Outcomes Of COVID-19 Patients Research Articles

The impact of smoking on COVID-19-related mortality: a Brazilian national cohort study

IntroductionCurrent evidence suggests the potential heightened vulnerability of smokers to severe coronavirus disease (COVID-19) outcomes. AimsThis study aimed to analyze the clinical outcomes and mortality related to tobacco use in a cohort of hospitalized Brazilian COVID-19 patients. MethodsThis retrospective cohort study analyzed adults hospitalized for COVID-19 in Brazil using the SIVEP-Gripe database (official data reported by public and private healthcare facilities for monitoring severe acute respiratory syndrome cases in Brazil). The inclusion criteria were patients over 18 years of age with a positive RT-qPCR test for SARS-CoV-2. The analysis focused on in-hospital mortality, considering smoking as an exposure variable, and included covariates such as age, gender, and comorbidities. Smoking history was collected from the self-reported field in the database. Statistical analyses included descriptive statistics, crude Odds Ratios, and multivariable binary logistic regression. ResultsThis study included 2,124,285 COVID-19 patients, among whom 44,774 (2.1 %) were smokers. The average age of the smokers was higher than that of the never-smokers (65.3 years vs. 59.7 years). The clinical outcomes revealed that smokers had higher rates of intensive care unit admission (51.6 % vs. 37.2 % for never-smokers), invasive ventilatory support (31.5 % vs. 20.2 % for never-smokers), and higher mortality (42.7 % vs. 31.8 % for never smokers). In the multivariable analysis, smokers demonstrated a heightened risk of death (aOR 1.23; 95 % CI 1.19–1.25). ConclusionsThis large populational-based cohort study confirms the current evidence and underscore the critical importance of recognizing smoking as a substantial risk factor for adverse outcomes in COVID-19 patients.

Prognostic significance of chronic kidney disease and impaired renal function in Japanese patients with COVID-19

BackgroundRenal impairment is a predictor of coronavirus disease (COVID-19) severity. No studies have compared COVID-19 outcomes in patients with chronic kidney disease (CKD) and patients with impaired renal function without a prior diagnosis of CKD. This study aimed to identify the impact of pre-existing impaired renal function without CKD on COVID-19 outcomes.MethodsThis retrospective study included 3,637 patients with COVID-19 classified into three groups by CKD history and estimated glomerular filtration rate (eGFR) on referral: Group 1 (n = 2,460), normal renal function without a CKD history; Group 2 (n = 905), impaired renal function without a CKD history; and Group 3 (n = 272), history of CKD. We compared the clinical characteristics of these groups and assessed the effect of CKD and impaired renal function on critical outcomes (requirement for respiratory support with high-flow oxygen devices, invasive mechanical ventilation, or extracorporeal membrane oxygen, and death during hospitalization) using multivariable logistic regression.ResultsThe prevalence of comorbidities (hypertension, diabetes, and cardiovascular disease) and incidence of inflammatory responses (white blood counts, and C-reactive protein, procalcitonin, and D-dimer levels) and complications (bacterial infection and heart failure) were higher in Groups 2 and 3 than that in Group 1. The incidence of critical outcomes was 10.8%, 17.7%, and 26.8% in Groups 1, 2, and 3, respectively. The mortality rate and the rate of requiring IMV support was lowest in Group 1 and highest in Group 3. Compared with Group 1, the risk of critical outcomes was higher in Group 2 (adjusted odds ratio [aOR]: 1.32, 95% confidence interval [CI]: 1.03–1.70, P = 0.030) and Group 3 (aOR: 1.94, 95% CI: 1.36–2.78, P < 0.001). Additionally, the eGFR was significantly associated with critical outcomes in Groups 2 (odds ratio [OR]: 2.89, 95% CI: 1.64–4.98, P < 0.001) and 3 (OR: 1.87, 95% CI: 1.08–3.23, P = 0.025) only.ConclusionsClinicians should consider pre-existing CKD and impaired renal function at the time of COVID-19 diagnosis for the management of COVID-19.

#1466 Age- and kidney function-dependent life expectancy of patients after COVID-19

Abstract Background and Aims The life expectancy among survivors of SARS-CoV-2 infection may be influenced by age, pre-existing health conditions, and the severity of the initial infection. This study aimed to investigate the life expectancy in patients that survived the acute phase of COVID-19 and the association with kidney function. Method Survival data of 649 unvaccinated patients from our previous study “Prospective Validation of a Proteomic Urine Test for Early and Accurate Prognosis of Critical Course Complications in Patients with SARS-CoV-2 Infection” (CRIT-COV-U) [1] was collected until December 2023 in six different countries. These patients had been recruited within the first and second wave in 2020-2021 (mostly infected with wild-type virus) and had survived the acute phase of COVID-19 (CritCov-U study period 21 days after infection). The age dependent death rate in this cohort was compared to age- and sex-matched data of non-SARS-CoV-2 infected patients (n = 5192) extracted from human urinary database. The association of chronic kidney disease biomarker CKD273 with mortality was investigated in both cohorts using Kaplan-Meier analysis. Cox-regression analysis was used to assess variables associated with mortality in the COVID-19 population. Results Mortality was age dependent in both cohorts and markedly higher in patients who had survived the acute phase of COVID-19 in comparison to non-infected individuals (Fig. A-E). Within the first year after infection, mortality was up to 16.5 times higher in patients younger than 50 years in comparison to non-infected controls. Kidney status estimated by the CKD273 score was associated with a poor outcome in both COVID-19 patients and age- and sex-matched controls, respectively (Fig. F-G). The hazard ratio (HR) for mortality during the first year of follow-up for patients with the highest CKD273 score was 12.7, a huge increase in comparison to HR = 6.6 in the matched control group. In the Cox-regression model, CKD273 significantly contributed to death prediction, next to age and COVID-19 severity score at baseline. Conclusion SARS-CoV-2 infection during the first and second wave increased the risk of mortality in the follow-up period beyond the acute phase of the first 21 days. Kidney function appears to be a key element in the underlying molecular pathology of this process, indicating the importance of kidney-protective measures. Of note, among those who survived the acute phase of COVID-19, increase in mortality within the first year after infection compared to a non-infected control group was highest in the younger individuals.

ROX Index Variation as a Predictor of Outcomes in COVID-19 Patients

Background: During the COVID-19 pandemic, emergency departments were overcrowded with critically ill patients, and many providers were confronted with ethical dilemmas in assigning respiratory support to them due to scarce resources. Quick tools for evaluating patients upon admission were necessary, as many existing scores proved inaccurate in predicting outcomes. The ROX Index (RI), a rapid and straightforward scoring system reflecting respiratory status in acute respiratory failure patients, has shown promise in predicting outcomes for COVID-19 patients. The 24 h difference in the RI accurately gauges mortality and the need for invasive mechanical ventilation (IMV) among patients with COVID-19. Methods: Study design: Prospective cohort study. A total of 204 patients were admitted to the emergency department from May to August 2020. Data were collected from the clinical records. The RI was calculated at admission and 24 h later, and the difference was used to predict the association with mortality and the need for IMV, a logistic regression model was used to adjust for age, sex, presence of comorbidities, and disease severity. Finally, the data were analyzed using ROC. Results: The difference in respiratory RI between admission and 24 h is a good predictor for death (AUC 0.92) and for mechanic ventilation (AUC: 0.75). Each one-unit decrease in the RI difference at 24 h was associated with an odds ratio of 1.48 for the risk of death (95%CI: 1.31–1.67) and an odds ratio of 1.16 for IMV (95% IC: 1.1–1.23). Conclusions: The 24 h variation of RI is a good prediction tool to allow healthcare professionals to identify the patients who will benefit from invasive treatment, especially in low-resource settings.

Surveying haemoperfusion impact on COVID-19 from machine learning using Shapley values.

Haemoperfusion (HP) is an innovative extracorporeal therapy that utilizes special cartridges to filter the blood, effectively removing pro-inflammatory cytokines, toxins, and pathogens in COVID-19 patients. This retrospective cohort study aimed to assess the clinical benefits of HP for severe COVID-19 cases using Shapley values for machine learning models. The research involved 578 inpatients (≥ 20years old) admitted to Baqiyatallah hospital (Tehran, Iran). The control group (359 patients) received standard treatment, including high doses of corticosteroids (a single 500mg methylprednisolone pulse, followed by 250mg for 2days), categorized as regimen (I). On the other hand, the HP group (219 patients) received regimen II, consisting of the same corticosteroid treatment (regimen I) along with haemoperfusion using Cytosorb H300. The frequency of haemoperfusion sessions varied based on the type of lung involvement determined by chest CT scans. In addition, the value function defines the Shapley value of the th feature for the query point , where the input matrix features represent individual characteristics, drugs, and history and clinical conditions of the patient. Our data showed a favorable clinical response in the HP group compared to the control group. Notably, one-to-three sessions of HP using the CytoSorb® 300 cartridge led to reduced ventilation requirements and mortality rates in severe COVID-19 patients. Shapley values were calculated to evaluate the contribution of haemoperfusion among other factors, such as side effects, medications, and individual characteristics, to COVID-19 patient outcomes. In addition, there is a significant difference between the two groups among the treatments and medications used remdesivir, adalimumab, tocilizumab, favipiravir, Interferon beta-1a, enoxaparin prophylaxis, enoxaparin full dose, heparin prophylaxis, and heparin full dose (P < 0.05). It seems that haemoperfusion has a positive impact on the reduction of inflammation markers and renal functional such as ferritin and creatinine, respectively, as well as D-dimer and WBC levels in the HP group were significantly lower than the control group. The findings indicated that haemoperfusion played a crucial role in predicting patient survival, making it a significant feature in classifying patients' prognoses.

Utility of Serum Procalcitonin and Its Clearance in Predicting Outcomes in COVID-19 Patients

Utility of Serum Procalcitonin and Its Clearance in Predicting Outcomes in COVID-19 Patients

Efficacy of Remdesivir on Clinical Outcomes in COVID-19 Patients: A Study in a Tertiary Care Hospital in Pakistan

Efficacy of Remdesivir on Clinical Outcomes in COVID-19 Patients: A Study in a Tertiary Care Hospital in Pakistan

Impact of COVID-19 Infection on Pancreato-Biliary Diseases Requiring Endoscopic Retrograde Cholangiopancreatography.

Viral infections are known to impact the pancreato-biliary system; however, there are limited data showing that the same is true of COVID-19. Endoscopic retrograde cholangiopancreatography (ERCP) can safely be performed in patients with COVID-19 infection, but outcomes of patients with COVID-19 infections and concomitant pancreatic and biliary disease requiring endoscopic intervention are unknown. This study aims to evaluate the severity of pancreaticobiliary diseases and post-ERCP outcomes in COVID-19 patients. Patients with pancreato-biliary disease that required inpatient ERCP from five centers in the United States and South America between January 1, 2020, and October 31, 2020 were included. A representative cohort of patients from each month were randomly selected from each site. Disease severity and post-ERCP outcomes were compared between COVID-19 positive and COVID-19 negative patients. A total of 175 patients were included: 95 COVID positive and 80 COVID negative. Mean CTSI score for the patients who had pancreatitis was higher in COVID-positive cohort by 3.2 points (p < .00001). The COVID-positive group had more cases with severe disease (n = 41) versus the COVID-negative group (n = 2) (p < .00001). Mortality was higher in the COVID-19 positive group (19%) compared to COVID-negative group (7.5%) even though the COVID-19-negative group had higher incidence of malignancy (n = 17, 21% vs n = 7, 7.3%) (p = 0.0455). This study shows that patients with COVID infection have more severe pancreato-biliary disease and worse post-ERCP outcomes, including longer length of stay and higher mortality rate. These are important considerations when planning for endoscopic intervention. gov: (NCT05051358).

Multimodal data fusion using sparse canonical correlation analysis and cooperative learning: a COVID-19 cohort study

Through technological innovations, patient cohorts can be examined from multiple views with high-dimensional, multiscale biomedical data to classify clinical phenotypes and predict outcomes. Here, we aim to present our approach for analyzing multimodal data using unsupervised and supervised sparse linear methods in a COVID-19 patient cohort. This prospective cohort study of 149 adult patients was conducted in a tertiary care academic center. First, we used sparse canonical correlation analysis (CCA) to identify and quantify relationships across different data modalities, including viral genome sequencing, imaging, clinical data, and laboratory results. Then, we used cooperative learning to predict the clinical outcome of COVID-19 patients: Intensive care unit admission. We show that serum biomarkers representing severe disease and acute phase response correlate with original and wavelet radiomics features in the LLL frequency channel (cor(Xu1, Zv1) = 0.596, p value < 0.001). Among radiomics features, histogram-based first-order features reporting the skewness, kurtosis, and uniformity have the lowest negative, whereas entropy-related features have the highest positive coefficients. Moreover, unsupervised analysis of clinical data and laboratory results gives insights into distinct clinical phenotypes. Leveraging the availability of global viral genome databases, we demonstrate that the Word2Vec natural language processing model can be used for viral genome encoding. It not only separates major SARS-CoV-2 variants but also allows the preservation of phylogenetic relationships among them. Our quadruple model using Word2Vec encoding achieves better prediction results in the supervised task. The model yields area under the curve (AUC) and accuracy values of 0.87 and 0.77, respectively. Our study illustrates that sparse CCA analysis and cooperative learning are powerful techniques for handling high-dimensional, multimodal data to investigate multivariate associations in unsupervised and supervised tasks.

The impact of innovative glucose-lowering drugs on the course and outcome of COVID-19 in patients with type 2 diabetes mellitus

Patients with type 2 diabetes mellitus (T2DM) are at high risk of adverse outcomes in coronavirus infection (COVID-19). Despite the gradual resolution of the pandemic, new strains of the virus are emerging, characterized by high contagiousness, and the risk of infection becoming a seasonal disease is increasing. In this connection, the issue of identifying risk factors that aggravate the course of COVID-19 in patients with T2DM, including the role of initial hypoglycemic therapy, remains relevant.The review presents and systematizes up-to-date information (according to randomized clinical trials and meta-analyses) on the effect of outpatient and inpatient use of metformin and innovative hypoglycemic drugs (glucagon-like peptide-1 receptor agonists, sodium-glucose cotransporter-2 inhibitors, dipeptidyl peptidase-4 inhibitors) on the course and outcome of COVID-19 in patients with T2DM. At the same time, the potential mechanisms of the pathogenetic effect of drugs on the course of COVID-19, positive and negative aspects of their administration are described.

Remdesivir and Kidney and Cardiovascular Outcomes in COVID-19 Patients With Reduced GFR

Remdesivir and Kidney and Cardiovascular Outcomes in COVID-19 Patients With Reduced GFR

Attitude, knowledge, and barriers of Chinese clinical and nursing students in implementing complementary and alternative medicine for COVID-19：a cross-sectional study

BackgroundComplementary and alternative medicine (CAM) has emerged to combat the global COVID-19 pandemic. However, no studies have been conducted to evaluate the attitudes, knowledge, and barriers of Chinese clinical and nursing students in implementing CAM during this period. ObjectiveThe aim of this study was to investigate the attitude, knowledge, and barriers of Chinese clinical and nursing students in using CAM in the context of COVID-19. MethodsAn online-based cross-sectional survey was carried out among Chinese medical students, majoring in clinical medicine or nursing, in Nanjing, Jiangsu Province, and Zhengzhou, Henan Province from May to July 2022. A total of 402 clinical and 644 nursing students responded to a self-administered questionnaire through the Questionnaire Star and WeChat APPs. SPSS 25 (version 25) was used for data analysis. Proportions were compared by Chi-square test. Level of significance between groups was analyzed using independent student t-test and Mann-Whitney U test. ResultsThe average score of attitude was 46.63 (SD: 7.38) in clinical students and 49.84 (SD: 6.76) in nursing students. The top four most commonly used CAM treatments in China were proprietary Chinese medicine, diet therapy, decoction, and acupuncture and moxibustion (59.66 %, 22.28 %, 11.66 %, 9.85 %). The students had a good mastery of knowledge about CAM-based prevention and control of COVID-19 (mean score 7.36). The score of CAM knowledge in nursing students was significantly higher than that in clinical students (7.56 VS 7.04, P = 0.000). Gender, grade, previous use, age, and knowledge score could affect students’ attitude towards CAM. The main barriers in spreading CAM use included time-consumption, bad taste, and fear of treatment-related pain (24.5 %). Compared with clinical students, nursing students were more likely to recommend CAM to patients in the future (P = 0.002). ConclusionsDuring the COVID-19 pandemic, nursing students were more positive towards CAM use, had a better mastery of CAM knowledge than clinical students. CAM is expected to provide better outcomes in COVID-19 patients. Future studies should focus on the changes in students’ attitudes over time and exploration of influencing factors on CAM use.

Characteristics and outcomes of COVID-19 patients admitted to hospital with and without respiratory symptoms

BackgroundCOVID-19 is primarily known as a respiratory illness; however, many patients present to hospital without respiratory symptoms. The association between non-respiratory presentations of COVID-19 and outcomes remains unclear. We investigated risk factors and clinical outcomes in patients with no respiratory symptoms (NRS) and respiratory symptoms (RS) at hospital admission. MethodsThis study describes clinical features, physiological parameters, and outcomes of hospitalised COVID-19 patients, stratified by the presence or absence of respiratory symptoms at hospital admission. RS patients had one or more of: cough, shortness of breath, sore throat, runny nose or wheezing; while NRS patients did not. ResultsOf 178,640 patients in the study, 86.4 % presented with RS, while 13.6 % had NRS. NRS patients were older (median age: NRS: 74 vs RS: 65) and less likely to be admitted to the ICU (NRS: 36.7 % vs RS: 37.5 %). NRS patients had a higher crude in-hospital case-fatality ratio (NRS 41.1 % vs. RS 32.0 %), but a lower risk of death after adjusting for confounders (HR 0.88 [0.83–0.93]). ConclusionApproximately one in seven COVID-19 patients presented at hospital admission without respiratory symptoms. These patients were older, had lower ICU admission rates, and had a lower risk of in-hospital mortality after adjusting for confounders.

Repurposing surgical wards in pandemics – An appraisal of outcomes of COVID-19 patients treated in Orthopaedic wards

ABSTRACT Background: The COVID-19 pandemic resulted in a shift in the way healthcare resources were used. While India faced limited effects in the first COVID wave primarily due to strict lockdown of the county, it was one of the worst affected in the second wave and at one time reported the highest number of daily cases. To address the lack of intensive care units (ICU) beds, the surgical wards of our institute were repurposed to take care of patients requiring supplementary oxygen and other supportive care till either they improved or an ICU bed was available. The medical personnel in charge of the surgical wards were entrusted with the care of patients with support from intensive care support teams (ICST). Aims: We aimed to examine the clinical details of patients admitted in the repurposed orthopaedic wards during the second COVID wave and to evaluate the factors that might affect the clinical outcomes in such patients. Methods: This was a retrospective review of records of patients admitted in the repurposed orthopaedic wards between 16 April 2021 and 20 May 2021. Details related to demography, COVID-19 presentation, COVID-19-related management and clinical course, including transfers to ICUs, and outcomes in terms of either discharge to home or death were recorded. They were analysed using statistical software. Results: One hundred and twenty three patients were treated during the said period. Twenty patients died during treatment, resulting in a mortality rate of 16.3%. Age, gender, RT-PCR status, pre-existing comorbidities, SpO2 at admission, method of supplemental oxygen supply, total leukocyte counts, haemoglobin values, serum C-reactive protein, Lactate dehydrogenase (LDH) and creatinine values had no statistically significant association with death of a patient during treatment. Conclusion: Based on the results, one can state that clinicians of surgical specialities having background knowledge of internal medicine from undergraduate education can manage patients of COVID-19 with support from ICST with reasonable outcomes. In case of future pandemics, surgical wards can be repurposed to tide over exigencies. Additionally, primary care physicians, who are often the first point of contact for patients, can allay their apprehensions adequately in future pandemics, thus preventing widespread panic and burdening of healthcare resources.

In Hospital Outcome of COVID-19 Patients with Acute Myocardial Infarction

Objective: To determine the hospital outcome of acute myocardial infarction patients with COVID-19 and compare it with patients without COVID-19. Study Design: Comparative cross-sectional study. Place and Duration of Study: Armed Forces Institute of Cardiology and National Institute of Heart Diseases, RawalpindiPakistan, from Mar to Oct 2021. Methodology: The study included PCR-positive patients with COVID-19 infection who had acute myocardial infarction diagnosed by a consultant cardiologist. The hospital recorded clinical outcomes within two days of acute myocardial infarction. Data regarding outcome was compared with patients who had acute myocardial infarction but did not have COVID-19. Results: Fifty cases of COVID-19 and myocardial infarction were included in the study. An equal number of patients with no evidence of COVID-19 but having myocardial infarction were also included. The mean age of the study participants was 49.96±897 years. Out of 100 patients, 79(79%) were male, while 21(21%) were female. Statistical analysis showed that all the outcome parameters studied had no significant difference in both the acute myocardial infarction patients with and without COVID-19 (p-value&gt;0.05). Conclusion: Our study results revealed no statistically significant difference in the hospital outcome of patients with acute myocardial infarction who were suffering from COVID-19 and those who were not.

Presepsin as a prognostic biomarker in COVID-19 patients: combining clinical scoring systems and laboratory inflammatory markers for outcome prediction

BackgroundThere is still limited research on the prognostic value of Presepsin as a biomarker for predicting the outcome of COVID-19 patients. Additionally, research on the combined predictive value of Presepsin with clinical scoring systems and inflammation markers for disease prognosis is lacking.MethodsA total of 226 COVID-19 patients admitted to Beijing Youan Hospital’s emergency department from May to November 2022 were screened. Demographic information, laboratory measurements, and blood samples for Presepsin levels were collected upon admission. The predictive value of Presepsin, clinical scoring systems, and inflammation markers for 28-day mortality was analyzed.ResultsA total of 190 patients were analyzed, 83 (43.7%) were mild, 61 (32.1%) were moderate, and 46 (24.2%) were severe/critically ill. 23 (12.1%) patients died within 28 days. The Presepsin levels in severe/critical patients were significantly higher compared to moderate and mild patients (p < 0.001). Presepsin showed significant predictive value for 28-day mortality in COVID-19 patients, with an area under the ROC curve of 0.828 (95% CI: 0.737–0.920). Clinical scoring systems and inflammation markers also played a significant role in predicting 28-day outcomes. After Cox regression adjustment, Presepsin, qSOFA, NEWS2, PSI, CURB-65, CRP, NLR, CAR, and LCR were identified as independent predictors of 28-day mortality in COVID-19 patients (all p-values < 0.05). Combining Presepsin with clinical scoring systems and inflammation markers further enhanced the predictive value for patient prognosis.ConclusionPresepsin is a favorable indicator for the prognosis of COVID-19 patients, and its combination with clinical scoring systems and inflammation markers improved prognostic assessment.

Machine learning to understand risks for severe COVID-19 outcomes: a retrospective cohort study of immune-mediated inflammatory diseases, immunomodulatory medications, and comorbidities in a large US health-care system

In the context of immune-mediated inflammatory diseases (IMIDs), COVID-19 outcomes are incompletely understood and vary considerably depending on the patient population studied. We aimed to analyse severe COVID-19 outcomes and to investigate the effects of the pandemic time period and the risks associated with individual IMIDs, classes of immunomodulatory medications (IMMs), chronic comorbidities, and COVID-19 vaccination status. In this retrospective cohort study, clinical data were derived from the electronic health records of an integrated health-care system serving patients in 51 hospitals and 1085 clinics across seven US states (Providence St Joseph Health). Data were observed for patients (no age restriction) with one or more IMID and for unmatched controls without IMIDs. COVID-19 was identified with a positive nucleic acid amplification test result for SARS-CoV-2. Two timeframes were analysed: March 1, 2020-Dec 25, 2021 (pre-omicron period), and Dec 26, 2021-Aug 30, 2022 (omicron-predominant period). Primary outcomes were hospitalisation, mechanical ventilation, and mortality in patients with COVID-19. Factors, including IMID diagnoses, comorbidities, long-term use of IMMs, and COVID-19 vaccination status, were analysed with multivariable logistic regression (LR) and extreme gradient boosting (XGB). Of 2 167 656 patients tested for SARS-CoV-2, 290 855 (13·4%) had confirmed COVID-19: 15 397 (5·3%) patients with IMIDs and 275 458 (94·7%) without IMIDs. In the pre-omicron period, 169 993 (11·2%) of 1 517 295 people who were tested for COVID-19 tested positive, of whom 23 330 (13·7%) were hospitalised, 1072 (0·6%) received mechanical ventilation, and 5294 (3·1%) died. Compared with controls, patients with IMIDs and COVID-19 had higher rates of hospitalisation (1176 [14·6%] vs 22 154 [13·7%]; p=0·024) and mortality (314 [3·9%] vs 4980 [3·1%]; p<0·0001). In the omicron-predominant period, 120 862 (18·6%) of 650 361 patients tested positive for COVID-19, of whom 14 504 (12·0%) were hospitalised, 567 (0·5%) received mechanical ventilation, and 2001 (1·7%) died. Compared with controls, patients with IMIDs and COVID-19 (7327 [17·3%] of 42 249) had higher rates of hospitalisation (13 422 [11·8%] vs 1082 [14·8%]; p<0·0001) and mortality (1814 [1·6%] vs 187 [2·6%]; p<0·0001). Age was a risk factor for worse outcomes (adjusted odds ratio [OR] from 2·1 [95% CI 2·0-2·1]; p<0·0001 to 3·0 [2·9-3·0]; p<0·0001), whereas COVID-19 vaccination (from 0·082 [0·080-0·085]; p<0·0001 to 0·52 [0·50-0·53]; p<0·0001) and booster vaccination (from 2·1 [2·0-2·2]; p<0·0001 to 3·0 [2·9-3·0]; p<0·0001) status were associated with better outcomes. Seven chronic comorbidities were significant risk factors during both time periods for all three outcomes: atrial fibrillation, coronary artery disease, heart failure, chronic kidney disease, chronic obstructive pulmonary disease, chronic liver disease, and cancer. Two IMIDs, asthma (adjusted OR from 0·33 [0·32-0·34]; p<0·0001 to 0·49 [0·48-0·51]; p<0·0001) and psoriasis (from 0·52 [0·48-0·56] to 0·80 [0·74-0·87]; p<0·0001), were associated with a reduced risk of severe outcomes. IMID diagnoses did not appear to be significant risk factors themselves, but results were limited by small sample size, and vasculitis had high feature importance in LR. IMMs did not appear to be significant, but less frequently used IMMs were limited by sample size. XGB outperformed LR, with the area under the receiver operating characteristic curve for models across different time periods and outcomes ranging from 0·77 to 0·92. Our results suggest that age, chronic comorbidities, and not being fully vaccinated might be greater risk factors for severe COVID-19 outcomes in patients with IMIDs than the use of IMMs or the IMIDs themselves. Overall, there is a need to take age and comorbidities into consideration when developing COVID-19 guidelines for patients with IMIDs. Further research is needed for specific IMIDs (including IMID severity at the time of SARS-CoV-2 infection) and IMMs (considering dosage and timing before a patient's first COVID-19 infection). Pfizer, Novartis, Janssen, and the National Institutes of Health.

Using machine learning algorithms based on patient admission laboratory parameters to predict adverse outcomes in COVID-19 patients

Amidst the global COVID-19 pandemic, the urgent need for timely and precise patient prognosis assessment underscores the significance of leveraging machine learning techniques. In this study, we present a novel predictive model centered on routine clinical laboratory test data to swiftly forecast patient survival outcomes upon admission. Our model integrates feature selection algorithms and binary classification algorithms, optimizing algorithmic selection through meticulous parameter control. Notably, we developed an algorithm coupling Lasso and SVM methodologies, achieving a remarkable area under the ROC curve of 0.9277 with the use of merely 8 clinical laboratory parameters collected upon admission. Our primary contribution lies in the utilization of straightforward laboratory parameters for prognostication, circumventing data processing intricacies, and furnishing clinicians with an expeditious and precise prognostic assessment tool.

Superinfections in COVID-19

Introduction Bacterial superinfection rates in SARS-CoV-2 (COVID-19) range from 8% to 49.6%, but the diagnosis remains a challenge. We conducted a study to determine the utility of the Pneumonia Severity Index (PSI) to predict the risk of superinfections and outcomes in COVID-19 patients. Methods A cross-sectional retrospective study was conducted on COVID-19 positive patients admitted during 2020–2022. The PSI scores were calculated at admission and at every 72-hour intervals. Data regarding clinical course, antibiotic use and overall outcome were collected. Results A total of 149 patients were included, with a mean age of 67 years. The PSI score at admission and the mean PSI score were higher for those who required antibiotics, intensive care unit (ICU) admission, or succumbed. Patients with a PSI score &gt;107 at admission had a high risk of ICU admission, &gt;113 had a high risk of antibiotic requirements, and &gt;110 had a higher risk of death. An increase in PSI score ≥25 between the day of admission and day 3 of hospitalization; or between day 3 and day 6 of hospitalization, predicted a higher chance of mortality; but had no association with the development of superinfections. Discussion The PSI score at admission can be used to predict the severity of disease requiring ICU admission, antibiotic requirement, and overall mortality, with serial monitoring of the score predicting possible clinical deterioration and increased mortality. However, it was not helpful in predicting the chances of developing superinfections and the need for antibiotic therapy. Conclusions The PSI score can be used to prognosticate the outcome in patients admitted with COVID-19, but further studies are needed to determine its utility in predicting the risk of superinfections.

The Outcomes of COVID-19 Patients with ARDS Who Received High Flow Nasal Oxygen in Medical Wards Outside Intensive Care Units Under Supervision of Non-intensivists.

Objective: Efficacy of high flow nasal oxygen (HFNO) use in COVID-19 patients who developed ARDS in medical wards is poorly studied. We aimed to investigate whether use of HFNO in wards outside intensive care unit under supervision of non-intensivists has clinical effects on acute respiratory failure and whether it reduces ICU workload. Methods: COVID 19 patients who received HFNO therapy for ARDS in medical wards of an academic hospital were analyzed retrospectively. Primary outcome was the proportion of patients who were successfully weaned from HFNO. Results: 43 patients ( 32 male, median age 61 [54-70] years) were investigated. 14 (33 %) patients weaned from HFNO and 29 (67%) patients failed HFNO and were tranferred to ICU. HFNO was applied in the group of HFNO with success with a median duration of 7 days (4-9) and in the failed group with median 3 days (2-5), p=0.002. Median SpO2 after HFNO was higher in patients with HFNO success compared to with HFNO failure [95 (94-97) vs 93 (92-95), p=0.015]. In the group of HFNO with success, there were more hypocapnic patients than in the group of HFNO with failure [19/29 (66 %) vs 3/14 (21%); p=0.015]. Logistic regression analysis indicated that patients with hypocapnia had 9.8 times the odds of having HFNO failure compared with patients with normocapnia.No patient died among the patients succeded HFNO however 90% of patients who transferred to ICU died. Conclusion: Use of HFNO for COVID-19 patients with ARDS at a non-critical setting seemed to be beneficial in avoiding intubation and reducing workload of ICU. However due to high mortality rate among the HFNO failed group, it would be better to be used undersupervision of intensivists and by skilled team.