Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Feb 23;11(5):650.
doi: 10.3390/healthcare11050650.

Long-Term Evolution of Activities of Daily Life (ADLs) in Critically Ill COVID-19 Patients, a Case Series

Samuele Ceruti  1 , Andrea Glotta  1 , Maira Biggiogero  2 , Martino Marzano  3 , Giovanni Bona  2 , Marco Previsdomini  4 , Andrea Saporito  5 , Xavier Capdevila  6
Affiliations

Long-Term Evolution of Activities of Daily Life (ADLs) in Critically Ill COVID-19 Patients, a Case Series

Samuele Ceruti et al. Healthcare (Basel). .

Abstract

Background: The most common long-term symptoms of critically ill COVID-19 patients are fatigue, dyspnea and mental confusion. Adequate monitoring of long-term morbidity, mainly analyzing the activities of daily life (ADLs), allows better patient management after hospital discharge. The aim was to report long-term ADL evolution in critically ill COVID-19 patients admitted to a COVID-19 center in Lugano (Switzerland).

Methods: A retrospective analysis on consecutive patients discharged alive from ICU with COVID-19 ARDS was performed based on a follow-up one year after hospital discharge; ADLs were assessed through the Barthel index (BI) and the Karnofsky Performance Status (KPS) scale. The primary objective was to assess differences in ADLs at hospital discharge (acute ADLs) and one-year follow-up (chronic ADLs). The secondary objective was to explore any correlations between ADLs and multiple measures at admission and during the ICU stay.

Results: A total of 38 consecutive patients were admitted to the ICU; a t-test analysis between acute and chronic ADLs through BI showed a significant improvement at one year post discharge (t = -5.211, p < 0.0001); similarly, every single task of BI showed the same results (p < 0.0001 for each task of BI). The mean KPS was 86.47 (SD 20.9) at hospital discharge and 99.6 at 1 year post discharge (p = 0.02). Thirteen (34%) patients deceased during the first 28 days in the ICU; no patient died after hospital discharge.

Conclusions: Based on BI and KPS, patients reached complete functional recovery of ADLs one year after critical COVID-19.

Keywords: Barthel index; Karnofsky Performance Status; PICS; SARS-CoV-2; activities of daily life; functional status; post-acute COVID-19 syndrome.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Patients’ distribution flowchart. Critically ill COVID-19 patients’ distribution according to temporal evolution. No patient died during the follow-up period.
Figure 2
Figure 2
Temporal evolution of ADLs according to Barthel index. Temporal evolution of single activity of daily life (ADLs) comparing acute ADLs (red bar) and chronic ADLs (blue bar) with their specific statistical significance.
Figure 3
Figure 3
Linear regression of acute Barthel index. Linear regressions of Barthel index at hospital discharge compared to age, ICU LOS, days of MV and admitting SOFA score. ICU LOS = intensive care unit length of stay, MV = mechanical ventilation and SOFA = Sequential Organ Failure Assessment.
Figure 4
Figure 4
Analysis of boxplot of Barthel index. Boxplot stratification of Barthel index at hospital discharge comparing patients with OSAS, invasive MV and the presence of other infections. OSAS = obstructive sleep apnea syndrome and MV = mechanical ventilation.
See this image and copyright information in PMC

References

    1. Phelan A.L., Katz R., Gostin L.O. The Novel Coronavirus Originating in Wuhan, China: Challenges for Global Health Governance. JAMA J. Am. Med. Assoc. 2020;323:709–710. doi: 10.1001/jama.2020.1097. - DOI - PubMed
    1. Grasselli G., Pesenti A., Cecconi M. Critical Care Utilization for the COVID-19 Outbreak in Lombardy, Italy: Early Experience and Forecast during an Emergency Response. JAMA J. Am. Med. Assoc. 2020;323:1545–1546. doi: 10.1001/jama.2020.4031. - DOI - PubMed
    1. Adhikari S.P., Meng S., Wu Y.J., Mao Y.P., Ye R.X., Wang Q.Z., Sun C., Sylvia S., Rozelle S., Raat H., et al. Epidemiology, causes, clinical manifestation and diagnosis, prevention and control of coronavirus disease (COVID-19) during the early outbreak period: A scoping review. Infect. Dis. Poverty. 2020;9:29. doi: 10.1186/s40249-020-00646-x. - DOI - PMC - PubMed
    1. Johns Hopkins Coronavirus Resource Center Cumulative Cases-Johns Hopkins Coronavirus Resource Center. [(accessed on 1 June 2022)]. Available online: https://coronavirus.jhu.edu/data/cumulative-cases.
    1. Wang D., Hu B., Hu C., Zhu F., Liu X., Zhang J., Wang B., Xiang H., Cheng Z., Xiong Y., et al. Clinical Characteristics of 138 Hospitalized Patients with 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA J. Am. Med. Assoc. 2020;323:1061–1069. doi: 10.1001/jama.2020.1585. - DOI - PMC - PubMed

LinkOut - more resources