Association between intensive care unit transfer delay and hospital mortality: A multicenter investigation

Early goal-directed therapy in the treatment of severe sepsis and septic shock

Rivers, E., Nguyen, B., Havstad, S., Ressler, J., Muzzin, A., Knoblich, B., Peterson, E., & Tomlanovich, M. (2001) · New England Journal of Medicine · doi:10.1056/nejmoa010307 · Cited by 10,743 · see citing works

Surviving Sepsis Campaign: International Guidelines for Management of Severe Sepsis and Septic Shock

Dellinger, R. P., Levy, M. M., Rhodes, A., Annane, D., Gerlach, H., Opal, S. M., Sevransky, J. E., Sprung, C. L., Douglas, I. S., Jaeschke, R., et al. (2013) · Critical Care Medicine · doi:10.1097/ccm.0b013e31827e83af · Cited by 9,694 · see citing works

Surviving Sepsis Campaign: International Guidelines for Management of Severe Sepsis and Septic Shock, 2012

Dellinger, R. P., Levy, M. M., Rhodes, A., Annane, D., Gerlach, H., Opal, S. M., Sevransky, J., Sprung, C. L., Douglas, I. S., Jaeschke, R., et al. (2013) · Intensive Care Medicine · doi:10.1007/s00134-012-2769-8 · Cited by 7,282 · see citing works

Intravenous Fluids and Acute Kidney Injury

Ding, X., Cheng, Z., & Qian, Q. (2017) · Blood Purification · doi:10.1159/000452702 · Cited by 6,866 · see citing works

Validation of a modified Early Warning Score in medical admissions

Subbe, C. P. (2001) · QJM · doi:10.1093/qjmed/94.10.521 · Cited by 1,767 · see citing works

Acute Physiology and Chronic Health Evaluation (APACHE) IV: Hospital mortality assessment for today’s critically ill patients*

Zimmerman, J. E., Kramer, A. A., McNair, D. S., & Malila, F. M. (2006) · Critical Care Medicine · doi:10.1097/01.ccm.0000215112.84523.f0 · Cited by 1,764 · see citing works

Confidential inquiry into quality of care before admission to intensive care

McQuillan, P., Pilkington, S., Allan, A., Taylor, B., Short, A., Morgan, G., Nielsen, M., Barrett, D., & Smith, G. B. (1998) · BMJ · doi:10.1136/bmj.316.7148.1853 · Cited by 1,465 · see citing works

Introduction of the medical emergency team (MET) system: a cluster-randomised controlled trial

‡ (2005) · The Lancet · doi:10.1016/s0140-6736(05)66733-5 · Cited by 1,291 · see citing works

Impact of delayed admission to intensive care units on mortality of critically ill patients: A cohort study.

Cardoso, L. T., Grion, C. M., Matsuo, T., Anami, E. H., Kauss, I. A., Seko, L., & Bonametti, A. M. (2011) · Critical Care · doi:10.1186/cc9975 · Cited by 461 · see citing works

Incidence, location and reasons for avoidable in-hospital cardiac arrest in a district general hospital

Hodgetts, T. J., Kenward, G., Vlackonikolis, I., Payne, S., Nicolas Castle, B., Crouch, R., Ineson, N., & Shaikh, L. A. H. A. (2002) · Resuscitation · doi:10.1016/s0300-9572(02)00098-9 · Cited by 413 · see citing works

Evaluation of triage decisions for intensive care admission

Sprung, C. L., Geber, D., Eidelman, L. A., Baras, M., Pizov, R., Nimrod, A., Oppenheim, A., Epstein, L. M., & Cotev, S. (1999) · Critical Care Medicine · doi:10.1097/00003246-199906000-00021 · Cited by 281 · see citing works

Multicenter Development and Validation of a Risk Stratification Tool for Ward Patients

Churpek, M. M., Yuen, T. C., Winslow, C. J., Robicsek, A. A., Meltzer, D. O., Gibbons, R. D., & Edelson, D. P. (2014) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201406-1022oc · Cited by 258 · see citing works

Inpatient transfers to the intensive care unit

Young, M. P., Gooder, V. J., McBride, K., James, B. C., & Fisher, E. S. (2003) · Journal of General Internal Medicine · doi:10.1046/j.1525-1497.2003.20441.x · Cited by 218 · see citing works

Predictors of intensive care unit refusal in French intensive care units: A multiple-center study*

Garrouste-Orgeas, M., Montuclard, L., Timsit, J., Reignier, J., Desmettre, T., Karoubi, P., Moreau, D., Montésino, L., Duguet, A., Boussat, S., et al. (2005) · Critical Care Medicine · doi:10.1097/01.ccm.0000157752.26180.f1 · Cited by 217 · see citing works

Mortality among appropriately referred patients refused admission to intensive-care units

Metcalfe, M. A., Sloggett, A., & McPherson, K. (1997) · The Lancet · doi:10.1016/s0140-6736(96)10018-0 · Cited by 206 · see citing works

Survival of critically ill patients hospitalized in and out of intensive care units under paucity of intensive care unit beds*

Simchen, E., Sprung, C. L., Galai, N., Zitser‐Gurevich, Y., Bar‐Lavie, Y., Gurman, G., Klein, M., Lev, A., Levi, L., Zveibil, F., et al. (2004) · Critical Care Medicine · doi:10.1097/01.ccm.0000133021.22188.35 · Cited by 184 · see citing works

Worthing physiological scoring system: derivation and validation of a physiological early-warning system for medical admissions. An observational, population-based single-centre study † ‡

Duckitt, R., Buxton-Thomas, R., Walker, J., Cheek, E., Bewick, V., Venn, R. M., & Forni, L. G. (2007) · British Journal of Anaesthesia · doi:10.1093/bja/aem097 · Cited by 175 · see citing works

Refusal of Intensive Care Unit Admission Due to a Full Unit: Impact on Mortality

Robert, R., Reignier, J., Tournoux‐Facon, C., Boulain, T., Lesieur, O., Gissot, V., Souday, V., Hamrouni, M., Chapon, C., & Gouëllo, J. P. (2012) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201104-0729oc · Cited by 151 · see citing works

Risk Stratification of Hospitalized Patients on the Wards

Churpek, M. M., Yuen, T. C., & Edelson, D. P. (2013) · CHEST Journal · doi:10.1378/chest.12-1605 · Cited by 142 · see citing works

Reasons for refusal of admission to intensive care and impact on mortality

Iapichino, G., Corbella, D., Minelli, C., MILLS, G. H., Artigas, A., Edbooke, D. L., Pezzi, A., Kesecioğlu, J., Patroniti, N. A., Baras, M., et al. (2010) · Intensive Care Medicine · doi:10.1007/s00134-010-1933-2 · Cited by 127 · see citing works

Differences in Vital Signs Between Elderly and Nonelderly Patients Prior to Ward Cardiac Arrest

Churpek, M. M., Yuen, T. C., Winslow, C. J., Hall, J. B., & Edelson, D. P. (2015) · Critical Care Medicine · doi:10.1097/ccm.0000000000000818 · Cited by 100 · see citing works

Should age be included as a component of track and trigger systems used to identify sick adult patients?

Smith, G. B., Prytherch, D. R., Schmidt, P. E., Featherstone, P. I., Kellett, J. G., Deane, B., & Higgins, B. (2008) · Resuscitation · doi:10.1016/j.resuscitation.2008.03.004 · Cited by 89 · see citing works

Relationship Between ICU Bed Availability, ICU Readmission, and Cardiac Arrest in the General Wards

Town, J. A., Churpek, M. M., Yuen, T. C., Huber, M. T., Kress, J. P., & Edelson, D. P. (2014) · Critical Care Medicine · doi:10.1097/ccm.0000000000000401 · Cited by 65 · see citing works

Real-Time Risk Prediction on the Wards: A Feasibility Study

Kang, M. A., Churpek, M. M., Zadravecz, F. J., Adhikari, R., Twu, N. M., & Edelson, D. P. (2016) · Critical Care Medicine · doi:10.1097/ccm.0000000000001716 · Cited by 61 · see citing works

Outcomes of patients considered for, but not admitted to, the intensive care unit*

Vanhecke, T. E., Gandhi, M., McCullough, P. A., Lazar, M. H., Ravikrishnan, K. P., Kadaj, P. A., & Begle, R. L. (2008) · Critical Care Medicine · doi:10.1097/ccm.0b013e318165fac7 · Cited by 27 · see citing works

Automated Identification of Adults at Risk for In-Hospital Clinical Deterioration

Escobar, G. J., Liu, V. X., Schuler, A., Lawson, B., Greene, J. D., & Kipnis, P. (2020) · New England Journal of Medicine · doi:10.1056/nejmsa2001090 · Cited by 314 · see citing works

The Japanese Clinical Practice Guidelines for Management of Sepsis and Septic Shock 2020 (J-SSCG 2020)

Egi, M., Ogura, H., Yatabe, T., Atagi, K., Inoue, S., Iba, T., Kakihana, Y., Kawasaki, T., Kushimoto, S., Kuroda, Y., et al. (2021) · Journal of Intensive Care · doi:10.1186/s40560-021-00555-7 · Cited by 226 · see citing works

Using Machine Learning to Predict ICU Transfer in Hospitalized COVID-19 Patients

Cheng, F.-Y., Joshi, H. N., Tandon, P., Freeman, R., Reich, D. L., Mazumdar, M., Kohli-Seth, R. D., Levin, M. A., Timsina, P., & Kia, A. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9061668 · Cited by 197 · see citing works

Minimal Impact of Implemented Early Warning Score and Best Practice Alert for Patient Deterioration*

Bedoya, A. D., Clement, M. E., Phelan, M., Steorts, R. C., O’Brien, C., & Goldstein, B. A. (2019) · Critical Care Medicine · doi:10.1097/ccm.0000000000003439 · Cited by 162 · see citing works

Wireless and continuous monitoring of vital signs in patients at the general ward

Weenk, M., Koeneman, M., van de Belt, T. H., Engelen, L. J., van Goor, H., & Bredie, S. J. H. (2019) · Resuscitation · doi:10.1016/j.resuscitation.2019.01.017 · Cited by 137 · see citing works

Effect of Emergency Department and ICU Occupancy on Admission Decisions and Outcomes for Critically Ill Patients*

Mathews, K. S., Durst, M. S., Vargas-Torres, C. C., Olson, A. D., Mazumdar, M., & Richardson, L. D. (2018) · Critical Care Medicine · doi:10.1097/ccm.0000000000002993 · Cited by 126 · see citing works

Prolonged length of stay in the emergency department and increased risk of hospital mortality in patients with sepsis requiring ICU admission

Zhang, Z., Bokhari, F., Guo, Y., & Goyal, H. (2018) · Emergency Medicine Journal · doi:10.1136/emermed-2018-208032 · Cited by 121 · see citing works

Early Warning Scores With and Without Artificial Intelligence

Edelson, D. P., Churpek, M. M., Carey, K. A., Lin, Z., Huang, C., Siner, J. M., Johnson, J. K., Krumholz, H. M., & Rhodes, D. J. (2024) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.38986 · Cited by 99 · see citing works

Predicting Progression to Septic Shock in the Emergency Department Using an Externally Generalizable Machine-Learning Algorithm

Wardi, G., Carlile, M., Holder, A. L., Shashikumar, S. P., Hayden, S. R., & Nemati, S. (2020) · Annals of Emergency Medicine · doi:10.1016/j.annemergmed.2020.11.007 · Cited by 101 · see citing works

The Japanese Clinical Practice Guidelines for Management of Sepsis and Septic Shock 2020 (J‐SSCG 2020)

Egi, M., Ogura, H., Yatabe, T., Atagi, K., Inoue, S., Iba, T., Kakihana, Y., Kawasaki, T., Kushimoto, S., Kuroda, Y., et al. (2021) · Acute Medicine & Surgery · doi:10.1002/ams2.659 · Cited by 86 · see citing works

Respiratory Rate: The Forgotten Vital Sign—Make It Count!

Loughlin, P. C., Sebat, F., & Kellett, J. G. (2018) · The Joint Commission Journal on Quality and Patient Safety · doi:10.1016/j.jcjq.2018.04.014 · Cited by 82 · see citing works

Clinical risk score to predict in-hospital mortality in COVID-19 patients: a retrospective cohort study

Fumagalli, C., Rozzini, R., Vannini, M., Coccia, F., Cesaroni, G., Mazzeo, F., Cola, M., Bartoloni, A., Fontanari, P., Lavorini, F., et al. (2020) · BMJ Open · doi:10.1136/bmjopen-2020-040729 · Cited by 74 · see citing works

The Impact of a Machine Learning Early Warning Score on Hospital Mortality: A Multicenter Clinical Intervention Trial

Winslow, C. J., Edelson, D. P., Churpek, M. M., Taneja, M., Shah, N. S., Datta, A., Wang, C.-H., Ravichandran, U., McNulty, P., Kharasch, M., et al. (2022) · Critical Care Medicine · doi:10.1097/ccm.0000000000005492 · Cited by 69 · see citing works

Delayed Admission to the Intensive Care Unit and Mortality of Critically Ill Adults: Systematic Review and Meta‐analysis

Kiekkas, P., Tzenalis, A., Gklava, V., Stefanopoulos, N., Voyagis, G., & Aretha, D. (2022) · BioMed Research International · doi:10.1155/2022/4083494 · Cited by 59 · see citing works

Real-time surveillance system for patient deterioration: a pragmatic cluster-randomized controlled trial

Rossetti, S. C., Dykes, P. C., Knaplund, C., Cho, S., Withall, J., Lowenthal, G., Albers, D., Lee, R. Y., Jia, H., Bakken, S., et al. (2025) · Nature Medicine · doi:10.1038/s41591-025-03609-7 · Cited by 54 · see citing works

Early Detection of In-Patient Deterioration: One Prediction Model Does Not Fit All

Blackwell, J., Keim‐Malpass, J., Clark, M., Kowalski, R. L., Najjar, S. N., Bourque, J. M., Lake, D. E., & Moorman, J. R. (2020) · Critical Care Explorations · doi:10.1097/cce.0000000000000116 · Cited by 51 · see citing works

Association between time of discharge from ICU and hospital mortality: a systematic review and meta-analysis

Yang, S., Wang, Z., Liu, Z., Wang, J., & Ma, L. (2016) · Critical Care · doi:10.1186/s13054-016-1569-x · Cited by 47 · see citing works

The rise of ward monitoring: opportunities and challenges for critical care specialists

Michard, F., Bellomo, R., & Taenzer, A. H. (2018) · Intensive Care Medicine · doi:10.1007/s00134-018-5384-5 · Cited by 38 · see citing works

Abnormal Vital Signs Predict Critical Deterioration in Hospitalized Pediatric Hematology-Oncology and Post-hematopoietic Cell Transplant Patients

Agulnik, A., Gossett, J. M., Carrillo, A. K., Kang, G., & Morrison, R. R. (2020) · Frontiers in Oncology · doi:10.3389/fonc.2020.00354 · Cited by 38 · see citing works

Development, Implementation, and Evaluation of an In-Hospital Optimized Early Warning Score for Patient Deterioration

O’Brien, C. L., Goldstein, B. A., Shen, Y., Phelan, M., Lambert, C., Bedoya, A., & Steorts, R. C. (2020) · MDM Policy & Practice · doi:10.1177/2381468319899663 · Cited by 36 · see citing works

Nursing and precision predictive analytics monitoring in the acute and intensive care setting: An emerging role for responding to COVID-19 and beyond

Keim‐Malpass, J., & Moorman, L. P. (2021) · International Journal of Nursing Studies Advances · doi:10.1016/j.ijnsa.2021.100019 · Cited by 36 · see citing works

Ranking Nursing Diagnoses by Predictive Relevance for Intensive Care Unit Transfer Risk in Adult and Pediatric Patients: A Machine Learning Approach with Random Forest

Cesare, M., Nurchis, M. C., Nursing and Public Health Group, Damiani, G., & Cocchieri, A. (2025) · Healthcare · doi:10.3390/healthcare13111339 · Cited by 30 · see citing works

Multi-modal learning for inpatient length of stay prediction

Chen, J., Wen, Y., Pokojovy, M., Tseng, T.-L., McCaffrey, P., Vo, A. H., Walser, E., & Moen, S. T. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.108121 · Cited by 26 · see citing works

Opportunities for machine learning to improve surgical ward safety

Loftus, T. J., Tighe, P. J., Filiberto, A. C., Balch, J. A., Upchurch, G. R., Rashidi, P., & Bihorac, A. (2020) · The American Journal of Surgery · doi:10.1016/j.amjsurg.2020.02.037 · Cited by 26 · see citing works

Delay of transfer from the intensive care unit: a prospective observational analysis on economic effects of delayed in-house transfer

Edenharter, G. M., Gärtner, D., Heim, M. H., Martin, J., Pfeiffer, U. J., Vogt, F. A., Braun, K. F., & Pförringer, D. (2019) · European journal of medical research · doi:10.1186/s40001-019-0388-3 · Cited by 27 · see citing works

Adverse events experienced with intrahospital transfer of critically ill patients

Temsah, M.-H. A., Alsohime, F., Alhaboob, A. A. N., Al-Eyadhy, A. A., Aljamaan, F., Hasan, G., Ali, S., Ashri, A. M., Nahass, A. A., Al-Barrak, R., et al. (2021) · Medicine · doi:10.1097/md.0000000000025810 · Cited by 24 · see citing works

What Do We Do After the Pilot Is Done? Implementation of a Hospital Early Warning System at Scale

Paulson, S. S., Dummett, B. A., Green, J., Scruth, E. A., Reyes, V., & Escobar, G. J. (2020) · The Joint Commission Journal on Quality and Patient Safety · doi:10.1016/j.jcjq.2020.01.003 · Cited by 24 · see citing works

A deep learning approach for inpatient length of stay and mortality prediction

Chen, J., Qi, D., Vu, J., & Wen, Y. (2023) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2023.104526 · Cited by 23 · see citing works

Emergency critical care: closing the gap between onset of critical illness and intensive care unit admission

Dünser, M. W., Noitz, M., Tschoellitsch, T., Bruckner, M., Brunner, M., Eichler, B., Erblich, R., Kalb, S., Knöll, M., Szasz, J., et al. (2024) · Wiener klinische Wochenschrift · doi:10.1007/s00508-024-02374-w · Cited by 25 · see citing works

Neural network-based multi-task learning for inpatient flow classification and length of stay prediction

He, L., Madathil, S. C., Servis, G., & Khasawneh, M. T. (2021) · Applied Soft Computing · doi:10.1016/j.asoc.2021.107483 · Cited by 23 · see citing works

Effectiveness of Remote Patient Monitoring Equipped With an Early Warning System in Tertiary Care Hospital Wards: Retrospective Cohort Study

Lakshman, P., Gopal, P. T., & Khurdi, S. (2025) · Journal of Medical Internet Research · doi:10.2196/56463 · Cited by 22 · see citing works

Pediatric Early Warning Systems aid in triage to intermediate versus intensive care for pediatric oncology patients in resource‐limited hospitals

Agulnik, A., Nadkarni, A., Robles, L. N. M., Vásquez, D. J. S., Mack, R. A., Antillón‐Klussmann, F., & Galindo, C. R. (2018) · Pediatric Blood & Cancer · doi:10.1002/pbc.27076 · Cited by 21 · see citing works

Time-to-event modeling for hospital length of stay prediction for COVID-19 patients

Wen, Y., Rahman, M. F., Zhuang, Y., Pokojovy, M., Xu, H., McCaffrey, P., Vo, A. H., Walser, E., Moen, S. T., & Tseng, T.-L. (2022) · Machine Learning with Applications · doi:10.1016/j.mlwa.2022.100365 · Cited by 19 · see citing works

Improving transitions in care from intensive care units: Development and pilot testing of an electronic communication tool for healthcare providers

Leigh, J. P., Brundin‐Mather, R., Zjadewicz, K., Soo, A., & Stelfox, H. T. (2020) · Journal of Critical Care · doi:10.1016/j.jcrc.2020.01.019 · Cited by 18 · see citing works

Energy-efficient and Reliable Wearable Internet-of-Things through Fog-Assisted Dynamic Goal Management

Anzanpour, A., Rashid, H., Rahmani, A. M., Jantsch, A., Dutt, N. D., & Liljeberg, P. (2019) · Procedia Computer Science · doi:10.1016/j.procs.2019.04.067 · Cited by 17 · see citing works

Mortality in severely injured patients: nearly one of five non-survivors have been already discharged alive from ICU

Hamsen, U., Drotleff, N., Lefering, R. L., Gerstmeyer, J. R., Schildhauer, T. A., Waydhas, C., & TraumaRegister, D. G. U. (2020) · BMC Anesthesiology · doi:10.1186/s12871-020-01159-8 · Cited by 16 · see citing works

The effectiveness of continuous respiratory rate monitoring in predicting hypoxic and pyrexic events: a retrospective cohort study

McCartan, T. A., Worrall, A. P., Conluain, R. Ó., Alaya, F., Mulvey, C., MacHale, E., Brennan, V., Lombard, L., Walsh, J., Murray, M., et al. (2021) · Physiological Measurement · doi:10.1088/1361-6579/ac05d5 · Cited by 16 · see citing works

Multicenter Development and Prospective Validation of eCARTv5: A Gradient-Boosted Machine-Learning Early Warning Score

Churpek, M. M., Carey, K. A., Snyder, A. M., Winslow, C. J., Gilbert, E. R., Shah, N. S., Patterson, B. W., Afshar, M., Weiss, A., Amin, D., et al. (2025) · Critical Care Explorations · doi:10.1097/cce.0000000000001232 · Cited by 18 · see citing works

Time Spent in the Emergency Department and Outcomes in Patients With Severe Sepsis and Septic Shock

Hirschy, R., Sterk, E. J., Dobersztyn, R., & Rech, M. A. (2018) · Advanced Emergency Nursing Journal · doi:10.1097/tme.0000000000000188 · Cited by 13 · see citing works

A systematic review of rapid response applications based on early warning score for early detection of inpatient deterioration

Baig, M. M., GholamHosseini, H., Afifi, S. M., & Lindén, M. (2021) · Informatics for Health and Social Care · doi:10.1080/17538157.2021.1873349 · Cited by 14 · see citing works

Central Venous Access Capability and Critical Care Telemedicine Decreases Inter-Hospital Transfer Among Severe Sepsis Patients: A Mixed Methods Design

Ilko, S. A., Vakkalanka, J. P., Ahmed, A., Harland, K. K., & Mohr, N. M. (2019) · Critical Care Medicine · doi:10.1097/ccm.0000000000003686 · Cited by 14 · see citing works

Associations between hospital occupancy, intensive care unit transfer delay and hospital mortality

Ofoma, U. R., Montoya, J., Saha, D., Berger, A. L., Kirchner, H. L., McIlwaine, J. K., & Kethireddy, S. (2020) · Journal of Critical Care · doi:10.1016/j.jcrc.2020.04.009 · Cited by 14 · see citing works

Validation of Dozee, a Ballistocardiography-based Device, for Contactless and Continuous Heart Rate and Respiratory Rate Measurement

Saran, V., Kumar, R., Kumar, G., Chokalingam, K., Rawooth, M., & Parchani, G. (2022) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc48229.2022.9871007 · Cited by 13 · see citing works

Predictors of Delayed Recognition of Critical Illness in Emergency Department Patients and Its Effect on Morbidity and Mortality

Goel, N. N., Durst, M. S., Vargas-Torres, C. C., Richardson, L. D., & Mathews, K. S. (2020) · Journal of Intensive Care Medicine · doi:10.1177/0885066620967901 · Cited by 11 · see citing works

Nighttime intensive care unit discharge and outcomes: A propensity matched retrospective cohort study

Corrêa, T. D., Ponzoni, C. R., Filho, R. R., Neto, A. S., Chaves, R. C. D. F., Pardini, A., de Assunção, M. S. C., Schettino, G. D. P. P., & Noritomi, D. T. (2018) · PLoS ONE · doi:10.1371/journal.pone.0207268 · Cited by 11 · see citing works

Is the Critical Care Resuscitation Unit Sustainable: A 5-Year Experience of a Beneficial and Novel Model

Powell, E. K., Sahadzic, I., Najafali, D., Berman, E., Andersen, K., Afridi, L. Z., Gasparotti, Z., Niles, E., Rea, J. H., Scalea, T. M., et al. (2022) · Critical Care Research and Practice · doi:10.1155/2022/6171598 · Cited by 11 · see citing works

Beyond prediction: Off‐target uses of artificial intelligence‐based predictive analytics in a learning health system

Keim‐Malpass, J., Moorman, L. P., Monfredi, O., Clark, M., & Bourque, J. M. (2022) · Learning Health Systems · doi:10.1002/lrh2.10323 · Cited by 10 · see citing works

The relationship between Intensive Care Unit Length of Stay information and its operational performance

Bahalkeh, E., Hasan, I., & Yih, Y. (2022) · Healthcare Analytics · doi:10.1016/j.health.2022.100036 · Cited by 11 · see citing works

Intensive care unit admission criteria: a scoping review

Soares, J., Leung, C., Campbell, V. K., van der Vegt, A. H., Malycha, J., & Andersen, C. (2024) · Journal of the Intensive Care Society · doi:10.1177/17511437241246901 · Cited by 11 · see citing works

Comparison of Multimodal Deep Learning Approaches for Predicting Clinical Deterioration in Ward Patients: Observational Cohort Study

Kotula, C. A., Martin, J., Carey, K. A., Edelson, D. P., Dligach, D., Mayampurath, A. M., Afshar, M., & Churpek, M. M. (2025) · Journal of Medical Internet Research · doi:10.2196/75340 · Cited by 10 · see citing works

Risk Prediction Models for Hospital Mortality in General Medical Patients: A Systematic Review

Hydoub, Y. M., Walker, A. P., Kirchoff, R. W., Alzu’bi, H., Chipi, P. Y., Gerberi, D., Burton, M. C., Murad, M. H., & Dugani, S. B. (2023) · American Journal of Medicine Open · doi:10.1016/j.ajmo.2023.100044 · Cited by 9 · see citing works

Causes, Diagnostic Testing, and Treatments Related to Clinical Deterioration Events Among High-Risk Ward Patients

Churpek, M. M., Ingebritsen, R., Carey, K. A., Rao, S. A., Murnin, E., Qyli, T., Oguss, M. K., Picart, J. K., Penumalee, L. S., Follman, B., et al. (2024) · Critical Care Explorations · doi:10.1097/cce.0000000000001161 · Cited by 8 · see citing works

Towards Predicting Length of Stay and Identification of Cohort Risk Factors Using Self-Attention-Based Transformers and Association Mining: COVID-19 as a Phenotype

Alam, F., Ananbeh, O., Malik, K. M., Odayani, A. A., Hussain, I. B., Kaabia, N. M., Aidaroos, A. Y. A., & Saudagar, A. K. J. (2023) · Diagnostics · doi:10.3390/diagnostics13101760 · Cited by 8 · see citing works

Effect of a fall within three months of admission on delirium in critically Ill elderly patients: a population-based cohort study

Bu, F., Cheng, H.-T., Wang, Z., Hou, Y.-S., Zhuang, Z., Li, C.-Y., Wang, Y., Zhang, Y., Lyu, J., & Lyu, Q.-Y. (2024) · Aging Clinical and Experimental Research · doi:10.1007/s40520-024-02740-8 · Cited by 8 · see citing works

Scratching the Surface of Clinical Deterioration With Deep Learning*

Churpek, M. M., & Edelson, D. P. (2021) · Critical Care Medicine · doi:10.1097/ccm.0000000000004982 · Cited by 8 · see citing works

Using Quality Improvement Methods to Understand Incidence, Timing, and Factors Associated With Unplanned Intensive Care Unit Transfers of Patients With End-Stage Liver Disease

Grimshaw, K. S., Fan, K., Mullins, A., & Parkosewich, J. A. (2019) · Progress in Transplantation · doi:10.1177/1526924819888132 · Cited by 7 · see citing works

Beyond Unplanned ICU Transfers: Linking a Revised Definition of Deterioration to Patient Outcomes

Byrd, T. F., Phelan, T., Ingraham, N. E., Langworthy, B., Bhasin, A., Kc, A., Melton, G. B., & Tignanelli, C. J. (2024) · Critical Care Medicine · doi:10.1097/ccm.0000000000006333 · Cited by 7 · see citing works

Demand for Intensive Care beds and patient classification according to the priority criterion

Nassiff, A., Menegüeti, M. G., de Araújo, T. R., Auxiliadora‐Martins, M., & Laüs, A. M. (2021) · Revista Latino-Americana de Enfermagem · doi:10.1590/1518-8345.4945.3489 · Cited by 7 · see citing works

Predictive performance and temporal dynamics of national early warning score 2 (NEWS2) in detecting clinical deterioration in general ward: A large-scale validation study in Singapore

Chen, L., Sun, Y., Kuek, S. Y., Chew, M. F., Tan, H. L., & Ho, S. (2025) · Resuscitation Plus · doi:10.1016/j.resplu.2025.101120 · Cited by 6 · see citing works

Clinical Characteristics and In-Hospital Mortality of Cardiac Arrest Survivors in Brazil: A Large Retrospective Multicenter Cohort Study

Kurtz, P., Storm, C., Soares, M., Bozza, F. A., Maciel, C. B., Greer, D. M., Bastos, L. D. S. L., Melo, U. O., Mazza, B. F., Santino, M. S., et al. (2021) · Critical Care Explorations · doi:10.1097/cce.0000000000000479 · Cited by 6 · see citing works

Development and Validation of a Deep Learning Model for Prediction of Adult Physiological Deterioration

Shashikumar, S. P., Le, J. P., Yung, N., Ford, J., Singh, K., Malhotra, A., Nemati, S., & Wardi, G. (2024) · Critical Care Explorations · doi:10.1097/cce.0000000000001151 · Cited by 7 · see citing works

Early Prediction of All-Cause Clinical Deterioration in General Wards Patients: Development and Validation of a Biomarker-Based Machine Learning Model Derived From Rapid Response Team Activations

Saab, A., Khalil, C. A., Jammal, M., Saikali, M., & Lamy, J.-B. (2022) · Journal of Patient Safety · doi:10.1097/pts.0000000000001069 · Cited by 6 · see citing works

Continuous Cloud-Based Early Warning Score Surveillance to Improve the Safety of Acutely Ill Hospitalized Patients

Morgan, C. K., Amspoker, A. B., Howard, C., Razjouyan, J., Siddique, M. K., Davignon, S., Rosen, T., Herlihy, J. P., & Naik, A. D. (2020) · Journal for Healthcare Quality · doi:10.1097/jhq.0000000000000272 · Cited by 6 · see citing works

Outcomes of boarding critically ill patients in U.S. EDs: A systematic review and meta-analysis

Htet, N. N., Walker, J., Jafari, D., Rech, M. A., Hintze, T., Moran, M., Bai, J., Dinh, K., Essaihi, A., Wilairat, S., et al. (2025) · The American Journal of Emergency Medicine · doi:10.1016/j.ajem.2025.10.036 · Cited by 5 · see citing works

Evaluating the efficacy of large language models in predicting intensive care unit admission needs

Turan, E. İ., Baydemir, A. E., Turan, Z. P., & Şahin, A. S. (2026) · Journal of Critical Care · doi:10.1016/j.jcrc.2026.155446 · Cited by 5 · see citing works

Patient diversion using real-time delay predictions across healthcare facility networks

Fatma, N., & Ramamohan, V. (2023) · OR Spectrum · doi:10.1007/s00291-022-00704-w · Cited by 5 · see citing works

A proposed method for identifying Interfacility transfers in Medicare claims data

Nikpay, S., Leeberg, M., Kozhimannil, K. B., Ward, M. J., Wolfson, J. A., Graves, J. A., & Virnig, B. A. (2024) · Health Services Research · doi:10.1111/1475-6773.14367 · Cited by 5 · see citing works

Peripheral oxygen saturation to inspiratory oxygen fraction ratio-based identification of critically ill coronavirus disease patients for early therapeutic interventions

Shimizu, M., & Hashimoto, S. (2021) · Journal of Anesthesia · doi:10.1007/s00540-021-02986-w · Cited by 5 · see citing works

Delayed Transfer of Critically Ill Patients from Emergency Department to Intensive Care Unit

Arora, P., Sahni, N., Jain, A., Yaddanapudi, L. N., Bosco, S., & Raj, V. (2023) · Indian Journal of Critical Care Medicine · doi:10.5005/jp-journals-10071-24502 · Cited by 5 · see citing works

Performance in mortality prediction of SAPS 3 And MPM-III scores among adult patients admitted to the ICU of a private tertiary referral hospital in Tanzania: a retrospective cohort study

Kassam, N., Aghan, E., Somji, S., Aziz, O., Orwa, J., & Surani, S. (2021) · PeerJ · doi:10.7717/peerj.12332 · Cited by 5 · see citing works

Increased Inpatient Length of Stay After Early Unplanned Transfer to Higher Levels of Care

Sykora, D., Traub, S. J., Buras, M. R., Hodgson, N. R., & Geyer, H. L. (2020) · Critical Care Explorations · doi:10.1097/cce.0000000000000103 · Cited by 5 · see citing works

Multisite Pragmatic Cluster-Randomized Controlled Trial of the CONCERN Early Warning SystemPreprint

Rossetti, S. C., Dykes, P. C., Knaplund, C., Cho, S., Withall, J. B., Lowenthal, G., Albers, D. J., Lee, R. Y., Jia, H., Henry, S. B., et al. (2024) · medRxiv · doi:10.1101/2024.06.04.24308436 · Cited by 5 · see citing works

Patient and Operative Factors Predict Risk of Discretionary Prolonged Postoperative Mechanical Ventilation in a Broad Surgical Cohort

Clark, M. G., Mueller, D. A., Dudaryk, R., Li, G., & Freundlich, R. E. (2022) · Anesthesia & Analgesia · doi:10.1213/ane.0000000000006205 · Cited by 4 · see citing works

Efficacy of Early Warning Scores as the Prediction Tool for Detecting Patients With Acute Deterioration in a High Dependent Unit

Ehara, J., Masuda, Y., Hayashi, K., Norisue, Y., & Fujitani, S. (2024) · Cureus · doi:10.7759/cureus.71971 · Cited by 4 · see citing works

Critical Care Nursing Workforce Retention From an Irish Perspective: A National Survey

McEvoy, N. L., Credland, N., Cribbin, D., Curley, G. F., & Humphries, N. (2025) · Nursing in Critical Care · doi:10.1111/nicc.70094 · Cited by 4 · see citing works

Emergency Department Boarding of Mechanically Ventilated Patients

Saggaf, A. M., Mugharbel, A. T., Aboalola, A. B., Mulla, A. W. M. A. A. A., Alasiri, M. M., Alabbasi, M., & Bakhsh, A. A. (2022) · Cureus · doi:10.7759/cureus.23990 · Cited by 4 · see citing works

Denied and Delayed Care: The Synergy Between the Emergency Department and the ICU*

Chalfin, D. B. (2018) · Critical Care Medicine · doi:10.1097/ccm.0000000000003055 · Cited by 4 · see citing works

How the high acuity unit changes mortality in the intensive care unit: a retrospective before-and-after study

Mitra, A. R., Griesdale, D. E. G., Haljan, G. J., O’Donoghue, A. L., & Stevens, J. P. (2020) · Canadian Journal of Anesthesia/Journal canadien d anesthésie · doi:10.1007/s12630-020-01775-5 · Cited by 4 · see citing works

Towards Predicting Length of Stay and Identification of Cohort Risk Factors Using Self-Attention Based Transformers and Association Mining: Covid-19 as PhenotypePreprint

Alam, F., Ananbeh, O., Malik, K. M., Odayani, A. A., Hussain, I. B., Kaabia, N. M., & Aidaroos, A. Y. A. (2023) · Preprints.org · doi:10.20944/preprints202301.0341.v1 · Cited by 4 · see citing works

Impact of emergency department-to-intensive care unit transfer time on in-hospital mortality: A retrospective cohort study

ÖZKAYA, S., & YURDAKUL, M. S. (2025) · Medicine · doi:10.1097/md.0000000000046724 · Cited by 3 · see citing works

Tele-Critical Care Support Outside the Intensive Care Unit

Siner, J. M. (2024) · Critical Care Clinics · doi:10.1016/j.ccc.2024.03.012 · Cited by 3 · see citing works

Mortality and Length of Stay Implications of Deterioration-Associated Transfer to the Intensive Care Unit over Different Time Frames

Belk, K. W., Beals, J., & McInnis, S. J. (2025) · Health Services Insights · doi:10.1177/11786329241312877 · Cited by 3 · see citing works

Ungeplante Aufnahmen oder Rückverlegungen auf die Intensivstation

Hamsen, U., Waydhas, C., Wildenauer, R., Schildhauer, T. A., & Schwenk, W. (2018) · Der Chirurg · doi:10.1007/s00104-018-0599-0 · Cited by 3 · see citing works

Association of Time to Rapid Response Team Activation With Patient Outcomes Using a Range of Physiologic Deterioration Thresholds

Mitchell, O. J. L., Neefe, S., Ginestra, J. C., Schweickert, W. D., Falk, S. A., Weissman, G. E., Covin, D. S., Justine Shults, A., Abella, B. S., & Shashaty, M. G. S. (2022) · Critical Care Explorations · doi:10.1097/cce.0000000000000786 · Cited by 3 · see citing works

Implementation of an Interdisciplinary Transfer Huddle Intervention for Prolonged Wait Times During Inter-ICU Transfer

Hyder, S. M., Tang, R., Huang, R., Ludwig, A., Scott, K., & Nadig, N. R. (2024) · The Joint Commission Journal on Quality and Patient Safety · doi:10.1016/j.jcjq.2024.01.009 · Cited by 3 · see citing works

The PaCO2/FiO2 ratio as outcome predictor in SARS-COV-2 related pneumonia: a retrospective study.

VUONO, S. D., Cianci, P., Berisha, S., Pierini, P., Baccarini, G., Balducci, F., LIGNANI, A., Settimi, L., Taliani, M. R., & Groff, P. (2022) · Acta bio-medica dell'Ateneo parmense/Acta biomedica · doi:10.23750/abm.v93i5.13229 · Cited by 3 · see citing works

Factors That Influence Nurses' Clinical Judgment During Episodes of Acute Physiologic Patient Deterioration

Dresser, S. C. (2019) · KU ScholarWorks (The University of Kansas) · Cited by 3 · see citing works

A roadmap for applying theoretical frameworks to implementation of hospital rapid response systems: A qualitative study using focus group interviews

Prins, G., Lagzimi, S., Ista, E., Trogrlić, Z., Groot, M. W., van Dijk, M., Gommers, D., & van Bommel, J. (2025) · Australian Critical Care · doi:10.1016/j.aucc.2025.101306 · Cited by 2 · see citing works

ICU transfer delay and mortality after ward-onset shock

Zou, T., Ngan, C., & Yin, W. (2026) · Journal of Critical Care · doi:10.1016/j.jcrc.2026.155423 · Cited by 2 · see citing works

Predicting Lead-Time RSV-Related Pediatric Hospitalizations From Historic Google Trend Search

Bhatt, P. J., Parmar, N. G., Parekh, T., Pemmasani, S., Shaikh, N., Boateng, A. J., Donda, K., Doshi, H., & Dapaah-Siakwan, F. M. (2023) · Hospital Pediatrics · doi:10.1542/hpeds.2022-007095 · Cited by 2 · see citing works

Development and Validation of a Machine Learning COVID-19 Veteran (COVet) Deterioration Risk Score

Govindan, S., Spicer, A. B., Bearce, M., Schaefer, R. S., Uhl, A., Alterovitz, G., Kim, M. J., Carey, K. A., Shah, N. S., Winslow, C. J., et al. (2024) · Critical Care Explorations · doi:10.1097/cce.0000000000001116 · Cited by 1 · see citing works

PRINCIPAIS INTERCORRÊNCIAS E DESFECHOS CLÍNICOS DE IDOSOS VÍTIMAS DE TRAUMA NA UNIDADE DE TERAPIA INTENSIVA

da Costa, A. C. C., & Fortes, R. C. (2018) · Cogitare Enfermagem · doi:10.5380/ce.v23i3.55366 · Cited by 2 · see citing works

Preferred Language Mediates Association Between Race, Ethnicity, and Delayed Presentation in Critically Ill Patients With COVID-19

Kelly, M. S., Mohammed, A., Okin, D. A., Alba, G. A., Jesudasen, S. J., Flanagan, S., Dandawate, N. A., Gavralidis, A., Chang, L. L., Moin, E. E., et al. (2023) · Critical Care Explorations · doi:10.1097/cce.0000000000000927 · Cited by 2 · see citing works

États de choc : grands cadres étiologiques, prise en charge initiale

Durand, A., Cartier, L., Duburcq, T., Onimus, T., Favory, R., & Préau, S. (2019) · La Revue de Médecine Interne · doi:10.1016/j.revmed.2019.08.006 · Cited by 2 · see citing works

Development and Validation of the VIOSync Sepsis Prediction Index: A Novel Machine Learning Model for Sepsis Prediction in ICU PatientsPreprint

Liliopoulos, S. G., Dejaco, A., Dimakopoulos, V. S., & Gkouzionis, I. (2024) · medRxiv · doi:10.1101/2024.02.22.24303211 · Cited by 2 · see citing works

Comparison of Multimodal Deep Learning Approaches for Predicting Clinical Deterioration in Ward PatientsPreprint

Kotula, C. A., Martin, J., Carey, K. A., Edelson, D. P., Dligach, D., Mayampurath, A. M., Afshar, M., & Churpek, M. M. (2025) · medRxiv · doi:10.1101/2025.03.06.25322855 · Cited by 2 · see citing works

Development and Validation of VC-MAES and VC-SEPS: Deep Learning-Based Early Warning Systems for Hospitalized PatientsPreprint

Kim, Y. J., Hahn, S., Kim, K. J., Yang, E., Kim, J., Lee, S., Han, C. H., Won, J.-Y., Ahn, B. E., Mun, Y., et al. (2025) · medRxiv · doi:10.1101/2025.08.20.25334022 · Cited by 2 · see citing works

The Association of Bedside Nurse Staffing on Patient Outcomes and Throughput in a Pediatric Cardiac Intensive Care Unit

Fundora, M. P., Liu, J., Diwas Singh, K. C., & Calamaro, C. (2023) · Journal of Pediatric Intensive Care · doi:10.1055/s-0043-1769118 · Cited by 2 · see citing works

Association between Intimate Partner Violence and Hospital-Based Healthcare Utilization: A Matched Cohort Analysis

Maitra, A., Schnipper, J. L., Yoon, C. S., & Mueller, S. K. (2025) · Journal of General Internal Medicine · doi:10.1007/s11606-025-09663-8 · Cited by 1 · see citing works

Treatment Recommendations for Clinical Deterioration on the Wards: Development and Validation of Machine Learning Models

Pulick, E., Carey, K. A., Qyli, T., Oguss, M. K., Picart, J. K., Penumalee, L. S., Nezirova, L., Tully, S. T., GILBERT, E. R., Shah, N. S., et al. (2026) · JMIR AI · doi:10.2196/81642 · Cited by 1 · see citing works

ASSOCIATION BETWEEN INTENSIVE CARE UNIT TRANSFER DELAY AND HOSPITAL MORTALITY

NAWADAT, Q., KHALID, M., & Parveen, A. (2023) · Biological and Clinical Sciences Research Journal · doi:10.54112/bcsrj.v2023i1.300

Adverse outcomes associated with delayed intensive care unit transfers in an integrated healthcare system

Liu, V. X., Kipnis, P., Rizk, N. W., & Escobar, G. J. (2011) · Journal of Hospital Medicine · doi:10.1002/jhm.964 · Cited by 137 · see citing works

Impact of emergency department-to-intensive care unit transfer time on in-hospital mortality: A retrospective cohort study

ÖZKAYA, S., & YURDAKUL, M. S. (2025) · Medicine · doi:10.1097/md.0000000000046724 · Cited by 3 · see citing works

ICU transfer delay and mortality after ward-onset shock

Zou, T., Ngan, C., & Yin, W. (2026) · Journal of Critical Care · doi:10.1016/j.jcrc.2026.155423 · Cited by 2 · see citing works

Delays in transfer to the ICU

Kaboli, P. J., & Rosenthal, G. E. (2003) · Journal of General Internal Medicine · doi:10.1046/j.1525-1497.2003.21217.x · Cited by 14 · see citing works