Prevalence of systemic complications of COVID-19 in critically ill patients: systematic review with meta-analysis^*

Objective: to identify the prevalence of systemic complications of COVID-19 in critically ill patients, to estimate the clinical conditions that may have a worse prognosis when associated with COVID-19.

Method: systematic review with meta-analysis of observational studies, based on the recommendations of the JBI Manual for Evidence Synthesis for systematic reviews of prevalence and incidence, in six databases and grey literature, period 2020 to 2024, languages Portuguese, English and Spanish. We identified 2393 publications. The selection, data extraction and methodological evaluation of the studies were carried out by two independent researchers. The meta-analysis was performed using the Freeman Tukey transformational random-effects statistical method.

Results: ten papers were included. The meta-analysis of seven papers dealing with respiratory complications due to COVID-19 demonstrated a mean prevalence of 42%, (95% CI 0.2-0.66) with heterogeneity I²=97.4; the meta-analysis of 4 papers involving the prevalence of neurological complications due to COVID-19 showed an average prevalence of 62%, (95% CI 0.49- 0.74) with heterogeneity I²=87.4 and the meta-analysis of 8 studies showed a prevalence of mortality due to COVID-19 of 33%, (95% CI 0.23- 0.44) with heterogeneity I²=93.6.

Conclusion: respiratory and neurological complications were the most prevalent in the reviewed studies. PROSPERO Registration: CRD42020214617.

Descriptors:
COVID-19; SARS-CoV-2; Comorbidity; Critical Illness; Critical Care; Systematic Review

Highlights:

(1) Respiratory and neurological complications stood out as the most prevalent complication. (2) The main risk factors are: being male, presenting comorbidities, having respiratory and cardiac diseases. (3) Evidence can guide the practice of health professionals. (4) Evidence can assist in the implementation of care for critically ill patients.

Objetivo: identificar a prevalência das complicações sistêmicas da COVID-19 em pacientes críticos, para estimar as condições clínicas que podem apresentar pior prognóstico quando associados à COVID-19.

Método: revisão sistemática com metanálise de estudos observacionais, baseada nas recomendações do JBI Manual for Evidence Synthesis para revisões sistemáticas de prevalência e incidência, em seis bases de dados e literatura cinzenta, período 2020 a 2024, idiomas português, inglês e espanhol, tendo sido identificadas 2393 publicações. A seleção, a extração dos dados e a avaliação metodológica dos estudos foram realizadas por dois pesquisadores independentes. A metanálise foi realizada pelo método estatístico de Freeman Tukey transformacional de efeito randômico.

Resultados: dez artigos foram incluídos. A metanálise de sete artigos que tratavam das complicações respiratórias por COVID-19, a prevalência média foi de 42%, (IC95% 0,2- 0,66) com heterogeneidade I²=97,4; a metanálise de quatro artigos que envolveram as complicações neurológicas por COVID-19 mostrou prevalência média de 62%, (IC95% 0,49- 0,74) com heterogeneidade I²=87,4 e a metanálise de oito estudos mostrou uma prevalência da mortalidade por COVID-19 de 33%, (IC95% 0,23- 0,44) com heterogeneidade I²=93,6.

Conclusão: as complicações respiratórias e neurológicas foram as mais prevalentes nos estudos revisados. Registro PROSPERO: CRD42020214617

Descritores:
COVID-19; SARS-CoV-2; Comorbidade; Estado Terminal; Cuidados Críticos; Revisão Sistemática

Destaques:

(1) As complicações respiratórias e neurológicas destacaram-se como as mais prevalentes. (2) Principais fatores de risco são sexo masculino, comorbidades, doenças respiratórias e cardíacas. (3) Evidências podem orientar a práxis dos profissionais de saúde. (4) Evidências podem auxiliar na implementação de assistência aos pacientes críticos.

Objetivo: identificar la prevalencia de las complicaciones sistémicas de la COVID-19 en pacientes críticos, para estimar las condiciones clínicas que pueden presentar peor pronóstico cuando se asocian a la COVID-19.

Método: revisión sistemática con metaanálisis de estudios observacionales, basada en las recomendaciones del JBI Manual for Evidence Synthesis para revisiones sistemáticas de prevalencia e incidencia, en seis bases de datos y literatura gris, período 2020 a 2024, en los idiomas portugués, inglés y español, habiéndose identificado 2393 publicaciones. La selección, la extracción de datos y la evaluación metodológica de los estudios fueron realizadas por dos investigadores independientes. El metaanálisis se realizó mediante el método estadístico transformacional de Freeman Tukey de efecto aleatorio.

Resultados: se incluyeron diez artículos. El metaanálisis de siete artículos que abordaban las complicaciones respiratorias por COVID-19 demostró una prevalencia media de 42%, (IC95% 0,2-0,66) con heterogeneidad I²=97,4; el metaanálisis de 4 artículos que involucraron la prevalencia de las complicaciones neurológicas por COVID-19 mostró una prevalencia media de 62%, (IC95% 0,49-0,74) con heterogeneidad I²=87,4 y el metaanálisis de 8 estudios mostró una prevalencia de la mortalidad por COVID-19 de 33%, (IC95% 0,23-0,44) con heterogeneidad I²=93,6.

Conclusión: las complicaciones respiratorias y neurológicas fueron las más prevalentes en los estudios revisados. Registro PROSPERO: CRD42020214617.

Descriptores:
COVID-19; SARS-CoV-2; Comorbilidad; Enfermedad Crítica; Cuidados Críticos; Revisión Sistemática

Destacados:

(1) Las complicaciones respiratorias y neurológicas se destacaron como las más prevalentes. (2) Los principales factores de riesgo son el sexo masculino, las comorbilidades, las enfermedades respiratorias y cardíacas. (3) La evidencia puede orientar la praxis de los profesionales de la salud. (4) La evidencia puede ayudar en la implementación de la asistencia a los pacientes críticos.

Introduction

The coronavirus, which belongs to the family of the same name and is responsible for the development of respiratory infections, has ravaged the world after the spread of a new strain called SARS-CoV-2, which causes COVID-19. On March 11^th, 2020, the World Health Organization classified the geographic distribution of the disease as a pandemic, a situation that lasted for almost 30 months(¹-³). From then on, preventive measures such as social distancing, quarantine and use of masks were implemented, aiming to reduce the transmissibility and lethality of the disease(⁴). These measures resulted in psychological suffering and mental disorders, such as anxiety, depression and stress(⁵). In addition, systemic complications caused by the disease began to be observed, mainly through impairments in the pulmonary and cardiovascular systems(⁶-⁷).

On October 14^th, 2021, the United States Center for Disease Control and Prevention (CDC) showed that COVID-19 did not affect all population groups equally(⁸). The risk of complications arising from the disease increases proportionally to the number of underlying conditions a person has. Previous studies indicate that individuals with certain disabilities are more likely to contract it and have adverse outcomes(⁹-¹⁰). In addition, some chronic conditions, such as lung disease, heart disease, diabetes, and obesity, are more prevalent in certain minority populations, affecting a younger age group. In the United States of America, an estimated increase of 700,000 excess deaths was observed, with the largest percentage increase in mortality among adults aged 25 to 44 and among Hispanics or Latinos(⁸). In 2022, COVID-19 was the fourth leading cause of death in that country(¹¹). Evidence supported by systematic reviews highlights that underlying conditions that increase the risk of progression to severe disease due to COVID-19 include lung disease(¹²-¹⁶), cancer(¹⁷-¹⁸), cerebrovascular disease(¹⁸-²¹), chronic kidney disease(²²-²³), chronic liver disease (cirrhosis, non-alcoholic fatty liver disease, alcoholic liver disease, autoimmune hepatitis)(²⁴-²⁶), Diabetes Mellitus (DM), Type 1 Diabetes Mellitus (DM1) and Type 2 Diabetes Mellitus (DM2)(²⁷), heart problems (such as heart failure, coronary artery disease or cardiomyopathies)(²⁸-²⁹), current and former smoking(³⁰-³²), tuberculosis(³³-³⁴), obesity(³⁵), pregnancy and recent pregnancy(³⁶) and mental health disorders (mood disorders, including depression and schizophrenia spectrum disorders)(³⁷-³⁸).

Given the above, risk groups appear to have a higher probability of developing systemic complications from COVID-19. Critical patients were considered to be those who were seriously ill, with clinical instability or risk of instability of the vital system with risk of death and, therefore, admitted to an intensive care unit (ICU)(³⁹). Thus, this study aimed to identify the prevalence of systemic complications of COVID-19 in critically ill patients. It is expected that the study can contribute to estimating the clinical conditions of patients who may have a worse prognosis when associated with COVID-19.

Method

Study design

This is a systematic review that followed the guidelines of the Brazilian Center for Evidence-Based Research COBE-UFSC(⁴⁰) and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist(⁴¹). Six stages were organized for its development: (1) elaboration of the research question; (2) preparation of the preliminary search strategy; (3) selection of databases; (4) definition of eligibility criteria; (5) data collection and analysis of risks of bias; and (6) reporting of the review(⁴⁰). The systematic review protocol was registered in the International Prospective Register of Ongoing Systematic Reviews – PROSPERO under number CRD42020214617.

Study question

This review sought to answer the following question: what is the prevalence of systemic complications resulting from SARS-CoV-2 contamination in adults with COVID-19 in critical condition? To formulate the question, PECOS strategy was used(⁴⁰), as follows: P - Participants: adults with COVID-19; E - Exposure: COVID-19 contamination; C - Control: absence of contamination; O - Outcome: systemic complications; S - Observational studies.

Data collection period

This systematic review was carried out from August 30^th, 2020 to March 30^th, 2024.

Criteria for eligibility

Observational studies that addressed adults with COVID-19 in critical condition were included, considering epidemiological aspects, clinical manifestations, diagnosis, prevention and control of the disease. As exclusion criteria, review studies, case control studies, case reports, case studies and series, publications of abstracts of annals of scientific events and editorials were disregarded.

Data collection and search strategy

The databases used were MEDLINE (via PubMed), EMBASE, LILACS, Web of Science Core Collection, Scopus and CINAHL. For the search strategy, the descriptors of Medical Subject Headings (MeSH), Emtree, CINAHL Titles and Health Sciences Descriptors (DeCS/MeSH) were used, in addition to synonymous terms, considering the specificities of each database. As an example, PubMed’s implemented search strategy stands out: ((“COVID-19”[Supplementary Concept] OR “COVID-19”[All Fields] OR “2019 novel coronavirus disease”[All Fields] OR “COVID19”[All Fields] OR “COVID-19 pandemic”[All Fields] OR “SARS-CoV-2 infection$”[All Fields] OR “COVID-19 virus disease”[All Fields] OR “2019 novel coronavirus infection$”[All Fields] OR “2019-nCoV infection$”[All Fields] OR “coronavirus disease 2019”[All Fields] OR “coronavirus disease-19”[All Fields] OR “2019-nCoV disease”[All Fields] OR “COVID-19 virus infection$”[All Fields] OR “Coronavirus Infections”[Mesh] OR “Coronavirus Infections”[All Fields] OR “Coronavirus Infection$”[All Fields] OR “Middle East Respiratory Syndrome”[All Fields] OR “MERS (Middle East Respiratory Syndrome)”[All Fields]) AND (“Systemic complications”[Title/Abstract] OR “Systemic complication$”[All Fields] OR “Covid-19 complication$”[All Fields] OR “Covid 19 complication$”[All Fields] OR “Covid19 complication$”[All Fields] OR “SARS-CoV-2 complication$”[All Fields])). The search was performed on August 30^th, 2023.

In addition, grey literature was also searched in Google Scholar, Proquest and OpenGrey sources and the reference lists of the included articles were manually searched.

The results identified in each database were exported to EndNote 20 desktop version to remove duplicates. The records were then exported to the online software Rayyan(⁴²) for individual selection of studies by two reviewers, by reading the titles and abstracts, followed by selection of the full text. After each selection phase, a consensus meeting was held to discuss and align conflicts.

Data collection

Data extraction was conducted using the Joanna Briggs Institute (JBI)(⁴³) collaboration instrument for observational studies, covering the following variables: country, context and location, participant characteristics, groups, outcome measures and description of the main results. Data collection was carried out independently by two researchers and conflicts were resolved with a third reviewer.

Data analysis

A qualitative synthesis was performed considering dependent variables (type of systemic complication) and independent variables (sex, age group, presence of comorbidities, and laboratory findings). In the quantitative synthesis, a meta-analysis of proportions was performed using the Freeman Tukey transformational random-effects statistical method, with a 95% confidence interval. The meta-analysis was performed using the JBI collaboration software(⁴³), grouping the studies in each group according to similar prevalence in relation to systemic complications of COVID-19. The analyses involved all included articles, regardless of methodological quality. Systemic complications of COVID-19 were classified according to their etiology as: neurological and respiratory or death.

To assess methodological quality, the tool proposed by the JBI collaboration(⁴⁴) for cohort studies was used, which includes eleven questions: Were the two groups similar and recruited from the same population? Were exposures measured similarly to assign people to the exposed and unexposed groups? Was the exposure measured in a valid and reliable manner? Were confounding factors identified? Were strategies to deal with confounding factors stated? Were the groups/participants free from the outcome at baseline (or at the time of exposure)? Were the outcomes measured in a valid and reliable manner? Was the follow-up time reported and sufficient for the results to occur? Was the follow-up complete and, if not, were the reasons for loss to follow-up described and explored? Were strategies used to address incomplete follow-up? Was adequate statistical analysis used? This assessment was performed by two reviewers independently, and any doubts were discussed in meetings to seek consensus. The overall methodological quality of each study was considered for the interpretation of the analysis, which was classified as “High”, “Moderate” or “Low”, based on the count or percentage of “Yes” responses to the tool items. Thus, we adopted, for the cutoff points, up to 25% of yes responses: “high risk of bias”; from 25 to ≤75%: “moderate” risk of bias; and greater than 75%: “low” risk of bias(⁴⁵).

The certainty of evidence was not assessed, since there is currently no formal Grading of Recommendations Assessment, Development and Evaluation (GRADE) guidance for systematic reviews of prevalence and incidence(⁴⁶).

Results

The search identified 2393 records, 97 from PubMed, 417 from Web of Science Core Collection, 556 from LILACS, 450 from Scopus, 501 from EMBASE, 26 from CINAHL, 100 from Google Scholar and 246 from ProQuest and none from OpenGrey. After removing duplicates and considering the eligibility criteria, 10 cohort studies resulted. Figure 1 shows the flowchart of the selection process of the studies included in the systematic review.

Figure 1 -
Flowchart of selection of studies included in the systematic review adapted from the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) (n = 10), 2020-2024

The summary of the 10 studies describes the identification of the study, country of conduct, context, characteristics of the participants, groups, outcome measures and main results and can be viewed at https://doi.org/10.48331/scielodata.4BEZDJ.

The proportions of occurrences of systemic complications of COVID-19 are described in Figure 2, Figure 3 and Figure 4 Figures 2, 3 and 4.

Figure 2 shows the meta-analysis of seven articles that dealt with respiratory complications due to COVID-19. It was possible to observe a mean prevalence (meta-prevalence) of 42%, (95%CI 0.2-0.66) with heterogeneity I²=97.4.

Figure 2 -
Meta-analysis of seven articles addressing the prevalence of respiratory complications from COVID-19, 2020-2024

Figure 3 shows the meta-analysis of four articles that involved the prevalence of neurological complications due to COVID-19. An average prevalence (meta-prevalence) of 62% was observed (95%CI 0.49-0.74) with heterogeneity I²=87.4

Figure 3 -
Meta-analysis of 4 studies showing the prevalence of neurological complications from COVID-19, 2020-2024

Figure 4 shows the meta-analysis of eight studies that showed the prevalence of mortality from COVID-19. An average prevalence (meta-prevalence) of 33% can be observed (95%CI 0.23-0.44) with heterogeneity I²=93.6.

Figure 4 -
Meta-analysis of eight studies showing the prevalence of COVID-19 mortality, 2020-2024

Heterogeneity was assessed by inconsistency (I²), which describes the percentage variation attributed to them beyond chance. The cutoff points considered were: 25% low; 50% moderate; and 75% high heterogeneity, with a p-value <0.05(⁴⁷).

Regarding the assessment of the methodological quality of the included cohort studies, 10% presented high methodological quality and 90% moderate quality, that is, 10% of the studies had a “low” risk of bias and 90% “moderate” risk of bias (Figure 5).

Figure 5 -
Assessment of methodological quality of included cohort studies (n = 10), 2020-2024

Discussion

This systematic review asked the question of the prevalence of systemic complications of COVID-19 in critically ill patients. We found that respiratory and neurological complications were the most prevalent in the reviewed studies, indicating that critically ill patients with COVID-19 may be at higher risk of developing these complications. Of the 10 studies included in the systematic review, three were produced in Europe(⁴⁸-⁵⁰), three in Asia(⁵¹-⁵³), one in Central America(⁵⁴), one in North America(⁵⁵) and two in South America(⁵⁶-⁵⁷), characterizing COVID-19 as a pandemic with serious repercussions in several countries and regions of the world. The oldest publications date back to 2020, the year the health emergency began(⁵⁸). The number of participants in the included cohort studies totalled 1,143 people, with an average age of 62 years old, predominantly male. In most studies, patients presented at least one comorbidity. The most prevalent comorbidities were: high blood pressure, diabetes mellitus, obesity, and heart disease.

Regarding pulmonary manifestations in COVID-19, these can manifest as mild, moderate, or severe. In the mild form, symptoms such as body aches, cough, or mild fever may be present. In the moderate form, the disease may present as mild pneumonia, associated with other symptoms. The severe form of the disease may be characterized by severe pneumonia and hypoxia. In critical cases that present significant hypoxia and organ failure, admission to the Intensive Care Unit (ICU) with mechanical ventilatory support may be necessary(⁵²,⁵⁹-⁶⁰).

The studies identified in this systematic review revealed that mechanical ventilation was initiated more frequently in patients with severe diseases compared to those with non-severe diseases (non-invasive ventilation, 32.4% versus -vs 0%; invasive ventilation, 14.5% vs 0%)(⁵¹). The study(⁵⁶) involving 168 critically ill patients with COVID-19 (average age 65 years old, 66% were male) indicated that arterial hypertension was the most frequent comorbidity, affecting 52.4% of patients. Of these, 67.9% required Invasive Mechanical Ventilation (IMV), and none were treated with non-invasive ventilation. Most patients on IMV (73.7%) required neuromuscular blockade due to severe hypoxemia and 36% were ventilated in the prone position. The average period for ICU stay was 13 days, with a mortality rate of 25%. The study showed that mechanical ventilation was associated with a higher chance of developing delirium (OR: 42.1; 95% CI: 13.0-137.1), with a mortality of 26.4% in patients with delirium compared to 15.8% in patients without such disorder(⁵⁵). Among 710 patients with SARS-CoV-2 pneumonia, 52 critically ill adults were included. The mean age was 59.7 years, 67% were men, and 40% had chronic medical conditions. Most patients (61.5%) died within 28 days, with a median duration from ICU admission to death of 7 days for nonsurvivors. Compared with survivors, nonsurvivors were older, more likely to develop acute respiratory distress syndrome (ARDS) [26 (81%) patients vs 9 (45%) patients], and more likely to receive mechanical ventilation [30 (94%) patients vs 7 (35%) patients], invasive or non-invasive. Most patients had organ dysfunction, including acute respiratory distress syndrome (ARDS) (67%), acute kidney injury (29%), cardiac disease (23%), liver dysfunction (29%), and pneumothorax (2%). Thirty-seven (71%) required IMV, and seven (13.5%) developed hospital infection(⁵²).

This association was also demonstrated in a study(⁵⁷), in which the most severe cases of COVID-19 had occurred in elderly, hypertensive and obese patients, with a significant increase in mortality when associated with kidney disease.

A study(⁵⁴) revealed that 30% of patients required IMV, all of whom were aged 65 years or older and predominantly female. Of these, 83.3% died (5), and four had severe or moderate ARDS (RR 16.7) according to the Berlin classification. The mean ideal positive end-expiratory pressure (PEEP) used was 16.5 (SD=2.1) cmH₂O (CI 15.6-17.4), with the initial ventilatory modality being volume-controlled ventilation (VCV). In one of the cases, the prone position was adopted after the first 12 hours of admission to the ICU. The prone position was contraindicated in other cases due to hemodynamic instability. The patient who was successfully weaned from ventilation used Bi-positive pressure (BiPAP) mode, which resulted in less need for sedation and muscle relaxation, in addition to a shorter time on IMV (5 days), despite the advanced age. Non-invasive ventilation was not used.

The meta-analysis of the prevalence of respiratory complications was 42% (CI: 0.39-0.46, I²: 98), resulting in the need for IMV, in a total population of 704 patients admitted to the ICU. The systematic review(⁶¹), carried out with the aim of understanding whether the presentations and manifestations of COVID-19 were limited exclusively to pulmonary manifestations, identified an incidence of 33% of Acute Respiratory Syndrome.

Regarding neurological complications, evidence from a systematic review(⁶²) indicated that the most common neurological manifestations associated with COVID-19 included myalgia, headache, sensory alteration, hyposmia, and hypogeusia. In addition, rare central nervous system manifestations, such as ischemic stroke, intracerebral hemorrhage, encephalomyelitis, and acute myelitis, as well as peripheral nerve manifestations, such as Guillain-Barré syndrome and Bell’s palsy, and skeletal muscle manifestations, such as rhabdomyolysis, have also been observed. Recent reports suggest that hypoxic-ischemic damage may be the main cause of neurological symptoms in patients with COVID-19(⁶³).

The studies included in this systematic review identified delirium as the most common neurological complication. In one of the studies(⁴⁸), no association was observed between delirium and the duration of mechanical ventilation. On the other hand, another study(⁵⁶) indicated a lower incidence of this condition in patients not undergoing mechanical ventilation (23, 42.5%) compared to patients on mechanical ventilation (61, 89.7%). One study(⁵⁵) found that delirium occurred in 73.6% of patients and that mechanical ventilation was associated with increased odds of developing delirium or coma in 76.4% (110/144). Sixty-three percent of patients tested positive for delirium (OR: 42.1, 95% CI: 13.0-137.1).

Another study(⁵³) showed that among 52 ICU patients with COVID-19, the mean age was 73 years old, and 19 (36.5%) had pre-existing neurological comorbidities. New-onset neurological complications occurred in 23 (44.2%) patients during their ICU stay. Those with pre-existing neurological comorbidities required tracheostomy more frequently, as well as more days of ventilation and ICU stay, compared to those without comorbidities.

The meta-analysis of the prevalence of neurological complications, involving 458 patients admitted to the ICU, revealed a high prevalence of 62% (CI: 0.49-0.74, I²: 87.4).

The systematic review with meta-analysis(⁶⁴) highlighted the risk factors for mortality in COVID-19, including a total of 14 studies with 29,909 patients infected by the virus, recording 1,445 cases of death. The study revealed significant associations between advanced age (≥65 vs <65 years) (pooled OR = 4.59, 95% CI = 2.61–8.04, p < 0.001), male gender compared to female gender (pooled OR = 1.50, 95% CIs = 1.06–2.12, p = 0.021), and the risk of death from COVID-19 infection. Additionally, conditions such as hypertension (pooled OR = 2.70, 95% CI = 1.40–5.24, p = 0.003), cardiovascular disease (CVD) (pooled OR = 3.72, 95% CI = 1.77–7.83, p = 0.001), diabetes (pooled OR = 2.41, 95% CI = 1.05–5.51, p = 0.037), chronic obstructive pulmonary disease (COPD) (pooled OR = 3.53, 95% CI = 1.79–6.96, p < 0.001), and cancer (pooled OR = 3.04, 95% CI = 1.80–5.14, p < 0.001) were associated with a higher risk of mortality(⁶⁴). The study(⁴⁹) demonstrated a higher percentage of complications during hospitalization in patients with bacteremic pneumococcal pneumonia during hospitalization. In contrast, patients with SARS-CoV-2 pneumonia had a higher in-hospital mortality rate (10.8% vs 6.8%; P=0.004) and longer hospital stay.

In patients with SARS-CoV-2 pneumonia, the predictors of in-hospital mortality were: age ≥65 years (OR 4.777, 95% CI 2.814–8.111; P<0.001); heart disease (OR 1.587, 95% CI 1.007–2.341; P=0.02); liver disease (OR 2.365, 95% CI 1.199–4.662); altered mental status (OR 2.464, 95% CI 1.586–3.827; P<0.001); respiratory rate ≥30 breaths/min (OR 2.117, 95% CI 1.362–3.289; P<0.001); hypoxemia (OR 1.599, 95% CI 1.045–2.447; P=0.03); blood urea nitrogen ≥30 mg/dL (OR 1.864, 95% CI 1.236–2.81; P=0.003); neutrophilia (every 10,000 unit increase in neutrophil count/μL) (OR 1.052, 95% CI 1.018–1.086; P=0.002); bilateral lung involvement (OR 1.868, 95% CI 1.142–3.056; P=0.013); pleural effusion (OR 2.894, 95% CI 1.282–6.536; P=0.011), and septic shock (OR 2.781, 95% CI 1.703–4.542; P<0.001). Seven or more days of symptoms at admission were protective factors against mortality (OR 0.464, 95% CI 0.314–0.685; P<0.001).

The results of this review corroborate the analysis of a study(⁶⁴), since all included studies highlighted risk factors, with a predominance of males. In seven (70%) of the studies, patients had at least one comorbidity, with a predominance of hypertension, diabetes, obesity, heart and lung diseases. The meta-analysis of mortality prevalence in this systematic review for COVID-19 was 33% (CI: 0.23–0.44, I²: 93.6), involving a population of 2215 patients admitted to the ICU.

Another study(⁵⁰) that evaluated the incidence of thrombotic complications and overall mortality in patients with COVID-19 admitted to the ICU during the first and second waves of the pandemic revealed that, of the 358 patients admitted to the ICU, 144 patients died (15%). The adjusted cumulative incidence of all thrombotic complications after 10, 20, and 30 days was 12% (95% confidence interval (CI) 9.8–15%), 16% (13–19%), and 21% (17–25%), respectively. Patient characteristics between the first and second waves were comparable. The adjusted hazard ratio (HR) for all-cause mortality in the second wave vs the first wave was 0.53 (95% CI 0.41–0.70). The adjusted HR for any thrombotic complication in the second wave vs the first was 0.89 (95% CI 0.65–1.2). In conclusion, a 47% reduction in mortality was observed in the second wave, but the rate of thrombotic complications remained high and comparable to the first wave. The need for cautious care and the guarantee of adequate thromboprophylaxis is emphasized.

Another important aspect is the patient’s admission to the emergency unit. A study(⁶⁵) identified the importance of using risk classification at the time of admission, in which patients with COVID-19, who had modified early warning scores greater than 4, were associated with the urgent, very urgent and emergency categories and had greater clinical deterioration such as respiratory failure and shock, evolving more often to death. This shows that the risk protocol correctly prioritized patients at risk of death.

As for the limitations of the study, this systematic review did not include texts in Mandarin, as no researchers were found on the team who were fluent in this language. Another limitation was the high heterogeneity of the studies found in the meta-analysis, which we attribute to the set of complications analysed by the papers. Perhaps a knowledge gap would be cohort studies with only one type of complication. In addition, most of the studies presented a moderate risk of bias; only one showed a low risk of bias, so there is a gap in studies with more rigorous methods.

This systematic review provides a significant contribution to the advancement of knowledge about systemic complications in patients admitted to the ICU. By presenting detailed evidence on the prevalence of respiratory and neurological complications and mortality, together with the identification of their risk factors, the review serves as a valuable tool to guide healthcare professionals in planning and providing care to this critical population. The information gathered in this study has the potential to improve clinical practices, promoting a more informed and effective approach to the care of critically ill COVID-19 patients.

Conclusion

Respiratory and neurological complications stood out as the most prevalent among critically ill patients with COVID-19 in the reviewed studies. Significant risk factors for complications and mortality related to COVID-19, such as male gender and comorbidities such as hypertension, diabetes mellitus, obesity, and respiratory and cardiac diseases, were consistently present in most of the studies analyzed. The findings highlight the importance of early identification and careful management of these risk factors to improve clinical outcomes in critically ill patients with COVID-19.

This review provides evidence that can guide the practice of health professionals, highlighting the main risk factors associated with respiratory and neurological complications in critically ill patients with COVID-19. The results offer valuable support for improving the prevention and management of these conditions, contributing to the design and implementation of more effective care.

References

• ^1. Smith LE, Mottershaw AL, Egan M, Waller J, Marteau TM, Rubin JG. The impact of believing you have had COVID-19 on self-reported behaviour: Cross-sectional survey. PLoS One. 2021;16(2):e0248076. https://doi.org/10.1371/journal.pone.0248076
  » https://doi.org/10.1371/journal.pone.0248076
• ^2. Cao Y, Liu X, Xiong L, Cai K. Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2: A systematic review and meta-analysis. J Med Virol. 2020;92(9):1449-59. https://doi.org/10.1002/jmv.25822
  » https://doi.org/10.1002/jmv.25822
• ^3. Organização Pan-Americana da Saúde. OMS declara fim da Emergência de Saúde Pública de Importância Internacional referente à COVID-19 [Internet]. Washington, D.C.: OPAS; 2023 [cited 2024 Jan 8]. Available from: https://www.paho.org/pt/noticias/5-5-2023-oms-declara-fim-da-emergencia-saude-publica-importancia-internacional-referente
  » https://www.paho.org/pt/noticias/5-5-2023-oms-declara-fim-da-emergencia-saude-publica-importancia-internacional-referente
• ^4. World Health Organization. Overview of public health and social measures in the context of COVID-19 [Internet]. Geneva: WHO; 2020 [cited 2024 Feb 18]. Available from: https://iris.who.int/bitstream/handle/10665/332115/WHO-2019-nCoV-PHSM_Overview-2020.1-eng.pdf?sequence=1
  » https://iris.who.int/bitstream/handle/10665/332115/WHO-2019-nCoV-PHSM_Overview-2020.1-eng.pdf?sequence=1
• ^5. Özdin S, Özdin ŞB. Levels and predictors of anxiety, depression and health anxiety during COVID-19 pandemic in Turkish society: The importance of gender. Int J Soc Psychiatry. 2020;66(5):504-11. https://doi.org/10.1177/0020764020927051
  » https://doi.org/10.1177/0020764020927051
• ^6. Young BE, Ong SWX, Kalimuddin S, Low JG, Tan SY, Loh J, et al. Epidemiologic Features and Clinical Course of Patients Infected With SARS-CoV-2 in Singapore. JAMA. 2020;323(15):1510. https://doi.org/10.1001/jama.2020.3204
  » https://doi.org/10.1001/jama.2020.3204
• ^7. Chen KY, Li T, Gong FH, Zhang JS, Li XK. Predictors of Health-Related Quality of Life and Influencing Factors for COVID-19 Patients, a Follow-Up at One Month. Front Psychiatry. 2020;11:668. https://doi.org/10.3389/fpsyt.2020.00668
  » https://doi.org/10.3389/fpsyt.2020.00668
• ^8. Centers for Disease Control and Prevention. Single-race population estimates United States, State and County for the years 2010-2022 [Internet]. Atlanta, GA: CDC; 2023 [cited 2023 feb 10]. Available from: https://wonder.cdc.gov/wonder/help/single-race.html
  » https://wonder.cdc.gov/wonder/help/single-race.html
• ^9. Gleason J, Ross W, Fossi A, Blonsky H, Tobias J, Stephens M. The Devastating Impact of Covid-19 on Individuals with Intellectual Disabilities in the United States. NEJM Catal Innov Care Deliv. 2021. https://doi.org/10.1056/CAT.21.0051
  » https://doi.org/10.1056/CAT.21.0051
• ^10. FAIR Health; West Health Institute; Makary M. Risk Factors for COVID-19 Mortality among Privately Insured Patients [Internet]. New York, NY: FAIR Health Inc.; 2020 [cited 2023 Jan 8]. Available from: https://s3.amazonaws.com/media2.fairhealth.org/whitepaper/asset/Risk%20Factors%20for%20COVID-19%20Mortality%20among%20Privately%20Insured%20Patients%20-%20A%20Claims%20Data%20Analysis%20-%20A%20FAIR%20Health%20White%20Paper.pdf
  » https://s3.amazonaws.com/media2.fairhealth.org/whitepaper/asset/Risk%20Factors%20for%20COVID-19%20Mortality%20among%20Privately%20Insured%20Patients%20-%20A%20Claims%20Data%20Analysis%20-%20A%20FAIR%20Health%20White%20Paper.pdf
• ^11. Kochanek KD, Murphy SL, Xu JQ, Arias E. Mortality in the United States, 2022 [Internet]. Hyattsville, MD: National Center for Health Statistics; 2024 [cited 2023 Jan 10]. Available from: https://doi.org/10.15620/cdc:135850
• ^12. Aveyard P, Gao M, Lindson N, Hartmann-Boyce J, Watkinson P, Young D, et al. Association between pre-existing respiratory disease and its treatment, and severe COVID-19: a population cohort study. Lancet Respir Med. 2021;9(8):909-23. https://doi.org/10.1016/s2213-2600(21)00095-3
  » https://doi.org/10.1016/s2213-2600(21)00095-3
• ^13. Guan WJ, Liang WH, Shi Y, Gan LX, Wang HB, He JX, et al. Chronic Respiratory Diseases and the Outcomes of COVID-19: A Nationwide Retrospective Cohort Study of 39,420 Cases. J Allergy Clin Immunol Pract. 2021;(7):2645-2655.e14. https://doi.org/10.1016/j.jaip.2021.02.041
  » https://doi.org/10.1016/j.jaip.2021.02.041
• ^14. Moeller A, Thanikkel L, Duijts L, Gaillard EA, Garcia-Marcos L, Kantar A, et al. COVID-19 in children with underlying chronic respiratory diseases: survey results from 174 centres. ERJ Open Res. 2020;6(4):00409-2020. https://doi.org/10.1183/23120541.00409-2020
  » https://doi.org/10.1183/23120541.00409-2020
• ^15. Estiri H, Strasser ZH, Klann JG, Naseri P, Wagholikar KB, Murphy SN. Predicting COVID-19 mortality with electronic medical records. NPJ Digit Med. 2021;4(15). https://doi.org/10.1038/s41746-021-00383-x
  » https://doi.org/10.1038/s41746-021-00383-x
• ^16. Beltramo G, Cottenet J, Mariet AS, Georges M, Piroth L, Tubert-Bitter P, et al. Chronic respiratory diseases are predictors of severe outcome in COVID-19 hospitalised patients: a nationwide study. Eur Respir J. 2021;58(6):2004474. https://doi.org/10.1183/13993003.04474-2020
  » https://doi.org/10.1183/13993003.04474-2020
• ^17. Saini KS, Tagliamento M, Lambertini M, McNally R, Romano M, Leone M, et al. Mortality in patients with cancer and coronavirus disease 2019: A systematic review and pooled analysis of 52 studies. Eur J Cancer. 2020;139:43-50. https://doi.org/10.1016/j.ejca.2020.08.011
  » https://doi.org/10.1016/j.ejca.2020.08.011
• ^18. 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. https://doi.org/10.1016/j.ijid.2020.07.029
  » https://doi.org/10.1016/j.ijid.2020.07.029
• ^19. Pranata R, Huang I, Lim MA, Wahjoepramono EJ, July J. Impact of cerebrovascular and cardiovascular diseases on mortality and severity of COVID-19-systematic review, meta-analysis, and meta-regression. J Stroke Cerebrovasc Dis. 2020;29(8):104949. https://doi.org/10.1016/j.jstrokecerebrovasdis.2020.104949
  » https://doi.org/10.1016/j.jstrokecerebrovasdis.2020.104949
• ^20. Wang B, Li R, Lu Z, Huang Y. Does comorbidity increase the risk of patients with COVID-19: evidence from meta-analysis. Aging (Albany NY). 2020;12(7):6049-57. https://doi.org/10.18632/aging.103000
  » https://doi.org/10.18632/aging.103000
• ^21. Ssentongo P, Ssentongo AE, Heilbrunn ES, Ba DM, Chinchilli VM. Association of cardiovascular disease and 10 other pre-existing comorbidities with COVID-19 mortality: A systematic review and meta-analysis. PLoS One. 2020;15(8):e0238215. https://doi.org/10.1371/journal.pone.0238215
  » https://doi.org/10.1371/journal.pone.0238215
• ^22. Khan MMA, Khan MN, Mustagir MG, Rana J, Islam MS, Kabir MI. Effects of underlying morbidities on the occurrence of deaths in COVID-19 patients: A systematic review and meta-analysis. J Glob Health. 2020;10(2):020503. https://doi.org/10.7189/jogh.10.020503
  » https://doi.org/10.7189/jogh.10.020503
• ^23. Fajgenbaum DC, Khor JS, Gorzewski A, Tamakloe MA, Powers V, Kakkis JJ, et al. Treatments Administered to the First 9152 Reported Cases of COVID-19: A Systematic Review. Infect Dis Ther. 2020;9(3):435-49. https://doi.org/10.1007/s40121-020-00303-8
  » https://doi.org/10.1007/s40121-020-00303-8
• ^24. Boettler T, Marjot T, Newsome PN, Mondelli MU, Maticic M, Cordero E, et al. Impact of COVID-19 on the care of patients with liver disease: EASL-ESCMID position paper after 6 months of the pandemic. JHEP Rep. 2020;2(5):100169. https://doi.org/10.1016/j.jhepr.2020.100169
  » https://doi.org/10.1016/j.jhepr.2020.100169
• ^25. Sharma A, Jaiswal P, Kerakhan Y, Saravanan L, Murtaza Z, Zergham A, et al. Liver disease and outcomes among COVID-19 hospitalized patients - A systematic review and meta-analysis. Ann Hepatol. 2021;21:100273. https://doi.org/10.1016/j.aohep.2020.10.001
  » https://doi.org/10.1016/j.aohep.2020.10.001
• ^26. Thuluvath PJ, Robarts P, Chauhan M. Analysis of antibody responses after COVID-19 vaccination in liver transplant recipients and those with chronic liver diseases. J Hepatol. 2021;75(6):1434-9. https://doi.org/10.1016/j.jhep.2021.08.008
  » https://doi.org/10.1016/j.jhep.2021.08.008
• ^27. Fadini GP, Morieri ML, Longato E, Avogaro A. Prevalence and impact of diabetes among people infected with SARS-CoV-2. J Endocrinol Invest. 2020;43(6):867-9. https://doi.org/10.1007/s40618-020-01236-2
  » https://doi.org/10.1007/s40618-020-01236-2
• ^28. Del Sole F, Farcomeni A, Loffredo L, Carnevale R, Menichelli D, Vicario T, et al. Features of severe COVID-19: A systematic review and meta-analysis. Eur J Clin Invest. 2020;50(10):e13378. https://doi.org/10.1111/eci.13378
  » https://doi.org/10.1111/eci.13378
• ^29. Yang J, Zheng Y, Gou X, Pu K, Chen Z, Guo Q, et al. Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis. Int J Infect Dis. 2020;94:91-5. https://doi.org/10.1016/j.ijid.2020.03.017
  » https://doi.org/10.1016/j.ijid.2020.03.017
• ^30. Patanavanich R, Glantz SA. Smoking Is Associated With COVID-19 Progression: A Meta-analysis. Nicotine Tob Res. 2020;22(9):1653-6. https://doi.org/10.1093/ntr/ntaa082
  » https://doi.org/10.1093/ntr/ntaa082
• ^31. Guo FR. Active smoking is associated with severity of coronavirus disease 2019 (COVID-19): An update of a meta-analysis. Tob Induc Dis. 2020;18:37. https://doi.org/10.18332/tid/121915
  » https://doi.org/10.18332/tid/121915
• ^32. Zhao Q, Meng M, Kumar R, Wu Y, Huang J, Lian N, et al. The impact of COPD and smoking history on the severity of COVID-19: A systemic review and meta-analysis. J Med Virol. 2020;92(10):1915-21. https://doi.org/10.1002/jmv.25889
  » https://doi.org/10.1002/jmv.25889
• ^33. Li G, Liu Y, Jing X, Wang Y, Miao M, Tao L, et al. Mortality risk of COVID-19 in elderly males with comorbidities: a multi-country study. Aging. 2020;13(1):27-60. https://doi.org/10.18632/aging.202456
  » https://doi.org/10.18632/aging.202456
• ^34. Liu J, Zhang S, Wu Z, Shang Y, Dong X, Li G, et al. Clinical outcomes of COVID-19 in Wuhan, China: a large cohort study. Ann. Intensive Care. 2020;10(99). https://doi.org/10.1186/s13613-020-00706-3
  » https://doi.org/10.1186/s13613-020-00706-3
• ^35. Yang J, Hu J, Zhu C. Obesity aggravates COVID-19: A systematic review and meta-analysis. J Med Virol. 2020;93:257-61. https://doi.org/10.1002/jmv.26237
  » https://doi.org/10.1002/jmv.26237
• ^36. Yang Z, Wang M, Zhu Z, Liu, Y. Coronavirus disease 2019 (COVID-19) and pregnancy: a systematic review. J Matern Fetal Neonatal Med. 2020;35(8):1619-22. https://doi.org/10.1080/14767058.2020.1759541
  » https://doi.org/10.1080/14767058.2020.1759541
• ^37. Fond G, Nemani K, Etchecopar-Etchart D, Loundou A, Goff DC, Lee SW, et al. Association Between Mental Health Disorders and Mortality Among Patients With COVID-19 in 7 Countries: A Systematic Review and Meta-analysis. JAMA Psychiatry. 2021;78(11):1208-17. https://doi.org/10.1001/jamapsychiatry.2021.2274
  » https://doi.org/10.1001/jamapsychiatry.2021.2274
• ^38. Ceban F, Nogo D, Carvalho IP, Lee Y, Nasri F, Xiong J, et al. Association Between Mood Disorders and Risk of COVID-19 Infection, Hospitalization, and Death: A Systematic Review and Meta-analysis. JAMA Psychiatry. 2021;78(10):1079-91. https://doi.org/10.1001/jamapsychiatry.2021.1818
  » https://doi.org/10.1001/jamapsychiatry.2021.1818
• ^39. Conselho Federal de Medicina. Resolução nº 2.271, de 14 de fevereiro de 2020. Define as unidades de terapia intensiva e unidades de cuidado intermediário conforme sua complexidade e nível de cuidado, determinando a responsabilidade técnica médica, as responsabilidades éticas, habilitações e atribuições da equipe médica necessária para seu adequado funcionamento. Diário Oficial da União [Internet]. 2020 Apr 23 [cited 2023 Jan 10];77(seção 1):90. Available from: https://www.in.gov.br/web/dou/-/resolucao-n-2.271-de-14-de-fevereiro-de-2020-253606068
  » https://www.in.gov.br/web/dou/-/resolucao-n-2.271-de-14-de-fevereiro-de-2020-253606068
• ^40. Canto GL, Porporatti A, Souza B, Massignan C, Flores-Mir, C, Casett E, et al. Revisões sistemáticas da literatura: guia prático. 1. ed. Curitiba: Brazil Publishing; 2020. 208 p. https://doi.org/10.31012/978-65-5016-353-2
  » https://doi.org/10.31012/978-65-5016-353-2
• ^41. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. https://doi.org/10.1136/bmj.n71
  » https://doi.org/10.1136/bmj.n71
• ^42. Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan - a web and mobile app for systematic reviews. Syst Rev. 2016;5:210. https://doi.org/10.1186/s13643-016-0384-4
  » https://doi.org/10.1186/s13643-016-0384-4
• ^43. Peters MDJ, Godfrey CM, Khalil H, McInerney P, Parker D, Soares CB. Guidance for conducting systematic scoping reviews. Int J Evid Based Healthc. 2015;13(3):141-6. https://doi.org/10.1097/xeb.0000000000000050
  » https://doi.org/10.1097/xeb.0000000000000050
• ^44. Aromataris E, Lockwood C, Porritt K, Pilla B, Jordan Z, editors. JBI Manual for Evidence Synthesis. [Internet]. Adelaide: JBI; 2024 [cited 2024 Jan 20]. Available from: https://doi.org/10.46658/JBIMES-24-01
  » https://doi.org/10.46658/JBIMES-24-01
• ^45. Oliveira JMD, Pauleto P, Werlich MO, Massignan C, Lehmkuhl KM, Porfírio GJM, et al. Prevalence of orofacial injuries in wheeled non-motor sports athletes: a systematic review and meta-analysis. Dent Traumatol. 2021;37(4):546-56. https://doi.org/10.1111/edt.12661
  » https://doi.org/10.1111/edt.12661
• ^46. Stern C, Munn Z, Barker TH, Porritt K, Stone JC, Pap R, et al. Implementing GRADE in systematic reviews that adhere to JBI methodological conduct. JBI Evid Synth. 2024;22(3):351-8. https://doi.org/10.11124/jbies-23-00543
  » https://doi.org/10.11124/jbies-23-00543
• ^47. Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al., editors. Cochrane Handbook for Systematic Reviews of Interventions [Internet]. Version 6.4. [s.l.]: Cochrane; 2023 [cited 2024 Jan 10]. Available from: https://[www.training.cochrane.org/handbook ]( http://www.training.cochrane.org/handbook )
  » https://[www.training.cochrane.org/handbook» http://www.training.cochrane.org/handbook
• ^48. Battaglini D, Santori G, Chandraptham K, Iannuzzi F, Bastianello M, Tarantino F, et al. Neurological Complications and Noninvasive Multimodal Neuromonitoring in Critically Ill Mechanically Ventilated COVID-19 Patients. Front Neurol. 2020;11:602114. https://doi.org/10.3389%2Ffneur.2020.602114
  » https://doi.org/10.3389/fneur.2020.602114
• ^49. Serrano Fernández L, Ruiz Iturriaga LA, España Yandiola PP, Méndez Ocaña R, Pérez Fernández S, Tabernero Huget E, et al. Bacteraemic pneumococcal pneumonia and SARS-CoV-2 pneumonia: differences and similarities. Int J Infect Dis. 2022;115:39-47. https://doi.org/10.1016%2Fj.ijid.2021.11.023
  » https://doi.org/10.1016/j.ijid.2021.11.023
• ^50. Dutch COVID & Thrombosis Coalition, Kaptein FHJ, Stals MAM, Grootenboers M, Braken SJE, Burggraaf JLI, et al. Incidence of thrombotic complications and overall survival in hospitalized patients with COVID-19 in the second and first wave. Thromb Res. 2021;199:143-8. https://doi.org/10.1016%2Fj.thromres.2020.12.019
  » https://doi.org/10.1016/j.thromres.2020.12.019
• ^51. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020;382(18):1708-20. https://doi.org/10.1056/nejmoa2002032
  » https://doi.org/10.1056/nejmoa2002032
• ^52. Yang X, Yu Y, Xu J, Shu H, Xia J, Liu H, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med. 2020;8(5):475-81. https://doi.org/10.1016/S2213-2600(20)30079-5
  » https://doi.org/10.1016/S2213-2600(20)30079-5
• ^53. Park J, Kwon YS, Kim HA, Kwon DH, Hwang J, Jang SH, et al. Clinical Implications of Neurological Comorbidities and Complications in ICU Patients with COVID-19. J Clin Med. 2021;10(11):2281. https://doi.org/10.3390%2Fjcm10112281
  » https://doi.org/10.3390/jcm10112281
• ^54. Ramírez GAD, Montero CM, Vázquez VL. Caracterización de pacientes con COVID-19 en una unidad cuidados intensivos. Rev Cubana Med Trop [Internet]. 2021 [cited 2024 May 20];73(1):1-18. Available from: http://scielo.sld.cu/pdf/mtr/v73n1/1561-3054-mtr-73-01-e592.pdf
  » http://scielo.sld.cu/pdf/mtr/v73n1/1561-3054-mtr-73-01-e592.pdf
• ^55. Khan SH, Lindroth H, Perkins AJ, Jamil Y, Wang S, Roberts S, et al. Delirium Incidence, Duration, and Severity in Critically III Patients With Coronavirus Disease 2019. Crit Care Explor. 2020;2(12):e0290. https://doi.org/10.1097%2FCCE.0000000000000290
  » https://doi.org/10.1097/CCE.0000000000000290
• ^56. Bisso IC, Huespe I, Lockhart C, Massó A, Gonzalez Anaya J, Hornos M, et al. Clinical characteristics of critically ill patients with COVID-19. Medicina (B Aires) [Internet]. 2021 [cited 2023 Sep 21];81(4):527-35. Available from: https://pubmed.ncbi.nlm.nih.gov/34453793/
  » https://pubmed.ncbi.nlm.nih.gov/34453793/
• ^57. Villagrán JPV, Villagrán LV, Santis C, Pairumani R, Ferri G, Valenzuela C, et al. Experiencia de manejo de pacientes críticos con COVID-19 en Hospital Barros Luco Análisis descriptivo en un Hospital público de Alta Complejidad. Rev Chil Med Intensiva [Internet]. 2021 [cited 2024 Feb 20];35(3). Available from: https://www.medicina-intensiva.cl/revista/pdf/72/33.pdf
  » https://www.medicina-intensiva.cl/revista/pdf/72/33.pdf
• ^58. Organização Pan-Americana de Saúde. Folha informativa sobre COVID-19 [Internet]. Washington, D.C.: OPAS; 2020 [cited 2023 Aug 6]. Available from: https://www.paho.org/bra/index.php?option=com_content&view=article&id=6101:covid19&Itemid=875
  » https://www.paho.org/bra/index.php?option=com_content&view=article&id=6101:covid19&Itemid=875
• ^59. Bajema KL, Oster AM, McGovern OL, Lindstrom S, Stenger MR, Anderson TC, et al. Persons Evaluated for 2019 Novel Coronavirus - United States, January 2020. MMWR Morb Mortal Wkly Rep. 2020;69(6):166-70. https://doi.org/10.15585/mmwr.mm6906e1
  » https://doi.org/10.15585/mmwr.mm6906e1
• ^60. Chan JF, Yuan S, Kok KH, To KK, Chu H, Yang J, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395(10223):514-23. https://doi.org/10.1016/S0140-6736(20)30154-9
  » https://doi.org/10.1016/S0140-6736(20)30154-9
• ^61. Elrobaa IH, New KJ. COVID-19: Pulmonary and Extra Pulmonary Manifestations. Front Public Health. 2021;9:711616. https://doi.org/10.3389/fpubh.2021.711616
  » https://doi.org/10.3389/fpubh.2021.711616
• ^62. Nepal G, Rehrig JH, Shrestha GS, Shing YK, Yadav JK, Ojha R, et al. Neurological manifestations of COVID-19: a systematic review. Crit Care. 2020;24(1):421. https://doi.org/10.1186/s13054-020-03121-z
  » https://doi.org/10.1186/s13054-020-03121-z
• ^63. Solomon IH, Normandin E, Bhattacharyya S, Mukerji SS, Keller K, Ali AS, et al. Neuropathological Features of COVID-19. N Engl J Med. 2020;383(10):989-92. https://doi.org/10.1056/NEJMc2019373
  » https://doi.org/10.1056/NEJMc2019373
• ^64. Parohan M, Yaghoubi S, Seraji A, Javanbakht MH, Sarraf P, Djalali M. Risk factors for mortality in patients with Coronavirus disease 2019 (COVID-19) infection: a systematic review and meta-analysis of observational studies. Aging Male. 2020;23(5):1416-24. https://doi.org/10.1080/13685538.2020.1774748
  » https://doi.org/10.1080/13685538.2020.1774748
• ^65. Neiman AE, Campanharo CRV, Lopes MCBT, Piacezzi LHV, Batista REA. COVID-19: Association of risk classification with the Modified Early Warning Score and hospital outcomes. Rev. Latino-Am. Enfermagem. 2023;31:e3977. https://doi.org/10.1590/1518-8345.6666.3977
  » https://doi.org/10.1590/1518-8345.6666.3977

• *
  This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) - Finance Code 001, Brazil.
• How to cite this article
  Sawada NO, Reis TM, Freitas PS, Moraes CM, Peloso-Carvalho BM, Assunção MRS, et al. Prevalence of systemic complications of COVID-19 in critically ill patients: systematic review with meta-analysis. Rev. Latino-Am. Enfermagem. [cited]. Available from: . https://doi.org/10.1590/1518-8345.7568.4608

Edited by

• Associate Editor:
  Maria Lúcia Zanetti

Publication Dates

• Publication in this collection
  11 July 2025
• Date of issue
  2025

History

• Received
  26 June 2024
• Accepted
  16 Feb 2025