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Health-related quality of life after critical care—the emperor’s new clothes

Background

Early in the 1970s, studies about critical care started to focus on outcome measures other than mortality, as mortality rates had decreased, and it now only was relevant to a smaller number of patients, i.e., those dying [1]. Ever since, health-related quality of life (HRQoL) has been examined extensively and most researchers have stressed that it is significantly affected by having undergone critical care treatment [2].

Assessing long-term outcomes for ICU patients, there is a distinct reduction in HRQoL (mainly physical), which usually has recovered 6 months later for a majority of the patient [3, 4], albeit there are subgroups with remaining issues [5, 6]. This is significantly less pronounced for the mental and social well-being in most patients which reaches long-term levels (about 20–30% lower than those in most corresponding control populations) as early as 2 months after leaving hospital [4, 7, 8]. However, it is important to acknowledge that the SF-36 instrument most commonly used for HRQoL assessment is less specific, as compared to other instruments to depict mental disorders [5]. Attempts to adjust for this have been done using more specific instruments in the severely injured burns patients and a similar outcome as seen for SF-36 mental dimensions has been claimed [7].

Many studies indicate that comparing post-ICU patients with a regular, control population is not always adequate [7]. There are several reasons for this. The theory that a substantial reduction in HRQoL is caused by critical care treatment has been supported in the past by the exclusion of comorbidities and other pre-morbid factors. This misconception may be analogous to the tale of “The emperor’s new clothes.”Footnote 1 (Fig. 1).

Fig. 1
figure1

Figure illustrating the problem with lack of knowledge of the patients’ habitual HRQoL before the ICU period, the “pre-ICU gap,” when assessing the HRQoL after the ICU stay, the “post ICU gap.” Compared to the general population many, ICU patients have lower HQoL prior to ICU, due to both constitutional patient factors and factors related to the current disease requiring intensive care

Critical appraisal

So, what supports the supposition that ICU time only has a limited effect on the long-term HRQoL for the majority of ICU patients?

First, and most importantly, a recurring flaw in this evaluation is that ICU patients are being compared with healthy controls or a population lacking comorbidities.

Second, the time spent in ICU is bound to worsen pre-existing comorbidities or “frailty” recorded before ICU care [9].

Third, in ICU subgroups HRQoL, such seen for patients with COPD, no effect can be found when comparing it with that of patients with the same stage of COPD disease who have not been treated in ICU [10]. This is further supported by the finding that there was no difference in HRQoL when a comparison is made between patients treated in ICU compared to a disease-stratified hospitalized control population [11].

Fourth, a recent important finding is that a considerable portion of ICU patients (about 15%) is diagnosed with a chronic health condition while in ICU [12]. This leads to a combined number of comorbidities of former ICU patients, added to the 75% prevalence prior to the ICU period and, then reaching up to almost 90%, in total. It is also well shown that the pre ICU health trajectory can be extrapolated to the post ICU period [13].

Fifth, a significant portion of the studies does not include adjustments for age and sex [3]. Age adjustment is important, not least when comorbidities are not included because there is a clear collinearity between the two [14]. At times, age has even been used as a surrogate for comorbidities. A further problem with this is that in the oldest age group, comorbidities do not increase linearly but, rather, exponentially [14]. An interesting observation is that the HRQoL is good in a previous cohort of octogenarians, but it must then be stressed that this is most certainly a selected cohort, most often with less than “normal” comorbidity profile [6]. Regarding sex, there is a relative overrepresentation of single men in ICU. Single men have been shown as an independent risk factor for reduced HRQoL [7, 8].

Sixth, in studies adjusting for comorbidities, small effects on the outcome can be related to classic factors in intensive care (such as length of stay (LoS), SAPS3, APACHE IV, and time on a ventilator) [7]. Even in the case of PTSD, it was concluded that the most important risk factor for PTSD after a stay in ICU is the existence of a psychiatric diagnosis beforehand [12, 15].

Despite this, many studies of HRQoL after critical illness still lack analysis of comorbidities.

Finally, Skandinavian ICU LoS, as elsewhere, is relatively short for the majority of patients. One may wonder, can LoS as brief as a couple of days (median of less than 2) have an important impact on HRQoL that can last for 5 years? When longer LoS are included, which then constitutes a smaller portion of all ICU patients, little effect of LoS can be related to the reduced level of HRQoL [7]. The less-pronounced, negative impact of LoS is also seen in patients with burns. These patients, the majority of which is younger, stay considerably longer in ICU and have more instances of organ failure. Despite all of this, there are appreciable difficulties in showing an effect on their HRQoL as a result of the time spent in ICU when comorbidities are adjusted for.

The general ICU population has a plethora of specific diseases, each of which has its own particular characteristics and that will affect patients. A rational approach would be to assess long-term outcomes on this basis with person-centered measures that will discriminate between the disease-specific symptoms from the individual problems of the patients and which are looked for in risk (decreased HRQoL) prone subgroups.

Conclusion

In conclusion, little of the final outcome in HRQoL for a majority of ICU patients can be connected to critical care itself. Instead, the most important effect on each individual is the result of their comorbidities or chronic conditions. Having said this, it needs to be stressed that there are subgroups that have ICU-related HRQoL effects that still deserve attention such as long-term ICU patients with, e.g., ARDS.

Availability of data and materials

Only referencing previous work.

Notes

  1. 1.

    An idiomatic expression from the Danish fairy tale by Hans Christian Andersen that no one dares to tell the obvious truth if it is contradictory to what everyone else is saying is right, at the risk of being considered ignorant.

References

  1. 1.

    Cullen DJ, Ferrara LC, Briggs BA, Walker PF, Gilbert J. Survival, hospitalization charges and follow-up results in critically ill patients. N Engl J Med. 1976;294(18):982–7.

    CAS  Article  Google Scholar 

  2. 2.

    Turnbull AE, Rabiee A, Davis WE, Nasser MF, Venna VR, Lolitha R, Hopkins RO, Bienvenu OJ, Robinson KA, Needham DM. Outcome measurement in ICU survivorship research from 1970 to 2013: a scoping review of 425 publications. Crit Care Med. 2016;44(7):1267–77.

    Article  Google Scholar 

  3. 3.

    Oeyen SG, Vandijck DM, Benoit DD, Annemans L, Decruyenaere JM. Quality of life after intensive care: a systematic review of the literature. Crit Care Med. 2010;38(12):2386–400.

    Article  Google Scholar 

  4. 4.

    Flaatten H, Kvale R. Survival and quality of life 12 years after ICU. A comparison with the general Norwegian population. Intensive Care Med. 2001;27(6):1005–11.

    CAS  Article  Google Scholar 

  5. 5.

    Hopkins RO, Weaver LK, Pope D, Orme JF, Bigler ED, Larson LV. Neuropsychological sequelae and impaired health status in survivors of severe acute respiratory distress syndrome. Am J Respir Crit Care Med. 1999;160(1):50–6.

    CAS  Article  Google Scholar 

  6. 6.

    Hofhuis JGM, van Stel HF, Schrijvers AJP, Rommes JH, Spronk PE. Changes of health-related quality of life in critically ill octogenarians: a follow-up study. Chest. 2011;140(6):1473–83.

    Article  Google Scholar 

  7. 7.

    Orwelius L, Fredrikson M, Kristenson M, Walther S, Sjoberg F. Health-related quality of life scores after intensive care are almost equal to those of the normal population: a multicenter observational study. Crit Care. 2013;17(5):R236.

    Article  Google Scholar 

  8. 8.

    Orwelius L, Willebrand M, Gerdin B, Ekselius L, Fredrikson M, Sjoberg F. Long term health-related quality of life after burns is strongly dependent on pre-existing disease and psychosocial issues and less due to the burn itself. Burns. 2013;39(2):229–35.

    CAS  Article  Google Scholar 

  9. 9.

    Bagshaw SM, Stelfox HT, Johnson JA, McDermid RC, Rolfson DB, Tsuyuki RT, Ibrahim Q, Majumdar SR. Long-term association between frailty and health-related quality of life among survivors of critical illness: a prospective multicenter cohort study. Crit Care Med. 2015;43(5):973–82.

    Article  Google Scholar 

  10. 10.

    Berkius J, Engerstrom L, Orwelius L, Nordlund P, Sjoberg F, Fredrikson M, Walther SM. A prospective longitudinal multicentre study of health related quality of life in ICU survivors with COPD. Crit Care. 2013;17(5):R211.

    Article  Google Scholar 

  11. 11.

    Williams TA, McConigley R, Leslie GD, Dobbs GJ, Phillips M, Davies H, Aoun S. A comparison of outcomes among hospital survivors with and without severe comorbidity admitted to the intensive care unit. Anaesth Intensive Care. 2015;43(2):230–7.

    CAS  Article  Google Scholar 

  12. 12.

    van Beusekom I, Bakhshi-Raiez F, de Keizer NF, Dongelmans DA, van der Schaaf M. Reported burden on informal caregivers of ICU survivors: a literature review. Crit Care. 2016;20:16.

    Article  Google Scholar 

  13. 13.

    Prescott HC, Carmichael AG, Langa KM, Gonzalez R, Iwashyna TJ. Paths into sepsis: trajectories of presepsis healthcare use. Ann Am Thorac Soc. 2019;16(1):116–23.

    Article  Google Scholar 

  14. 14.

    Charlson M, Wells MT, Ullman R, King F, Shmukler C. The Charlson comorbidity index can be used prospectively to identify patients who will incur high future costs. PLoS One. 2014;9(12):e112479.

    Article  Google Scholar 

  15. 15.

    Paparrigopoulos T, Melissaki A, Tzavellas E, Karaiskos D, Ilias I, Kokras N. Increased co-morbidity of depression and post-traumatic stress disorder symptoms and common risk factors in intensive care unit survivors: a two-year follow-up study. Int J Psychiatry Clin Pract. 2014;18(1):25–31.

    Article  Google Scholar 

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Acknowledgements

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The work was supported by funding from Linköping University and the Östergötland County Council.

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All three authors have contributed to the writing process. The authors read and approved the final manuscript.

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Correspondence to Folke Sjöberg.

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Sjöberg, F., Orwelius, L. & Berg, S. Health-related quality of life after critical care—the emperor’s new clothes. Crit Care 24, 308 (2020). https://doi.org/10.1186/s13054-020-03012-3

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