Innovative Diagnostic and Therapeutic Methods in Clinical Medicine: A Systematic Review
DOI:
https://doi.org/10.57125/FEM.2026.03.30.01Keywords:
Innovative diagnostics, AI in medicine, precision medicine, telemedicine.Abstract
Aims: Clinical medicine has evolved rapidly since the COVID-19 pandemic owing to accelerated development of innovative diagnostic and therapeutic technologies. Despite substantial progress, most existing studies focus on isolated technologies rather than integrated systems. This systematic review aimed to synthesise recent evidence on emerging innovations in diagnosis and treatment, assess their clinical effectiveness and safety, and identify implementation barriers affecting real-world adoption.
Study design: Systematic review conducted in accordance with PRISMA 2020 guidelines.
Methodology: Five major databases (PubMed, Scopus, Web of Science, Google Scholar, and the Cochrane Library) were searched for studies published between January 2020 and December 2025. Eligible publications included randomised controlled trials, cohort studies, diagnostic accuracy studies, systematic reviews, and implementation research evaluating innovative diagnostic or therapeutic approaches in clinical settings. Preclinical studies, small case series, commentaries, and paediatric-only studies were excluded. Two reviewers independently screened 4,580 titles and abstracts and assessed 210 full-text articles, resulting in 29 included studies. Data extraction encompassed study design, population characteristics, innovation type, clinical outcomes, and implementation factors.
Results: The included studies addressed AI-based diagnostic systems, molecular and immunotherapies, digital health tools, imaging techniques, CRISPR-based diagnostics, vaccines, and therapeutic management strategies. Vaccines and antibody-based interventions demonstrated highest effectiveness, followed by clinical therapies and telemedicine applications. AI-based diagnostic tools performed comparably to non-expert clinicians but remained inferior to specialist assessment. Digital health interventions improved outcomes in heart failure and diabetes management, while molecular and immunotherapies yielded inconsistent results. Implementation barriers included high costs, infrastructural constraints, limited digital literacy, and regulatory challenges.
Conclusion: Emerging innovations have enhanced diagnostic accuracy, treatment efficacy, and patient monitoring across clinical domains. Nevertheless, methodological heterogeneity and technology adoption limitations moderated overall effectiveness. These findings highlight the need for adaptive trial designs, implementation research, and equity-oriented deployment strategies to enable scalable integration of emerging technologies into routine clinical practice.
References
Giansanti D. The future of healthcare is digital: Unlocking the potential of mobile health and E-health solutions. Healthcare (Basel) 2025;13:802. https://doi.org/10.3390/healthcare13070802
Goswami N. A dual burden dilemma: Navigating the global impact of communicable and non-communicable diseases and the way forward. Int J Med Res 2024;1:29–41. https://doi.org/10.55489/ijmr.11202412
Abdullahi ZM, Kingsley OI, Yusuf M, Uwaka E.O, Otutu M, Nwose EU. Epidemiology, prevention and management of non-communicable diseases (NCDS): A review. Journal of Health, Wellness and Safety Research 2025. https://doi.org/10.70382/hujhwsr.v7i3.015
Morrison C, Rimpiläinen S, Bosnic I. Emerging trends in digital health and care : A refresh post-COVID. Digital Health & Care Institute; 2022. https://doi.org/10.17868/strath.00082203
Ogundiya O, Rahman TJ, Valnarov-Boulter I, Young TM. Looking back on digital medical education over the last 25 years and looking to the future: Narrative review. J Med Internet Res 2024;26:e60312. https://doi.org/10.2196/60312
Ogut E. Artificial intelligence in clinical medicine: Challenges across diagnostic imaging, clinical decision support, surgery, pathology, and drug discovery. Clin Pract 2025;15:169. https://doi.org/10.3390/clinpract15090169
Shafi S, Parwani AV. Artificial intelligence in diagnostic pathology. Diagn Pathol 2023;18:109. https://doi.org/10.1186/s13000-023-01375-z
Jamalinia M, Weiskirchen R. Advances in personalized medicine: translating genomic insights into targeted therapies for cancer treatment. Ann Transl Med 2025;13:18. https://doi.org/10.21037/atm-25-34
Rituraj, Pal RS, Wahlang J, Pal Y, Chaitanya M, Saxena S. Precision oncology: transforming cancer care through personalized medicine. Med Oncol 2025;42:246. https://doi.org/10.1007/s12032-025-02817-y
Afzal A, Abbasi MH, Ahmad S, Sheikh N, Khawar MB. Current trends in messenger RNA technology for cancer therapeutics. Biomater Res 2025;29:0178. https://doi.org/10.34133/bmr.0178
Rafii S, Mukherji D, Komaranchath AS, Khalil C, Iqbal F, Abdelwahab SI, et al. Advancing CAR T-cell therapy in solid tumors: Current landscape and future directions. Cancers (Basel) 2025;17:2898. https://doi.org/10.3390/cancers17172898
Simkhada D, Teo SHC, Deorkar N, Vemuri MC. Transfection technologies for next-generation therapies. J Clin Med 2025;14:5515. https://doi.org/10.3390/jcm14155515
Mbunge E, Muchemwa B, Jiyane S, Batani J. Sensors and healthcare 5.0: transformative shift in virtual care through emerging digital health technologies. Glob Health J 2021;5:169–77. https://doi.org/10.1016/j.glohj.2021.11.008
Petracca F, Ciani O, Cucciniello M, Tarricone R. Harnessing digital health technologies during and after the COVID-19 pandemic: Context matters. J Med Internet Res 2020;22:e21815. https://doi.org/10.2196/21815
Dagnino G, Kundrat D. Robot-assistive minimally invasive surgery: trends and future directions. Int J Intell Robot Appl 2024. https://doi.org/10.1007/s41315-024-00341-2
Yousif MG. Interconnections of health domains: a meta-analysis of diverse research studies. Med Adv Innov J. 2023; 1(1). Available from: https://www.isohe.org/wp-content/uploads/2023/07/Interconnections-of-Health-Domains-A-Meta-analysis-of-Diverse-Research-Studies.pdf
Mishra S, Jain K. Innovations in Healthcare: A systematic literature review. J Bus Res 2025;194:115364. https://doi.org/10.1016/j.jbusres.2025.115364
Thacharodi A, Singh P, Meenatchi R, Tawfeeq Ahmed ZH, Kumar RRS, V N, et al. Revolutionizing healthcare and medicine: The impact of modern technologies for a healthier future-A comprehensive review. Health Care Sci 2024;3:329–49. https://doi.org/10.1002/hcs2.115
Soyege OS, Nwokedi CN, Tomoh BO, Mustapha SY, Mbata AO, Balogun OD, et al. Comprehensive review of healthcare innovations in enhancing patient outcomes through advanced pharmacy practices. Int J Sci Res Sci Eng Technol 2024;11:425–37. https://doi.org/10.32628/ijserset242434
Alex C, Bridget W, Idowu B. Redefining healthcare innovation: cross-cutting advances in antimicrobial resistance, cancer prognosis, and critical care outcomes. https://shorturl.at/T9MEb
Ali A, Alghamdi M, Marzuki SS, Tengku Din TADAA, Yamin MS, Alrashidi M, et al. Exploring AI approaches for breast cancer detection and diagnosis: A review article. Breast Cancer (Dove Med Press) 2025;17:927–47. https://doi.org/10.2147/BCTT.S550307
Xu N, Yang D, Arikawa K, Bai C. Application of artificial intelligence in modern medicine. Clin eHealth 2023;6:130–7. https://doi.org/10.1016/j.ceh.2023.09.001
Battazza A, Brasileiro FC da S, Tasaka AC, Bulla C, Ximenes PP, Hosomi JE, et al. Integrating telepathology and digital pathology with artificial intelligence: An inevitable future. Vet World 2024;17:1667–71. https://doi.org/10.14202/vetworld.2024.1667-1671
Katsoulakis E, Wang Q, Wu H, Shahriyari L, Fletcher R, Liu J, et al. Digital twins for health: a scoping review. NPJ Digit Med 2024;7:77. https://doi.org/10.1038/s41746-024-01073-0
Chen Y, Huang A, Bi Y, Wei W, Huang Y, Ye Y. Genomic insights and prognostic significance of novel biomarkers in pancreatic ductal adenocarcinoma: A comprehensive analysis. Biochem Biophys Rep 2024;37:101580. https://doi.org/10.1016/j.bbrep.2023.101580
Horgan D, Van den Bulcke M, Malapelle U, Normanno N, Capoluongo ED, Prelaj A, et al. Aligning cancer research priorities in Europe with recommendations for conquering cancer: A comprehensive analysis. Healthcare (Basel) 2024;12:259. https://doi.org/10.3390/healthcare12020259
Mumtaz H, Saqib M, Jabeen S, Muneeb M, Mughal W, Sohail H, et al. Exploring alternative approaches to precision medicine through genomics and artificial intelligence - a systematic review. Front Med (Lausanne) 2023;10:1227168. https://doi.org/10.3389/fmed.2023.1227168
Chafai N, Bonizzi L, Botti S, Badaoui B. Emerging applications of machine learning in genomic medicine and healthcare. Crit Rev Clin Lab Sci 2024;61:140–63. https://doi.org/10.1080/10408363.2023.2259466
Juhasz G, Gecse K, Baksa D. Towards precision medicine in migraine: Recent therapeutic advances and potential biomarkers to understand heterogeneity and treatment response. Pharmacol Ther 2023;250:108523. https://doi.org/10.1016/j.pharmthera.2023.108523
Xiong M, Chen Z, Tian J, Peng Y, Song D, Zhang L, et al. Exosomes derived from programmed cell death: mechanism and biological significance. Cell Commun Signal 2024;22:156. https://doi.org/10.1186/s12964-024-01521-0
Stamate E, Piraianu A-I, Ciobotaru OR, Crassas R, Duca O, Fulga A, et al. Revolutionizing cardiology through artificial intelligence-big data from proactive prevention to precise diagnostics and cutting-edge treatment-A comprehensive review of the past 5 years. Diagnostics (Basel) 2024;14:1103. https://doi.org/10.3390/diagnostics14111103
Corral-Acero J, Margara F, Marciniak M, Rodero C, Loncaric F, Feng Y, et al. The “Digital Twin” to enable the vision of precision cardiology. Eur Heart J 2020;41:4556–64. https://doi.org/10.1093/eurheartj/ehaa159
Huang Y, Ni Z, Lu Z, He X, Hu J, Li B, et al. Heterogeneous temporal representation for diabetic blood glucose prediction. Front Physiol 2023;14:1225638. https://doi.org/10.3389/fphys.2023.1225638
Wu M, Du X, Gu R, Wei J. Artificial intelligence for clinical decision support in sepsis. Front Med (Lausanne) 2021;8:665464. https://doi.org/10.3389/fmed.2021.665464
Bode C, Weis S, Sauer A, Wendel-Garcia P, David S. Targeting the host response in sepsis: current approaches and future evidence. Crit Care 2023;27:478. https://doi.org/10.1186/s13054-023-04762-6
Vardas PE, Asselbergs FW, van Smeden M, Friedman P. The year in cardiovascular medicine 2021: digital health and innovation. Eur Heart J 2022;43:271–9. https://doi.org/10.1093/eurheartj/ehab874
Meister S, Deiters W, Becker S. Digital health and digital biomarkers – enabling value chains on health data. Curr Dir Biomed Eng 2016;2:577–81. https://doi.org/10.1515/cdbme-2016-0128
Shah M, Zimmer R, Kollefrath M, Khandwalla R. Digital technologies in heart failure management. Curr Cardiovasc Risk Rep 2020;14. https://doi.org/10.1007/s12170-020-00643-7
Busnatu Ștefan S, Niculescu A-G, Bolocan A, Andronic O, Pantea Stoian AM, Scafa-Udriște A, et al. A review of digital health and biotelemetry: Modern approaches towards personalized medicine and remote health assessment. J Pers Med 2022;12:1656. https://doi.org/10.3390/jpm12101656
Sawyer-Morris G, Wilde JA, Molfenter T, Taxman F. Use of digital health and digital therapeutics to treat SUD in criminal justice settings: A review. Curr Addict Rep 2024;11:149–62. https://doi.org/10.1007/s40429-023-00523-1
Mancioppi G, Fiorini L, Timpano Sportiello M, Cavallo F. Novel technological solutions for assessment, treatment, and assistance in mild cognitive impairment. Front Neuroinform 2019;13:58. https://doi.org/10.3389/fninf.2019.00058
Romagnoli A, Ferrara F, Langella R, Zovi A. Healthcare systems and artificial Intelligence: Focus on challenges and the international regulatory framework. Pharm Res 2024;41:721–30. https://doi.org/10.1007/s11095-024-03685-3
Karalis VD. The integration of artificial intelligence into clinical practice. Applied Biosciences 2024;3:14–44. https://doi.org/10.3390/applbiosci3010002
Shandhi MMH, Dunn JP. AI in medicine: Where are we now and where are we going? Cell Rep Med 2022;3:100861. https://doi.org/10.1016/j.xcrm.2022.100861
Swartling Peterson S, Kobusingye O, Mayega R, Orem J, Waiswa P. A life-course multisectoral approach to precision health in LMICs. Nat Med 2024;30:1813–5. https://doi.org/10.1038/s41591-024-03108-1
Ngoma T, Adewole I, Ainsworth V, Chin D, Chin J, Elzawawy A, et al. Cancer control collaborations between China and African countries. Lancet Oncol 2024;25:e164–72. https://doi.org/10.1016/S1470-2045(23)00634-4
Chang A. The role of artificial intelligence in digital health. Health Informatics, Cham: Springer International Publishing; 2020, p. 71–81. https://doi.org/10.1007/978-3-030-12719-0_7
Fried AJ, Dorn SD, Leland WJ, Mullen E, Williams DM, Zaas AK, et al. Large language models in internal medicine residency: current use and attitudes among internal medicine residents. Discov Artif Intell 2024;4. https://doi.org/10.1007/s44163-024-00173-w
Cornelius C, Deffner T, Hill A, Rohlfes C, Ellner B, Klarmann S, et al. Arbeiten in der Schwangerschaft auf der Intensivstation. Med Klin Intensivmed Notfmed 2024;119:364–72. https://doi.org/10.1007/s00063-024-01122-2
Krittanawong C, Johnson KW, Rosenson RS, Wang Z, Aydar M, Baber U, et al. Deep learning for cardiovascular medicine: a practical primer. Eur Heart J 2019;40:2058–73. https://doi.org/10.1093/eurheartj/ehz056
Houssein EH, Saber E, Ali AA, Wazery YM. Integrating metaheuristics and artificial intelligence for healthcare: basics, challenging and future directions. Artif Intell Rev 2024;57. https://doi.org/10.1007/s10462-024-10822-2
Swartz MK. PRISMA 2020: An update. J Pediatr Health Care 2021;35:351. https://doi.org/10.1016/j.pedhc.2021.04.011
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. https://doi.org/10.1136/bmj.n71
Alatawi AD, Hetta HF, Ali MAS, Ramadan YN, Alaqyli AB, Alansari WK, et al. Diagnostic innovations to combat antibiotic resistance in critical care: Tools for targeted therapy and stewardship. Diagnostics (Basel) 2025;15:2244. https://doi.org/10.3390/diagnostics15172244
Takita H, Kabata D, Walston SL, Tatekawa H, Saito K, Tsujimoto Y, et al. A systematic review and meta-analysis of diagnostic performance comparison between generative AI and physicians. NPJ Digit Med 2025;8:175. https://doi.org/10.1038/s41746-025-01543-z
Zhang M, Liu C, Tu J, Tang M, Ashrafizadeh M, Nabavi N, et al. Advances in cancer immunotherapy: historical perspectives, current developments, and future directions. Mol Cancer 2025;24:136. https://doi.org/10.1186/s12943-025-02305-x
Wale A, Shaw H, Ayres T, Okolie C, Morgan H, Everitt J, et al. A rapid review exploring the effectiveness of artificial intelligence for cancer diagnosis. bioRxiv 2023. https://doi.org/10.1101/2023.11.09.23298257
Yun S, Comín-Colet J, Calero-Molina E, Hidalgo E, José-Bazán N, Cobo Marcos M, et al. Evaluation of mobile health technology combining telemonitoring and teleintervention versus usual care in vulnerable-phase heart failure management (HERMeS): a multicentre, randomised controlled trial. Lancet Digit Health 2025;7:100866. https://doi.org/10.1016/j.landig.2025.02.006
Pal P, Mateen MA, Pooja K, Rajadurai N, Gupta R, Tandan M, et al. Intestinal ultrasound in Crohn’s disease: A systematic review of its role in diagnosis, monitoring, and treatment response. World J Metaanal 2025;13. https://doi.org/10.13105/wjma.v13.i2.104080
Ross JM, Forté S, Soulières D. Emerging drugs for the treatment of sickle cell disease: a review of phase II/III trials. Expert Opin Emerg Drugs 2022;27:211–24. https://doi.org/10.1080/14728214.2022.2105835
Aftab M, Mehmood F, Zhang C, Nadeem A, Dong Z, Jiang Y, et al. AI in oncology. arXiv. 2025;arXiv:2501.15489
El Kheir DYM, Boumarah DN, Bukhamseen FM, Masoudi JH, Boubshait LA. The Saudi experience of health-related social media use: A scoping review. Saudi J Health Syst Res 2021;1:81–92. https://doi.org/10.1159/000516473
Sathianathen NJ, Pan HYC, Furrer M, Thomas B, Dundee P, Corcoran N, et al. Comparison of robotic vs open cystectomy: A systematic review. Bladder Cancer 2023;9:253–69. https://doi.org/10.3233/BLC-220065
Van Dat T, Binh V, Hoang TM, Tu VL, Luyen PD, Anh LTK. The effectiveness of telemedicine in the management of type 2 diabetes: A systematic review. SAGE Open Med 2024;12:20503121241271846. https://doi.org/10.1177/20503121241271846
Okada R, Furusawa A, Vermeer DW, Inagaki F, Wakiyama H, Kato T, et al. Near-infrared photoimmunotherapy targeting human-EGFR in a mouse tumor model simulating current and future clinical trials. EBioMedicine 2021;67:103345. https://doi.org/10.1016/j.ebiom.2021.103345
Chu L, McPhee R, Huang W, Bennett H, Pajon R, Nestorova B, et al. A preliminary report of a randomized controlled phase 2 trial of the safety and immunogenicity of mRNA-1273 SARS-CoV-2 vaccine. Vaccine 2021;39:2791–9. https://doi.org/10.1016/j.vaccine.2021.02.007
Toyoshima S, Sakamoto-Sasaki T, Kurosawa Y, Hayama K, Matsuda A, Watanabe Y, et al. miR103a-3p in extracellular vesicles from FcεRI-aggregated human mast cells enhances IL-5 production by group 2 innate lymphoid cells. J Allergy Clin Immunol 2021;147:1878–91. https://doi.org/10.1016/j.jaci.2021.01.002
Lewis KL, Turbitt E, Chan PA, Epps S, Biesecker BB, Erby LAH, et al. Engagement and return of results preferences among a primarily African American genomic sequencing research cohort. Am J Hum Genet 2021;108:894–902. https://doi.org/10.1016/j.ajhg.2021.04.002
Copin R, Baum A, Wloga E, Pascal KE, Giordano S, Fulton BO, et al. The monoclonal antibody combination REGEN-COV protects against SARS-CoV-2 mutational escape in preclinical and human studies. Cell 2021;184:3949-3961.e11. https://doi.org/10.1016/j.cell.2021.06.002
Frasca M, La Torre D, Pravettoni G, Cutica I. Explainable and interpretable artificial intelligence in medicine: a systematic bibliometric review. Discov Artif Intell 2024;4. https://doi.org/10.1007/s44163-024-00114-7
Akeel S, Almazrooa S, Ali SA, Alhindi NA, Alhamed S, Felemban OM, et al. Assessing Tele-oral medicine in Saudi Arabia: A cross-sectional study on specialists’ experiences and effectiveness in oral healthcare. Healthcare (Basel) 2023;11:3089. https://doi.org/10.3390/healthcare11233089
Wang Y, Liu S, Liu H, Li W, Lin F, Jiang L, et al. SARS-CoV-2 infection of the liver directly contributes to hepatic impairment in patients with COVID-19. J Hepatol 2020;73:807–16. https://doi.org/10.1016/j.jhep.2020.05.002
Shen L, Jhund PS, Anand IS, Bhatt AS, Desai AS, Maggioni AP, et al. Incidence and outcomes of pneumonia in patients with Heart Failure. J Am Coll Cardiol 2021;77:1961–73. https://doi.org/10.1016/j.jacc.2021.03.001
Fozouni P, Son S, Díaz de León Derby M, Knott GJ, Gray CN, D’Ambrosio MV, et al. Amplification-free detection of SARS-CoV-2 with CRISPR-Cas13a and mobile phone microscopy. Cell 2021;184:323-333.e9. https://doi.org/10.1016/j.cell.2020.12.001
RECOVERY Collaborative Group, Horby P, Lim WS, Emberson JR, Mafham M, Bell JL, et al. Dexamethasone in hospitalized patients with Covid-19. N Engl J Med 2021;384:693–704. https://doi.org/10.1056/NEJMoa2021436
Dong J, Geng Y, Lu D, Li B, Tian L, Lin D, et al. Clinical trials for artificial intelligence in cancer diagnosis: A cross-sectional study of registered trials in Clinicaltrials.gov. Front Oncol 2020;10:1629. https://doi.org/10.3389/fonc.2020.01629
Arellanes IC, Choe N, Solomon V, He X, Kavin B, Martinez AE, et al. Brain delivery of supplemental docosahexaenoic acid (DHA): A randomized placebo-controlled clinical trial. EBioMedicine 2020;59:102883. https://doi.org/10.1016/j.ebiom.2020.102883
Paull EO, Aytes A, Jones SJ, Subramaniam PS, Giorgi FM, Douglass EF, et al. A modular master regulator landscape controls cancer transcriptional identity. Cell 2021;184:334-351.e20. https://doi.org/10.1016/j.cell.2020.11.045
Gavriilidis P, Inston NG. Recipient and allograft survival following donation after circulatory death versus donation after brain death for renal transplantation: A systematic review and meta-analysis. Transplant Rev (Orlando) 2020;34:100563. https://doi.org/10.1016/j.trre.2020.100563
Hennessy M, Hamid M, Goggin C, Nay MO, Carrigan M, Mockler D, et al. Participation of older patients with advanced gastroesophageal cancer in clinical trials: A systematic review of age-restrictive inclusion criteria over the last 25 years. J Clin Oncol 2021;39:e24017–e24017. https://doi.org/10.1200/jco.2021.39.15_suppl.e24017
Bakhuis J, Kamp LM, Barbour N, Chappin ÉJL. Frameworks for multi-system innovation analysis from a sociotechnical perspective: A systematic literature review. Technol Forecast Soc Change 2024;201:123266. https://doi.org/10.1016/j.techfore.2024.123266
Jain S, Sikka G, Dhir R. A systematic literature review on pancreas segmentation from traditional to non-supervised techniques in abdominal medical images. Artif Intell Rev 2024;57. https://doi.org/10.1007/s10462-024-10966-1
Edison G. Transforming medical decision-making: A comprehensive review of AI’s impact on diagnostics and treatment. BULLET 2023;2:1121–33. Available from: https://journal.mediapublikasi.id/index.php/bullet/article/view/3490
Khalifa M, Albadawy M. AI in diagnostic imaging: Revolutionising accuracy and efficiency. Comput Methods Programs Biomed Update 2024;5:100146. https://doi.org/10.1016/j.cmpbup.2024.100146
Nebangwa DN, Shey RA, Shadrack DM, Shintouo CM, Yaah NE, Yengo BN, et al. Predictive immunoinformatics reveal promising safety and anti-onchocerciasis protective immune response profiles to vaccine candidates (Ov-RAL-2 and Ov-103) in anticipation of phase I clinical trials. PLoS One 2024;19:e0312315. https://doi.org/10.1371/journal.pone.0312315
Youssef EG, Elnesr K, Hanora A. In silico design of a multiepitope vaccine against intestinal pathogenic Escherichia coli based on the 2011 German O104:H4 outbreak strain using reverse vaccinology and an immunoinformatic approach. Diseases 2025;13:259. https://doi.org/10.3390/diseases13080259
Schwartz KA, Britton B. Use of telehealth to improve chronic disease management. N C Med J 2011;72:216–8. https://doi.org/10.18043/ncm.72.3.216.
Polisena J, Coyle D, Coyle K, McGill S. Home telehealth for chronic disease management: a systematic review and an analysis of economic evaluations. Int J Technol Assess Health Care 2009;25:339–49. https://doi.org/10.1017/S0266462309990201
Felker GM, Anstrom KJ, Adams KF, Ezekowitz JA, Fiuzat M, Houston-Miller N, et al. Effect of natriuretic peptide-guided therapy on hospitalization or cardiovascular mortality in high-risk patients with Heart Failure and reduced ejection fraction: A randomized clinical trial. JAMA 2017;318:713–20. https://doi.org/10.1001/jama.2017.10565
Felker GM, Pang PS, Adams KF, Cleland JGF, Cotter G, Dickstein K, et al. Clinical trials of pharmacological therapies in acute heart failure syndromes: lessons learned and directions forward: Lessons learned and directions forward. Circ Heart Fail 2010;3:314–25. https://doi.org/10.1161/CIRCHEARTFAILURE.109.893222
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
