Discussion
In this cohort study emotional, social, functional and behavioural
prognostic factors were tested for patients undergoing cardiac surgery.
The principal findings were that 1) living alone predicted both
prolonged ICU stay and death for the total cohort of 3217 patients, and
2) low HRQoL and loneliness (not having someone to talk to) predicted
prolonged hospital stay for the nested cohort of 982 patients undergoing
cardiac surgery. Thus, information on cohabitation status may
potentially be added to existing risk evaluation models due to its
predictive value.
The predictive value of living alone is supported by Murphy &
colleagues who found patients undergoing CABG surgery and living alone,
were more than three times more likely to be readmitted to hospital (OR,
3.42; 95% CI, 1.38– 8.48) than those living with others (32). Being
married, especially being in a highly satisfying marriage, has been
found to offer a significant benefit to long-term survival after CABG
(OR, 2.49; 95% CI, 1.47–4.24) (33). The beneficial effect of
cohabitation and relationship satisfaction on survival is likely
multifactorial, which has been emphasised by earlier studies linking
living alone with poor health outcomes. Patients who are socially
isolated are more likely to smoke and have excessive alcohol intake
(34,35), delay seeking treatment (36), and demonstrate non-compliance
with medical regimens (37), which may be due to a lack of emotional or
practical support gained through living with another person (32).
In earlier studies a feeling of loneliness has been linked to several
adverse health outcomes. For example, endorsing “yes” to “I feel
lonely” was associated with increased 30-day (Rate Ratio (RR), 2.61;
95% CI, 1.15-5.95) and 5-year (RR, 1.78; 95% CI, 1.17-2.71) mortality
among patients undergoing CABG (38) , and a response of “often” to the
question “do you feel lonely” was associated with increased
cardiovascular mortality among elderly Danish men (Hazard Ratio, 1.70;
95% CI, 1.03-2.81) (39).
Several studies agree that HRQoL has become a necessary addition and key
indicator of cardiac surgical outcomes (40–42). This study found that
reduced health-related quality of life predicts prolonged LOS-HOSP. The
predictive value of HRQoL has been confirmed in earlier studies that
have found low HRQoL to be predictive of both mortality following CABG
with a 10 point lower SF-36 Physical Component Summary score having an
OR of 1.39; 95% CI, 1.11-1.77 (43) and of one year cardiac functional
status (OR, 2.73; 95% CI, 1.43–5.23) (44).
For this study the intention was to investigate factors beyond the
clinical indicators and physical health of the patients planned to
undergo cardiac surgery. Traditional risk assessment in cardiac surgery
has been a tool for patient selection and has been aimed at the
perioperative patient pathways. With the proposed supplement the risk
assessment can potentially be used to identify vulnerable groups of
patients leading to improved patient management still with the overall
aim to improve patient outcomes. Information on cohabitation status,
loneliness and HRQoL could potentially be added to existing risk
evaluation models in cardiac surgery. However, further research is
warranted to validate the findings of the current study and to
investigate interventions supporting the identified vulnerable groups of
patients.
Strength and limitations
This study has several
limitations. Firstly, we were restricted to the use of predictor
variables based on existing data measured in previously collected data
sets, which is a beneficial way to make full use of already collected
data to address potentially important new research questions and avoid
disturbing patients unnecessarily. However, we may not have included
important prognostic variables (e.g. cognitive status and frailty),
because they were not measured in the original studies. Secondly, the
present study used corresponding datasets. When doing this there is a
risk that the datasets differ in important aspects, such as baseline
risk. However, in the current study a prediction model was developed for
each dataset reducing bias due to this.
Non-response for the DenHeart study was high at 49% which might bias
the results. Responders and non-responders of the DenHeart study has
earlier been established to be similar regarding socio-demographics,
however, the non-responders were more severely ill, had more comorbidity
and thus a much higher mortality rate compared to responders (45), which
could have resulted in an underestimation of the associations between
the predictor variables and the outcomes .
Imputations were utilised in the present study to maintain the sample
size, assuming the missing values were missing at random. The use of
mean imputations does not affect the estimate of the mean for the
variable; however, it reduces the variance of the imputed variables.
Furthermore, it assumes that the mean value of the respondents was a
good estimate of the missing values, which may have resulted in
conservative bias.
We used an automated stepwise approach to specify the models,
principally due to its objectivity and that it generally results in
smaller, clinically applicable models (46), but stepwise methods have
well-known limitations such as unstable variable selection (47) and
biased coefficient estimation (46). It is therefore conceivable that our
choice to use stepwise selection may have reduced the predictive
performance of the models. The overall model fit statistics indicate
that the variance explained by our prediction models is at best modest.
Perhaps some factors that are yet to be tested thoroughly in cardiac
surgery, for example, frailty and mental state, explain additional
variance in cardiac surgery. Despite the limitations of the study the
models made informative predictions that should be externally validated
in a similar population of patients undergoing cardiac surgery.
Conclusion
We tested several emotional, social, functional and behavioural
prognostic factors as a supplement to EuroSCORE and reported different
aspects of model performance that can be interpreted for further
research applications. Based on the cohorts included, living alone
predicts death, prolonged hospital admission and prolonged ICU stay
following cardiac surgery. Low educational level and impaired HRQoL
were, furthermore found to be predictive of prolonged hospital
admission.