» Articles » PMID: 25684007

Readmission to Medical Intensive Care Units: Risk Factors and Prediction

Overview
Journal Yonsei Med J
Specialty General Medicine
Date 2015 Feb 17
PMID 25684007
Citations 18
Authors
Affiliations
Soon will be listed here.
Abstract

Purpose: The objectives of this study were to find factors related to medical intensive care unit (ICU) readmission and to develop a prediction index for determining patients who are likely to be readmitted to medical ICUs.

Materials And Methods: We performed a retrospective cohort study of 343 consecutive patients who were admitted to the medical ICU of a single medical center from January 1, 2008 to December 31, 2012. We analyzed a broad range of patients' characteristics on the day of admission, extubation, and discharge from the ICU.

Results: Of the 343 patients discharged from the ICU alive, 33 (9.6%) were readmitted to the ICU unexpectedly. Using logistic regression analysis, the verified factors associated with increased risk of ICU readmission were male sex [odds ratio (OR) 3.17, 95% confidence interval (CI) 1.29-8.48], history of diabetes mellitus (OR 3.03, 95% CI 1.29-7.09), application of continuous renal replacement therapy during ICU stay (OR 2.78, 95% CI 0.85-9.09), white blood cell count on the day of extubation (OR 1.13, 95% CI 1.07-1.21), and heart rate just before ICU discharge (OR 1.03, 95% CI 1.01-1.06). We established a prediction index for ICU readmission using the five verified risk factors (area under the curve, 0.76, 95% CI 0.66-0.86).

Conclusion: By using specific risk factors associated with increased readmission to the ICU, a numerical index could be established as an estimation tool to predict the risk of ICU readmission.

Citing Articles

Multicenter validation of a machine learning model to predict intensive care unit readmission within 48 hours after discharge.

Lim L, Kim M, Cho K, Yoo D, Sim D, Ryu H EClinicalMedicine. 2025; 81:103112.

PMID: 40034564 PMC: 11872568. DOI: 10.1016/j.eclinm.2025.103112.


Factors associated with unplanned intensive care unit readmission among trauma patients in Republic of Korea.

Lee Y, Kang B Acute Crit Care. 2024; 39(4):583-592.

PMID: 39600250 PMC: 11617833. DOI: 10.4266/acc.2024.00584.


Development of a Nomogram for Predicting ICU Readmission.

Nakano K, Haruna J, Harada A, Tatsumi H Cureus. 2024; 16(10):e71555.

PMID: 39544597 PMC: 11563696. DOI: 10.7759/cureus.71555.


Characteristics and Outcome of ICU Unplanned Readmission in Trauma Patients During the Same Hospitalization.

Arabian S, Davoodi A, Karajizadeh M, Naderi N, Bordbar N, Sabetian G Bull Emerg Trauma. 2024; 12(2):81-87.

PMID: 39224467 PMC: 11366269. DOI: 10.30476/BEAT.2024.102331.1508.


Determinants of Readmission in the Intensive Care Unit: A Prospective Observational Study.

Kumar R, Singh B, Arshad Z, Srivastava V, Prakash R, Singh M Cureus. 2024; 16(6):e62840.

PMID: 39036166 PMC: 11260421. DOI: 10.7759/cureus.62840.


References
1.
Rosenberg A, Watts C . Patients readmitted to ICUs* : a systematic review of risk factors and outcomes. Chest. 2000; 118(2):492-502. DOI: 10.1378/chest.118.2.492. View

2.
Hosein F, Bobrovitz N, Berthelot S, Zygun D, Ghali W, Stelfox H . A systematic review of tools for predicting severe adverse events following patient discharge from intensive care units. Crit Care. 2013; 17(3):R102. PMC: 4056089. DOI: 10.1186/cc12747. View

3.
Skowronski G . Bed rationing and allocation in the intensive care unit. Curr Opin Crit Care. 2002; 7(6):480-4. DOI: 10.1097/00075198-200112000-00020. View

4.
Metnitz P, Fieux F, Jordan B, Lang T, Moreno R, Le Gall J . Critically ill patients readmitted to intensive care units--lessons to learn?. Intensive Care Med. 2003; 29(2):241-8. DOI: 10.1007/s00134-002-1584-z. View

5.
Heidegger C, Treggiari M, Romand J . A nationwide survey of intensive care unit discharge practices. Intensive Care Med. 2005; 31(12):1676-82. DOI: 10.1007/s00134-005-2831-x. View