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. 2022 Jul 15;22(1):584.
doi: 10.1186/s12877-022-03274-2.

Performance of the APOP-screener for predicting in-hospital mortality in older COVID-19 patients: a retrospective study

Marleen G A M van der Velde #  1   2 , Merel J van der Aa #  3 , Merel H C van Daal  4 , Marjolein N T Kremers  4   5   6 , Carolina J P W Keijsers  3 , Sander M J van Kuijk  7 , Harm R Haak  4   5   8
Affiliations

Performance of the APOP-screener for predicting in-hospital mortality in older COVID-19 patients: a retrospective study

Marleen G A M van der Velde et al. BMC Geriatr. .

Abstract

Background: A variety of prediction models concerning COVID-19 have been proposed since onset of the pandemic, but to this date no gold standard exists. Mortality rates show a sharp increase with advancing age but with the large heterogeneity of this population in terms of comorbidities, vulnerability and disabilities, identifying risk factors is difficult. Therefore, we aimed to research the multidimensional concept of frailty, measured by the Acute Presenting Older Patient (APOP)-screener, as a risk factor for in-hospital mortality in older COVID-19 patients.

Methods: All consecutive patients of 70 years or older, with a PCR confirmed COVID-19 infection and a completed APOP-score, presenting at the Emergency Department (ED) of the Jeroen Bosch Hospital, the Netherlands, between February 27th 2020 and February 1st 2021 were retrospectively included. We gathered baseline characteristics and scored the CCI and CFS from patient records. The primary outcome was in-hospital mortality.

Results: A total of 292 patients met the inclusion criteria. Approximately half of the patients were considered frail by the APOP or CFS. 127 patients (43.5%) scored frail on the CFS, 158 (54.1%) scored high risk on the APOP-screener. 79 patients (27.1%) died during their hospital admission. The APOP-screener showed a significantly elevated risk of in-hospital mortality when patients scored both high risk of functional and evidence of cognitive impairment (OR 2.24, 95% 1.18-4.25). Significant elevation of in-hospital mortality was found for the high CCI-scores (≥ 5)(OR 1.78, 95% 1.02-3.11), but not for the highest CFS category (5-9, frail) (OR 1.35, 95% 0.75-2.47). The discriminatory performance of the APOP, CFS and CCI were comparable (AUC resp. 0.59 (0.52-0.66), 0.54 (0.46-0.62) and 0.58 (0.51-0.65)).

Conclusion: Although the elevated risk for in-hospital mortality found for the most frail patients as scored by the APOP, this instrument has poor discriminatory value. Additionally, the CFS did not show significance in predicting in-hospital mortality and had a poor discriminatory value as well. Therefore, treatment decisions based on frailty or comorbidities alone should be made with caution. Approaching the heterogeneity of the older population by adding frailty as assessed by the APOP-score to existing prediction models may enhance the predictive value of these models.

Keywords: COVID-19; Frailty; Mortality; Predictive; SARS-Cov2.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Subdivisions of the clinical frailty scores within the APOP-screener categories. APOP: Acute Presenting Older Patient. The four pie charts correlate with the four possible outcomes of the APOP-screener. The subdivisions within the pie chart consist of the distribution of frailty when assessed following the Clinical Frailty Scale
See this image and copyright information in PMC

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References

    1. Yang J, Tian C, Chen Y, Zhu C, Chi H, Li J. Obesity aggravates COVID-19: an updated systematic review and meta-analysis. J Med Virol. 2020;93(5):2662–2674. doi: 10.1002/jmv.26677. - DOI - PMC - PubMed
    1. Booth A, Reed AB, Ponzo S, Yassaee A, Aral M, Plans D, et al. Population risk factors for severe disease and mortality in COVID-19: a global systematic review and meta-analysis. PLoS One. 2021;16(3):e0247461. doi: 10.1371/journal.pone.0247461. - DOI - PMC - PubMed
    1. Patel U, Malik P, Mehta D, Shah D, Kelkar R, Pinto C, et al. Early epidemiological indicators, outcomes, and interventions of COVID-19 pandemic: a systematic review. J Glob Health. 2020;10(2):020506. doi: 10.7189/jogh.10.020506. - DOI - PMC - PubMed
    1. Zhou Y, Yang Q, Chi J, Dong B, Lv W, Shen L, et al. Comorbidities and the risk of severe or fatal outcomes associated with coronavirus disease 2019: a systematic review and meta-analysis. Int J Infect Dis. 2020;99:47–56. doi: 10.1016/j.ijid.2020.07.029. - DOI - PMC - PubMed
    1. Izcovich A, Ragusa MA, Tortosa F, Lavena Marzio MA, Agnoletti C, Bengolea A, et al. Prognostic factors for severity and mortality in patients infected with COVID-19: a systematic review. PLoS One. 2020;15(11):e0241955. doi: 10.1371/journal.pone.0241955. - DOI - PMC - PubMed