PREVALENCE, CLINICAL MANIFESTATIONS, AND ASSOCIATED FACTORS OF LONG COVID-19

ARTICULO ORIGINAL

REVISTA DE LA FACULTAD DE MEDICINA HUMANA 2021 - Universidad Ricardo Palma
10.25176/RFMH.v22i3.5043

PREVALENCE, CLINICAL MANIFESTATIONS, AND ASSOCIATED FACTORS OF LONG COVID-19

PREVALENCIA, MANIFESTACIONES CLÍNICAS Y FACTORES ASOCIADOS AL COVID-19 DE LARGA DURACIÓN

Daniel Rojas-Bolivar1,a, Fabiola Huaroto-Ramírez1,b, Maricela Curisinche-Rojas1,c, Diana Gonzales Zurita1,a, Ericson Gutiérrez1,2,d

1Unidad de Análisis y Generación de Evidencias en Salud Pública, Centro Nacional de Salud Pública, Instituto Nacional de Salud, Lima, Perú.
2Instituto de Investigación en Ciencias Biomédicas (INICIB), Universidad Ricardo Palma, Lima. Perú.
aMédico cirujano
bMédico especialista en enfermedades infecciosas y tropicales
cDoctora en Salud Pública, Licenciada en Enfermería
dMédico especialista en Gestión en Salud

ABSTRACT

The aim was to describe the prevalence, clinical manifestations, and associated factors of long-COVID. A bibliographic search of systematic reviews and meta-analyses was carried out in MEDLINE (through PubMed) until April 7th, 2022. 37 articles were found and 3 were included. Evidence quality was assessed via AMSTAR 2 criteria. Long-COVID prevalence is 43% (IC95%: 39% – 46%). Main clinical manifestations were weakness (41% [IC95%: 25% – 59%]), malaise (33% [IC95%: 15% – 57%]), fatigue (31% [IC95%: 24% – 39%]), concentration impairment (26% [IC95%: 21% – 32%]), and breathlessness (25% [IC95%: 18% – 34%]). Factors associated with long COVID were female sex, initial disease severity, age, and presence of comorbidities.

Keywords: COVID-19; post-acute COVID-19 syndrome; long COVID-19. (fuente: MeSH NLM).

RESUMEN

El objetivo fue describir la prevalencia, las manifestaciones clínicas y los factores asociados de COVID-19 de larga duración. Se realizó una búsqueda bibliográfica de revisiones sistemáticas y metaanálisis sobre COVID-19 de larga duración en MEDLINE (vía PubMed) hasta el 7 de abril de 2022. Se encontraron 37 artículos y se incluyeron 3. La calidad de la evidencia fue evaluada a través de los criterios de AMSTAR 2. La prevalencia reportada de COVID-19 de larga duración fue 43% (IC95%: 39% – 46%). Las principales manifestaciones clínicas fueron debilidad (41% [IC95%: 25% – 59%]), malestar general (33% [IC95%: 15% – 57%]), fatiga (31% [IC95%: 24% – 39%]), alteración en la concentración (26% [IC95%: 21% – 32%]) y sensación de falta de aire (25% [IC95%: 18% – 34%]). Los factores asociados a COVID de larga duración incluyeron sexo femenino, severidad de cuadro inicial, edad y presencia de comorbilidades.

Palabras Clave: COVID-19; síndrome de COVID-19 post-agudo; COVID-19 de larga duración.(fuente: DeCS BIREME).

Introduction

COVID-19 has been characterized by its acute clinical manifestations, including fever, cough, dyspnea, and fatigue (1,2); As the disease progresses, approximately 10% of patients require intensive care (3). Although it is true that most people who contract COVID-19 fully recover, there is a proportion that reported persistence of symptoms in the medium and long term (4–6), this picture is called by some researchers COVID-19 of long duration (long COVID) (4,7,8).

Despite the existence of cases of people with persistent symptoms after SARS-CoV-2 infection, there is still no clear consensus on the definition of long COVID-19. On the one hand, there is research evaluating the sequelae of COVID-19 (1,9), on the other hand, others define it as post-acute COVID-19 syndrome or PACS (10,11), as well as there is also a definition of the post-COVID syndrome (12,13). Such differences result in different estimates of prevalence, as well as different clinical implications. In this sense, the WHO defined long COVID-19 as “the disease contracted by people with a history of probable or confirmed SARS-CoV-2 infection; usually within three months of the onset of COVID-19 and with symptoms or effects lasting at least two months” (14).

Research has considered different definitions, outcomes, and follow-up times, so the state of knowledge about long COVID-19 is still insufficient. Our objective was to synthesize the available scientific information from systematic reviews regarding the prevalence, clinical manifestations, and associated factors of long COVID-19. The information presented was part of the evidence synthesis report prepared by the National Health Institute at the request of the Peruvian Ministry of Health (15).

Systematic research methodology and selection of results

Question formulation

Two clinical questions were formulated: in adults with a history of SARS-CoV-2 infection, what is the prevalence of long COVID-19 and the frequency of long COVID-19 symptoms? And, in adults with a history of SARS-CoV-2 infection, what are the factors associated with the presentation of long COVID-19?

Search and selection of evidence

The bibliographic search was carried out in MEDLINE (via PubMed), through a search strategy that included free terms and controlled language descriptors for long COVID-19 (Supplementary material 1: search strategy), the search was carried out until April 7th, 2022.

The selection of the articles was carried out individually by the authors, considering an initial phase of reading the titles and abstracts through the Rayyan platform (www.rayyan.ai) and a phase of reading the full text of the potentially relevant publications to determine their eligibility. The inclusion criteria were: 1) systematic reviews and meta-analyses of cohort, case-control, or cross-sectional studies that report results for outcomes of interest, evaluated at least three months from the onset of COVID-19 in adults; 2) reviews published in English and Spanish. If more than one systematic review was identified, the one with the best methodological quality was chosen. The following were excluded: 1) systematic reviews that had not assessed the risk of bias or the methodologic quality of the included studies; 2) systematic reviews focused on determining the prevalence of symptoms of a single organ or system and 3) letters to the editor, narrative reviews, preclinical studies (studies in vitro or animal models), and opinion articles.

Data extraction

The data was extracted in a standardized form that included the following information: author, year of publication, number of studies included in the review, number of participants, design, place, population characteristics, prevalence outcomes, associated factors, and assessment tool. risk of bias assessment and AMSTAR 2 score.

Assessment of methodological quality and risk of bias

The AMSTAR 2 tool (16) was used to assess the methodological quality of identified systematic reviews. The evaluation was carried out by four authors (FHR, DG, DR, MCR) in a paired and independent manner and discrepancies were resolved by consensus. The risk of bias in the included studies was considered from the reviews with the best AMSTAR 2 score.

Results

37 articles were identified in the bibliographic search. After reading the titles and abstracts, 17 articles were selected for full-text reading. Finally, after verifying eligibility criteria and applying the AMSTAR 2 criteria, 3 systematic reviews were selected for data synthesis (Figure 1), one of them was peer-reviewed and published after the search, considering the information provided by this latest version (9). Excluded articles and reasons for exclusion are described in Supplementary Material 2. The main characteristics of the selected systematic reviews are summarized in Table 1.


Figura 1: PRISMA diagram for study selection.


Table 1. Characteristics of the selected systematic reviews.

Author and year Number of studies/participants Design Place / Region Population characteristics Reported Prevalence Outcomes Evaluated factors Risk of study bias Score AMSTAR 2 of the RS
Chen 2021 50 studies 1,680,003 people -    Prospective cohorts (n=28) -    Retrospective cohorts (n=7) -    Bidirectional cohorts (n=6) -   Transversal (n=9) -    Europe: 22/50 -    North America: 11/50 -    South America: 1/40 -    Asia: 13/50 -    International: 3/50 -    Not hospitalized: 4165 (5 studies) -    Hospitalized: 67,161 (22 studies) -    1,608,677 positive COVID-19 patients, regardless of their hospitalization condition Prevalence in positive COVID-19 patients Hospitalized prevalence Prevalence 90 days Prevalence of general symptoms: -   Fatigue -   Dyspnea -   Sleeping problems -   Memory problems -    Sex -   Presence of asthma -    39 studies scored 6/9 or 7/9 -    1 study got 9/9 12/16 2 critical weaknesses Critically low confidence
Michelen 2021 39 studies 10 951 people -    Cohort (n=32) -    Transversal (n=6) -    Case-control (n=1) 12 countries -   Europe: 24/39 -   Asia: 9/39 -   United States: 3/39 -   Middle East: 3/39 -   People diagnosed with COVID-19 with symptoms ≥ 12 weeks, after the onset of COVID-19 -   Age: 90% adults only -   Female sex: 48% -   Hospitalization during acute COVID-19: 78% Prevalence of signs and symptoms -    Systemic -    Cardiopulmonary -    Upper respiratory -    Gastrointestinal -    Musculoskeletal -    Neurological and Neuromuscular -    Psychological and social -    Neurocognitive -    Others (skin rash, hair loss, conjunctivitis) -    Sex -    Age -    Severity of the initial disease -    Presence of comorbidities -    High risk (n=12) -    Moderate risk (n=22) -    Low risk (n=5) 13/16 1 critical weakness low confidence
Maglietta 2022 20 studies 13 340 people -    Prospective cohorts (n=8) -    Ambidirectional (cohorts, descriptive n=12) -   Europe: 11/20 -   China: 8/20 -   South America: 1/20 -    Adults discharged from hospitalization for COVID-19 with prospective follow-up ≥ 12 weeks -    Female sex: 48% Not rated -    Sex -    Severity of the initial disease   -    High risk (n=11) -    Moderate risk (n=9) 13/16 1 critical weakness low confidence
95% CI: 95% confidence interval, OR: Odds ratio, SR: systematic review


Characteristics of the studies

The study by Chen et al. (2022) was a systematic review and meta-analysis that aimed to examine the prevalence of post-acute sequelae of COVID-19 around the world (9). The databases consulted were PubMed, Embase, and iSearch for studies without peer review (preprints) of medRxiv, bioRxiv, Social Science Research Network (SSRN), and others (search performed on July 5, 2021, with an extension to March 13 of 2022). Studies in English that evaluated long COVID-19, defined as conditions that persist for at least 28 days after diagnosis or recovery from SARS-CoV-2 infection, were selected. The outcomes evaluated were prevalence, risk factors, duration, or associated symptoms. The search identified 5125 studies, from which 40 were included for qualitative synthesis, and 33 for meta-analysis (number of participants: 886,388). The selected studies were of the prospective cohort type (n = 23), retrospective cohort (n = 6), bidirectional cohort (n = 3), and cross-sectional studies (n = 8). The risk of bias assessment was carried out using the Joanna Briggs Institute tool for studies with prevalence results, for which they added the total responses classified as "Yes" concerning 9 questions of the tool (score from 0 to 9) where Aspects such as the representativeness of the population included (sampling framework, sampling), the size of the sample, the description of the population and the environment, the methods to evaluate the study condition, the statistical analysis and the percentage of response of the participants (17). After updating the search to March 13, 2022, an additional 10 studies were included for qualitative synthesis, of which 8 were included in the meta-analysis. The selected studies were of the prospective cohort type (n = 5), retrospective cohort (n = 1), bidirectional cohort (n = 3), and cross-sectional studies (n = 1). The total number of participants after the new systematic search was 1,680,003. The characteristics of the participants were: non-hospitalized participants (4,165 of 5 studies), hospitalized participants (67,161 of 22 studies), and any COVID-19 positive patient, regardless of their hospitalization status (1,608,677 of 23 studies). According to the risk of bias assessment with the Joanna Briggs Institute tool, the most frequent methodological limitations were: sampling was not adequate (16 of 50 studies), a valid method was not used to identify the study condition (15 of 50 studies), the sampling frame was not appropriate to address the target population (7 of 50 studies) and the data analysis was not performed with sufficient coverage of the identified sample (7 of 50 studies).

The study by Michelen et al. (2021) aimed to synthesize the evidence on the characteristics of long-lasting COVID-19 (8). The study design was of the living systematic review type. The authors performed the systematic search in the MEDLINE, CINAHL, Global Health (Ovid), WHO Global Research on COVID-19, LitCOVID, and Google Scholar databases (search period from January 1, 2002, to March 17, 2021). The outcomes evaluated were the prevalence of signs and symptoms and associated factors. A total of 39 studies were selected (cohort studies: 32; cross-sectional studies: 6; case-control studies: 1). The total number of participants was 10,951 (48% women) from 12 countries. The main finding was the estimation of the prevalence of symptoms of long COVID, in addition, a qualitative synthesis was carried out on diagnostic imaging (13 of 39; diagnostic methods included tomography, ultrasound, and artificial intelligence) and functional tests (10 of 39; methods included spirometry, diffusing capacity, lung volume, and exercise tests). The risk of bias was evaluated with the instrument developed by Hoy et al. (18), which is a validated tool for bias assessment in prevalence studies. The studies had a low risk of bias (4/39), moderate risk (23/39), and high risk (12/39). The domains that presented more studies with a high risk of bias were: 1) representation of the national population (21 of 39 studies), 2) true sampling frame or close representation of the target population (24 of 39) and 3) random selection used for sample selection (32 of 39 studies).

The study by Maglietta et al. (2022) aimed to identify, in patients who had been hospitalized for COVID-19, which factors were already present or emerging during hospitalization, It was associated with a higher risk of presenting new or persistent symptoms (12). The study design was a systematic review and a bibliographic search was carried out in 2 databases (MEDLINE and Web of Science) until September 20, 2021, including observational studies in English, with 12 weeks or more of prospective follow-up. Odds ratios were estimated for each assessed factor using unadjusted data. They also performed a random effects meta-analysis, using the Paule and Mandel method for estimating variance between studies (19,20). The confidence intervals for the global effect of the factors of interest were adjusted by applying the Hartung-Knapp-Sidik-Jonkman (HKSJ) approach, which takes into account the uncertainty in the variance of the estimates (21). Risk of bias assessment was performed using the QUIPS tool (22). This review provides evidence based on 20 observational studies and association measures for the factors of gender and severity of the initial condition concerning outcomes such as any symptoms, respiratory symptoms, mental health symptoms, and fatigue. Most studies (11 of 20) were rated as high risk of bias in at least 1 domain of the QUIPS tool and included: loss of participants to follow up (10 studies), the study sample was not representative of the population of interest (4 studies), limitations in statistical analysis and reporting of results (3 studies), and potential confounders not adequately addressed (1 study). The remaining studies (9 of 20) were at moderate risk of bias.

Prevalence of Long COVID-19

According to Chen et al. (2022), the overall prevalence of post-acute COVID-19 syndrome was 0.43 (95% CI: 0.39 – 0.46) (I2 = 100%; p


Prevalence of long-term clinical manifestations of COVID-19

According to Chen et al. (2022), the most frequent clinical manifestations of PACS were: fatigue (prevalence: 0.23 [95% CI: 0.17 – 0.30]), memory problems (0.14 [95% CI: 0.10 – 0.19]), dyspnea (0.13 [95% CI: 0.11 – 0.15]), insomnia (0.11 [95% CI: 0.05 – 0.23]), and joint pain (0.10 [95% CI: 0.04 – 0.22]).

On the other hand, according to Michelen et al. (2021), the most frequent clinical manifestations were weakness (prevalence: 41% [95% CI: 25.43 - 59.01]), malaise (33% [95% CI: 14.91 - 57.36]), fatigue (31% [95% CI: 23.91 – 39.03]), altered concentration (26% [95% CI: 20.96 – 31.73]), and shortness of breath (25% [95% CI: 17.86 – 33.97]). The list of signs and symptoms is described in Table 2.

Tabla 2. Prevalence of signs and symptoms of long COVID-19, according to the meta-analysis by Michelen (2021) (continued).

  Number of studies Proportion (95% CI) Heterogeneity I2 (%)
Neurological and neuromuscular      
Headache 11 4.88 (2.30 – 10.06) 94.88
Tremor 3 3.53 (0.30 – 30.63) 89.14
seizures 1 1.33 (0.49 – 2.87) NA
Bradykinesia 1 5.19 (2.11 – 10.39) NA
Dissymmetry 1 1.48 (0.18 – 5.25) NA
Muscular atrophy 1 6.67 (3.09 – 12.28) NA
Altered muscle tone 1 4.44 (1.65 – 9.42) NA
Altered gait or posture 3 4.20 (2.02 – 8.53) 0
Taste disturbance 17 13.52 (8.96 – 19.89) 96.75
Alteration of smell 19 15.17 (10.75 – 20.97) 96.2
Hearing disturbance 1 1.11 (0.36 – 2.57) NA
Vision disturbance 2 4.78 (3.32 – 6.83) 26.01
Dysarthria/speech difficulty 1 2.22 (0.46 – 6.36) NA
Sensation of decreased sensitivity 2 10.90 (6.71 – 17.22) 71.76
Paresthesia 2 9.12 (2.21 – 30.87) 93.07
Trigeminal neuralgia 1 3.28 (0.90 – 8.18) NA
Impaired reflexes 1 22.96 (16.17 – 30.98) NA
Others 1 14.81 (9.29 – 21.95) NA
Psychological and social      
Anxiety 7 18.73 (8.89 – 35.35) 97.2
Depression 6 8.06 (4.14 – 15.10) 97.45
Sleep disturbance 9 18.15 (9.61 – 31.63) 93.87
Post-traumatic stress disorder 6 9.14 (3.66 – 21.04) 96.44
Dysphoria 3 1.79 (0.00 – 98.74) 97.83
Reduced quality of life 3 36.76 (18.43 – 59.83) 91.07
Care dependency 3 5.89 (0.46 – 45.96) 98.37
Neurocognitive      
Memory disturbance 5 17.94 (5.26 – 46.25) 95.08
Altered concentration 2 25.98 (20.96 – 31.73) 0
Confusion 2 2.71 (1.93 – 3.79) 0
Frontal Release Signs 1 14.81 (9.29 – 21.95) NA
Others 3 17.77 (0.08 – 98.23) 98.68
Others      
skin rash 4 2.83 (0.95 – 8.16) 80.76
Hair loss 5 14.34 (5.33 – 33.23) 94.64
Conjunctivitis 1 1.77 (0.77 – 3.47) NA


A stratification was performed according to hospitalization status for COVID-19 and it was found that the prevalence of clinical manifestations was significantly higher in hospitalized patients, compared to non-hospitalized patients with fatigue (hospitalized: 37.10% [95% CI: 26.54 – 49.06]; not hospitalized: 24.60% [95% CI: 20.11 – 29.72]; p = 0.012), shortness of breath (hospitalized: 28.68% [95% CI: 18.48 – 41.64]; no hospitalized: 13.72% [95% CI: 8.51 – 21.37]; p = 0.003), weight loss (hospitalized: 37.31% [95% CI: 29.55 – 45.79]; non-hospitalized: 10.83% [95% CI: 8.23 – 14.12]; p


In both studies, limitations focused on the heterogeneity of the selected investigations in aspects such as design, population, measurement of the disease (heterogeneity in access to diagnostic tests), measurement of outcomes (self-diagnosis and differences in access to health), and follow-up period. In addition, there were inconsistencies in the terms used to describe symptoms, as well as limitations in the details and stratification of pre-existing comorbidities, the severity of COVID-19, and treatment methods. Also, the geographical distribution of the participants was another limitation. For example, few studies on long COVID-19 in low- or middle-income countries were identified, no studies were found in the pediatric population, and analyses stratified by ethnicity were also not performed. Other factors that can affect the measurement of prevalence are the type of predominant variant; thus, the Omicron variant (B.1.1.529) is related to mild acute symptoms in the vaccinated population; furthermore, the selection of articles in the English language excludes other important studies published in different languages.

Associated factors

The evidence came mainly from studies on people with a history of hospitalization for COVID-19, included in the systematic review by Michelen et al. (2021) and Maglietta et al. (2022) (8.12). There was high heterogeneity between the studies included in the reviews, given the different operational definitions for the prognostic factors evaluated and the outcomes of interest (Table 3).

Table 3. Factores asociados al COVID-19 de larga duración.

Factor Outcome Number of studies OR (CI95%) Heterogeneity I2 (%)
Female sex Any symptom 8 OR: 1.52 (1.27 – 1.82) 68%
Respiratory symptoms 12 OR: 1.20 (1.00 – 1.45) 65%
Any respiratory symptoms 2 OR: 1.10 (0.83 – 1.47) 63%
Cough 3 OR: 0.99 (0.75 – 1.31) 34%
DLCO<80% 4 OR: 2.28 (0.99 – 5.27) 71%
Dyspnea 4 OR: 1.07 (0.70 – 1.65) 87%
Difficulty breathing 2 OR: 1.12 (0.73 – 1.71) 63%
Odynophagia 3 OR: 1.40 (0.94 – 2.07) 0%
Mental health symptoms 7 OR: 1.67 (1.21 – 2.29) 58%
Anxiety 3 OR: 1.95 (1.52 – 2.49) 8%
PTSD 3 OR: 2.78 (0.63 – 12.22) 76%
Sleeping difficulties 3 OR: 1.26 (0.98 – 1.63) 32.5%
Others 3 OR: 1.72 (1.14 – 2.60) 41%
Fatigue 7 OR: 1.54 (1.32 – 1.79) 49%
Severity of the initial disease Respiratory symptoms 9 OR: 1.66 (1.03 – 2.68) 71%
Cough 2 OR: 1.78 (1.05 – 3.03) 0%
DLCO<80% 6 OR: 2.05 (1.06 – 3.96) 49%
Dyspnea 1 OR: 1.53 (0.66 – 3.54) NA
Difficulty breathing 2 OR: 1.12 (0.73 – 1.71) 63%
Fatigue 5 OR: 1.23 (0.73 – 2.07) 71%
Age       NA
Age > 60 years Olfactory dysfunction 1 OR: 0.42 (0.19 – 0.91)
Age Limitations in functional status (grade II to IV on the Post-COVID Functional Status Scale) 1 OR: 2.60 (1.19 – 5.67)
Age ≥ 60 years Low Quality of Life scores 1 OR: 2.44 (1.33 – 4.47)
Age 50-66 years vs younger age Persistence of symptoms (at 125 days) 1 vs 0-17 years: p=0.003 vs 18-34 years: p=0.001
Comorbidities       NA
Previous psychiatric diagnosis Persistence of depressive symptoms 1 P=0.006
1 comorbidity 2 comorbidities Olfactory dysfunction 1 OR: 0.39 (0.16–0.91) OR: 0.33 (0.19–0.99)
≥ 2 comorbidities Symptoms at follow-up 1 OR: 2.52 (1.58 – 4.02)
Cardiovascular disease (CVD) and diabetes Spirometric abnormalities 3 months after discharge 1 Reduced FEV1: ECV: 34.2% vs 9.4% Diabetes: 28.9% vs 12% Reduced FVC: ECV: 29.7% vs 11%
DLCO: Carbon monoxide diffusing capacity; FVC: Forced Vital Capacity; FEV1: Forced Expired Volume in the first second; PTSD: post-traumatic stress disorder.


Female gender was associated with the presence of any long-lasting COVID-19 symptoms (8 studies; OR: 1.52 [95% CI: 1.27 – 1.82]; I2 = 68%), with the presence of mental health symptoms, such as anxiety, post-traumatic stress disorder, insomnia, among others. (7 studies; OR: 1.67 [95% CI: 1.21 – 2.29]; I2 = 58%), and with fatigue (7 studies; OR: 1.54 [95% CI: 1.32 – 1.79]; I2 = 49%). However, no association was found between the female gender and respiratory symptoms (12 studies; OR: 1.20 [95% CI: 1.00 – 1.45]; I2 = 65%).

The severity of the initial symptoms of COVID-19 was associated with the persistence of respiratory symptoms (9 studies; OR: 1.66 [95% CI: 1.03 – 2.68]; I2 = 71%). In the analysis by symptom, the severity of the initial symptoms was associated with the persistence of cough (2 studies; OR: 1.78 [CI95%: 1.05 – 3.03]; I2 = 0%), and with the diffusing capacity of carbon monoxide ( DLCO) < 80% (6 studies; OR: 2.05 [95% CI: 1.06 – 3.96]; I2 = 49%). No statistically significant association was found with the presence of fatigue (5 studies; OR: 1.23 [95% CI: 0.73 – 2.07]; I2 = 71%).

In the review by Michelen et al. (2021), age was not included in the meta-analysis due to the high variability of the definitions for this variable and the different outcomes. Age ≥ 50-60 years was associated with a higher frequency of low quality of life scores (1 study), the persistence of symptoms assessed at 125 days of follow-up (1 study), and a lower frequency of olfactory dysfunction (1 study). Likewise, as age increased, an increased risk of deterioration in functional status measured by the post-COVID-19 functional status scale was observed (1 study).

Michelen et al. (2021) narratively synthesized the assessment of the presence of comorbidities and their association with the long-term persistence of COVID-19 symptoms. Having a previous diagnosis of psychiatric illness was significantly associated with the persistence of depressive symptoms (1 study). Likewise, having 2 or more comorbidities were risk factors for the persistence of symptoms during follow-up (1 study). An additional study identified that the presence of spirometric abnormalities 3 months after hospital discharge was more frequent among those with a history of cardiovascular disease and diabetes.

Methodological quality of the included systematic reviews

The quality assessment of the reviews included with AMSTAR 2 is presented in Table 4. Two of the reviews (8,12) had low confidence due to the presence of a critical weakness (item 7: list of items not provided). excluded studies and justification for exclusions), and confidence was very low in a further review due to two critical weaknesses (item 2: lack of an explicit statement of the existence of a protocol and item 7 already noted).

Table 4. Assessment of methodological quality according to AMSTAR 2.

Item Criteria Michelen 2021 Maglietta 2022 Chen 2022
1 Do the research questions and inclusion criteria for the review include the PICO components? (YES/NO) YES YES YES
2 Does the report contain an explicit statement that the review methods had been established before the review was conducted and did it justify any significant deviations from the protocol? (YES / YES PARTIAL / NO) YES YES NO
3 Did the authors explain the selection of study designs to include in the review? (YES/NO) YES YES YES
4 Did the authors use a comprehensive literature search strategy? (YES / YES PARTIAL / NO) YES YES PARTIAL YES PARTIAL
5 Did the authors perform the study selection in duplicate? (YES/NO) YES YES YES
6 Did the authors perform data extraction in duplicate? (YES/NO) NO YES YES
7 Did the authors provide a list of excluded studies and justify the exclusions? (YES / YES PARTIAL / NO) NO NO NO
8 Did the authors describe the included studies in adequate detail? (YES / YES PARTIAL / NO) YES YES PARTIAL YES
9 Did the authors use a satisfactory technique to assess the risk of bias in the individual studies that were included in the review? (YES / YES PARTIAL / NO) YES YES YES
10 Did the authors report funding sources for the studies included in the review? (YES/NO) NO NO NO
11 If they performed a meta-analysis, did the authors use appropriate methods for statistical pooling of results? (YES/ NO/ NO META-ANALYSIS) YES YES YES
12 Did the authors assess the potential impact of risk of bias in individual studies on the results of the meta-analysis or other evidence synthesis? (YES/ NO/ NO META-ANALYSIS) YES NO NO
13 Did the authors account for the risk of bias in individual studies when interpreting/discussing the results of the review? (YES/NO) YES YES YES
14 Did the review authors provide a satisfactory explanation and discussion of any observed heterogeneity in the review results? (BUT) YES YES YES
15 Did the authors conduct an adequate investigation of publication bias and discuss its possible impact on the results of the review? (YES/ NO/ NO META-ANALYSIS) YES YES YES
16 Did the authors disclose possible sources of conflict of interest, including the funding they received to conduct the review? (YES/NO) YES YES YES
Score 13/16 13/16 12/16
Number of critical weaknesses 1 (ítem 7) 1 (ítem 7) 2 (ítems 2 y 7)
Overall Confidence Low Low Critically low


Conclusions

Long COVID-19 is a problem that persists despite patients recovering from SARS-CoV-2 infection. According to the findings, the prevalence is greater than 40%, the most frequent clinical manifestations are weakness, malaise, fatigue, impaired concentration, and shortness of breath. Female sex, greater severity of the initial condition, increasing age, and the presence of comorbidities were found to be associated with long-lasting COVID-19 symptoms. Both in the assessment of prevalence and the analysis of associated factors, the findings came from studies with a moderate to high risk of bias.

This review has limitations to consider, such as the restriction to systematic reviews in Spanish or English, the search was limited to PubMed, and the selection and extraction of data were not carried out in a paired manner. However, considering the results of systematic reviews with better methodological quality, an overview of the best evidence available to date on this condition is provided and the need for better quality research for an adequate characterization of COVID-19 has been identified. of long duration and identification of its risk factors.


Authorship contributions: All authors participated in the conception and design of the article. DRB formulated and executed the search strategy. DRB, FHR, MCR, and DGZ performed study selection, data extraction, and methodological quality assessment. DRB wrote the first draft of the article and incorporated suggestions from the other authors. FHR, MCR, DGZ, and EG participated in a critical review of the manuscript and provided suggestions for improvement. All authors approved the final version of the article.
Funding sources: National Institute of Health (INS) of Peru.
Conflicts of interest: All authors declare no conflicts of interest.
Received: May 25, 2022
Approved: July 02, 2022


Correspondence: Daniel Rojas-Bolivar.
Address: 2268 Defensores del Morro Avenue, Chorrillos, Lima, Perú. Postal Code: 15066.
Telephone number: 51992789914
E-mail: drojasb@ins.gob.pe


Article published by the Journal of the faculty of Human Medicine of the Ricardo Palma University. It is an open access article, distributed under the terms of the Creatvie Commons license: Creative Commons Attribution 4.0 International, CC BY 4.0(https://creativecommons.org/licenses/by/1.0/), that allows non-commercial use, distribution and reproduction in any medium, provided that the original work is duly cited. For commercial use, please contact revista.medicina@urp.edu.pe.


REFERENCES

    1. Fu L, Wang B, Yuan T, Chen X, Ao Y, Fitzpatrick T, et al. Clinical characteristics of coronavirus disease 2019 (COVID-19) in China: A systematic review and meta-analysis. J Infect [Internet]. 2020 Jun;80(6):656–65. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0163445320301705
    2. Docherty AB, Harrison EM, Green CA, Hardwick HE, Pius R, Norman L, et al. Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study. BMJ [Internet]. 2020 May 22;m1985. Available from: https://www.bmj.com/lookup/doi/10.1136/bmj.m1985
    3. Khalili M, Karamouzian M, Nasiri N, Javadi S, Mirzazadeh A, Sharifi H. Epidemiological Characteristics of COVID-19: A Systematic Review and Meta-Analysis. Epidemiol Infect [Internet]. 2020 Jun 29;148:e130. Available from: https://www.cambridge.org/core/product/identifier/S0950268820001430/type/journal_article
    4. Akbarialiabad H, Taghrir MH, Abdollahi A, Ghahramani N, Kumar M, Paydar S, et al. Long COVID, a comprehensive systematic scoping review. Infection [Internet]. 2021 Dec 28;49(6):1163–86. Available from: https://link.springer.com/10.1007/s15010-021-01666-x
    5. Lopez-Leon S, Wegman-Ostrosky T, Perelman C, Sepulveda R, Rebolledo PA, Cuapio A, et al. More than 50 long-term effects of COVID-19: a systematic review and meta-analysis. Sci Rep [Internet]. 2021 Dec 9;11(1):16144. Available from: https://www.nature.com/articles/s41598-021-95565-8
    6. Ceban F, Ling S, Lui LMW, Lee Y, Gill H, Teopiz KM, et al. Fatigue and cognitive impairment in Post-COVID-19 Syndrome: A systematic review and meta-analysis. Brain Behav Immun [Internet]. 2022 Mar;101:93–135. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0889159121006516
    7. Cabrera Martimbianco AL, Pacheco RL, Bagattini ÂM, Riera R. Frequency, signs and symptoms, and criteria adopted for long COVID-19: A systematic review. Int J Clin Pract [Internet]. 2021 Oct 2;75(10):e14357. Available from: https://pubmed.ncbi.nlm.nih.gov/33977626/
    8. Michelen M, Manoharan L, Elkheir N, Cheng V, Dagens A, Hastie C, et al. Characterising long COVID: A living systematic review. BMJ Glob Heal [Internet]. 2021 Sep 27;6(9):e005427. Available from: https://gh.bmj.com/lookup/doi/10.1136/bmjgh-2021-005427
    9. Chen C, Haupert SR, Zimmermann L, Shi X, Fritsche LG, Mukherjee B. Global Prevalence of Post COVID-19 Condition or Long COVID: A Meta-Analysis and Systematic Review. J Infect Dis [Internet]. 2022 Apr 16; Available from: https://academic.oup.com/jid/advance-article/doi/10.1093/infdis/jiac136/6569364
    10. Malik P, Patel K, Pinto C, Jaiswal R, Tirupathi R, Pillai S, et al. Post-acute COVID-19 syndrome (PCS) and health-related quality of life (HRQoL)—A systematic review and meta-analysis. J Med Virol [Internet]. 2022 Jan 7;94(1):253–62. Available from: https://onlinelibrary.wiley.com/doi/10.1002/jmv.27309
    11. van Kessel SAM, Olde Hartman TC, Lucassen PLBJ, van Jaarsveld CHM. Post-acute and long-COVID-19 symptoms in patients with mild diseases: a systematic review. Fam Pract [Internet]. 2022 Jan 19;39(1):159–67. Available from: https://pubmed.ncbi.nlm.nih.gov/34268556/
    12. Maglietta G, Diodati F, Puntoni M, Lazzarelli S, Marcomini B, Patrizi L, et al. Prognostic Factors for Post-COVID-19 Syndrome: A Systematic Review and Meta-Analysis. J Clin Med [Internet]. 2022 Mar 11;11(6):1541. Available from: https://www.embase.com/search/results?subaction=viewrecord&id=L2015920578&from=export
    13. Iqbal FM, Lam K, Sounderajah V, Clarke JM, Ashrafian H, Darzi A. Characteristics and predictors of acute and chronic post-COVID syndrome: A systematic review and meta-analysis. EClinicalMedicine [Internet]. 2021 Jun;36:100899. Available from: https://pubmed.ncbi.nlm.nih.gov/34036253/
    14. OMS. Enfermedad por coronavirus (COVID-19): afección posterior a la COVID-19 [Internet]. OMS. 2021. Available from: https://www.who.int/es/news-room/questions-and-answers/item/coronavirus-disease-(covid-19)-post-covid-19-condition
    15. Rojas-Bolivar D, Gonzales-Zurita D, Huaroto-Ramírez F, Curisinche-Rojas M. Prevalencia, manifestaciones clínicas y factores asociados al desarrollo de COVID-19 de larga duración (Nota Técnica COVID-19 No022-2022) [Internet]. Lima, Peru: Instituto Nacional de Salud; 2022. Available from: https://web.ins.gob.pe/sites/default/files/Archivos/authenticated%2C administrator%2C editor/publicaciones/2022-04-28/NT_22_LongCOVID.pdf
    16. Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ [Internet]. 2017 Sep 21;358:j4008. Available from: https://www.bmj.com/lookup/doi/10.1136/bmj.j4008
    17. The Joanna Briggs Institute. The Joanna Briggs Institute Critical Appraisal tools for use in JBI Systematic Reviews: checklist for prevalence studies [Internet]. 2017. Available from: https://jbi.global/sites/default/files/2019-05/JBI_Critical_Appraisal-Checklist_for_Prevalence_Studies2017_0.pdf
    18. Hoy D, Brooks P, Woolf A, Blyth F, March L, Bain C, et al. Assessing risk of bias in prevalence studies: Modification of an existing tool and evidence of interrater agreement. J Clin Epidemiol [Internet]. 2012 Sep;65(9):934–9. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0895435612000790
    19. Axfors C, Janiaud P, Schmitt AM, van’t Hooft J, Smith ER, Haber NA, et al. Association between convalescent plasma treatment and mortality in COVID-19: a collaborative systematic review and meta-analysis of randomized clinical trials. BMC Infect Dis [Internet]. 2021 Dec 20;21(1):1170. Available from: https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-021-06829-7
    20. Veroniki AA, Jackson D, Viechtbauer W, Bender R, Bowden J, Knapp G, et al. Methods to estimate the between-study variance and its uncertainty in meta-analysis. Res Synth Methods [Internet]. 2016 Mar 2;7(1):55–79. Available from: https://onlinelibrary.wiley.com/doi/10.1002/jrsm.1164
    21. Inthout J, Ioannidis JP, Borm GF. The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method. BMC Med Res Methodol [Internet]. 2014 Dec 18;14(1):25. Available from: https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/1471-2288-14-25
    22. Hayden JA, van der Windt DA, Cartwright JL, Côté P, Bombardier C. Assessing bias in studies of prognostic factors. Ann Intern Med [Internet]. 2013 Feb 19;158(4):280–6. Available from: http://annals.org/article.aspx?doi=10.7326/0003-4819-158-4-201302190-00009

Supplementary material 1
Search strategy
Database: MEDLINE / PubMed

Search Strategy Result
"post acute covid 19 syndrome"[Supplementary Concept] OR "long covid"[Title/Abstract] OR "long haul covid"[Title/Abstract] OR "post-acute COVID syndrome"[Title/Abstract] OR "persistent COVID-19"[Title/Abstract] OR "post-acute COVID19 syndrome"[Title/Abstract] OR "long hauler COVID"[Title/Abstract] OR "long covid"[Title/Abstract] OR "post-acute sequelae of SARS-CoV-2 infection"[Title/Abstract] OR "long haul covid"[Title/Abstract] OR "chronic COVID syndrome"[Title/Abstract] 1384
FILTROS: Meta-Analysis, Systematic Review 37


Supplementary material 2
Reason for exclusion of articles

Nro Excluded articles Reason for exclusion
1 Ahmad et al. Did not assess the risk of bias in the included studies
2 Akbarialiabad et al. Did not assess the risk of bias in the included studies.
3 Behnood et al. Other population.
4 Cabrera et al. AMSTAR score 12/13, 1 critical weakness (item 13).
5 Cares-Marambio et al. Focused only on respiratory system symptoms, short follow-up period (21 days).
6 Ceban et al. Focused only on fatigue or cognitive impairment.
7 Han et al. AMSTAR score 11/16, 2 critical weaknesses (items 2 and 7).
8 Hayes et al. Other design (panoramic review).
9 Iqbal et al. AMSTAR score 12/16, 2 critical weaknesses (items 7 and 15).
10 Jennings et al. AMSTAR score 9/13, 1 critical weakness (item 7).
11 Lopez-Leon et al. Did not assess the risk of bias in the included studies.
12 Malik et al. AMSTAR score 8/16, 5 critical weaknesses (items 2, 4, 7, 13, and 15).
13 Nguyen et al. Includes studies with a short follow-up period (4 weeks).
14 van Kessel et al. Includes studies with ineligible designs.


Supplementary material 3
Excluded Studies

Ahmad MS, Shaik RA, Ahmad RK, Yusuf M, Khan M, Almutairi AB, et al. “LONG COVID”: an insight. Eur Rev Med Pharmacol Sci. septiembre de 2021;25(17):5561–77.
Akbarialiabad H, Taghrir MH, Abdollahi A, Ghahramani N, Kumar M, Paydar S, et al. Long COVID, a comprehensive systematic scoping review. Infection. diciembre de 2021;49(6):1163–86.
Behnood SA, Shafran R, Bennett SD, Zhang AXD, O’Mahoney LL, Stephenson TJ, et al. Persistent symptoms following SARS-CoV-2 infection amongst children and young people: A meta-analysis of controlled and uncontrolled studies. J Infect. febrero de 2022;84(2):158–70.
Cabrera Martimbianco AL, Pacheco RL, Bagattini ÂM, Riera R. Frequency, signs and symptoms, and criteria adopted for long COVID-19: A systematic review. Int J Clin Pract. octubre de 2021;75(10):e14357.
Cares-Marambio K, Montenegro-Jiménez Y, Torres-Castro R, Vera-Uribe R, Torralba Y, Alsina-Restoy X, et al. Prevalence of potential respiratory symptoms in survivors of hospital admission after coronavirus disease 2019 (COVID-19): A systematic review and meta-analysis. Chron Respir Dis. diciembre de 2021;18:14799731211002240.
Ceban F, Ling S, Lui LMW, Lee Y, Gill H, Teopiz KM, et al. Fatigue and cognitive impairment in Post-COVID-19 Syndrome: A systematic review and meta-analysis. Brain Behav Immun. marzo de 2022;101:93–135.
Han Q, Zheng B, Daines L, Sheikh A. Long-Term Sequelae of COVID-19: A Systematic Review and Meta-Analysis of One-Year Follow-Up Studies on Post-COVID Symptoms. Pathogens. el 19 de febrero de 2022;11(2):269.
Hayes LD, Ingram J, Sculthorpe NF. More Than 100 Persistent Symptoms of SARS-CoV-2 (Long COVID): A Scoping Review. Front Med (Lausanne). 2021;8:750378.
Iqbal FM, Lam K, Sounderajah V, Clarke JM, Ashrafian H, Darzi A. Characteristics and predictors of acute and chronic post-COVID syndrome: A systematic review and meta-analysis. EClinicalMedicine. junio de 2021;36:100899.
Jennings G, Monaghan A, Xue F, Mockler D, Romero-Ortuño R. A Systematic Review of Persistent Symptoms and Residual Abnormal Functioning following Acute COVID-19: Ongoing Symptomatic Phase vs. Post-COVID-19 Syndrome. J Clin Med. el 16 de diciembre de 2021;10(24):5913.
Lopez-Leon S, Wegman-Ostrosky T, Perelman C, Sepulveda R, Rebolledo PA, Cuapio A, et al. More than 50 long-term effects of COVID-19: a systematic review and meta-analysis. Sci Rep. el 9 de agosto de 2021;11(1):16144.
Malik P, Patel K, Pinto C, Jaiswal R, Tirupathi R, Pillai S, et al. Post-acute COVID-19 syndrome (PCS) and health-related quality of life (HRQoL)—A systematic review and meta-analysis. Journal of Medical Virology [Internet]. 2022 [citado el 7 de abril de 2022];94(1):253–62. Disponible en: https://onlinelibrary.wiley.com/doi/abs/10.1002/jmv.27309
Nguyen NN, Hoang VT, Dao TL, Dudouet P, Eldin C, Gautret P. Clinical patterns of somatic symptoms in patients suffering from post-acute long COVID: a systematic review. Eur J Clin Microbiol Infect Dis. abril de 2022;41(4):515–45.
van Kessel SAM, Olde Hartman TC, Lucassen PLBJ, van Jaarsveld CHM. Post-acute and long-COVID-19 symptoms in patients with mild diseases: a systematic review. Family Practice [Internet]. el 1 de febrero de 2022 [citado el 7 de abril de 2022];39(1):159–67. Disponible en: https://doi.org/10.1093/fampra/cmab076


http://www.scielo.org.pe/scielo.php?script=sci_serial&pid=2223-2516&lng=en&nrm=iso


¿Quieres dejar tu comentario o sugerencia sobre este artículo?

---> CLICK AQUI <---