A risk model to predict an unplanned admission to the intensive care unit following lung resection. (24th January 2022)
- Record Type:
- Journal Article
- Title:
- A risk model to predict an unplanned admission to the intensive care unit following lung resection. (24th January 2022)
- Main Title:
- A risk model to predict an unplanned admission to the intensive care unit following lung resection
- Authors:
- Brunelli, Alessandro
Begum, Housne
Chaudhuri, Nilanjan
Agzarian, John
Milton, Richard
Finley, Christian
Tcherveniakov, Peter
Valuckiene, Laura
Gioutsos, Konstantinos
Hanna, Wael
Papagiannopoulos, Kostas
Shargall, Yaron - Abstract:
- Abstract: OBJECTIVES: The goal of this study was to develop a risk-adjusting model to stratify the risk of an unplanned admission to the intensive care unit (following lung resection). METHODS: We performed a retrospective analysis of 3123 patients undergoing anatomical lung resections (2014–2019) in 2 centres. A risk score was developed by testing several variables for a possible association with a subsequent ICU admission using stepwise logistic regression analyses, validated by the bootstrap resampling technique. Variables associated with ICU admission were assigned weighted scores based on their regression coefficients. These scores were summed for each patient to generate the ICU risk score, and patients were grouped into risk classes. RESULTS: A total of 103 patients (3.3%) required an unplanned admission to the ICU after the operation. The average ICU stay was 17.6 days. The following variables remained significantly associated with ICU admission following logistic regression: male gender ( P = 0.004), body mass index <18.5 ( P = 0.002), predicted postoperative forced expiratory volume in 1 s < 60% ( P = 0.004), predicted postoperative carbon monoxide lung diffusion capacity <50% ( P = 0.013), open access ( P = 0.004) and pneumonectomy ( P = 0.041). All variables were weighted 1 point except body mass index <18.5 (2 points). The final ICU risk score ranged from 0 to 7 points. Patients were grouped into 6 risk classes showing an incremental unplanned ICUAbstract: OBJECTIVES: The goal of this study was to develop a risk-adjusting model to stratify the risk of an unplanned admission to the intensive care unit (following lung resection). METHODS: We performed a retrospective analysis of 3123 patients undergoing anatomical lung resections (2014–2019) in 2 centres. A risk score was developed by testing several variables for a possible association with a subsequent ICU admission using stepwise logistic regression analyses, validated by the bootstrap resampling technique. Variables associated with ICU admission were assigned weighted scores based on their regression coefficients. These scores were summed for each patient to generate the ICU risk score, and patients were grouped into risk classes. RESULTS: A total of 103 patients (3.3%) required an unplanned admission to the ICU after the operation. The average ICU stay was 17.6 days. The following variables remained significantly associated with ICU admission following logistic regression: male gender ( P = 0.004), body mass index <18.5 ( P = 0.002), predicted postoperative forced expiratory volume in 1 s < 60% ( P = 0.004), predicted postoperative carbon monoxide lung diffusion capacity <50% ( P = 0.013), open access ( P = 0.004) and pneumonectomy ( P = 0.041). All variables were weighted 1 point except body mass index <18.5 (2 points). The final ICU risk score ranged from 0 to 7 points. Patients were grouped into 6 risk classes showing an incremental unplanned ICU admission rate: class A (score 0), 0.7%; class B (score 1), 1.7%; class C (score 2), 3%; class D (score 3), 7.1%; class E (score 4), 12%; and class F (score > 4), 13% ( P < 0.001). CONCLUSIONS: This risk score may assist in reliably planning the response to a sudden increase in the demand of critical care resources. Abstract : Unplanned admission to the intensive care unit (ICU) following lung resection occurs in about 3–9% of patients [1–9], and thoracic surgery is one of the surgical specialties often utilizing intensive care beds [10]. … (more)
- Is Part Of:
- European journal of cardio-thoracic surgery. Volume 61:Number 6(2022)
- Journal:
- European journal of cardio-thoracic surgery
- Issue:
- Volume 61:Number 6(2022)
- Issue Display:
- Volume 61, Issue 6 (2022)
- Year:
- 2022
- Volume:
- 61
- Issue:
- 6
- Issue Sort Value:
- 2022-0061-0006-0000
- Page Start:
- 1232
- Page End:
- 1239
- Publication Date:
- 2022-01-24
- Subjects:
- Lung cancer -- Lung resection -- Intensive care unit -- Risk modelling -- Outcome -- Mortality
Heart -- Surgery -- Periodicals
Chest -- Surgery -- Periodicals
617.54 - Journal URLs:
- http://ejcts.oxfordjournals.org/ ↗
http://www.sciencedirect.com/science/journal/10107940 ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/ejcts/ezac027 ↗
- Languages:
- English
- ISSNs:
- 1010-7940
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3829.725620
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21745.xml