First wave of COVID-19 hospital admissions in Denmark: a Nationwide population-based cohort study

Follow-Up Study of Effectiveness of 23-Valent Pneumococcal Polysaccharide Vaccine Against All-Type and Serotype-Specific Invasive Pneumococcal Disease, Denmark

As a follow-up to a previous study, we investigated vaccine effectiveness (VE) of 23-valent pneumococcal polysaccharide vaccine (PPSV23) against invasive pneumococcal disease (IPD) among 1,254,498 persons >65 years of age as part of a vaccination program in Denmark during April 2020-January 2023. We assessed VE by using a Cox regression model and adjusted for age, sex, and underlying conditions. Using nationwide data, we estimated a VE of PPSV23 against all-type IPD of 32% and against PPSV23-serotype IPD of 41%. Because this follow-up study had more statistical power than the original study, we also estimated VE against IPD caused by PPSV23-serotypes excluding serotype 3; serotype 3; serotype 8; serotype 22F; PPSV23 non-PCV15 serotypes; PPSV23 non-PCV20 serotypes; and IPD over time. Our findings suggest PPSV23 vaccination can protect persons >65 years of age against IPD caused by all serotypes or serotype groupings, except serotype 3.

Age-adjusted Charlson comorbidity index is associated with the risk of osteoporosis in older fall-prone men: a retrospective cohort study

BACKGROUND

There is growing evidence linking the age-adjusted Charlson comorbidity index (aCCI), an assessment tool for multimorbidity, to fragility fracture and fracture-related postoperative complications. However, the role of multimorbidity in osteoporosis has not yet been thoroughly evaluated. We aimed to investigate the association between aCCI and the risk of osteoporosis in older adults at moderate to high risk of falling.

METHODS

A total of 947 men were included from January 2015 to August 2022 in a hospital in Beijing, China. The aCCI was calculated by counting age and each comorbidity according to their weighted scores, and the participants were stratified into two groups by aCCI: low (aCCI < 5), and high (aCCI ≥5). The Kaplan Meier method was used to assess the cumulative incidence of osteoporosis by different levels of aCCI. The Cox proportional hazards regression model was used to estimate the association of aCCI with the risk of osteoporosis. Receiver operating characteristic (ROC) curve was adapted to assess the performance for aCCI in osteoporosis screening.

RESULTS

At baseline, the mean age of all patients was 75.7 years, the mean BMI was 24.8 kg/m2, and 531 (56.1%) patients had high aCCI while 416 (43.9%) were having low aCCI. During a median follow-up of 6.6 years, 296 participants developed osteoporosis. Kaplan-Meier survival curves showed that participants with high aCCI had significantly higher cumulative incidence of osteoporosis compared with those had low aCCI (log-rank test: P < 0.001). When aCCI was examined as a continuous variable, the multivariable-adjusted model showed that the osteoporosis risk increased by 12.1% (HR = 1.121, 95% CI 1.041-1.206, P = 0.002) as aCCI increased by one unit. When aCCI was changed to a categorical variable, the multivariable-adjusted hazard ratios associated with different levels of aCCI [low (reference group) and high] were 1.00 and 1.557 (95% CI 1.223-1.983) for osteoporosis (P <  0.001), respectively. The aCCI (cutoff ≥5) revealed an area under ROC curve (AUC) of 0.566 (95%CI 0.527-0.605, P = 0.001) in identifying osteoporosis in older fall-prone men, with sensitivity of 64.9% and specificity of 47.9%.

CONCLUSIONS

The current study indicated an association of higher aCCI with an increased risk of osteoporosis among older fall-prone men, supporting the possibility of aCCI as a marker of long-term skeletal-related adverse clinical outcomes.

Three Years of the Coronavirus Disease 2019 Pandemic in a European Region: A Population-Based Longitudinal Assessment in Madrid Between 2020 and 2022

Background

Our objective was to assess the health impact of coronavirus disease 2019 (COVID-19) during 2020-2022 in the Madrid region.

Methods

We included all individuals registered in the Madrid Health System Registry as of 31 December 2019, and followed them until 31 December 2022. Using a unique personal identifier, we linked the databases of primary care, hospitals, pharmacies, certified laboratories performing diagnostic tests, vaccines, and mortality.

Results

Of 6 833 423 individuals, 21.4% had a confirmed COVID-19 diagnosis, and 1.5% had a COVID-19 hospitalization (primary diagnosis). Thirty-day mortality was 1.6% for confirmed COVID-19 (from 11.4% in first semester 2020 to 0.4% in first semester 2022). Thirty-day mortality was 10.8% for COVID-19 hospitalizations (from 14.0% in first semester 2020 to 6.0% in second semester 2022). There were 24 073 deaths within 30 days of a confirmed COVID-19 diagnosis. Advanced age, male sex, higher socioeconomic deprivation, and comorbidities were associated with higher mortality.

Conclusions

By linking administrative and clinical databases, we characterized the burden of the COVID-19 pandemic in Madrid over 3 years. Our analysis proposes a high-level framework for comparisons of the burden of COVID-19 across areas worldwide.

Clinical characteristics and predictors for in-hospital mortality in adult COVID-19 patients: A retrospective single center cohort study in Vilnius, Lithuania

BACKGROUND

The COVID-19 infection had spread worldwide causing many deaths. Mortality rates and patients' characteristics varied within and between countries, making it important to understand the peculiarities of different populations. The aim of this study was to identify the main predictors associated with in-hospital mortality due to COVID-19 in Vilnius, Lithuania.

MATERIALS AND METHODS

This was a retrospective observational cohort study conducted at Vilnius University Hospital Santaros Clinics, Lithuania. The study included SARS-CoV-2 positive patients aged over 18 years and hospitalized between March 2020 and May 2021. Depersonalized data were retrieved from electronic medical records. The predictive values of laboratory parameters were evaluated using ROC analysis. Multivariable binary logistic regression was performed to reveal predictors of in-hospital mortality due to COVID-19.

RESULTS

Among 2794 patients, 54.4% were male, the age median was 59 years (IQR 48-70), 47.4% had at least one comorbidity. The most common comorbidities were arterial hypertension (36.9%) and diabetes mellitus (13.7%). Overall, 12.7% of patients died. Multivariable regression revealed that age (OR 1.04, 95%CI 1.02-1.06), congestive heart failure (OR 3.06, 95%CI 1.96-4.77), obesity (OR 3.90, 95%CI 2.12-7.16), COPD (OR 2.92, 95%CI 1.12-7.60), previous stroke (OR 5.80, 95%CI 2.07-16.21), urea >7.01 mmol/l (OR 2.32, 95%CI 1.47-3.67), AST/ALT >1.49 (OR 1.54, 95%CI 1.08-2.21), LDH >452.5 U/l (OR 2.60, 95%CI 1.74-3.88), CRP >92.68 mg/l (OR 1.58, 95%CI 1.06-2.35), IL-6 >69.55 ng/l (OR 1.62, 95%CI 1.10-2.40), and troponin I >18.95 ng/l (OR 2.04, 95%CI 1.38-3.02), were associated with increased risk for in-hospital mortality in COVID-19 patients.

CONCLUSIONS

Age, congestive heart failure, obesity, COPD, prior stroke, and increased concentration of urea, LDH, CRP, IL-6, troponin I, ALT to AST ratio were identified to be the predictors for in-hospital mortality of COVID-19 patients.

COVID-19 second wave and clinical characteristics of cases in Uganda: A retrospective cross-sectional survey of confirmed SARS-CoV-2 cases, March-June 2021

We conducted a retrospective cross-sectional population-based survey among recovered COVID-19 cases in Uganda to establish the case presentations of the second wave SARS-CoV-2 infections. We interviewed 1,120 recovered COVID-19 cases from 10 selected districts in Uganda. We further conducted 38 key informant interviews with members of the COVID-19 District Taskforce and 19 in-depth interviews among COVID-19 survivors from March to June 2021. Among them, 62% were aged 39 years and below and 51.5% were female with 90.9% under home-based care management. Cases were more prevalent among businesspeople (25.9%), students (16.2%), farmers (16.1%), and health workers (12.4%). Being asymptomatic was found to be associated with not seeking healthcare (APR 2, P < 0.001). The mortality rate was 3.6% mostly among the elderly (6.3%) and 31.3% aged 40 years and above had comorbidities of high blood pressure, diabetes, and asthma. Being asymptomatic, or under home-based care management (HBCM), working/operating/studying at schools, and not being vaccinated were among the major drivers of the second wave of the resurgence of COVID19 in Uganda. Managing future COVID-19 waves calls for proactive efforts for improving homebased care services, ensuring strict observation of SOPs in schools, and increasing the uptake of COVID-19 vaccination.

Comparative subgenomic mRNA profiles of SARS-CoV-2 Alpha, Delta and Omicron BA.1, BA.2 and BA.5 sub-lineages using Danish COVID-19 genomic surveillance data

BACKGROUND

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has rapidly spread worldwide in the population since it was first detected in late 2019. The transcription and replication of coronaviruses, although not fully understood, is characterised by the production of genomic length RNA and shorter subgenomic RNAs to make viral proteins and ultimately progeny virions. Observed levels of subgenomic RNAs differ between sub-lineages and open reading frames but their biological significance is presently unclear.

METHODS

Using a large and diverse panel of virus sequencing data produced as part of the Danish COVID-19 routine surveillance together with information in electronic health registries, we assessed the association of subgenomic RNA levels with demographic and clinical variables of the infected individuals.

FINDINGS

Our findings suggest no significant statistical relationship between levels of subgenomic RNAs and host-related factors.

INTERPRETATION

Differences between lineages and subgenomic ORFs may be related to differences in target cell tropism, early virus replication/transcription kinetics or sequence features.

FUNDING

The author(s) received no specific funding for this work.

Disease severity in hospitalized COVID-19 patients: comparing routine surveillance with cohort data from the LEOSS study in 2020 in Germany

INTRODUCTION

Studies investigating risk factors for severe COVID-19 often lack information on the representativeness of the study population. Here, we investigate factors associated with severe COVID-19 and compare the representativeness of the dataset to the general population.

METHODS

We used data from the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS) of hospitalized COVID-19 patients diagnosed in 2020 in Germany to identify associated factors for severe COVID-19, defined as progressing to a critical disease stage or death. To assess the representativeness, we compared the LEOSS cohort to cases of hospitalized patients in the German statutory notification data of the same time period. Descriptive methods and Poisson regression models were used.

RESULTS

Overall, 6672 hospitalized patients from LEOSS and 132,943 hospitalized cases from the German statutory notification data were included. In LEOSS, patients above 76 years were less likely represented (34.3% vs. 44.1%). Moreover, mortality was lower (14.3% vs. 21.5%) especially among age groups above 66 years. Factors associated with a severe COVID-19 disease course in LEOSS included increasing age, male sex (adjusted risk ratio (aRR) 1.69, 95% confidence interval (CI) 1.53-1.86), prior stem cell transplantation (aRR 2.27, 95% CI 1.53-3.38), and an elevated C-reactive protein at day of diagnosis (aRR 2.30, 95% CI 2.03-2.62).

CONCLUSION

We identified a broad range of factors associated with severe COVID-19 progression. However, the results may be less applicable for persons above 66 years since they experienced lower mortality in the LEOSS dataset compared to the statutory notification data.

Sex differences in D-dimer and critical illness in patients with COVID-19: A systematic review and meta-analysis

Background

Observed sex differences in COVID-19 outcomes suggest that men are more likely to experience critical illness and mortality. Thrombosis is common in severe COVID-19, and D-dimer is a significant marker for COVID-19 severity and mortality. It is unclear whether D-dimer levels differ between men and women, and the effect of D-dimer levels on disease outcomes remains under investigation.

Objectives

We aimed to evaluate the sex difference in the D-dimer level among hospitalized patients with COVID-19 and the effect of sex and D-dimer level on disease outcomes.

Methods

We meta-analyzed articles reporting D-dimer levels in men and women hospitalized for COVID-19, until October 2021, using random effects. Primary outcomes were mortality, critical illness, and thrombotic complications.

Results

In total, 11,682 patients from 10 studies were analyzed (N = 5606 men (55.7%), N = 5176 women (44.3%)). Men had significantly higher odds of experiencing mortality (odds ratios (OR) = 1.41, 95% CI: [1.25, 1.59], P ≤ .001, I² = 0%) and critical illness (OR = 1.76, 95% CI: [1.43, 2.18], P ≤ .001, I² = 61%). The mean D-dimer level was not significantly different between men and women (MD = 0.08, 95% CI: [-0.23, 0.40], P = .61, I² = 52%). In the subgroup analysis, men had significantly higher odds of experiencing critical illness compared with women in both the "higher" (P = .006) and "lower" (P = .001) D-dimer subgroups.

Conclusion

Men have significantly increased odds of experiencing poor COVID-19 outcomes compared with women. No sex difference was found in the D-dimer level between men and women with COVID-19. The diversity in D-dimer reporting impacts data interpretation and requires further attention.

Hospitalisation at Home of Patients with COVID-19: A Qualitative Study of User Experiences

Hospitalisation at Home (HaH) is a new model providing hospital-level care at home as a substitute for traditional care. Biometric monitoring and digital communication are crucial, but little is known about user perspectives. We aim to explore how in-patients with severe COVID-19 infection and clinicians engage with and experience communication and self-monitoring activities following the HaH model. A qualitative study based on semi-structured interviews of patients and clinicians participating in the early development phase of HaH were conducted. We interviewed eight clinicians and six patients. Five themes emerged from clinicians: (1) staff fear and concerns, (2) workflow, (3) virtual closeness, (4) patient relatives, and (5) future HaH models; four themes emerged from patients: (1) transition to home, (2) joint responsibility, (3) acceptability of technologies, and (4) relatives. Despite technical problems, both patients and clinicians were enthusiastic about the conceptual HaH idea. If appropriately introduced, treatment based on self-monitoring and remote communication was perceived acceptable for the patients; however, obtaining vitals at night was an overwhelming challenge. HaH is generally acceptable, perceived patient-centred, influencing routine clinical workflow, role and job satisfaction. Therefore, it calls for educational programs including more perspective than issues related to technical devices.

A systematic review and meta-analysis of the association between the neutrophil, lymphocyte, and platelet count, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio and COVID-19 progression and mortality

BACKGROUND AND AIMS

Severe manifestations of coronavirus disease 2019 (COVID-19) are associated with alterations in blood cells that regulate immunity, inflammation, and hemostasis. We conducted an updated systematic review and meta-analysis of the association between the neutrophil, lymphocyte, and platelet count, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), and COVID-19 progression and mortality.

METHODS

A systematic literature search was conducted in PubMed, Web of Science, and Scopus for studies published between January 2020 and June 2022.

RESULTS

In 71 studies reporting the investigated parameters within 48 hours of admission, higher NLR (HR 1.21, 95% CI 1.16 to 1.27, p < 0.0001), relative neutrophilia (HR 1.62, 95% CI 1.46 to 1.80, p < 0.0001), relative lymphopenia (HR 1.62, 95% CI 1.27 to 2.08, p < 0.001), and relative thrombocytopenia (HR 1.74, 95% CI 1.36 to 2.22, p < 0.001), but not PLR (p = 0.11), were significantly associated with disease progression and mortality. Between-study heterogeneity was large-to-extreme. The magnitude and direction of the effect size were not modified in sensitivity analysis.

CONCLUSIONS

NLR and neutrophil, lymphocyte, and platelet count significantly discriminate COVID-19 patients with different progression and survival outcomes. (PROSPERO registration number: CRD42021267875).

The cross-scale correlations between individuals and nations in COVID-19 mortality

It is challenging to quantitatively clarify the determining medical and social factors of COVID-19 mortality, which varied by 2 to 3 orders of magnitude across countries. Here, we present evidence that the temporal evolution of mortality follows a logistic law for 54 countries in four waves. A universal linear law is found between the early mortality growth time and the epidemic duration, one of the most important quantities, with a factor of 7.3 confirmed by data. Saturation mortality is found to have a power law relationship with median age and bed occupancy, which quantitatively explains the great variation in mortality based on the two key thresholds of median age (= 38) and bed occupancy (= 22%). We predict that deaths will be reduced by 38.5% when the number of beds is doubled for countries with older populations. Facing the next wave of the epidemic, this model can make early predictions on the epidemic duration and hospital bed demand.

Clinical characteristics and outcomes of hospitalized patients with COVID-19 in a Brazilian hospital: a retrospective study of the first and second waves

•

This study describes the characteristics and outcomes of patients with coronavirus disease 2019 (COVID-19) in a Brazilian hospital.

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Characteristics from the first and second waves were compared.

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The number of cases was higher in the second wave, but hospitalizations were lower, compared with the first wave.

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Admission and death rates were slightly lower in the study hospital compared with national rates.

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This study can help managers to plan resources needed for the treatment of patients with COVID-19.

Objectives

To describe clinical characteristics, hospitalization flow and outcomes in a cohort of patients with coronavirus disease 2019 (COVID-19) in a Brazilian hospital in the first and second waves of the pandemic.

Methods

This retrospective, observational study included patients with confirmed COVID-19 who were evaluated in the emergency department (ED) between 1 March 2020 and 30 June 2021. Descriptive statistics have been used to report clinical characteristics, admissions and outcomes. Comparison between the two waves was inferred using hypothesis test techniques.

Results

During the study period, 7723 (86.54%) patients were evaluated in the ED, of which 1908 (24.70%) were admitted. Of these, 476 (24.95%) patients were initially allocated to the intensive care unit (ICU) and 1432 (75.05%) to the general ward. Of the patients initially allocated to the general ward, 349 (24.37%) were later transferred to the ICU. One hundred and fifty-eight patients were intubated (19.15% of ICU admissions) and 110 patients died (5.77% of all admissions). In the second wave, the admission rates decreased in both the ICU (from 13.84% to 9.56%; P<0.01) and the general ward (from 22.41% to 17.16%; P<0.01). The average age in the second wave decreased from 44.06 to 41.87 years (P<0.01). Patients with severe symptoms, such as dyspnoea, decreased from 25.51% to 13.13% (P<0.01) in the second wave. The death rate among admitted patients decreased by 17.84% (from 6.52% to 5.38%; P<0.01).

Conclusion

Despite the greater number of patients in the second wave, the admission and death rates were lower compared with the first wave. The mean age of patients was lower in the second wave, and patients arrived at the hospital with less severe symptoms compared with the first wave.

Comparison of the clinical presentation across two waves of COVID-19: a retrospective cohort study

BACKGROUND

Only a few studies have performed comprehensive comparisons between hospitalized patients from different waves of COVID-19. Thus, we aimed to compare the clinical characteristics and laboratory data of patients admitted to the western part of Denmark during the first and second waves of COVID-19 in 2020. Furthermore, we aimed to identify risk factors for critical COVID-19 disease and to describe the available information on the sources of infection.

METHODS

We performed a retrospective study of medical records from 311 consecutive hospitalized patients, 157 patients from wave 1 and 154 patients from wave 2. The period from March 7 to June 30, 2020, was considered wave 1, and the period from July 1st to December 31, 2020, was considered wave 2. Data are presented as the total study population, as a comparison between waves 1 and 2, and as a comparison between patients with and without critical COVID-19 disease (nonsurvivors and patients admitted to the intensive care unit (ICU)).

RESULTS

Patients admitted during the first COVID-19 wave experienced a more severe course of disease than patients admitted during wave 2. Admissions to the ICU and fatal disease were significantly higher among patients admitted during wave 1 compared to wave 2. The percentage of patients infected at hospital decreased in wave 2 compared to wave 1, whereas more patients were infected at home during wave 2. We found no significant differences in sociodemographics, lifestyle information, or laboratory data in the comparison of patients from waves 1 and 2. However, age, sex, smoking status, comorbidities, fever, and dyspnea were identified as risk factors for critical COVID-19 disease. Furthermore, we observed significantly increased levels of C-reactive protein and creatinine, and lower hemoglobin levels among patients with critical disease.

CONCLUSIONS

At admission, patients were more severely ill during wave 1 than during wave 2, and the outcomes were worse during wave 1. We confirmed previously identified risk factors for critical COVID-19 disease. In addition, we found that most COVID-19 infections were acquired at home.

Body composition, physical capacity, and immuno-metabolic profile in community-acquired pneumonia caused by COVID-19, influenza, and bacteria: a prospective cohort study

BACKGROUND

Different pathogens can cause community-acquired pneumonia (CAP); however, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) has re-emphasized the vital role of respiratory viruses as a cause of CAP. The aim was to explore differences in metabolic profile, body composition, physical capacity, and inflammation between patients hospitalized with CAP caused by different etiology.

METHODS

A prospective study of Danish patients hospitalized with CAP caused by SARS-CoV-2, influenza, or bacteria. Fat (FM) and fat-free mass (FFM) were assessed with bioelectrical impedance analysis. Physical activity and capacity were assessed using questionnaires and handgrip strength. Plasma (p)-glucose, p-lipids, hemoglobin A1c (HbA1c), p-adiponectin, and cytokines were measured.

RESULTS

Among 164 patients with CAP, etiology did not affect admission levels of glucose, HbA1c, adiponectin, or lipids. Overall, 15.2% had known diabetes, 6.1% had undiagnosed diabetes, 51.3% had pre-diabetes, 81% had hyperglycemia, and 60% had low HDL-cholesterol, with no difference between groups. Body mass index, FM, and FFM were similar between groups, with 73% of the patients being characterized with abdominal obesity, although waist circumference was lower in patients with COVID-19. Physical capacity was similar between groups. More than 80% had low handgrip strength and low physical activity levels. Compared to patients with influenza, patients with COVID-19 had increased levels of interferon (IFN)-γ (mean difference (MD) 4.14; 95% CI 1.36-12.58; p = 0.008), interleukin (IL)-4 (MD 1.82; 95% CI 1.12-2.97; p = 0.012), IL-5 (MD 2.22; 95% CI 1.09-4.52; p = 0.024), and IL-6 (MD 2.41; 95% CI 1.02-5.68; p = 0.044) and increased IFN-γ (MD 6.10; 95% CI 2.53-14.71; p < 0.001) and IL-10 (MD 2.68; 95% CI 1.53-4.69; p < 0.001) compared to patients with bacterial CAP, but no difference in IL-1β, tumor necrosis factor-α, IL-8, IL-18, IL-12p70, C-reactive protein, and adiponectin.

CONCLUSION

Despite higher inflammatory response in patients with COVID-19, metabolic profile, body composition, and physical capacity were similar to patients with influenza and bacterial CAP.

The Impact of the SARS-CoV-2 Pandemic on Healthcare Provision in Italy to non-COVID Patients: a Systematic Review

BACKGROUND

Italy has been one of the countries most affected by the SARS-CoV-2 pandemic, and the regional healthcare system has had to quickly adapt its organization to meet the needs of infected patients. This has led to a drastic change in the routine management of non-communicable diseases with a potential long-term impact on patient health care. Therefore, we investigated the management of non-COVID-19 patients across all medical specialities in Italy.

METHODS

A PRISMA guideline-based systematic review of the literature was performed using PubMed, Embase, and Scopus, restricting the search to the main outbreak period in Italy (from February 20 to June 25 2020). We selected articles in English or Italian that detailed changes in the Italian hospital care for non-COVID-19 patients due to the pandemic. Our keywords included all medical specialities combined with our geographical focus (Italy) and COVID-19.

RESULTS

Of the 4643 potentially eligible studies identified by the search, 247 were included. A decrease in the management of emergencies in non-COVID patients was found together with an increase in mortality. Similarly, non-deferrable conditions met a tendency toward decreased diagnosis. All specialities have been affected by the re-organization of healthcare provision in the hub-and-spoke system and have benefited from telemedicine.

CONCLUSIONS

Our work highlights the changes in the Italian public healthcare system to tackle the developing health crisis due to the COVID-19 pandemic. The findings of our review may be useful to analyse future directions for the healthcare system in the case of new pandemic scenarios.

Factors associated with poor outcomes among hospitalized patients with COVID-19: Experience from a MERS-CoV referral hospital

BACKGROUND

Coronavirus disease 2019 (COVID-19) has resulted in millions of deaths, including more than 6000 deaths in the Kingdom of Saudi Arabia (KSA). Identifying key predictors of intensive care unit (ICU) admission and mortality among infected cases would help in identifying individuals at risk to optimize their care. We aimed to determine factors of poor outcomes in hospitalized patients with COVID-19 in a large academic hospital in Riyadh, KSA that serves as a Middle East Respiratory Syndrome coronavirus (MERS-CoV) referral center.

METHODS

This is a single-center retrospective cohort study of hospitalized patients between March 15 and August 31, 2020. The study was conducted at King Saud University Medical City (KSUMC). COVID-19 infection was confirmed using real-time reverse transcriptase polymerase chain reaction (RT-PCR) for SARS-COV-2. Demographic data, clinical characteristics, laboratory, radiological features, and length of hospital stay were obtained. Poor outcomes were, admission to ICU, need for invasive mechanical ventilation (IMV), and in-hospital all-cause mortality.

RESULTS

Out of 16,947 individuals tested in KSUMC, 3480 (20.5%) tested positive for SARS-CoV-2 and of those 743 patients (21%) were hospitalized. There were 62% males, 77% were younger than 65 years. Of all cases, 204 patients (28%) required ICU admission, 104 (14%) required IMV, and 117 (16%) died in hospital. In bivariate analysis, multiple factors were associated with mortality among COVID-19 patients. Further multivariate analysis revealed the following factors were associated with mortality: respiratory rate more than 24/min and systolic blood pressure <90 mmHg in the first 24h of presentation, lymphocyte count <1 × 109/L and aspartate transaminase level >37 units/L in the first 48 h of presentation, while a RT-PCR cycle threshold (Ct) value ≤24 was a predictor for IMV.

CONCLUSION

Variable factors were identified as predictors of different outcomes among COVID-19 patients. The only predictor of IMV was a low initial Ct values of SARS-CoV-2 PCR. The presence of tachypnea, hypotension, lymphopenia, and elevated AST in the first 48h of presentation were independently associated with mortality. This study provides possible independent predictors of mortality and invasive mechanical ventilation. The data may be helpful in the early identification of high-risk COVID-19 patients in areas endemic with MERS-CoV.

Prognosis of patients hospitalized with a diagnosis of COVID-19 pneumonia in a tertiary hospital in Turkey

BACKGROUND

SARS-CoV2/COVID-19 emerged in China and caused a global pandemic in 2020. The mortality rate has been reported to be between 0% and 14.6% in all patients. In this study, we determined the clinical and laboratory parameters of COVID-19 related morbidity and mortality in our hospital.

OBJECTIVES

Investigate the relationship between demographic, clinical, and laboratory parameters on COVID-19-related morbidity and mortality.

DESIGN

Retrospective observational study.

SETTINGS

Tertiary care hospital.

PATIENTS AND METHODS

Patients diagnosed with COVID-19 pneumonia from March until the end of December were included in the study.

MAIN OUTCOME MEASURES

The relationship between demographic, clinical, and laboratory parameters and the morbidity and mortality rates of patients diagnosed with COVID-19.

SAMPLE SIZE

124 patients RESULTS: The mortality rate was 9.6% (12/124). Coronary artery disease (P<.0001) diabetes mellitus (P=.04) fever (>38.3°C) at presentation (P=.04) hypertension (P<.0001), and positive smoking history (P<.0001) were significantly associated with mortality. Patients who died were older, had a higher comorbid disease index, pneumonia severity index, fasting blood glucose, baseline serum creatinine, D-dimer, and had lower baseline haemoglobin, SaO₂, percentage of lymphocyte counts and diastolic blood pressure. Patients admitted to the ICU were older, had a higher comorbidity disease index, pneumonia severity index, C-reactive protein, WBC, D-dimer, creatinine, number of antibiotics used, longer O₂ support duration, lower hemoglobin, lymphocyte (%), and baseline SaO₂ (%).

CONCLUSIONS

Our results were consistent with much of the reported data. We suggest that the frequency, dosage, and duration of steroid treatment should be limited.

LIMITATIONS

Low patient number, uncertain reason of mortality, no standard treatment regimen, limited treatment options, like ECMO.

CONFLICT OF INTEREST

None.

Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort

BACKGROUND

Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes.

METHODS

A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported.

RESULTS

1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict "survival". Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients' age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy.

CONCLUSIONS

Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration "ClinicalTrials" (clinicaltrials.gov) under NCT04455451.

Six-Month Outcomes in COVID-19 ICU Patients and Their Family Members: A Prospective Cohort Study

Background: The COVID-19 pandemic has resulted in a major influx of intensive care unit (ICU) admissions. Currently, there is limited knowledge on the long-term outcomes of COVID-19 ICU-survivors and the impact on family members. This study aimed to gain an insight into the long-term physical, social and psychological functioning of COVID-19 ICU-survivors and their family members at three- and six-months following ICU discharge. Methods: A single-center, prospective cohort study was conducted among COVID-19 ICU-survivors and their family members. Participants received questionnaires at three and six months after ICU discharge. Physical functioning was evaluated using the MOS Short-Form General Health Survey, Clinical Frailty Scale and spirometry tests. Social functioning was determined using the McMaster Family Assessment Device and return to work. Psychological functioning was assessed using the Hospital Anxiety and Depression Scale. Results: Sixty COVID-19 ICU-survivors and 78 family members participated in this study. Physical functioning was impaired in ICU-survivors as reflected by a score of 33.3 (IQR 16.7–66.7) and 50 (IQR 16.7–83.3) out of 100 at 3- and 6-month follow-ups, respectively. Ninety percent of ICU-survivors reported persistent symptoms after 6 months. Social functioning was impaired since 90% of COVID-19 ICU-survivors had not reached their pre-ICU work level 6 months after ICU-discharge. Psychological functioning was unaffected in COVID-19 ICU-survivors. Family members experienced worse work status in 35% and 34% of cases, including a decrease in work rate among 18.3% and 7.4% of cases at 3- and 6-months post ICU-discharge, respectively. Psychologically, 63% of family members reported ongoing impaired well-being due to the COVID-19-related mandatory physical distance from their relatives. Conclusion: COVID-19 ICU-survivors suffer from a prolonged disease burden, which is prominent in physical and social functioning, work status and persisting symptoms among 90% of patients. Family members reported a reduction in return to work and impaired well-being. Further research is needed to extend the follow-up period and study the effects of standardized rehabilitation in COVID-19 patients and their family members.

Descriptive analysis of long COVID sequelae identified in a multidisciplinary clinic serving hospitalised and non-hospitalised patients

BACKGROUND

There are emerging data of long-term effects of coronavirus disease 2019 (COVID-19) comprising a diversity of symptoms. The aim of this study was to systematically describe and measure pulmonary and extra-pulmonary post-COVID-19 complications in relation to acute COVID-19 severity.

METHODS

Patients attending a standard of care 3 months post-hospitalisation follow-up visit and those referred by their general practitioner because of persistent post-COVID-19 symptoms were included. Patients underwent symptomatic, quality of life, pulmonary (lung function and high-resolution computed tomography (HRCT)), cardiac (high-resolution ECG), physical (1-min sit and stand test (1-MSTST), handgrip strength, cardiopulmonary exercise testing (CPET)) and cognitive evaluations.

RESULTS

All 34 hospitalised and 22 out of 23 non-hospitalised patients had ≥1 complaint or abnormal finding at follow-up. Overall, 67% of patients were symptomatic (Medical Research Council (MRC) ≥2 or COPD assessment test (CAT) ≥10), with no difference between hospitalised versus non-hospitalised patients. Pulmonary function (forced expiratory volume in 1 s (FEV1) or diffusing capacity of the lung for carbon monoxide (D LCO)) <80% of predicted) was impaired in 68% of patients. D LCO was significantly lower in those hospitalised compared to non-hospitalised (70.1±18.0 versus 80.2±11.2% predicted, p=0.02). Overall, 53% had an abnormal HRCT (predominantly ground-glass opacities) with higher composite computed tomography (CT) scores in hospitalised versus non-hospitalised patients (2.3 (0.1-4.8) and 0.0 (0.0-0.3), p<0.001). 1-MSTST was below the 25th percentile in almost half of patients, but no signs of cardiac dysfunction were found. Cognitive impairments were present in 59-66% of hospitalised and 31-44% of non-hospitalised patients (p=0.08).

CONCLUSION

Three months after COVID-19 infection, patients were still symptomatic and demonstrated objective respiratory, functional, radiological and cognitive abnormalities, which were more prominent in hospitalised patients. Our study underlines the importance of multidimensional management strategies in these patients.

Rehabilitation needs and mortality associated with the Covid-19 pandemic: a population-based study of all hospitalised and home-healthcare individuals in a Swedish healthcare region

BACKGROUND

This first report of the Linköping Covid-19 Study (LinCoS) aimed at determination of Covid-19-associated mortality, impairments, activity and participation limitations denoting rehabilitation needs four months after discharge from hospital.

METHODS

An ambidirectional population-based cohort study including all confirmed Covid-19 cases admitted to hospital during 1/03-31/05 and those living in home healthcare settings identified through a regional registry and evaluated through medical records, including WHO Clinical Progression Scale (CPS). All patients discharged from hospital were followed-up by structured telephone interview at 4 months post-discharge. Respondents indicated any new or aggravated persisting problems in any of 25 body functions and 12 activity/participation items and rated them for impact on daily life.

FINDINGS

Out of 734 hospitalised patients, 149 were excluded, 125 died, and 460 were alive at 4-month follow-up of whom 433 (94.1%) were interviewed. In total, 40% reported impairments and activity/participation limitations affecting daily life and warranted further multi-professional rehabilitation assessment, predominantly those with severe disease and a considerable proportion of those with moderate disease. Cognitive and affective impairments were equally common in all groups and were reported by 20-40% of cases. Limb weakness was reported by 31%, with CPS 7-9 being four times more likely to report this problem as compared to CPS 4-5. 26% of those working or studying reported difficulties returning to these activities, this being 3.5 times more likely in CPS 7-9 as compared to CPS 4-5. 25% reported problems walking >1 km, with CPS 7-9 over three times more likely to report this as compared to the other two sub-groups. 90-day mortality rate of Covid-19 associated deaths was 15.1%.

INTERPRETATION

Most rehabilitation needs after Covid-19 involved higher cerebral dysfunction both in patients with moderate and severe disease. This should be considered when designing services aiming at minimizing long-term disability.

FUNDING

ALF grant and Region Östergötland.