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Br J Anaesth ; 128(3): 449-456, 2022 03.
Article in English | MEDLINE | ID: mdl-35012739

ABSTRACT

BACKGROUND: Days alive and out of hospital (DAOH) is a composite, patient-centred outcome measure describing a patient's postoperative recovery, encompassing hospitalisation and mortality. DAOH is the number of days not in hospital over a defined postoperative period; patients who die have DAOH of zero. The Standardising Endpoints in Perioperative Medicine (StEP) group recommended DAOH as a perioperative outcome. However, DAOH has never been validated in patients undergoing emergency laparotomy. Here, we validate DAOH after emergency laparotomy and establish the optimal duration of observation. METHODS: Prospectively collected data of patients having emergency laparotomy in England (December 1, 2013-November 30, 2017) were linked to national hospital admission and mortality records for the year after surgery. We evaluated construct validity by assessing DAOH variation with known perioperative risk factors and predictive validity for 1 yr mortality using a multivariate Bayesian mixed-effects logistic regression. The optimal postoperative DAOH period (30 or 90 days) was judged on distributional and pragmatic properties. RESULTS: We analysed 78 921 records. The median 30-day DAOH (DAOH30) was 16 (inter-quartile range [IQR], 0-22) days and the median DAOH90 was 75 (46-82) days. DAOH was shorter in the presence of known perioperative risk factors. For patients surviving the first 30 postoperative days, shorter DAOH30 was associated with higher 1-yr mortality (odds ratio=0.94; 95% credible interval, 0.94-0.94). CONCLUSION: DAOH is a valid, patient-centred outcome after emergency laparotomy. We recommend its use in clinical trials, quality assurance, and quality improvement, measured at 30 days as mortality heavily skews DAOH measured at 90 days and beyond.


Subject(s)
Hospitalization/statistics & numerical data , Hospitals/supply & distribution , Laparotomy/statistics & numerical data , Outcome Assessment, Health Care/statistics & numerical data , Adolescent , Adult , Aged , Aged, 80 and over , Bayes Theorem , England , Female , Humans , Male , Middle Aged , Patient Readmission/statistics & numerical data , Retrospective Studies , Risk Factors , Time Factors , Treatment Outcome , Young Adult
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