Clinical Examination for the Prediction of Mortality in the Critically Ill

The Simple Intensive Care Studies-I

Bart Hiemstra, MD; Ruben J. Eck, MD; Renske Wiersema, BSc; Thomas Kaufmann, MD; Geert Koster, MD; Thomas W.L. Scheeren, MD, PhD; Harold Snieder, PhD; Anders Perner, MD, PhD; Ville Pettilä, MD, PhD; Jørn Wetterslev, MD, PhD; Frederik Keus, MD, PhD; Iwan C.C. van der Horst, MD, PhD; SICS Study Group

Disclosures

Crit Care Med. 2019;47(10):1301-1309. 

In This Article

Discussion

Clinical examination in 1,075 adult patients acutely admitted to the ICU had reasonable prognostic accuracy. Five of the 19 tested clinical examination findings, that is, increased respiratory rate, increased systolic blood pressure, lower core temperature, altered consciousness, and decreased urine output, were independently associated with 90-day mortality. The predictive and discriminative value of a simple clinical examination approached that of the SAPS-II and APACHE-IV and outperformed the SOFA score.

In line with previous studies, we found that clinical signs reflecting cerebral, renal, and skin hypoperfusion were independently associated with mortality in the critically ill.[5,6,11] In our data, severe skin mottling had a suggestively significant association with an OR of 2.48 (95% CI, 1.13–5.44), whereas others who assessed the persistence of skin mottling over time found a stronger association with an OR of 16 (95% CI, 11–1,568)[19] and an OR of 3.29 (95% CI, 2.08–5.19).[4] The independent association of decreased urine output with 90-day mortality confirms findings from the FINNAKI studies.[5,31] Similar to the modified early warning score, an altered consciousness regardless of sedation significantly predicted mortality in the critically ill.[32] All abovementioned variables may reflect the severity of critical illness on the first day of ICU admission and as such identify patients at higher risk for circulatory failure and mortality. An alternative explanation might be that patients with these clinical signs are treated differently.

The reasonable performance of our prediction models on 90-day mortality is in line with previous models derived from similar cohorts.[33] All prognostic scores performed worse than expected from previous literature.[14,15] The inclusion criteria of the SICS-I may explain this discrepancy: we studied 90-day mortality in patients acutely admitted to the ICU, whereas most prognostic scores perform best in evaluating in-hospital mortality or specific populations such as patients with trauma or suspected infection.[34,35] The use of an unselected population may produce unbiased risk estimates and increases external validity.[24] The main disadvantage of this approach is that average associations may be neutral or balanced out by different characteristics in different subgroups. The secondary analyses in clinically different subgroups were conducted to explore such associations: for example, a high systolic blood pressure was no longer independently associated with mortality in patients requiring vasopressors or in patients with septic shock (eTable 9, Supplemental Digital Content 2, http://links.lww.com/CCM/E746).

Implications and Generalizability

The SICS-I provides evidence that a thorough clinical examination conducted on the first day of ICU admission may be used to obtain a rough estimation of 90-day mortality. By establishing the prognostic value of 19 clinical examination findings, we set the first step for a parsimonious clinical examination, that is, the fewest number of clinical signs that yield the most prognostic value.[36] These simple and easily obtainable clinical variables may better inform physicians in their clinical decision making. The examinations were conducted within 24 hours of ICU admission, usually in the morning, and after primary resuscitation efforts. There was no prespecified moment in time for the examination, which may decrease generalizability of the results. Nonetheless, this research practice does reflect daily clinical care where most patients are routinely assessed in the morning, regardless of the time that has passed since ICU admission.

The dynamic care process of the critically ill patient may limit an accurate prediction of 90-day mortality with a single clinical examination or a prognostic score, which reflects a baseline mortality risk based on medical history and findings from the first 24 hours of ICU admission. The clinical status and treatment of a critically ill patient change frequently, and repeated clinical examinations might predict the individual patient prognosis more accurately. Previous studies have already shown that prolonged mechanical ventilation with high pressures or persistently low blood pressures, skin mottling, a decrease in urine output and increasing central-to-peripheral temperature gradients have strong associations with mortality.[4,5,9,37–39] Our clinical examination was limited to a single time point, which could explain why not all these common prognostic variables were also statistically significant in the SICS-I. Future research should study the variation of clinical examination and associated interventions over time to assess its prognostic value.[40]

Strengths and Limitations

The SICS-I was an unselected, single-center cohort of consecutive ICU patients, and its findings require external validation in an independent cohort. To address this limitation, we assessed the robustness of our findings by adjusting for multiple outcomes, conducting multiple imputations and sensitivity analyses, and internally validating each predictive variable by bootstrap sampling. We evaluated a heterogeneous ICU population, and certain prognostic associations may be more pronounced in patient subgroups, which is why we studied clinically relevant subgroups in our secondary analyses. Our findings do not apply to pediatric or electively admitted patients.

The clinical examination findings collected in our study were not shared with caregivers. However, some of these findings (i.e., blood pressure and heart rate) were also assessed by caregivers and may have informed subsequent treatment decisions or were influenced by their interventions. The predictive value of a clinical variable measured at baseline therefore included the value of this variable combined with the subsequent intervention(s) to correct such a value. Since treatment strategies between physicians and countries differ, this fact may explain why different studies identify different predictors of mortality, in addition to population differences and other confounders. The prognostic value of clinical variables will be more transparent in a randomized setting where interventions are given based on different clinical treatment targets.[41,42]

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