techniques will make anesthesia administration in adverse environments like at depths, high altitude and aerospace precise and safe. (Fig 7)

Fig 7: Underwater, High Altitude And Aerospace Anesthetic challenges


Preliminary candidate gene studies suggest that susceptibility to adverse perioperative events is genetically determined. Biomarkers in perioperative medicine and critical care include prognosis, diagnosis, and monitoring of adverse outcomes, as well as informing and refining therapeutic decisions. (Fig 8) Patterns of human genome variation, gene regulation, basic population genetic methodology, gene and protein expression analysis, and evaluating dynamic genomic markers can evaluate and catalog organ-specific responses to surgical stress. This can assist with organ-protective strategies by better understanding of genetic control of anesthetic mechanisms and responses. Mutations in the ryanodine receptor gene, RYR1, are found in 50–70% of cases susceptible to malignant hyperthermia and statin induced myopathy. Genetic profiling of drug metabolizing enzymes, carrier proteins, and receptors, using molecular technologies will enable personalized choice of drugs and dosage regimens tailored to suit a patient\\\'s pharmacogenetic profile. In the future, an individual\\\'s pharmacological needs will be based on age, sex, and genomics. 20,21,22

Fig 8: Pharmacogenetics and Precision Medicine


Anesthesiology is at a crossroad with new models of care with increased utilization of technology. Expansion in telemedicine has enabled care for more patients in diverse settings and to better monitor patients remotely while ensuring immediate intervention as needed. Resident training needs constant upgrading to ensure continued competency and core training in the evolving technology to support patient and health system needs. 23


1. Mebangkopi E, Cole DJ, Cannesspn M. Progress ie Patient Safety in Anesthesia. JAMA 2020;324(24):2485-2486

2. taw RC, Cohen NH. The future of anesthesiology: implications of the changing healthcare environment. Current Opinion in Anaesthesiology 2016; 29(2): 198-205

3. Ramsingh D, Yoriy. 5, Bronshtexa SH, Zimmerman J. Perioperative Point-of-Care Ultrasound: From Concept to Application. Anesthesiology 2020; 132: 908-916

4. Moore CL, Copej JA. Point-of-care ultrasonography. NFrigjJ Med 2011; 364: 749-57

5. Li L, Yong RJ, Kaye AD, Liman RD. Perioperative Point of Care Ultrasound (POCUS) for Anesthesiologists: an Overview. Qic Pain Headache Rep 2020 Mar 21;24(5):20

6. Heinz ER., Vincent, A Point-of-Care Ultrasound for the Trauma Anesthesiologist SAW AnesthesioiRep 207212:Z1Z-225.

7. Kmiec N, Jain L. Tel em edicin e: A Digital Interface for Perioperative Anesthetic Care. 811011180)g2020;130(2):272-275

8. Jacob AK, Belch LM, p, aj SL. admit in Anesthesia. Aifr40estb 2021 39:259-268.

9. Schoen DC, Prater K. Role of TAlehPalthin Pre-anesthetic Evaluations. AANA J 2019;87(1):43-49

10. Hashimoto DA, Witkovaki,E, fag, L Meireles 0, &snail G. Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations. Anesthesiology 2020;132(2):379-394

11. Gupta R, Via, D, atm M, Debt S, Am haeta RK, Kumar P. Artificial intelligence to deep learning: machine intelligence approach for drug discovery. &LQJ Divers 2021;25(3):1315-1360

12. Jimenez-Luna J, Grisoni, F, Weskamp N, Schneider G. Artificial intelligence in drug discovery: recent advances and future perspectives. Expert Qpia Drug away 2021;16(9):949-959
13. JingY,thepY, Hu Z, Wang L,2c.i.eXQ. Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era. AAPS J 2018; 20(3):58.

14. Nag 5,15.534ta ATK, MandaLA, Mathew AT, Das B, Devi B, Kumar R. Deep learning tools for advancing drug discovery and development. 3 Bidech,2022J2(5):110.

15. ande( B, So el berg J, Osborne-Smith L. Distance Ed ucation inAnesthesia Using Scr een-Based Simulation - A Brief Integrative Review. Asly. Med Um End 2020;11:563- 567

16. Bergmans E Meteirriann C, Metekriann B, altisam ML, von Au F, Thin KC. Technology-enhanced learning in anesthesiology and emergency medicine: A new approach to medical school teaching in the wake of the pandemic. Anaesthasialogig 2022:11(6):444- 451.

17. Anderson BJ,Bagshaw  0. Practicalities of total intravenous anesthesia and target controlled infusion in children. Anesthesiology 2019; 131(1):164-185 18. Wingert T, Lee C, Capaessen, M. Machine Learning, Deep learning and Closed Loop Devices-Anesthesia Delivery. Ariestitesiolgia 2021;39(3):565-581

19. Baja SJS, Stalin V, Sucekha Set al. Recent advancements in total intravenous an aesthesia and anaesthetic. pharmacology. Indian Journal of Anaesthesia 2023; 67(1): 56-62

20. a agii Leo HDJ. Sex, age, and genetics in anesthesia. Current Opinion in Anasthesiatogy, 2008;21(4): 462-466

21. Ashley EA, Butte AJ, Wheeler MT, et al. Clinical assessment incorporating a personal  genome. Lancet 2010; 375:1525-1535.

22. Eeerp WG, cautimachez AE, Collins FS. Genomic medicine—an updated primer. N fag J Med2010;362:2001-2011 23. Bridges KH, McSwairiJR, Wilson PR. To Infinity and Beyond: The Past, Present, and Future of Tele-Anesthesia. efipedvaTheig 2020 aall(2):276-284. 

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