{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T21:19:29Z","timestamp":1768598369432,"version":"3.49.0"},"reference-count":39,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Early identification of risks improves patient outcomes and overall health. The early identification of high-risk status helps in early medical attention and prevents complications. Understanding a patient\u2019s risk level enables better management of chronic conditions. Identifying high-risk patients is essential for the efficient allocation of healthcare resources. This approach focuses on predicting abnormalities by analysing the correlation between multiple vital signs. This review highlights body temperature, heart rate, respiratory rate, oxygen saturation, and blood pressure as important vital signs for determining a patient\u2019s risk level. A total of 180 articles were reviewed, of which 20 were selected for inclusion. This study focuses mainly on research conducted from 2016 to 2024. The identified studies focused on critical illnesses (4, 20\u202f%), cardiovascular diseases (4, 20\u202f%), chronic conditions (3, 15\u202f%), abnormalities (3, 15\u202f%), Coronavirus Disease 2019 (COVID-19) (2, 10\u202f%), mortality (2, 10\u202f%), falls (1, 5\u202f%), and hypertension (1, 5\u202f%). Most studies have focused on physiological parameters, such as oxygen saturation, blood pressure, heart rate, respiratory rate, and body temperature. The severity level of a patient can be determined and treated by monitoring these vital signs. Developments in wearable sensor technology have facilitated the continuous monitoring of vital signs and assisted healthcare professionals.<\/jats:p>","DOI":"10.1515\/jisys-2025-0120","type":"journal-article","created":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T11:15:53Z","timestamp":1768562153000},"source":"Crossref","is-referenced-by-count":0,"title":["Significance of essential vital signs for analysis of risk level of critical care patients\u00a0\u2013\u00a0a review"],"prefix":"10.1515","volume":"35","author":[{"given":"Savithri","family":"Prabhu","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering , Manipal Institute of Technology, Manipal Academy of Higher Education , Manipal , 576104 , India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9710-2289","authenticated-orcid":false,"given":"G. Muralidhar","family":"Bairy","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering , Manipal Institute of Technology, Manipal Academy of Higher Education , Manipal , 576104 , India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3345-360X","authenticated-orcid":false,"given":"Niranjana","family":"Sampathila","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering , Manipal Institute of Technology, Manipal Academy of Higher Education , Manipal , 576104 , India"}]}],"member":"374","published-online":{"date-parts":[[2026,1,16]]},"reference":[{"key":"2026011611154824877_j_jisys-2025-0120_ref_001","doi-asserted-by":"crossref","unstructured":"Y. Gu et al., \u201cPrediction of severe adverse event from vital signs for post-operative patients,\u201d in 2021 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Guadalajara, Mexico, IEEE, 2021, pp. 971\u2013974.","DOI":"10.1109\/EMBC46164.2021.9630918"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_002","doi-asserted-by":"crossref","unstructured":"A. Rhodes et al., \u201cSurviving sepsis campaign: International guidelines for management of sepsis and septic shock: 2016,\u201d Intensive Care Med., vol.\u00a043, no. 3, pp.\u00a0304\u2013377, 2017, https:\/\/doi.org\/10.1007\/s00134-017-4683-6.","DOI":"10.1007\/s00134-017-4683-6"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_003","doi-asserted-by":"crossref","unstructured":"J.\u00a0P. Metlay et al., \u201cDiagnosis and treatment of adults with community-acquired pneumonia,\u201d Am. J.\u00a0Respir. Crit. Care Med., vol.\u00a0200, no. 7, pp.\u00a0e45\u2013e67, 2019, https:\/\/doi.org\/10.1164\/rccm.201908-1581ST.","DOI":"10.1164\/rccm.201908-1581ST"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_004","unstructured":"American College of Surgeons, Committee on Trauma, ATLS: Advanced Trauma Life Support for Doctors: Student Course Manual, 8th ed., Chicago, American College of Surgeons, 2008."},{"key":"2026011611154824877_j_jisys-2025-0120_ref_005","doi-asserted-by":"crossref","unstructured":"H. P. Adams et al., \u201cGuidelines for the early management of adults with ischemic stroke: A guideline from the American heart Association\/American Stroke Association Stroke Council, Clinical Cardiology Council, Cardiovascular Radiology and Intervention Council, and the Atherosclerotic Peripheral Vascular Disease and Quality of Care Outcomes in Research Interdisciplinary Working Groups: The American Academy of Neurology affirms the value of this guideline as an educational tool for neurologists,\u201d Stroke, vol.\u00a038, no. 5, pp.\u00a01655\u20131711, 2007, https:\/\/doi.org\/10.1161\/STROKEAHA.107.181486.","DOI":"10.1161\/STROKEAHA.107.181486"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_006","doi-asserted-by":"crossref","unstructured":"S. Prabhu, G. M. Bairy, N. Sampathila, and K. Chadaga, \u201cPatient risk classification based on vital signs using machine learning algorithm,\u201d in 2023 4th International Conference on Intelligent Technologies (CONIT), Hubli, Karnataka, IEEE, 2024, pp. 1\u20135.","DOI":"10.1109\/CONIT61985.2024.10627036"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_007","doi-asserted-by":"crossref","unstructured":"Y. Chen and B. Qi, \u201cRepresentation learning in intraoperative vital signs for heart failure risk prediction,\u201d BMC Med. Inf. Decis. Making, vol.\u00a019, no. 1, p.\u00a0260, 2019, https:\/\/doi.org\/10.1186\/s12911-019-0994-7.","DOI":"10.1186\/s12911-019-0978-6"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_008","doi-asserted-by":"crossref","unstructured":"M. Schellenberg et al., \u201cPrehospital vital signs accurately predict initial emergency department vital signs,\u201d Prehospital Disaster Med., vol.\u00a035, no. 3, pp.\u00a0254\u2013259, 2020, https:\/\/doi.org\/10.1017\/S1049023X20000225.","DOI":"10.1017\/S1049023X2000028X"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_009","doi-asserted-by":"crossref","unstructured":"V. S. Kumar and C. Krishnamoorthi, \u201cDevelopment of electrical transduction based wearable tactile sensors for human vital signs monitor: Fundamentals, methodologies and applications,\u201d Sensor Actuator Phys., vol.\u00a0321, 2021, Art. no. 112582, https:\/\/doi.org\/10.1016\/j.sna.2021.112582.","DOI":"10.1016\/j.sna.2021.112582"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_010","doi-asserted-by":"crossref","unstructured":"S. Eaton, S. Roberts, and B. Turner, \u201cDelivering person-centred care in long-term conditions,\u201d BMJ, vol.\u00a0350, 2015, Art. no. h181, https:\/\/doi.org\/10.1136\/bmj.h181.","DOI":"10.1136\/bmj.h181"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_011","doi-asserted-by":"crossref","unstructured":"B. G. Candel et al., \u201cThe association between vital signs and clinical outcomes in emergency department patients of different age categories,\u201d Emerg. Med. J., vol.\u00a039, no. 12, pp.\u00a0903\u2013911, 2022, https:\/\/doi.org\/10.1136\/emermed-2020-210628.","DOI":"10.1136\/emermed-2020-210628"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_012","doi-asserted-by":"crossref","unstructured":"M. Ljunggren, M. Castr\u00e9n, M. Nordberg, and L. Kurland, \u201cThe association between vital signs and mortality in a retrospective cohort study of an unselected emergency department population,\u201d Scand. J.\u00a0Trauma Resuscitation Emerg. Med., vol.\u00a024, pp.\u00a01\u201311, 2016, https:\/\/doi.org\/10.1186\/s13049-016-0213-8.","DOI":"10.1186\/s13049-016-0213-8"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_013","doi-asserted-by":"crossref","unstructured":"A. R. M. Forkan and I. Khalil, \u201cA clinical decision-making mechanism for context-aware and patient-specific remote monitoring systems using the correlations of multiple vital signs,\u201d Comput. Methods Progr. Biomed., vol.\u00a0139, pp.\u00a01\u201316, 2017, https:\/\/doi.org\/10.1016\/j.cmpb.2016.10.018.","DOI":"10.1016\/j.cmpb.2016.10.018"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_014","doi-asserted-by":"crossref","unstructured":"G. Hawthorne et al., \u201cA proof of concept for continuous, non-invasive, free-living vital signs monitoring to predict readmission following an acute exacerbation of COPD: A prospective cohort study,\u201d Respir. 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Rep., vol.\u00a014, no. 1, p.\u00a07198, 2024, https:\/\/doi.org\/10.1038\/s41598-024-57712-9.","DOI":"10.1038\/s41598-024-57712-9"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_017","doi-asserted-by":"crossref","unstructured":"L. W. Andersen et al., \u201cThe prevalence and significance of abnormal vital signs prior to in-hospital cardiac arrest,\u201d Resuscitation, vol.\u00a098, pp.\u00a0112\u2013117, 2016, https:\/\/doi.org\/10.1016\/j.resuscitation.2015.08.016.","DOI":"10.1016\/j.resuscitation.2015.08.016"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_018","doi-asserted-by":"crossref","unstructured":"W. Hong, A. Earnest, P. Sultana, Z. Koh, N. Shahidah, and M. E. H. Ong, \u201cHow accurate are vital signs in predicting clinical outcomes in critically ill emergency department patients,\u201d Eur. J.\u00a0Emerg. Med., vol.\u00a020, no. 1, pp.\u00a027\u201332, 2013, https:\/\/doi.org\/10.1097\/MEJ.0b013e32834fdcf3.","DOI":"10.1097\/MEJ.0b013e32834fdcf3"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_019","doi-asserted-by":"crossref","unstructured":"\u00c6. \u00d6. Kristinsson et al., \u201cPrediction of serious outcomes based on continuous vital sign monitoring of high-risk patients,\u201d Comput. Biol. Med., vol.\u00a0147, 2022, Art. no. 105559, https:\/\/doi.org\/10.1016\/j.compbiomed.2022.105559.","DOI":"10.1016\/j.compbiomed.2022.105559"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_020","doi-asserted-by":"crossref","unstructured":"T. Adiono et al., \u201cRespinos: A portable device for remote vital signs monitoring of COVID-19 patients,\u201d IEEE Trans. Biomed. Circ. Syst., vol.\u00a016, no. 5, pp.\u00a0947\u2013961, 2022, https:\/\/doi.org\/10.1109\/TBCAS.2022.3204632.","DOI":"10.1109\/TBCAS.2022.3204632"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_021","unstructured":"D. P. Johns, J.\u00a0A. Walters, and E. H. Walters, \u201cDiagnosis and early detection of COPD using spirometry,\u201d J.\u00a0Thorac. Dis., vol.\u00a06, no. 11, pp.\u00a01557\u20131569, 2014, https:\/\/doi.org\/10.3978\/j.issn.2072-1439.2014.11.34."},{"key":"2026011611154824877_j_jisys-2025-0120_ref_022","doi-asserted-by":"crossref","unstructured":"B. F. Nobakht, M. Gh, R. Aliannejad, M. Rezaei-Tavirani, S. Taheri, and A. A. Oskouie, \u201cThe metabolomics of airway diseases, including COPD, asthma and cystic fibrosis,\u201d Biomarkers, vol.\u00a020, no. 1, pp.\u00a05\u201316, 2015, https:\/\/doi.org\/10.3109\/1354750X.2014.975941.","DOI":"10.3109\/1354750X.2014.983167"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_023","doi-asserted-by":"crossref","unstructured":"N. Ji et al., \u201cRecommendation to use wearable-based mHealth in closed-loop management of acute cardiovascular disease patients during the COVID-19 pandemic,\u201d IEEE J.\u00a0Biomed. Health Inform., vol.\u00a025, no. 4, pp.\u00a0903\u2013908, 2021, https:\/\/doi.org\/10.1109\/JBHI.2020.3003970.","DOI":"10.1109\/JBHI.2021.3059883"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_024","doi-asserted-by":"crossref","unstructured":"M. M. Baig, H. Gholamhosseini, and M. J. Connolly, \u201cFalls risk assessment for hospitalised older adults: A combination of motion data and vital signs,\u201d Aging Clin. Exp. Res., vol.\u00a028, no. 6, pp.\u00a01159\u20131168, 2016, https:\/\/doi.org\/10.1007\/s40520-015-0510-5.","DOI":"10.1007\/s40520-015-0510-5"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_025","doi-asserted-by":"crossref","unstructured":"T. T. Han et al., \u201cMachine learning based classification model for screening of infected patients using vital signs,\u201d Inform. Med. Unlocked, vol.\u00a024, 2021, Art. no. 100592, https:\/\/doi.org\/10.1016\/j.imu.2021.100592.","DOI":"10.1016\/j.imu.2021.100592"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_026","unstructured":"World Health Organization, WHO Guidelines on Tularaemia: Epidemic and Pandemic Alert and Response, Geneva, World Health Organization, 2007."},{"key":"2026011611154824877_j_jisys-2025-0120_ref_027","doi-asserted-by":"crossref","unstructured":"K. Alghatani, N. Ammar, A. Rezgui, and A. Shaban-Nejad, \u201cPrecision clinical medicine through machine learning: Using high and low quantile ranges of vital signs for risk stratification of ICU patients,\u201d IEEE Access, vol.\u00a010, pp.\u00a052418\u201352430, 2022, https:\/\/doi.org\/10.1109\/ACCESS.2022.3175304.","DOI":"10.1109\/ACCESS.2022.3175304"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_028","doi-asserted-by":"crossref","unstructured":"A. I. Ibrahim, Q. I. Muaidi, and A. A. Alghamde, \u201cAbnormalities of vital signs in children with cerebral palsy: Relationship to physical disabilities,\u201d J.\u00a0Dev. Phys. Disabil., vol.\u00a030, no. 1, pp.\u00a055\u201367, 2018, https:\/\/doi.org\/10.1007\/s10882-017-9577-6.","DOI":"10.1007\/s10882-017-9577-6"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_029","doi-asserted-by":"crossref","unstructured":"C. L. Tsai, T. C. Lu, C. H. Wang, C. C. Fang, W. J. Chen, and C. H. Huang, \u201cTrajectories of vital signs and risk of in-hospital cardiac arrest,\u201d Front. Med., vol.\u00a08, 2022, Art. no. 800943, https:\/\/doi.org\/10.3389\/fmed.2021.800943.","DOI":"10.3389\/fmed.2021.800943"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_030","doi-asserted-by":"crossref","unstructured":"J.\u00a0H. Yoon, V. Jeanselme, A. Dubrawski, M. Hravnak, M. R. Pinsky, and G. Clermont, \u201cPrediction of hypotension events with physiologic vital sign signatures in the intensive care unit,\u201d Crit. Care, vol.\u00a024, 2020, Art. no. 661, https:\/\/doi.org\/10.1186\/s13054-020-03379-3.","DOI":"10.1186\/s13054-020-03379-3"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_031","doi-asserted-by":"crossref","unstructured":"M. Walsh et al., \u201cRelationship between intraoperative mean arterial pressure and clinical outcomes after noncardiac surgery: Toward an empirical definition of hypotension,\u201d Anesthesiology, vol.\u00a0119, no. 3, pp.\u00a0507\u2013515, 2013, https:\/\/doi.org\/10.1097\/ALN.0b013e3182a10e26.","DOI":"10.1097\/ALN.0b013e3182a10e26"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_032","doi-asserted-by":"crossref","unstructured":"S. Ahuja et al., \u201cAssociations of intraoperative radial arterial systolic, diastolic, mean, and pulse pressures with myocardial and acute kidney injury after noncardiac surgery: A retrospective cohort analysis,\u201d Anesthesiology, vol.\u00a0132, no. 2, pp.\u00a0291\u2013306, 2020, https:\/\/doi.org\/10.1097\/ALN.0000000000003048.","DOI":"10.1097\/ALN.0000000000003048"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_033","doi-asserted-by":"crossref","unstructured":"D. J. Kelm, J.\u00a0T. Perrin, R. Cartin-Ceba, O. Gajic, L. Schenck, and C. C. Kennedy, \u201cFluid overload in patients with severe sepsis and septic shock treated with early goal-directed therapy is associated with increased acute need for fluid-related medical interventions and hospital death,\u201d Shock, vol.\u00a043, no. 1, pp.\u00a068\u201373, 2015, https:\/\/doi.org\/10.1097\/SHK.0000000000000268.","DOI":"10.1097\/SHK.0000000000000268"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_034","doi-asserted-by":"crossref","unstructured":"N. van Mourik et al., \u201cCumulative fluid balance predicts mortality and increases time on mechanical ventilation in ARDS patients: An observational cohort study,\u201d PLoS One, vol.\u00a014, no. 10, 2019, Art. no. e0224563, https:\/\/doi.org\/10.1371\/journal.pone.0224563.","DOI":"10.1371\/journal.pone.0224563"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_035","doi-asserted-by":"crossref","unstructured":"A. Raji, P. G. Jeyasheeli, and T. Jenitha, \u201cIoT based classification of vital signs data for chronic disease monitoring,\u201d in 2016 10th International Conference on Intelligent Systems and Control (ISCO), IEEE, 2016, pp.\u00a01\u20135.","DOI":"10.1109\/ISCO.2016.7727048"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_036","doi-asserted-by":"crossref","unstructured":"J. Xia et al., \u201cHigh-flow nasal oxygen in coronavirus disease 2019 patients with acute hypoxemic respiratory failure: A multicenter, retrospective cohort study,\u201d Crit. Care Med., vol.\u00a048, no. 11, pp.\u00a0e1079\u2013e1086, 2020, https:\/\/doi.org\/10.1097\/CCM.0000000000004558.","DOI":"10.1097\/CCM.0000000000004558"},{"key":"2026011611154824877_j_jisys-2025-0120_ref_037","doi-asserted-by":"crossref","unstructured":"T. Bhavani, P. VamseeKrishna, C. Chakraborty, and P. Dwivedi, \u201cStress classification and vital signs forecasting for IoT-health monitoring,\u201d IEEE ACM Trans. Comput. Biol. 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