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Delirium severity and outcomes of critically ill COVID-19 patients

ABSTRACT

Objective:

To investigate the impact of delirium severity in critically ill COVID-19 patients and its association with outcomes.

Methods:

This prospective cohort study was performed in two tertiary intensive care units in Rio de Janeiro, Brazil. COVID-19 patients were evaluated daily during the first 7 days of intensive care unit stay using the Richmond Agitation Sedation Scale, Confusion Assessment Method for Intensive Care Unit (CAM-ICU) and Confusion Method Assessment for Intensive Care Unit-7 (CAM-ICU-7). Delirium severity was correlated with outcomes and one-year mortality.

Results:

Among the 277 COVID-19 patients included, delirium occurred in 101 (36.5%) during the first 7 days of intensive care unit stay, and it was associated with a higher length of intensive care unit stay in days (IQR 13 [7 - 25] versus 6 [4 - 12]; p < 0.001), higher hospital mortality (25.74% versus 5.11%; p < 0.001) and additional higher one-year mortality (5.3% versus 0.6%, p < 0.001). Delirium was classified by CAM-ICU-7 in terms of severity, and higher scores were associated with higher in-hospital mortality (17.86% versus 34.38% versus 38.46%, 95%CI, p value < 0.001). Severe delirium was associated with a higher risk of progression to coma (OR 7.1; 95%CI 1.9 - 31.0; p = 0.005) and to mechanical ventilation (OR 11.09; 95%CI 2.8 - 58.5; p = 0.002) in the multivariate analysis, adjusted by severity and frailty.

Conclusion:

In patients admitted with COVID-19 in the intensive care unit, delirium was an independent risk factor for the worst prognosis, including mortality. The delirium severity assessed by the CAM-ICU-7 during the first week in the intensive care unit was associated with poor outcomes, including progression to coma and to mechanical ventilation.

Keywords:
Delirium; COVID-19; Coronavirus infections; Critical illness; Psychiatric status rating scales; Surveys and questionnaires; Risk factors; Prognosis; Critical care outcomes; Intensive care units

RESUMO

Objetivo:

Investigar como a gravidade do delirium afeta pacientes graves com COVID-19 e sua associação com os desfechos.

Métodos:

Estudo de coorte prospectivo realizado em duas unidades de terapia intensiva terciárias no Rio de Janeiro (RJ). Os pacientes com COVID-19 foram avaliados diariamente durante os primeiros 7 dias de internação na unidade de terapia intensiva usando a escala de agitação e sedação de Richmond, a Confusion Assessment Method for Intensive Care Unit (CAM-ICU) e a Confusion Assessment Method for Intensive Care Unit-7 (CAM-ICU-7). A gravidade do delirium foi correlacionada com os desfechos e a mortalidade em 1 ano.

Resultados:

Entre os 277 pacientes com COVID-19 incluídos, o delirium ocorreu em 101 (36,5%) durante os primeiros 7 dias de internação na unidade de terapia intensiva e foi associado a maior tempo de internação na unidade de terapia intensiva em dias (IQ: 13 [7 - 25] versus 6 [4 - 12]; p < 0,001), maior mortalidade hospitalar (25,74% versus 5,11%; p < 0,001) e maior mortalidade em 1 ano (5,3% versus 0,6%, p < 0,001). O delirium foi classificado pela CAM-ICU-7 em termos de gravidade, e escores maiores foram associados à maior mortalidade hospitalar (17,86% versus 34,38% versus 38,46%, IC95%, valor de p < 0,001). O delirium grave foi associado a um risco maior de progressão ao coma (RC de 7,1; IC95% 1,9 - 31,0; p = 0,005) e à ventilação mecânica (RC de 11,09; IC95% 2,8 - 58,5; p = 0,002) na análise multivariada, ajustada por gravidade e fragilidade

Conclusão:

Em pacientes internados com COVID-19 na unidade de terapia intensiva, o delirium foi fator de risco independente para o pior prognóstico, incluindo mortalidade. A gravidade do delirium avaliada pela CAM-ICU-7 durante a primeira semana na unidade de terapia intensiva foi associada a desfechos desfavoráveis, incluindo a progressão ao coma e à ventilação mecânica.

Descritores:
Delirium; COVID-19; Infecções por coronavírus; Estado terminal; Escalas de graduação psiquiátrica; Inquéritos e questionários; Fatores de risco; Prognóstico; Resultado de cuidados críticos; Unidades de terapia intensiva

INTRODUCTION

In addition to pulmonary manifestations and acute respiratory failure, novel coronavirus disease 2019 (COVID-19) may cause neurological conditions,(11 Helms J, Kremer S, Merdji H, Clere-Jehl R, Schenck M, Kummerlen C, et al. Neurologic features in severe SARS-CoV-2 infection. N Engl J Med. 2020;382(23):2268-70.) including encephalopathy, delirium, and coma.(22 Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, Liu L, Shan H, Lei CL, Hui DSC, Du B, Li LJ, Zeng G, Yuen KY, Chen RC, Tang CL, Wang T, Chen PY, Xiang J, Li SY, Wang JL, Liang ZJ, Peng YX, Wei L, Liu Y, Hu YH, Peng P, Wang JM, Liu JY, Chen Z, Li G, Zheng ZJ, Qiu SQ, Luo J, Ye CJ, Zhu SY, Zhong NS; China Medical Treatment Expert Group for Covid-19. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;382(18):1708-20.

3 Helms J, Kremer S, Merdji H, Schenck M, Severac F, Clere-Jehl R, et al. Delirium and encephalopathy in severe COVID-19: a cohort analysis of ICU patients. Crit Care. 2020;24(1):491.

4 Mao L, Jin H, Wang M, Hu Y, Chen S, He Q, et al. Neurologic manifestations of hospitalized patients with coronavirus disease 2019 in Wuhan, China. JAMA Neurol. 2020;77(6):683-90.
-55 Khan SH, Lindroth H, Perkins AJ, Jamil Y, Wang S, Roberts S, et al. Delirium incidence, duration, and severity in critically ill patients with coronavirus disease 2019. Crit Care Explor. 2020;2(12):e0290.) A direct effect of the virus on the central nervous system, the release of inflammatory cytokines, and the activation of the coagulation cascade are some of the underlying mechanisms for neurological complications of COVID-19.(66 Frontera JA, Melmed K, Fang T, Granger A, Lin J, Yaghi S, et al. Toxic metabolic encephalopathy in hospitalized patients with COVID-19. Neurocrit Care. 2021;35(3):693-706.) Moreover, critically ill COVID-19 patients are frequently exposed to hypoxemia, deep sedation, systemic corticosteroids,(33 Helms J, Kremer S, Merdji H, Schenck M, Severac F, Clere-Jehl R, et al. Delirium and encephalopathy in severe COVID-19: a cohort analysis of ICU patients. Crit Care. 2020;24(1):491.,77 Alhazzani W, Møller MH, Arabi YM, Loeb M, Gong MN, Fan E, et al. Surviving Sepsis Campaign: guidelines on the management of critically ill adults with Coronavirus Disease 2019 (COVID-19). Intensive Care Med. 2020;46(5):854-87.) restrictions on family visits and prolonged mechanical ventilation (VM),(88 Ely EW, Inouye SK, Bernard GR, Gordon S, Francis J, May L, et al. Delirium in mechanically ventilated patients: validity and reliability of the confusion assessment method for the intensive care unit (CAM-ICU). JAMA. 2001;286(21):2703-10.) which are well-described risk factors for the occurrence of persistent delirium in intensive care unit (ICU) patients.(33 Helms J, Kremer S, Merdji H, Schenck M, Severac F, Clere-Jehl R, et al. Delirium and encephalopathy in severe COVID-19: a cohort analysis of ICU patients. Crit Care. 2020;24(1):491.,99 Andrews PS, Wang S, Perkins AJ, Gao S, Khan S, Lindroth H, et al. Relationship between intensive care unit delirium severity and 2-year mortality and health care utilization. Am J Crit Care. 2020;29(4):311-7.

10 Andrews LJ, Benken ST. COVID-19: ICU delirium management during SARS-CoV-2 pandemic - pharmacological considerations. Crit Care. 2020;24(1):375.
-1111 Burry LD, Cheng W, Williamson DR, Adhikari NK, Egerod I, Kanji S, et al. Pharmacological and non pharmacological interventions to prevent delirium in critically ill patients: a systematic review and network meta analysis. Intensive Care Med. 2021;47(9):943-60.) Delirium occurrence has a well-documented association with worse patient outcomes, such as increased ICU length of stay (LOS), cognitive decline, depression, postintensive care syndrome and higher short-term mortality.(1212 Uginet M, Breville G, Assal F, Lövblad KO, Vargas MI, Pugin J, et al. COVID-19 encephalopathy: clinical and neurobiological features. J Med Virol. 2021;93(7):4374-81.

13 Stollings JL, Kotfis K, Chanques G, Pun BT, Pandharipande PP, Ely EW. Delirium in critical illness: clinical manifestations, outcomes, and management. Intensive Care Med. 2021;47(10):1089-103.
-1414 Grasselli G, Greco M, Zanella A, Albano G, Antonelli M, Bellani G, Bonanomi E, Cabrini L, Carlesso E, Castelli G, Cattaneo S, Cereda D, Colombo S, Coluccello A, Crescini G, Forastieri Molinari A, Foti G, Fumagalli R, Iotti GA, Langer T, Latronico N, Lorini FL, Mojoli F, Natalini G, Pessina CM, Ranieri VM, Rech R, Scudeller L, Rosano A, Storti E, Thompson BT, Tirani M, Villani PG, Pesenti A, Cecconi M; COVID-19 Lombardy ICU Network. Risk factors associated with mortality among patients with COVID-19 in intensive care units in Lombardy, Italy. JAMA Intern Med. 2020;180(10):1345-55.) Severity and duration of delirium are also independently associated with higher mortality and morbidity in the ICU.(1515 Salluh JI, Wang H, Schneider EB, Nagaraja N, Yenokyan G, Damluji A, et al. Outcome of delirium in critically ill patients: systematic review and meta-analysis. BMJ. 2015;350:h2538.,1616 Serafim RB, Soares M, Bozza FA, Lapa E Silva JR, Dal-Pizzol F, Paulino MC, et al. Outcomes of subsyndromal delirium in ICU: a systematic review and meta-analysis. Crit Care. 2017;21(1):179.)

Although there are many studies assessing the incidence and impact of delirium in critically ill COVID-19 patients,(1414 Grasselli G, Greco M, Zanella A, Albano G, Antonelli M, Bellani G, Bonanomi E, Cabrini L, Carlesso E, Castelli G, Cattaneo S, Cereda D, Colombo S, Coluccello A, Crescini G, Forastieri Molinari A, Foti G, Fumagalli R, Iotti GA, Langer T, Latronico N, Lorini FL, Mojoli F, Natalini G, Pessina CM, Ranieri VM, Rech R, Scudeller L, Rosano A, Storti E, Thompson BT, Tirani M, Villani PG, Pesenti A, Cecconi M; COVID-19 Lombardy ICU Network. Risk factors associated with mortality among patients with COVID-19 in intensive care units in Lombardy, Italy. JAMA Intern Med. 2020;180(10):1345-55.,1717 Westphal GA, Fernandes RP, Pereira AB, Moerschberger MS, Pereira MR, Gonçalves AR. Incidence of delirium in critically ill patients with and without COVID-19. J Intensive Care Med. 2023;38(8):751-9.,1818 Williamson CA, Faiver L, Nguyen AM, Ottenhoff L, Rajajee V. Incidence, predictors and outcomes of delirium in critically ill patients with COVID-19. Neurohospitalist. 2022;12(1):31-7.) few have focused on delirium severity in this setting.(55 Khan SH, Lindroth H, Perkins AJ, Jamil Y, Wang S, Roberts S, et al. Delirium incidence, duration, and severity in critically ill patients with coronavirus disease 2019. Crit Care Explor. 2020;2(12):e0290.,1313 Stollings JL, Kotfis K, Chanques G, Pun BT, Pandharipande PP, Ely EW. Delirium in critical illness: clinical manifestations, outcomes, and management. Intensive Care Med. 2021;47(10):1089-103.,1919 Kotfis K, Witkiewicz W, Szylińska A, Witkiewicz K, Nalewajska M, Feret W, et al. Delirium severely worsens outcome in patients with covid-19-a retrospective cohort study from temporary critical care hospitals. J Clin Med. 2021;10(13):2974.) Therefore, the aim of the present study is to investigate the impact of delirium severity in critically ill COVID-19 patients and its association with the main outcomes.

METHODS

Study design and participants

We conducted a prospective cohort study in the ICUs of two tertiary hospitals in Rio de Janeiro, Brazil, between May 1st and 31st August 2020. All adult patients admitted with clinical and radiological suspicion of COVID-19 were evaluated daily during the first seven days of ICU stay. Subsequently, according to the results of the polymerase chain reaction (PCR) tests, we excluded and removed patients with negative results from the analysis. Only those with a confirmed diagnosis of coronavirus infection by a positive PCR for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in nasopharynx and oropharynx swabs were included in the study. Exclusion criteria were inability to collaborate with the delirium assessment (deafness, amaurosis, previous severe dementia or other severe cognitive impairment), persistence of coma (defined by Richmond Agitation-Sedation Scale [RASS] -4 and -5 in first week of admission) and a previous decision of palliative care. Patients who could not be evaluated in the first 24 hours of ICU stay were also excluded. A flowchart of patient inclusion is provided in figure 1.

Figure 1
Flowchart of the inclusion of patients.

The study was approved by the Research Ethics Committee (Instituto D’Or de Pesquisa e Ensino, CAAE 17079119.7.0000.5249), with a waiver in the application of informed consent due to the observational nature of the study.

Data collection

Demographic and clinical data were collected prospectively from the charts, electronic records or patient proxies, including the date of symptom onset and presence of comorbidities (dementia or cognitive deficit, diabetes mellitus, chronic obstructive pulmonary disease, alcoholism, systemic arterial hypertension, heart failure, immunosuppression or active cancer, chronic kidney disease or obesity). The E-predeliric,(2020 Wassenaar A, van den Boogaard M, van Achterberg T, Slooter AJ, Kuiper MA, Hoogendoorn ME, et al. Multinational development and validation of an early prediction model for delirium in ICU patients. Intensive Care Med. 2015;41(6):1048-56.) Charlson Comorbidities Index (CCI),(2121 Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-83.) modified Frailty Index (m-FI)(2222 Farhat JS, Falvo AJ, Horst HM, Swartz A, Velanovich V, Patton JH, et al. Are the frail destined to fail?: Frailty index as a predictor of surgical morbidity and mortality in the elderly. J Am Coll Surg. 2011;213(3S):S65.) and Simplified Acute Physiology Score 3 (SAPS 3)(2323 Jahn M, Rekowski J, Gerken G, Kribben A, Canbay A, Katsounas A. The predictive performance of SAPS 2 and SAPS 3 in an intermediate care unit for internal medicine at a German university transplant center; A retrospective analysis. PLoS One. 2019;14(9):e0222164.) on admission were calculated and recorded. During the first seven days of ICU stay, the RASS,(2424 Sessler CN, Gosnell MS, Grap MJ, Brophy GM, O’Neal PV, Keane KA, et al. The Richmond Agitation-Sedation Scale: validity and reliability in adult intensive care unit patients. Am J Respir Crit Care Med. 2002;166(10):1338-44.) Confusion Assessment Method for the ICU (CAM-ICU)(2525 Ely EW, Margolin R, Francis J, May L, Truman B, Dittus R, et al. Evaluation of delirium in critically ill patients: validation of the Confusion Assessment Method for the intensive Care Unit (CAM-ICU). Crit Care Med. 2001;29(7):1370-9.) and Confusion Assessment Method for the ICU-7 (CAM-ICU-7, a validated delirium severity 7-point scale that graduates and sums each component of the CAM-ICU);(2626 Khan BA, Perkins AJ, Gao S, et al. The confusion assessment method for the ICU-7 delirium severity scale: A novel delirium severity instrument for use in the ICU. Crit Care Med. 2017;45(5):851-857.) the use of systemic corticosteroids, sedatives, and antipsychotics; and laboratory data and Sequential Organ Failures Assessment (SOFA)(2727 Moreno R, Vincent JL, Matos R, Mendonça A, Cantraine F, Thijs L, et al. The use of maximum SOFA score to quantify organ dysfunction/failure in intensive care. Results of a prospective, multicentre study. Working Group on Sepsis related Problems of the ESICM. Intensive Care Med. 1999;25(7):686-96.) were checked and recorded daily.

Every morning during the first seven days of ICU stays, a systematic evaluation of sedation, coma and delirium was performed by three senior intensivists, most of the time by the same intensivists, using the RASS scale, the CAM-ICU and the CAM-ICU-7,.

Assessment of delirium was only possible in patients with RASS scores greater than RASS-3. Patients with RASS-4 and RASS-5 scores were categorized as comas. Patients who had delirium on at least one of the days of analysis were considered patients in the group with delirium, and patients who did not have delirium on any of the days analyzed were considered without delirium. Patients who remained in a coma for the entire time of the analysis were excluded. The CAM-ICU-7 mean was calculated by the arithmetic mean of the days that this patient was assessed for delirium during the seven days of the analysis.

Outcomes

Our primary outcomes were delirium incidence and severity (measured by the CAM-ICU-7 score) and its association with hospital mortality rates. In addition, we evaluated secondary outcomes: progression to coma and to MV, ICU LOS and one-year mortality in survivors after discharge (these last data were extracted from the governmental database of Corregedoria Geral do Tribunal de Justiça do Rio de Janeiro - TJRJ). We emphasize that nonclinical factors had an impact on our length of hospital stay, such as respiratory isolation time and lack of availability of hospital ICU and non-ICU beds to receive these patients.

Statistical analysis

Data are presented as medians with interquartile ranges (IQRs) for continuous variables and absolute values and percentages for categorical variables. As appropriate, categorical variables were compared using the chi squared or Fisher’s exact test, and continuous variables were compared using the Kruskal-Wallis or Mann-Whitney U test.

Delirium severity was described by calculating the CAM-ICU-7 means in the first seven days of ICU stay and stratified accordingly with strata as described in the original article (< 3: mild delirium; 3 - 5.99: moderate delirium and 6 - 7: severe delirium).(2626 Khan BA, Perkins AJ, Gao S, et al. The confusion assessment method for the ICU-7 delirium severity scale: A novel delirium severity instrument for use in the ICU. Crit Care Med. 2017;45(5):851-857.) The length of stay in the ICU and in the hospital was analyzed using the Fine-Gray subdistribution hazard competing risk model.(2828 Austin PC, Fine JP. Practical recommendations for reporting Fine-Gray model analyses for competing risk data. Stat Med. 2017;36(27):4391-400.,2929 Fine JP, Gray RJ. A Proportional Hazards Model for the Subdistribution of a Competing Risk. J Am Stat Assoc. 1999;94(446):496-509.) The hazard ratio of discharge chance from the hospital and ICU was calculated by comparing delirium and non-delirium patients with the median time to discharge of the total sample.

The association of delirium severity with outcomes was explored using a univariate analysis by estimating the risk ratios. After univariate analysis, variables that presented a p < 0.25 were entered in the multivariate analysis to correlate delirium with the primary and secondary outcomes. Multivariable adjusted logistic regression models adjusted by SAPS 3 and frailty were used to estimate the odds ratios (for mortality, late mortality, progression to coma and to MV) and hazard ratios (chance of hospital and ICU discharge) and 95% confidence intervals (95%CI). All tests were two-sided, and statistical significance was defined at a level of 95%CI, with a p value < 0.05. All analyses were performed with R software version 4.2.1 using the final fit and survival packages.

RESULTS

A total of 277 patients were included in the study (Figure 1), and overall, delirium occurred in 101 patients (36.5%). Most patients (70.4%) were men, and the mean CCI was 1.0 (0-3.0). Patients had a mean SAPS 3 score of 47.0 (42.0 - 54.0), and the mean m-FI was 18.2 (9.1 - 27.3).

Patients who presented delirium had more comorbidities, were frailer and had higher severity of illness scores (as expressed by a higher CCI, m-FI, SOFA and SAPS 3, respectively), and had higher C-reactive protein - CRP (9.72mg/dL [5.26 - 17.20] versus 6.90mg/dL [3.70 - 13.95]; p = 0.048] at admission. The use of sedative and neuromuscular blockage was more frequent in patients with delirium: midazolam (37.6% versus 15%; p < 0.001), fentanyl (42.5% versus 22%; p < 0.001), neuromuscular blockage (9.9% versus 7.9%; p = 0.29) and dexamethasone (47.5% versus 14.8%, p < 0.001) (Table 1).

Table 1
Clinical and demographic variables of the population with and without delirium

The in-hospital mortality rates in the delirium and non delirium groups were 25.74% versus 5.11%, respectively (p < 0.001). The additional one-year mortality of patients who were discharged alive from the hospital was 5.3% in delirium versus 0.6% in non delirium patients, p < 0.001 (Table 2).

Table 2
Clinical outcomes of the population with and without delirium

Patients were at increased risk of requiring invasive MV after developing delirium (OR 51.35 [95%CI 11.65 - 226.35]; p < 0.001) and had a lower chance of discharge from the ICU (HR 0.54 [95%CI 0.40 - 0.71]; p < 0.001)) than those without delirium. In multivariate analysis, delirium was also independently associated with mortality OR 3.04 (95%CI 1.26 - 7.36); p = 0.014 (Table 3).

Table 3
Delirium and outcomes in multivariate analysis

Delirium was classified according to the CAM-ICU-7 mean in three levels of severity: mild, moderate, and severe. A higher level of delirium was associated with a higher frailty status prevalence (41.1% versus 71.9% versus 77%; p < 0.001) and higher in-hospital mortality (17.9% versus 34.4% versus 38.5%; p < 0.001) (Table 4).

Table 4
Clinical scores and patient outcomes relative to the stratification of delirium severity by Confusion Assessment Method for Intensive Care Unit-7

After multivariate analysis, using mild delirium as a reference and adjusting by the SAPS 3 score and frailty, moderate and severe delirium had a higher risk of progression to invasive MV (patients who were not in invasive MV and evolved with acute respiratory failure, requiring invasive MV; OR 2.2 [95%CI 0.8 - 6.0]; p = 0.119; and OR 11.09 [95%CI 2.8 - 58.5]; p = 0.002) and a higher risk of progression to coma (OR 2.2 [95%CI 0.8 - 6.0]; p = 0.126 and OR 7.1 [95%CI 1.9 - 31.0 ]; p = 0.005, respectively) (Figure 2). Moderate and severe delirium, had comparable results for chance of ICU discharge (HR 0.7 [95%CI 0.4 - 1.1]; p = 0.120 and 0.6 [95%CI 0.3 - 1.4]; p = 0.220) and for mortality (1.46 (95%CI 0.4 - 4.8); p = 0.534 versus 1.77 [95%CI 0.4 - 7.6]; p = 0.447), respectively (Table 5).

Table 5
Outcomes in delirium patients classified by Confusion Assessment Method for Intensive Care Unit-7 mean in multivariate analysis

Figure 2
Comparison of the three median strata of delirium severity with the following outcomes (in odds ratio or hazard ratio, 95% confidence intervals): mortality, late mortality, chance (in percentage) of intensive care unit discharge, chance (in percentage) of hospital discharge, chance of evolution to coma (in percentage) and chance (in percentage) of evolution to invasive mechanical ventilation. (A) Confusion Assessment Method for the Intensive Care Unit-7 mean < 3; (B) Confusion Assessment Method for the Intensive Care Unit-7 mean between 3 - 5.99; (C) Confusion Assessment Method for the Intensive Care Unit-7 mean > 6..

DISCUSSION

In our prospective cohort, the incidence of delirium was high (36.5%), and it was associated with increased in-hospital mortality, increased ICU and hospital LOS and a higher use of MV, even when adjusted for other severity scores (SAPS 3 and frailty).

The delirium occurrence was higher when compared to a similar ICU population without COVID-19.(1515 Salluh JI, Wang H, Schneider EB, Nagaraja N, Yenokyan G, Damluji A, et al. Outcome of delirium in critically ill patients: systematic review and meta-analysis. BMJ. 2015;350:h2538.,1616 Serafim RB, Soares M, Bozza FA, Lapa E Silva JR, Dal-Pizzol F, Paulino MC, et al. Outcomes of subsyndromal delirium in ICU: a systematic review and meta-analysis. Crit Care. 2017;21(1):179.,3030 Serafim RB, Póvoa P, Souza-Dantas V, Kalil AC, Salluh JI. Clinical course and outcomes of critically ill patients with COVID-19 infection: a systematic review. Clin Microbiol Infect. 2021;27(1):47-54.) This finding was similar to that of other studies in critically ill COVID-19 patients.(3131 Pranata R, Huang I, Lim MA, Yonas E, Vania R, Kuswardhani RA. Delirium and mortality in coronavirus disease 2019 (COVID-19) - A systematic review and meta-analysis. Arch Gerontol Geriatr. 2021;95:104388.

32 Garcez FB, Aliberti MJ, Poco PC, Hiratsuka M, Takahashi SF, Coelho VA, et al. Delirium and adverse outcomes in hospitalized patients with COVID-19. J Am Geriatr Soc. 2020;68(11):2440-6.
-3333 Martinotti G, Bonanni L, Barlati S, Miuli A, Sepede G, Prestia D, et al. Delirium in COVID 19 patients: a multicentric observational study in Italy. Neurol Sci. 2021;42(10):3981-8.)

Our cohort described a very low one-year mortality of patients with delirium after discharge (5.3%); nevertheless, it was 8 times higher than late mortality in non-COVID patients. Despite few studies describing late mortality in patients with COVID-19, our result was similar to other recent observational studies that found only 1% one-year mortality in COVID-19 survivors.(3434 Ceccato A, Pérez-Arnal R, Motos A, Barbé F, Torres A; CiberesUCICOVID Consortium. One-year mortality after ICU admission due to COVID-19 infection. Intensive Care Med. 2022;48(3):366-8.) Although delirium occurrence in non-COVID-19 patients has been associated with a higher 1-year mortality,(3535 Lokhandwala S, McCague N, Chahin A, Escobar B, Feng M, Ghassemi MM, et al. One-year mortality after recovery from critical illness: a retrospective cohort study. PLoS One. 2018;13(5):e0197226.,3636 Pisani MA, Kong SY, Kasl SV, Murphy TE, Araujo KL, Van Ness PH. Days of delirium are associated with 1-year mortality in an older intensive care unit population. Am J Respir Crit Care Med. 2009;180(11):1092-7.) late survival to COVID-19 is closely associated with comorbidities and functional status.(3737 Boehme AK, Doyle K, Thakur KT, Roh D, Park S, Agarwal S, et al. Disorders of consciousness in hospitalized patients with COVID-19: the role of the systemic inflammatory response syndrome. Neurocrit Care. 2022;36(1):89-96.) In our cohort, delirium survivors were less frail (m-FI: 27.3 [95%CI 18.0 - 36.4] versus 18.0 [95%CI 9.1 - 27]; p < 0.001), had a lower CCI (CCI: 3.0 [95% CI 2.7-3.2] versus 4.8 [95%CI 3.8 - 5.7]; p < 0.001) and had a lower severity score (SAPS3: 50.8 [95%CI 50.4 - 51.3] versus 65.1 [95%CI 64.1 - 66.1]; p < 0.001) than nonsurvivors. We also described the correlation between delirium severity (according to the mean CAM-ICU-7 assessment) and outcomes.

There are only a few studies comparing delirium severity and outcomes in critically ill COVID-19 patients.(3838 Wassenaar A, Schoonhoven L, Devlin JW, van Haren FM, Slooter AJ, Jorens PG, et al. Delirium prediction in the intensive care unit: comparison of two delirium prediction models. Crit Care. 2018;22(1):114.) Only one study described an increase in mortality in coma patients but did not describe subgroups of delirium severity.(3737 Boehme AK, Doyle K, Thakur KT, Roh D, Park S, Agarwal S, et al. Disorders of consciousness in hospitalized patients with COVID-19: the role of the systemic inflammatory response syndrome. Neurocrit Care. 2022;36(1):89-96.) Our study described that the mortality of patients with moderate to severe delirium was nearly twice that observed in mild delirium (respectively 17.9% and 34.4% versus 38.5%; p < 0.001). Similar to rapid reverse delirium, mild delirium represents a lower risk of death.(55 Khan SH, Lindroth H, Perkins AJ, Jamil Y, Wang S, Roberts S, et al. Delirium incidence, duration, and severity in critically ill patients with coronavirus disease 2019. Crit Care Explor. 2020;2(12):e0290.)

In our cohort, severe delirium was also associated with a high amount of resources used (MV or length of stay). Monitoring delirium severity can identify high-risk patients and resource allocation. The imbalance between supply and demand for medical resources during the pandemic highlights the importance of projecting future demands in the ICU regarding delirium severity.

Delirium diagnosis and monitoring was also a challenge during the COVID-19 pandemic. Spread barriers need to be adopted, and the main emphasis has been placed on organizational barriers in the COVID-19 population. In our sample, E-predeliric had a discriminative performance similar to that of patients without COVID-19, with an issue hindering bedside delirium screening. Our performance of the E-predelic score in delirium prediction had an area under the ROC curve of 0.783, p < 0.001, which is very similar to that described in non-COVID-19 patients.(2020 Wassenaar A, van den Boogaard M, van Achterberg T, Slooter AJ, Kuiper MA, Hoogendoorn ME, et al. Multinational development and validation of an early prediction model for delirium in ICU patients. Intensive Care Med. 2015;41(6):1048-56.,3838 Wassenaar A, Schoonhoven L, Devlin JW, van Haren FM, Slooter AJ, Jorens PG, et al. Delirium prediction in the intensive care unit: comparison of two delirium prediction models. Crit Care. 2018;22(1):114.) Understanding delirium patterns and characteristics can help to select appropriate screening tools and preventive measures for future conditions.

Our study has many strengths, including the prospective design, the bedside data collection (not chart-based method), the size of our sample, the multivariate analysis adjusting for possible confounders and mainly the assessment of delirium severity and its prognosis in this population. There are few studies describing outcomes and late mortality in patients with delirium and COVID-19, and the CAM-ICU-7 has been underexplored in this population.

While effective pharmacological therapies for delirium are not yet available,(1818 Williamson CA, Faiver L, Nguyen AM, Ottenhoff L, Rajajee V. Incidence, predictors and outcomes of delirium in critically ill patients with COVID-19. Neurohospitalist. 2022;12(1):31-7.) our data emphasize delirium as a predictor of poor outcomes in the ICU population admitted with COVID-19 and the importance of implementing a screening protocol as well as monitoring the severity of delirium.

However, some limitations need to be highlighted. First, it is worth noting that our analysis focused only on the first week of ICU stay, which may have underestimated the incidence of delirium. However, it is important to recognize that delirium is more likely to occur during the initial days of admission.(55 Khan SH, Lindroth H, Perkins AJ, Jamil Y, Wang S, Roberts S, et al. Delirium incidence, duration, and severity in critically ill patients with coronavirus disease 2019. Crit Care Explor. 2020;2(12):e0290.) Therefore, early monitoring for delirium remains critical in guiding decision-making during ICU treatment. Second, as we performed this study at the beginning of the first wave of the pandemic and there was a large concern about the virus spreading, we limited patient assessment to one visit a day, which may also have reduced our detection of delirium. Third, the sample we analyzed may not represent the entire population, as many patients were unable to be evaluated using the CAM-ICU or CAM-ICU-7. This could result in a potentially less severe patient population. A significant number of patients needed MV and deep sedation due to severe hypoxemia. Additionally, many patients require benzodiazepines for sedation due to a shortage of short-acting drugs.(3939 Watne LO, Tonby K, Holten AR, Olasveengen TM, Romundstad LG, Neerland BE. Delirium is common in patients hospitalized with COVID-19. Intern Emerg Med. 2021;16(7):1997-2000.,4040 Pun BT, Badenes R, Heras La Calle G, Orun OM, Chen W, Raman R, Simpson BK, Wilson-Linville S, Hinojal Olmedillo B, Vallejo de la Cueva A, van der Jagt M, Navarro Casado R, Leal Sanz P, Orhun G, Ferrer Gómez C, Núñez Vázquez K, Piñeiro Otero P, Taccone FS, Gallego Curto E, Caricato A, Woien H, Lacave G, O’Neal HR Jr, Peterson SJ, Brummel NE, Girard TD, Ely EW, Pandharipande PP; COVID-19 Intensive Care International Study Group. Prevalence and risk factors for delirium in critically ill patients with COVID-19 (COVID-D): a multicentre cohort study. Lancet Respir Med. 2021;9(3):239-50.) Fourth, the lack of details regarding corticosteroid use in our study population could represent a confounding bias. It is important to note that our study was conducted in the early stages of the pandemic when there was still controversy and concern about the use of corticosteroids, especially in advanced infection cases. Finally, we evaluated only late mortality, and we did not evaluate other late outcomes, such as the prevalence of functional decline or the presence of posttraumatic stress syndrome.

CONCLUSION

The incidence of delirium was high in COVID-19 patients. Delirium was an independent risk factor for the worst prognosis, including mortality during hospitalization, but had a slight impact on 1-year mortality.

Our study emphasizes the applicability of the CAM-ICU-7 scale in the COVID-19 intensive care unit population and reinforces the importance of graduating delirium and its correlation with worse outcomes. The delirium severity assessed by the CAM-ICU-7 during the first week in the intensive care unit was associated with poor outcomes, including evolution to coma and to mechanical ventilation.

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Edited by

Responsible editor: Antonio Paulo Nassar Jr.

Publication Dates

  • Publication in this collection
    22 Jan 2024
  • Date of issue
    Oct-Dec 2023

History

  • Received
    07 July 2023
  • Accepted
    03 Oct 2023
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