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Decision making in emergency laparotomy: the role of predicted life expectancy.

ABSTRACT: Increasing numbers of older patients are undergoing emergency laparotomy (EL). They are at increased risk of adverse outcomes, making the shared decision on whether to operate challenging. This retrospective cohort study aimed to assess the role of age and life-expectancy predictions on short- and long-term survival in patients undergoing EL. All patients who underwent EL at one hospital in the West of Scotland between March 2014 to December 2016 were included. Clinical parameters were collected, and patients were followed up to allow reporting of 30-, 60- and 90-day and 1-year mortality rates. Period life expectancy was used to stratify patients into below life expectancy (bLEP) and at-or-above life expectancy (aLEP) groups at presentation. Remaining life expectancy was used to calculate the net years of life gained (NYLG). Some 462 patients underwent EL: 20 per cent in the aLEP group. These patients were older (P < 0.001), had more co-morbidities (P < 0.001) and were high risk on P-POSSUM scoring (P = 0.008). The 30-, 60- and 90-day and 1-year mortality rates were 11, 14, 16 and 23 per cent respectively. Advanced age (P = 0.011) and high ASA score (P = 0.004) and P-POSSUM score (P < 0.001) were independent predictors of death at 1 year on multivariable analysis. The cohort NYLG were 19.2 years. Comparing patients aged less than 70 with those aged 70 years or older, the NYLG were 25.9 versus 5.5 years. Comparing bLEP and aLEP, the NYLG were 22.2 versus 4.4 years. In patients aged 70 years and older, NYLG decreased by more than half in patients with co-morbidities (ASA score 3,4,5) (9.3 versus 4.3 years). Discussions around long-term outcomes after emergency surgery remain difficult. Although age is an influencing factor, predicted life expectancy alone does not provide additional value to shared decision making.

SUBMITTER: Choong JX

PROVIDER: S-EPMC8504444 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ImportanceDespite clinical practice guidelines recommending against routine cancer screening in older adults with limited life expectancy, older adults are still frequently screened for breast, colorectal, and prostate cancers.ObjectiveTo examine primary care clinicians' decision-making on stopping breast, colorectal, or prostate cancer screening in older adults with limited life expectancy.Design, setting, and participantsIn qualitative interviews coupled with medical record-stimulated recall, clinicians from 17 academic and community clinics affiliated with a large health system were asked how they came to specific cancer screening decisions in 2 or 3 of their older patients with less than 10-year of estimated life expectancy, including patients with and without recent screening. Patients were surveyed by telephone. Data collection occurred between October 2018 and May 2019.Main outcomes and measuresClinician interviews were audio-recorded and transcribed verbatim. Transcripts were analyzed with qualitative content analysis to identify major themes. Patient surveys assessed perception of cancer screening decisions, importance of clinician recommendation, and willingness to stop screening.ResultsTwenty-five primary care clinicians (mean [SD] age, 47.1 [9.7] years; 14 female [56%]) discussed 53 patients during medical record-stimulated recall, ranging from 2 to 3 patients per clinician; 46 patients and 1 caregiver (mean [SD] age 74.9 [5.4]; 31 female [66%]) participated in the survey. Clinician interviews revealed 5 major themes: (1) cancer screening decisions were not always conscious, deliberate decisions; (2) electronic medical record alerts were connected with less deliberate decision-making; (3) cancer screening was not binary and clinicians often considered other options to scale back screening without actually stopping; (4) in addition to patient characteristics, clinicians were influenced by patient request and anecdotal experiences; and (5) influences outside of the primary care clinician-patient dyad were important, such as from specialists and patients' family or friends. Patient surveys asked approximately 64 cancer screening decisions of 47 patients. Patients did not recall approximately half (31 of 64) of their cancer screening decisions. Among those with recent screening, the mean score for willingness to stop screening was 3.2 (95% CI 2.5-3.9) on a 5-point Likert scale (with 1 indicating "extremely unlikely" and 5 indicating "extremely likely"). In most screening decisions that involved specialists (13 of 16), patients valued specialists' recommendations over those of primary care clinicians.Conclusions and relevanceCancer screening decision-making is complex. Study findings suggest that strategies that facilitate more deliberate decision-making may be important in cancer screening of older adults with limited life expectancy.

Project description:In the event of a new infectious disease outbreak, mathematical and simulation models are commonly used to inform policy by evaluating which control strategies will minimize the impact of the epidemic. In the early stages of such outbreaks, substantial parameter uncertainty may limit the ability of models to provide accurate predictions, and policymakers do not have the luxury of waiting for data to alleviate this state of uncertainty. For policymakers, however, it is the selection of the optimal control intervention in the face of uncertainty, rather than accuracy of model predictions, that is the measure of success that counts. We simulate the process of real-time decision-making by fitting an epidemic model to observed, spatially-explicit, infection data at weekly intervals throughout two historical outbreaks of foot-and-mouth disease, UK in 2001 and Miyazaki, Japan in 2010, and compare forward simulations of the impact of switching to an alternative control intervention at the time point in question. These are compared to policy recommendations generated in hindsight using data from the entire outbreak, thereby comparing the best we could have done at the time with the best we could have done in retrospect. Our results show that the control policy that would have been chosen using all the data is also identified from an early stage in an outbreak using only the available data, despite high variability in projections of epidemic size. Critically, we find that it is an improved understanding of the locations of infected farms, rather than improved estimates of transmission parameters, that drives improved prediction of the relative performance of control interventions. However, the ability to estimate undetected infectious premises is a function of uncertainty in the transmission parameters. Here, we demonstrate the need for both real-time model fitting and generating projections to evaluate alternative control interventions throughout an outbreak. Our results highlight the use of using models at outbreak onset to inform policy and the importance of state-dependent interventions that adapt in response to additional information throughout an outbreak.

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Decision making in emergency laparotomy: the role of predicted life expectancy.

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