Tag: covid hospitalization

Two-year follow-up of patients with post-COVID-19 condition in Sweden: a prospective cohort study

Summary:

Background: Few studies have reported the long-term health effects of COVID-19. The regional population-based Linköping COVID-19 study (LinCoS) included all patients hospitalised due to COVID-19 during the first pandemic wave. Four months post-discharge, over 40% (185/433) experienced persisting symptoms and activity/participation limitations, indicating post-COVID-19 condition (PCC). The present follow-up study aimed to determine the long-term recovery among these patients 24 months post-admission.

Methods: This prospective cohort study included all patients from LinCoS with PCC at four months post-discharge. We repeated the same structured interview at a 24-month follow-up to identify persisting symptoms and their impact on daily life. Intercurrent health issues were identified by reviewing medical records.

Findings: Of 185 patients with PCC at 4 months post-discharge, 181 were alive at the 24-month assessment and 165 agreed to participate. Of those, 21% (35/165) had been readmitted to hospital for various causes in the interim period. The majority of patients (139/165, 84%) reported persisting problems affecting everyday life at 24 months. Significant improvements were seen in the prevalence and magnitude of some symptoms/limitations compared with four months post-discharge. Cognitive, sensorimotor, and fatigue symptoms were the most common persisting symptoms at 24 months. No clear difference was evident between individuals treated in the intensive care unit (ICU) and non-ICU-treated individuals. Approximately half of those who were on sick leave related to PCC at four months after infection were on sick leave at 24 months.

Interpretation: This is one of the first studies to report 2-year outcomes in patients with PCC following COVID-19 hospitalisation. Despite some improvements over time, we found a high prevalence of persisting symptoms and a need for long-term follow-up and rehabilitation post COVID-19 infection.

Source: Carl Wahlgren et al. Two-year follow-up of patients with post-COVID-19 condition in Sweden: a prospective cohort study. The Lancet Regional Health – Europe. DOI:https://doi.org/10.1016/j.lanepe.2023.100595 https://www.thelancet.com/journals/lanepe/article/PIIS2666-7762(23)00013-3/fulltext (Full text)

The Very Long COVID: Persistence of Symptoms after 12–18 Months from the Onset of Infection and Hospitalization

Abstract:

According to the World Health Organization’s definition, long COVID is the persistence or development of new symptoms 3 months after the initial infection. Various conditions have been explored in studies with up to one-year follow-up but very few looked further. This prospective cohort study addresses the presence of a wide spectrum of symptoms in 121 patients hospitalized during the acute phase of COVID-19 infection, and the association between factors related to the acute phase of the disease and the presence of residual symptoms after one year or longer from hospitalization.
The main results are as follows: (i) post-COVID symptoms persist in up to 60% of the patient population at a mean follow-up of 17 months; (ii) the most frequent symptoms are fatigue and dyspnea, but neuropsychological disturbances persist in about 30% of the patients (iii) when corrected for the duration of follow-up with a freedom-from-event analysis; only complete (2 doses) vaccination at the time of hospital admission remained independently associated with persistence of the major physical symptoms, while vaccination and previous neuropsychological symptoms remained independently associated with persistence of major neuropsychological symptoms.
Source: Ranucci M, Baryshnikova E, Anguissola M, Pugliese S, Ranucci L, Falco M, Menicanti L. The Very Long COVID: Persistence of Symptoms after 12–18 Months from the Onset of Infection and Hospitalization. Journal of Clinical Medicine. 2023; 12(5):1915. https://doi.org/10.3390/jcm12051915 https://www.mdpi.com/2077-0383/12/5/1915 (Full text)

Vaccination status and long COVID symptoms in patients discharged from hospital

Abstract:

Effective vaccination against coronavirus mitigates the risk of hospitalisation and mortality; however, it is unclear whether vaccination status influences long COVID symptoms in patients who require hospitalisation. The available evidence is limited to outpatients with mild disease.

Here, we evaluated 412 patients (age: 60 ± 16 years, 65% males) consecutively admitted to two Hospitals in Brazil due to confirmed coronavirus disease 2019 (COVID-19). Compared with patients with complete vaccination (n = 185) before infection or hospitalisation, those with no or incomplete vaccination (n = 227) were younger and had a lower frequency of several comorbidities.

Data during hospitalisation revealed that the no or incomplete vaccination group required more admissions to the intensive care unit (ICU), used more corticosteroids, and had higher rates of pulmonary embolism or deep venous thrombosis than the complete vaccination group. Ninety days after hospital discharge, patients with no or incomplete vaccination presented a higher frequency of symptoms (≥ 1) than patients with complete vaccination (40 vs. 27%; p = 0.013).

After adjusting for confounders, no or incomplete vaccination (odds ratio [OR] 1.819; 95% confidence interval [CI] 1.175-2.815), female sex (OR 2.435; 95% CI 1.575-3.764) and ICU admission during hospitalisation (OR 1.697; 95% CI 1.062-2.712) were independently associated with ≥ 1 symptom 90 days after hospital discharge.

In conclusion, even in patients with severe COVID-19, vaccination mitigates the probability of long COVID symptoms.

Source: Nascimento TCDC, do Valle Costa L, Ruiz AD, Ledo CB, Fernandes VPL, Cardoso LF, Junior JMV, Saretta R, Kalil-Filho R, Drager LF. Vaccination status and long COVID symptoms in patients discharged from hospital. Sci Rep. 2023 Feb 11;13(1):2481. doi: 10.1038/s41598-023-28839-y. PMID: 36774419; PMCID: PMC9922040. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9922040/ (Full text)

A machine learning approach identifies distinct early-symptom cluster phenotypes which correlate with hospitalization, failure to return to activities, and prolonged COVID-19 symptoms

Abstract:

Background: Accurate COVID-19 prognosis is a critical aspect of acute and long-term clinical management. We identified discrete clusters of early stage-symptoms which may delineate groups with distinct disease severity phenotypes, including risk of developing long-term symptoms and associated inflammatory profiles.

Methods: 1,273 SARS-CoV-2 positive U.S. Military Health System beneficiaries with quantitative symptom scores (FLU-PRO Plus) were included in this analysis. We employed machine-learning approaches to identify symptom clusters and compared risk of hospitalization, long-term symptoms, as well as peak CRP and IL-6 concentrations.

Results: We identified three distinct clusters of participants based on their FLU-PRO Plus symptoms: cluster 1 (“Nasal cluster”) is highly correlated with reporting runny/stuffy nose and sneezing, cluster 2 (“Sensory cluster”) is highly correlated with loss of smell or taste, and cluster 3 (“Respiratory/Systemic cluster”) is highly correlated with the respiratory (cough, trouble breathing, among others) and systemic (body aches, chills, among others) domain symptoms. Participants in the Respiratory/Systemic cluster were twice as likely as those in the Nasal cluster to have been hospitalized, and 1.5 times as likely to report that they had not returned-to-activities, which remained significant after controlling for confounding covariates (P < 0.01). Respiratory/Systemic and Sensory clusters were more likely to have symptoms at six-months post-symptom-onset (P = 0.03). We observed higher peak CRP and IL-6 in the Respiratory/Systemic cluster (P < 0.01).

Conclusions: We identified early symptom profiles potentially associated with hospitalization, return-to-activities, long-term symptoms, and inflammatory profiles. These findings may assist in patient prognosis, including prediction of long COVID risk.

Source: Epsi NJ, Powers JH, Lindholm DA, Mende K, Malloy A, Ganesan A, Huprikar N, Lalani T, Smith A, Mody RM, Jones MU, Bazan SE, Colombo RE, Colombo CJ, Ewers EC, Larson DT, Berjohn CM, Maldonado CJ, Blair PW, Chenoweth J, Saunders DL, Livezey J, Maves RC, Sanchez Edwards M, Rozman JS, Simons MP, Tribble DR, Agan BK, Burgess TH, Pollett SD; EPICC COVID-19 Cohort Study Group. A machine learning approach identifies distinct early-symptom cluster phenotypes which correlate with hospitalization, failure to return to activities, and prolonged COVID-19 symptoms. PLoS One. 2023 Feb 9;18(2):e0281272. doi: 10.1371/journal.pone.0281272. PMID: 36757946; PMCID: PMC9910657. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9910657/ (Full text)

Risks and burdens of incident dyslipidaemia in long COVID: a cohort study

Abstract:

Background: Non-clinical evidence and a few human studies with short follow-ups suggest increased risk of dyslipidaemia in the post-acute phase of COVID-19 (ie, >30 days after SARS-CoV-2 infection). However, detailed large-scale controlled studies with longer follow-ups and in-depth assessment of the risks and burdens of incident dyslipidaemia in the post-acute phase of COVID-19 are not yet available. We, therefore, aimed to examine the risks and 1-year burdens of incident dyslipidaemia in the post-acute phase of COVID-19 among people who survive the first 30 days of SARS-CoV-2 infection.

Methods: In this cohort study, we used the national health-care databases of the US Department of Veterans Affairs to build a cohort of 51 919 participants who had a positive COVID-19 test and survived the first 30 days of infection between March 1, 2020, and Jan 15, 2021; a non-infected contemporary control group (n=2 647 654) that enrolled patients between March 1, 2020, and Jan 15, 2021; and a historical control group (n=2 539 941) that enrolled patients between March 1, 2018, and Jan 15, 2019. Control groups had no evidence of SARS-CoV-2 infection, and participants in all three cohorts were free of dyslipidaemia before cohort enrolment. We then used inverse probability weighting using predefined and algorithmically-selected high dimensional variables to estimate the risks and 1-year burdens of incident dyslipidaemia, lipid-lowering medications use, and a composite of these outcomes. We reported two measures of risk: hazard ratios (HRs) and burden per 1000 people at 12 months. Additionally, we estimated the risks and burdens of incident dyslipidaemia outcomes in mutually exclusive groups based on the care setting of the acute infection (ie, participants who were non-hospitalised, hospitalised, or admitted to intensive care during the acute phase of SARS-CoV-2 infection).

Findings: In the post-acute phase of the SARS-CoV-2 infection, compared with the non-infected contemporary control group, those in the COVID-19 group had higher risks and burdens of incident dyslipidaemia, including total cholesterol greater than 200 mg/dL (hazard ratio [HR] 1·26, 95% CI 1·22-1·29; burden 22·46, 95% CI 19·14-25·87 per 1000 people at 1 year), triglycerides greater than 150 mg/dL (1·27, 1·23-1·31; 22·03, 18·85-25·30), LDL cholesterol greater than 130 mg/dL (1·24, 1·20-1·29; 18·00, 14·98-21·11), and HDL cholesterol lower than 40 mg/dL (1·20, 1·16-1·25; 15·58, 12·52-18·73). The risk and burden of a composite of these abnormal lipid laboratory outcomes were 1·24 (95% CI 1·21-1·27) and 39·19 (95% CI 34·71-43·73), respectively. There was also increased risk and burden of incident lipid-lowering medications use (HR 1·54, 95% CI 1·48-1·61; burden 25·50, 95% CI 22·61-28·50). A composite of any dyslipidaemia outcome (laboratory abnormality or lipid-lowering medications use) yielded an HR of 1·31 (95% CI 1·28-1·34) and a burden of 54·03 (95% CI 49·21-58·92). The risks and burdens of these post-acute outcomes increased in a graded fashion corresponding to the severity of the acute phase of COVID-19 infection (ie, whether patients were non-hospitalised, hospitalised, or admitted to intensive care). The results were consistent in analyses comparing the COVID-19 group to the non-infected historical control group.

Interpretation: Our findings suggest increased risks and 1-year burdens of incident dyslipidaemia and incident lipid-lowering medications use in the post-acute phase of COVID-19 infection. Post-acute care for those with COVID-19 should involve attention to dyslipidaemia as a potential post-acute sequela of SARS-CoV-2 infection.

Source: Xu E, Xie Y, Al-Aly Z. Risks and burdens of incident dyslipidaemia in long COVID: a cohort study. Lancet Diabetes Endocrinol. 2023 Feb;11(2):120-128. doi: 10.1016/S2213-8587(22)00355-2. Epub 2023 Jan 6. PMID: 36623520; PMCID: PMC9873268. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9873268/ (Full text)

Can Baseline IL-6 Levels Predict Long COVID in Subjects Hospitalized for SARS-CoV-2 Disease?

Abstract:

The immune response to infection plays a crucial role in the pathogenesis of COVID-19, but several patients develop a wide range of persistent symptoms, which is becoming a major global health and economic burden. However, reliable indicators are not yet available to predict the persistence of symptoms typical of the so-called long COVID. Our study aims to explore an eventual role of IL-6 levels as a marker of long COVID. Altogether, 184 patients admitted to the COVID Medicine Unit of the University Hospital in Palermo, Italy, from the 1st of September 2020, were analyzed.

Patients were divided into two groups according to the IL-6 serum levels (normal or elevated), considering the serum IL-6 levels measured during the first four days of hospitalization. In our study, higher serum IL-6 levels were associated with a doubled higher risk of long COVID (OR = 2.05; 95% CI: 1.04-4.50) and, in particular, they were associated with a higher incidence of mobility decline (OR = 2.55; 95% CI: 1.08-9.40) and PTSD (OR = 2.38; 95% CI: 1.06-8.61). The analysis of our case series confirmed the prominent role of IL-6 levels in response to SARS-CoV-2 infection, as predictors not only of COVID-19 disease severity and unfavorable outcomes, but also long COVID development trends.

Source: Giannitrapani L, Mirarchi L, Amodeo S, Licata A, Soresi M, Cavaleri F, Casalicchio S, Ciulla G, Ciuppa ME, Cervello M, Barbagallo M, Veronese N, The Comepa Group. Can Baseline IL-6 Levels Predict Long COVID in Subjects Hospitalized for SARS-CoV-2 Disease? Int J Mol Sci. 2023 Jan 15;24(2):1731. doi: 10.3390/ijms24021731. PMID: 36675242. https://www.mdpi.com/1422-0067/24/2/1731 (Full text)

Clinical Characteristics in the Acute Phase of COVID-19 That Predict Long COVID: Tachycardia, Myalgias, Severity, and Use of Antibiotics as Main Risk Factors, While Education and Blood Group B Are Protective

Abstract:

Background: Risk factors for developing long COVID are not clearly established. The present study was designed to determine if any sign, symptom, or treatment of the acute phase, or personal characteristics of the patient, is associated with the development of long COVID.
Methods: A cohort study was carried out, randomly selecting symptomatic COVID-19 patients and not vaccinated. The severity of the acute illness was assessed through the number of compatible COVID-19 symptoms, hospitalizations, and the symptom severity score using a 10-point visual analog scale.
Results: After multivariate analysis, a severity score ≥8 (RR 2.0, 95%CI 1.1–3.5, p = 0.022), hospitalization (RR 2.1, 95%CI 1.0–4.4, p = 0.039), myalgia (RR 1.9, 95%CI 1.08–3.6, p = 0.027), tachycardia (RR 10.4, 95%CI 2.2–47.7, p = 0.003), and use of antibiotics (RR 2.0, 95%CI 1.1–3.5, p = 0.022), was positively associated with the risk of having long COVID. Higher levels of education (RR 0.6, 95%CI 0.4–0.9, p = 0.029) and type positive B blood group (B + AB, RR 0.44, 95%CI 0.2–0.9, p = 0.044) were protective factors. The most important population attributable fractions (PAFs) for long COVID were myalgia (37%), severity score ≥8 (31%), and use of antibiotics (27%).
Conclusions: Further studies in diverse populations over time are needed to expand the knowledge that could lead us to prevent and/or treat long COVID.
Source: Guzman-Esquivel J, Mendoza-Hernandez MA, Guzman-Solorzano HP, Sarmiento-Hernandez KA, Rodriguez-Sanchez IP, Martinez-Fierro ML, Paz-Michel BA, Murillo-Zamora E, Rojas-Larios F, Lugo-Trampe A, Plata-Florenzano JE, Delgado-Machuca M, Delgado-Enciso I. Clinical Characteristics in the Acute Phase of COVID-19 That Predict Long COVID: Tachycardia, Myalgias, Severity, and Use of Antibiotics as Main Risk Factors, While Education and Blood Group B Are Protective. Healthcare. 2023; 11(2):197. https://doi.org/10.3390/healthcare11020197 https://www.mdpi.com/2227-9032/11/2/197 (Full text)

Cognitive impairments among patients in a long-COVID clinic: Prevalence, pattern and relation to illness severity, work function and quality of life

Abstract:

Background: A considerable proportion of people experience lingering symptoms after Coronavirus Disease 2019 (COVID-19). The aim of this study was to investigate the frequency, pattern and functional implications of cognitive impairments in patients at a long-COVID clinic who were referred after hospitalisation with COVID-19 or by their general practitioner.

Methods: Patients underwent cognitive screening and completed questionnaires regarding subjective cognition, work function and quality of life. Patients’ cognitive performance was compared with that of 150 age-, sex-, and education-matched healthy controls (HC) and with their individually expected performance calculated based on their age, sex and education.

Results: In total, 194 patients were assessed, on average 7 months (standard deviation: 4) after acute COVID-19.44-53 % of the patients displayed clinically relevant cognitive impairments compared to HC and to their expected performance, respectively. Moderate to large impairments were seen in global cognition and in working memory and executive function, while mild to moderate impairments occurred in verbal fluency, verbal learning and memory. Hospitalised (n = 91) and non-hospitalised (n = 103) patients showed similar degree of cognitive impairments in analyses adjusted for age and time since illness. Patients in the cognitively impaired group were older, more often hospitalised, had a higher BMI and more frequent asthma, and were more often female. More objective cognitive impairment was associated with more subjective cognitive difficulties, poorer work function and lower quality of life.

Limitations: The study was cross-sectional, which precludes causality inferences.

Conclusions: These findings underscore the need to assess and treat cognitive impairments in patients at long-COVID clinics.

Source: Miskowiak KW, Pedersen JK, Gunnarsson DV, Roikjer TK, Podlekareva D, Hansen H, Dall CH, Johnsen S. Cognitive impairments among patients in a long-COVID clinic: Prevalence, pattern and relation to illness severity, work function and quality of life. J Affect Disord. 2022 Dec 28;324:162-169. doi: 10.1016/j.jad.2022.12.122. Epub ahead of print. PMID: 36586593; PMCID: PMC9795797. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9795797/ (Full text)

Deep Dive into the Long Haul: Analysis of Symptom Clusters and Risk Factors for Post-Acute Sequelae of COVID-19 to Inform Clinical Care

Abstract:

Long COVID is a chronic condition characterized by symptoms such as fatigue, dyspnea, and cognitive impairment that persist or relapse months after an acute infection with the SARS-CoV-2 virus. Many distinct symptoms have been attributed to Long COVID; however, little is known about the potential clustering of these symptoms and risk factors that may predispose patients to certain clusters. In this study, an electronic survey was sent to patients in the UC San Diego Health (UCSDH) system who tested positive for COVID-19, querying if patients were experiencing symptoms consistent with Long COVID.

Based on survey results, along with patient demographics reported in the electronic health record (EHR), linear and logistic regression models were used to examine putative risk factors, and exploratory factor analysis was performed to determine symptom clusters. Among 999 survey respondents, increased odds of Long COVID (n = 421; 42%) and greater Long COVID symptom burden were associated with female sex (OR = 1.73, 99% CI: 1.16-2.58; β = 0.48, 0.22-0.75), COVID-19 hospitalization (OR = 4.51, 2.50-8.43; β = 0.48, 0.17-0.78), and poorer pre-COVID self-rated health (OR = 0.75, 0.57-0.97; β = -0.19, -0.32–0.07).

Over one-fifth of Long COVID patients screened positive for depression and/or anxiety, the latter of which was associated with younger age (OR = 0.96, 0.94-0.99). Factor analysis of 16 self-reported symptoms suggested five symptom clusters-gastrointestinal (GI), musculoskeletal (MSK), neurocognitive (NC), airway (AW), and cardiopulmonary (CP), with older age (β = 0.21, 0.11-0.30) and mixed race (β = 0.27, 0.04-0.51) being associated with greater MSK symptom burden. Greater NC symptom burden was associated with increased odds of depression (OR = 5.86, 2.71-13.8) and anxiety (OR = 2.83, 1.36-6.14).

These results can inform clinicians in identifying patients at increased risk for Long COVID-related medical issues, particularly neurocognitive symptoms and symptom clusters, as well as informing health systems to manage operational expectations on a population-health level.

Source: Goldhaber NH, Kohn JN, Ogan WS, Sitapati A, Longhurst CA, Wang A, Lee S, Hong S, Horton LE. Deep Dive into the Long Haul: Analysis of Symptom Clusters and Risk Factors for Post-Acute Sequelae of COVID-19 to Inform Clinical Care. Int J Environ Res Public Health. 2022 Dec 15;19(24):16841. doi: 10.3390/ijerph192416841. PMID: 36554723; PMCID: PMC9778884. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9778884/ (Full text)

Characteristics and predictors of Long COVID among diagnosed cases of COVID-19

Abstract:

Background: Long COVID or long-term symptoms after COVID-19 has the ability to affect health and quality of life. Knowledge about the burden and predictors could aid in their prevention and management. Most of the studies are from high-income countries and focus on severe acute COVID-19 cases. We did this study to estimate the incidence and identify the characteristics and predictors of Long COVID among our patients.

Methodology: We recruited adult (≥18 years) patients who were diagnosed as Reverse Transcription Polymerase Chain Reaction (RTPCR) confirmed SARS-COV-2 infection and were either hospitalized or tested on outpatient basis. Eligible participants were followed up telephonically after four weeks and six months of diagnosis of SARS-COV-2 infection to collect data on sociodemographic, clinical history, vaccination history, Cycle threshold (Ct) values during diagnosis and other variables. Characteristics of Long COVID were elicited, and multivariable logistic regression was done to find the predictors of Long COVID.

Results: We have analyzed 487 and 371 individual data with a median follow-up of 44 days (Inter quartile range (IQR): 39,47) and 223 days (IQR:195,251), respectively. Overall, Long COVID was reported by 29.2% (95% Confidence interval (CI): 25.3%,33.4%) and 9.4% (95% CI: 6.7%,12.9%) of participants at four weeks and six months of follow-up, respectively. Incidence of Long COVID among patients with mild/moderate disease (n = 415) was 23.4% (95% CI: 19.5%,27.7%) as compared to 62.5% (95% CI: 50.7%,73%) in severe/critical cases(n = 72) at four weeks of follow-up. At six months, the incidence among mild/moderate (n = 319) was 7.2% (95% CI:4.6%,10.6%) as compared to 23.1% (95% CI:12.5%,36.8%) in severe/critical (n = 52). The most common Long COVID symptom was fatigue. Statistically significant predictors of Long COVID at four weeks of follow-up were-Pre-existing medical conditions (Adjusted Odds ratio (aOR) = 2.00, 95% CI: 1.16,3.44), having a higher number of symptoms during acute phase of COVID-19 disease (aOR = 11.24, 95% CI: 4.00,31.51), two doses of COVID-19 vaccination (aOR = 2.32, 95% CI: 1.17,4.58), the severity of illness (aOR = 5.71, 95% CI: 3.00,10.89) and being admitted to hospital (Odds ratio (OR) = 3.89, 95% CI: 2.49,6.08).

Conclusion: A considerable proportion of COVID-19 cases reported Long COVID symptoms. More research is needed in Long COVID to objectively assess the symptoms and find the biological and radiological markers.

Source: Arjun MC, Singh AK, Pal D, Das K, G A, Venkateshan M, Mishra B, Patro BK, Mohapatra PR, Subba SH. Characteristics and predictors of Long COVID among diagnosed cases of COVID-19. PLoS One. 2022 Dec 20;17(12):e0278825. doi: 10.1371/journal.pone.0278825. PMID: 36538532; PMCID: PMC9767341. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9767341/ (Full text)