[Risk factors for adverse outcomes in elderly patients with asthma and severe COVID-19 at the hospital and early post-hospital stages].

BACKGROUND: Mortality and COVID-19 related factors are thoroughly analyzed. Given the large number of hospitalized patients, the potential short- and long-term COVID-19 related complications, further research is needed on the possible consequences of hospitalization, especially in higher-risk patients, after prolonged hospitalization and intensive care admission. AIM: To study the clinical course and outcomes of severe COVID-19 in elderly patients with asthma at the hospital and early post-hospital stages. MATERIALS AND METHODS: The study included 131 elderly patients (WHO, 2020) >60 years old, n=131 with asthma, hospitalized for severe COVID-19. Of these, 86 (65.6%) patients survived, 30 (22.9%) died in the hospital, and 15 (14.9%) patients died after discharge from the hospital (in the 90-day post-hospital period). COVID-19 was confirmed by laboratory tests (SARS-CoV-2 PCR RNA test) and/or clinically and radiologically. All patients had a documented history of asthma. Patients were followed up during the hospital stay and for 90 days after discharge. RESULTS: Comparison of outcomes showed that in the groups of patients with a fatal outcome (regardless of the stage), the Charlson comorbidity index, respiratory rate, extent of lung damage assessed by computed tomography, the absolute leukocyte and neutrophil number and the ratio of neutrophils to lymphocytes were statistically significantly higher. The absolute number of eosinophils was lower in these groups. In the group of patients who died during hospitalization, severe (IV-V) asthma (p=0.03), steroid use during the previous year (p=0.02), chronic heart failure with a reduced ejection fraction (p=0.009) were more common, and atopic asthma phenotype was less common (p=0.02). In those who died after discharge, more common were non-invasive ventilation and diabetes mellitus (p<0.001). The multivariate regression analysis model revealed the most significant predictors of mortality at the hospital and early post-hospital stages. CONCLUSION: Adverse outcomes of severe COVID-19 in elderly patients with asthma include hospital and post-hospital mortality. The most significant predictors of mortality are the comorbidity index and low eosinophil count. Hospital mortality is associated with a higher ratio of neutrophils to lymphocytes and lower total protein levels; early (90-day) post-hospital mortality is associated with extensive lung damage shown by computed tomography and diabetes mellitus.

Is it safe and effective to administer COVID-19 vaccines during pregnancy? A systematic review and meta-analysis.

OBJECTIVE: To evaluate the safety and efficacy of COVID-19 vaccines in pregnant women performing an updated meta-analysis. METHODS: We searched PubMed, Cochrane Central, and SCOPUS from inception to March 2022. Outcomes of interest were incidence of adverse maternal, fetal and neonatal consequences pertaining to safety of the vaccines. Secondarily, we analyzed the number of SARS-CoV-2 infections, hospitalization for COVID-19, and admission to the I.C.U. for COVID-19 assessing the effectiveness of vaccines. Results were pooled using a random effects model. RESULTS: Ten observational studies (n=326,499) analyzing pregnant women were included. Our results suggest that COVID-19 vaccination prevents infection (OR: 0.56, 95% CI: 0.47, 0.67; P = <0.00001) and related hospitalizations (OR: 0.50, 95% CI: 0.31, 0.82; P = 0.006) effectively. It was also observed that vaccination does not change adverse outcomes in pregnancy, namely preeclampsia or eclampsia, stroke (four weeks of delivery), meconium-stained amniotic fluid, spontaneous vaginal delivery, operative vaginal delivery, cesarean delivery, postpartum hemorrhage, and blood transfusions. Furthermore, the vaccine was observed to be protective against neonatal COVID-19 I.C.U. admissions (OR: 0.85; 95% CI: 0.81, 0.90; P = <0.00001). CONCLUSION: Our pooled analysis suggests that the COVID-19 vaccination in pregnant women prevents infection effectively and has no adverse outcomes. Future large-scale trials in a randomized fashion are needed to confirm our results.

Influence of vaccination on adverse health outcomes after SARS-CoV-2 infection among individuals with alcohol use disorder: a population-based study.

BACKGROUND AND AIMS: Alcohol use disorders (AUD) have not been included in the priority groups for early vaccine against SARS-CoV-2. We aimed to determine adverse outcomes after SARS-CoV-2 infection among individuals with AUD and how this is modified by vaccination. DESIGN, SETTING AND PARTICIPANTS: This was a registry-based cohort study carried out in Denmark, 27 February 2020 to 15 October 2021, comprising 2157 individuals with AUD and 237 541 without AUD who had had a polymerase chain reaction (PCR)-confirmed SARS-CoV-2 infection during the study period. MEASUREMENTS: The association of AUD with the absolute and relative risk of hospitalization, intensive care and 60-day mortality after SARS-CoV-2 infection and of all-cause mortality throughout the follow-up period were measured. Potential interactions with SARS-CoV-2 vaccination, education and sex were explored in stratified analyses and tested by including interaction terms and using likelihood ratio tests. FINDINGS: Individuals with AUD had an increased absolute and relative risk of adverse outcomes, including hospitalization [incidence rate ratio (IRR) = 1.72, 95% confidence interval (CI) = 1.51-1.95], intensive care (IRR = 1.47, 95% CI = 1.07-2.02) and 60-day mortality [mortality rate ratio (MRR) = 2.35, 95% CI = 1.94-2.85] compared with SARS-CoV-2-positive individuals without AUD. Irrespective of AUD, highest risks of these adverse health outcomes were observed for individuals not vaccinated against SARS-CoV-2 infection, for individuals of low educational level and in males. However, for all-cause mortality throughout the follow-up period, SARS-CoV-2 infection showed a lower relative mortality risk increase, whereas being unvaccinated showed a higher relative mortality risk increase, in individuals with AUD than in the reference population without AUD (P of interaction tests < 0.0001). CONCLUSIONS: Both alcohol use disorder and being unvaccinated for SARS-CoV-2 appear to be independent risk factors for adverse health outcomes following SARS-CoV-2 infection.

Adverse outcomes associated with recorded victimization in mental health electronic records during the first UK COVID-19 lockdown.

PURPOSE: The impact of COVID-19 pandemic policies on vulnerable groups such as people with mental health problems who experience violence remains unknown. This study aimed to investigate the prevalence of victimization recorded in mental healthcare records during the first UK lockdown, and associations with subsequent adverse outcomes. METHODS: Using a large mental healthcare database, we identified all adult patients receiving services between 16.12.2019 and 15.06.2020 and extracted records of victimisation between 16.03.2020 and 15.06.2020 (first UK COVID-19 lockdown). We investigated adverse outcomes including acute care, emergency department referrals and all-cause mortality in the year following the lockdown (16.06.2020- 01.11.2021). Multivariable Cox regressions models were constructed, adjusting for socio-demographic, socioeconomic, clinical, and service use factors. RESULTS: Of 21,037 adults receiving mental healthcare over the observation period, 3,610 (17.2%) had victimisation mentioned between 16.03.2020 and 15.06.2020 (first UK COVID-19 lockdown). Service users with mentions of victimisation in their records had an elevated risk for all outcomes: acute care (adjusted HR: 2.1; 95%CI 1.9-2.3, p < 0.001), emergency department referrals (aHR: 2.0; 95%CI 1.8-2.2; p < 0.001), and all-cause mortality (aHR: 1.5; 95%CI 1.1-1.9; p = 0.003), when compared to service users with no recorded victimisation. We did not observe a statistically significant interaction with gender; however, after adjusting for possible confounders, men had slightly higher hazard ratios for all-cause mortality and emergency department referrals than women. CONCLUSION: Patients with documented victimisation during the first UK lockdown were at increased risk for acute care, emergency department referrals and all-cause mortality. Further research is needed into mediating mechanisms.

Associations of COVID-19 vaccination during pregnancy with adverse neonatal and maternal outcomes: A systematic review and meta-analysis.

Objectives: The low COVID-19 vaccine uptake rate among pregnant women is mainly due to safety concerns about COVID-19 vaccines due to limited safety evidence. Our goal was to evaluate the safety of COVID-19 vaccination during pregnancy with up-to-date evidence. Methods: A comprehensive search of MEDLINE, EMBASE, the Cochrane Library, and clinicaltrials.gov was performed on April 5th, 2022, and updated on May 25th, 2022. Studies evaluating the association of COVID-19 vaccination during pregnancy with adverse maternal and neonatal outcomes were included. Two reviewers independently performed the risk of bias assessment and data extraction. Inverse variance random effect meta-analyses were performed to pool outcome data. Results: Forty-three observational studies were included. COVID-19 vaccination [96,384 (73.9%) BNT162b2, 30,889 (23.7%) mRNA-1273, and 3,172 (2.4%) other types] during pregnancy [23,721 (18.3%) in the first trimester, 52,778 (40.5%) in the second trimester, and 53,886 (41.2%) in the third trimester].was associated with reduced risks of stillbirth or neonatal death (OR, 0.74; 95% CI, 0.60-0.92). Sensitivity analysis restricted to studies in participants without COVID-19 showed that the pooled effect was not robust. COVID-19 vaccination during pregnancy was not associated with congenital anomalies (OR, 0.83; 95% CI, 0.63-1.08), preterm birth (OR, 0.98; 95% CI, 0.90-1.06), NICU admission or hospitalization (OR, 0.94; 95% CI, 0.84-1.04), an Apgar score at 5 min <7 (OR, 0.93; 95% CI, 0.86-1.01), low birth weight (OR, 1.00; 95% CI, 0.88-1.14), miscarriage (OR, 0.99; 95% CI, 0.88-1.11), cesarean delivery (OR, 1.07; 95% CI, 0.96-1.19), or postpartum hemorrhage (OR, 0.91; 95% CI, 0.81-1.01). Conclusions: COVID-19 vaccination during pregnancy was not associated with any of the adverse neonatal or maternal outcomes studied. Interpretation of study findings is limited by the types and timing of vaccination. The vaccinations in our study received during pregnancy were primarily mRNA vaccines administered in the second and third trimester. Future RCTs and meta-analysis are warranted to evaluate the efficacy and long-term effects of the COVID-19 vaccines. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022322525, identifier: PROSPERO, CRD42022322525.

Severe maternal morbidity and mortality during the COVID-19 pandemic: a cohort study in Rio de Janeiro.

Objectives: To identify factors associated with adverse maternal outcomes during the COVID-19 pandemic. Methods: Single-center prospective cohort study at a maternity department in a public general hospital in Rio de Janeiro. All pregnant women evaluated for emergency care, for labor and delivery, for respiratory symptoms, for obstetrical or medical reasons between May 2020 to March 2022 at the participating institution were offered enrollment. The endpoint was maternal mortality or ICU admission. Results: 1609 pregnant women were enrolled; 25.5% participants (n=410) were infected with SARS-CoV-2 based on RT-PCR or an antigen test. There were 21 deaths and 67 ICU admissions in 4% of the cohort. Severe maternal morbidity and mortality incidence was higher during the Gamma than Delta waves (p =0.003). Vaccination conferred protection against the endpoint (RR: 0.4, 95% CI:0.1-0.9, p=0.0169). Factors associated with severe morbidity and mortality included Cesarean section (RR: 3.7, 95% CI: 1.7-7.9, p=0.0008), SARS-CoV-2 infection in the third trimester (RR: 2.4, 95% CI: 1.1-5.6, p=0.0006) and comorbidities (RR: 3, 95% CI= 1.8-5.2, p< 0.0001). Conclusions: : COVID-19 was significantly associated with the risk of severe maternal morbidity and mortality. Immunization of pregnant women against COVID-19 was highly protective against adverse outcomes and should be encouraged during pregnancy.

Prevalence and outcomes of hyponatremia among COVID-19 patients: A systematic review and meta-analysis.

Objectives: On March 2020, the WHO declared coronavirus disease 2019 (COVID-19) pandemic. COVID-19 is associated with various clinical syndromes, with electrolytes imbalances involved. This review aims to quantify the prevalence and outcomes of hyponatremia among COVID-19 patients, as well as to review the underlying pathophysiological mechanisms of hyponatremia among these patients. Methods: Using Preferred Reporting Items for Systematic Reviews and Meta Analyses guidelines, we conducted a systematic literature search using the electronic databases of Google Scholar, MEDLINE (PubMed), WHO Virtual Health Library, and ScienceDirect, without limitations regarding gender, geographical area, race or publication date, up until December 13, 2021. Primary outcomes measured were mortality, intensive care unit (ICU) admission, assisted ventilation need, and length of hospital stay (LOS). Secondary outcome was the mechanism underlying hyponatremia among COVID-19 patients. Results: From a total of 52 included studies, 23 underwent quantitative analysis. For the primary outcomes; proportions, odds ratios (OR), and standardized mean difference (SMD) were calculated using random effects model. The prevalence of hyponatremia was found to be 25.8%. Hyponatremia was found to be significantly associated with increased odds for mortality (OR = 1.97[95% CI, 1.50-2.59]), ICU admission (OR = 1.91 [95% CI, 1.56-2.35]), assisted ventilation need (OR = 2.04 [95% CI, 1.73-2.38]), and with increased LOS (SMD of 5.74 h [95% CI, 0.092-0.385]). Regarding the mechanisms underlying hyponatremia, syndrome of inappropriate anti-diuretic hormone secretion (SIADH) was most commonly reported, followed by adrenal insufficiency, and finally hypovolemic hyponatremia due to gastrointestinal losses. Conclusion: Hyponatremia among COVID-19 patients is generally associated with poor outcomes, with SIADH being the most common underlying mechanism.

Annexin A1 Is Associated with Adverse Clinical Outcomes in Patients with COVID-19.

Severe coronavirus disease 2019 (COVID-19) is characterized by hyperinflammation, vascular damage, and hypercoagulability. Insufficient responses of Annexin A1 (AnxA1), a pro-resolving inhibitor of neutrophil infiltration and activation, might contribute to a severe course of the disease. We longitudinally evaluated AnxA1's role in terms of inflammation, vascular damage, and clinical outcomes in a large prospective cohort of patients with COVID-19. AnxA1 was measured at presentation and during follow-up in the sera of 220 consecutive patients who presented at our hospital during the first wave. AnxA1 was significantly higher in the moderate and severe cases of COVID-19 compared to the healthy controls. Elevated AnxA1 was associated with markers of inflammation and endothelial damage. AnxA1 was significantly higher in patients with thrombotic events and ICU admission. Multivariable logistic regression indicated baseline AnxA1 (per ten units) as a predictor of thrombotic events. Linear mixed models predicted that AnxA1 tended to increase more steeply over time in patients without adverse events, with a statistically significant rise in patients without thrombotic events. These findings might reflect an insufficient increase in AnxA1 as a response to the excessive hyperinflammation in COVID-19. Future studies should evaluate whether hyperinflammation could be reduced through the administration of human recombinant AnxA1 or Ac2-26 peptide.

Adverse outcomes of GHB use: Analysis of ambulance attendances in metropolitan and regional Victoria.

BACKGROUND: Gamma-hydroxybutyrate (GHB) use and attributable harms have been increasing in Australia, however changes over time, including the impact of COVID-19 lockdowns and restrictions on harms requiring an ambulance attendance, are unknown. This study utilised a novel population-based surveillance system to identify the types of GHB-related harms between January 2018 and 31 December 2021 in Victoria, Australia. METHODS: A cross-sectional, retrospective analysis of all GHB-related ambulance attendances between January 2018 and 31 December 2021 in Victoria, Australia was undertaken. Paramedic clinical notes and Glasgow Coma Scale scores were used to assess conscious state. Event codes were classified using dispatch information available in the database. Crude rates (per 100,000 population) and descriptive analyses were calculated for metropolitan and regional settings. Adjusted Odds ratios (aOR) with 95% confidence intervals [95% CI] were used to assess the relationship between GCS severity and polysubstance combinations with GHB. RESULTS: There were 6,836 ambulance attendances for GHB recorded during the study period. A statistically significant increase in GHB-related attendance numbers was observed State-wide in 2019 (n = 1,402, p<0.001) and 2020 (n = 2,622, p<0.001), when comparing year on year attendances. While both numbers and rates (per 100,000 population) of GHB-related attendances were significantly lower in regional areas, significant increases were evident in both metropolitan and regional areas in 2019 and 2020 (both p<0.001). Attendances involving GHB and alcohol had higher odds of a severe GCS score (aOR:1.25; 95%: 1.04-1.49; p<0.019). A high proportion of GHB-attendances involved harms of significant concern including: overdose (56%) and a loss of, or altered state of consciousness (45%). CONCLUSIONS: We observed increases in GHB-related ambulance attendances over time in both metropolitan and regional areas, placing a significant burden on ambulance services. Our study demonstrates the value of using ambulance surveillance to obtain representative data on acute GHB-related harms.

Assessing Associations Between COVID-19 Symptomology and Adverse Outcomes After Piloting Crowdsourced Data Collection: Cross-sectional Survey Study.

BACKGROUND: Crowdsourcing is a useful way to rapidly collect information on COVID-19 symptoms. However, there are potential biases and data quality issues given the population that chooses to participate in crowdsourcing activities and the common strategies used to screen participants based on their previous experience. OBJECTIVE: The study aimed to (1) build a pipeline to enable data quality and population representation checks in a pilot setting prior to deploying a final survey to a crowdsourcing platform, (2) assess COVID-19 symptomology among survey respondents who report a previous positive COVID-19 result, and (3) assess associations of symptomology groups and underlying chronic conditions with adverse outcomes due to COVID-19. METHODS: We developed a web-based survey and hosted it on the Amazon Mechanical Turk (MTurk) crowdsourcing platform. We conducted a pilot study from August 5, 2020, to August 14, 2020, to refine the filtering criteria according to our needs before finalizing the pipeline. The final survey was posted from late August to December 31, 2020. Hierarchical cluster analyses were performed to identify COVID-19 symptomology groups, and logistic regression analyses were performed for hospitalization and mechanical ventilation outcomes. Finally, we performed a validation of study outcomes by comparing our findings to those reported in previous systematic reviews. RESULTS: The crowdsourcing pipeline facilitated piloting our survey study and revising the filtering criteria to target specific MTurk experience levels and to include a second attention check. We collected data from 1254 COVID-19-positive survey participants and identified the following 6 symptomology groups: abdominal and bladder pain (Group 1); flu-like symptoms (loss of smell/taste/appetite; Group 2); hoarseness and sputum production (Group 3); joint aches and stomach cramps (Group 4); eye or skin dryness and vomiting (Group 5); and no symptoms (Group 6). The risk factors for adverse COVID-19 outcomes differed for different symptomology groups. The only risk factor that remained significant across 4 symptomology groups was influenza vaccine in the previous year (Group 1: odds ratio [OR] 6.22, 95% CI 2.32-17.92; Group 2: OR 2.35, 95% CI 1.74-3.18; Group 3: OR 3.7, 95% CI 1.32-10.98; Group 4: OR 4.44, 95% CI 1.53-14.49). Our findings regarding the symptoms of abdominal pain, cough, fever, fatigue, shortness of breath, and vomiting as risk factors for COVID-19 adverse outcomes were concordant with the findings of other researchers. Some high-risk symptoms found in our study, including bladder pain, dry eyes or skin, and loss of appetite, were reported less frequently by other researchers and were not considered previously in relation to COVID-19 adverse outcomes. CONCLUSIONS: We demonstrated that a crowdsourced approach was effective for collecting data to assess symptomology associated with COVID-19. Such a strategy may facilitate efficient assessments in a dynamic intersection between emerging infectious diseases, and societal and environmental changes.

2D speckle-tracking echocardiography as a prognostic imaging modality for COVID-19 adverse outcomes.

Aim: 2D speckle-tracking echocardiography (2D-STE) has been used to assess cardiac recovery during the COVID-19 patient follow-ups within the pandemic. The novel role of STE in predicting adverse outcomes of COVID-19 has received attention due to its high sensitivity in identifying subclinical myocardial dysfunction. We reviewed the studies on using 2D-STE to assess COVID-19 prognosis. Methods: a literature search was conducted on PubMed and Scopus for eligible articles, 24 of which discussed using prognostic 2D-STE for COVID-19 patients. Results: 2D-STE predicts cardiovascular impairments more rapidly and precisely than conventional echocardiography. The 2D-STE technique presents an independent prognostic factor in COVID-19 infection. Conclusion: 2D-STE could be considered a time-efficient and accurate risk predictor of all-cause mortality in COVID-19 patients.

In this review, we have gathered every article that discusses the association between COVID-19 prognosis and speckle-tracking echocardiography, which is a novel, fast and accurate method and does not need expert operators to perform. We have shown that according to the current literature, we can use this imaging technique on the right and left heart ventricles to estimate the prognosis of the patients infected with COVID-19.

Increased circulating microparticles contribute to severe infection and adverse outcomes of COVID-19 in patients with diabetes.

Patients with diabetes infected with COVID-19 have greater mortality than those without comorbidities, but the underlying mechanisms remain unknown. This study aims to identify the mechanistic interactions between diabetes and severe COVID-19. Microparticles (MPs), the cell membrane-derived vesicles released on cell activation, are largely increased in patients with diabetes. To date, many mechanisms have been postulated for increased severity of COVID-19 in patients with underlying conditions, but the contributions of excessive MPs in patients with diabetes have been overlooked. This study characterizes plasma MPs from normal human subjects and patients with type 2 diabetes in terms of amount, cell origins, surface adhesive properties, ACE2 expression, spike protein binding capacity, and their roles in SARS-CoV-2 infection. Results showed that over 90% of plasma MPs express ACE2 that binds the spike protein of SARS-CoV-2. MPs in patients with diabetes increase 13-fold in quantity and 11-fold in adhesiveness when compared with normal subjects. Perfusion of human plasma with pseudo-typed SARS-CoV-2 virus or spike protein-bound MPs into human endothelial cell-formed microvessels-on-a chip demonstrated that MPs from patients with diabetes, not normal subjects, interact with endothelium and carry SARS-CoV-2 into cells through endocytosis, providing additional virus entry pathways and enhanced infection. Results also showed a large percentage of platelet-derived tissue factor-bearing MPs in diabetic plasma, which could contribute to thrombotic complications with SARS-CoV-2 infection. This study reveals a dual role of diabetic MPs in promoting SARS-CoV-2 entry and propagating vascular inflammation. These findings provide novel mechanistic insight into the high prevalence of COVID-19 in patients with diabetes and their propensity to develop severe vascular complications.NEW & NOTEWORTHY This study provides the first evidence that over 90% of human plasma microparticles express ACE2 that binds SARS-CoV-2 S protein with high affinity. Thus, the highly elevated adhesive circulating microparticles identified in patients with diabetes not only have greater SARS-CoV-2 binding capacity but also enable additional viral entry through virus-bound microparticle-endothelium interactions and enhanced infection. These findings reveal a novel mechanistic insight into the adverse outcomes of COVID-19 in patients with diabetes.

Acute Pancreatitis Related to COVID-19 Infection: A Systematic Review and Analysis of Data.

There is increasing literature mentioning severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (COVID-19 infection) causing acute pancreatitis (AP). It is hypothesized that SARS-Cov-2 causes pancreatic injury either by direct cytotoxic effect of the virus on pancreatic cells through the angiotensin-converting enzyme 2 (ACE2) receptors - the main receptors for the virus located on pancreatic cells - or by the cytokine storm that results from COVID-19 infection or a component of both. Many viruses are related to AP including mumps, coxsackievirus, cytomegalovirus (CMV), Epstein-Barr virus (EBV), and as data evolves SARS-CoV-2 virus may be one of them as well. We conducted a systematic literature review to explore the current literature and provide an overview of the evidence of AP in COVID-19 infection. We studied the presence of AP in patients with SARS-CoV-2 infection and calculated the time of diagnosis of SARS-CoV-2 infection with respect to the time of diagnosis of AP. We also studied the age, gender, clinical manifestations, time of onset of symptoms, laboratory values, imaging findings, mortality, length of stay, comorbidities, need for Intensive Care Unit (ICU) care, and excluded any other common causes of AP. We included 40 articles comprising 46 patients. All patients had a positive SARS-CoV-2 polymerase chain reaction (PCR) test and all patients had AP as per Atlanta's criteria. The most common clinical presentation was abdominal pain in 29 (63.0%). Edematous pancreas was the most common Computed Tomography Abdomen Pelvis (CTAP) scan finding in these patients (35 patients). Seventeen (37%) patients required ICU admission and six (13%) patients died. Our study provides an important overview of the available data on AP in COVID-19 patients and concludes that AP is an important complication in COVID-19 infection and should be considered as an important differential in patients with COVID-19 infection who complain of abdominal pain.

Prediction of Adverse Outcomes among Women in the Third Trimester of Pregnancy with Coronavirus Disease 2019.

BACKGROUND: This study aimed to compare the clinical and laboratory characteristics of two groups of women (favorable and adverse outcome groups) in the third trimester of pregnancy with coronavirus disease 2019 (COVID-19) and to investigate the predictors of specific adverse outcomes. MATERIALS AND METHODS: We retrospectively reviewed the medical records of patients hospitalized with COVID-19 between November 2020 and October 2021 at Kyungpook National University Chilgok Hospital. Adverse outcomes were clinically defined using the Novel Coronavirus Pneumonia Emergency Response Epidemiology Team criteria. The group without adverse outcomes was defined as the "favorable outcome" group and the rest as the "adverse outcome" group. We compared the clinical characteristics between the two groups and examined the correlation between their laboratory results and adverse outcomes. RESULTS: Of the 70 pregnant women included, 37 were in their third trimester. No significant differences in clinical characteristics, except the length of hospitalization, were noted between the groups. In laboratory tests conducted immediately after hospitalization, C-reactive protein (CRP) (1.0 [0.3 - 1.4] vs. 2.3 [1.3 - 3.6], P = 0.001) and ferritin (25.0 [14.5 - 34.5] vs. 53.1 [36.0 - 98.0], P <0.03) levels were significantly different between the groups. Logistic regression analysis revealed that CRP (odds ratio [OR]: 2.26; 95% confidence interval [CI]: 1.09 - 5.51, P = 0.040) and ferritin (OR: 1.06; 95% CI: 1.01 - 1.15, P = 0.047) levels were predictors of adverse outcomes. CONCLUSION: CRP and ferritin levels are associated with poor prognosis and can predict adverse outcomes in women with COVID-19 in the third trimester of pregnancy.

Prevalence and outcomes of hyponatremia among COVID-19 patients: A systematic review and meta-analysis

Objectives: On March 2020, the WHO declared coronavirus disease 2019 (COVID-19) pandemic. COVID-19 is associated with various clinical syndromes, with electrolytes imbalances involved. This review aims to quantify the prevalence and outcomes of hyponatremia among COVID-19 patients, as well as to review the underlying pathophysiological mechanisms of hyponatremia among these patients. Methods: Using Preferred Reporting Items for Systematic Reviews and Meta Analyses guidelines, we conducted a systematic literature search using the electronic databases of Google Scholar, MEDLINE (PubMed), WHO Virtual Health Library, and ScienceDirect, without limitations regarding gender, geographical area, race or publication date, up until December 13, 2021. Primary outcomes measured were mortality, intensive care unit (ICU) admission, assisted ventilation need, and length of hospital stay (LOS). Secondary outcome was the mechanism underlying hyponatremia among COVID-19 patients. Results: From a total of 52 included studies, 23 underwent quantitative analysis. For the primary outcomes;proportions, odds ratios (OR), and standardized mean difference (SMD) were calculated using random effects model. The prevalence of hyponatremia was found to be 25.8%. Hyponatremia was found to be significantly associated with increased odds for mortality (OR = 1.97[95% CI, 1.50–2.59]), ICU admission (OR = 1.91 [95% CI, 1.56–2.35]), assisted ventilation need (OR = 2.04 [95% CI, 1.73– 2.38]), and with increased LOS (SMD of 5.74 h [95% CI, 0.092–0.385]). Regarding the mechanisms underlying hyponatremia, syndrome of inappropriate anti-diuretic hormone secretion (SIADH) was most commonly reported, followed by adrenal insufficiency, and finally hypovolemic hyponatremia due to gastrointestinal losses. Conclusion: Hyponatremia among COVID-19 patients is generally associated with poor outcomes, with SIADH being the most common underlying mechanism. [ FROM AUTHOR] Copyright of Journal of Health Sciences (Qassim University) is the property of Journal of Health Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Performance of Machine Learning Algorithms for Predicting Adverse Outcomes in Community-Acquired Pneumonia.

Background: The ability to assess adverse outcomes in patients with community-acquired pneumonia (CAP) could improve clinical decision-making to enhance clinical practice, but the studies remain insufficient, and similarly, few machine learning (ML) models have been developed. Objective: We aimed to explore the effectiveness of predicting adverse outcomes in CAP through ML models. Methods: A total of 2,302 adults with CAP who were prospectively recruited between January 2012 and March 2015 across three cities in South America were extracted from DryadData. After a 70:30 training set: test set split of the data, nine ML algorithms were executed and their diagnostic accuracy was measured mainly by the area under the curve (AUC). The nine ML algorithms included decision trees, random forests, extreme gradient boosting (XGBoost), support vector machines, Naïve Bayes, K-nearest neighbors, ridge regression, logistic regression without regularization, and neural networks. The adverse outcomes included hospital admission, mortality, ICU admission, and one-year post-enrollment status. Results: The XGBoost algorithm had the best performance in predicting hospital admission. Its AUC reached 0.921, and accuracy, precision, recall, and F1-score were better than those of other models. In the prediction of ICU admission, a model trained with the XGBoost algorithm showed the best performance with AUC 0.801. XGBoost algorithm also did a good job at predicting one-year post-enrollment status. The results of AUC, accuracy, precision, recall, and F1-score indicated the algorithm had high accuracy and precision. In addition, the best performance was seen by the neural network algorithm when predicting death (AUC 0.831). Conclusions: ML algorithms, particularly the XGBoost algorithm, were feasible and effective in predicting adverse outcomes of CAP patients. The ML models based on available common clinical features had great potential to guide individual treatment and subsequent clinical decisions.

Quantifying the Excess Risk of Adverse COVID-19 Outcomes in Unvaccinated Individuals With Diabetes Mellitus, Hypertension, Ischaemic Heart Disease or Myocardial Injury: A Meta-Analysis.

Background: More than 80% of individuals in low and middle-income countries (LMICs) are unvaccinated against coronavirus disease 2019 (COVID-19). In contrast, the greatest burden of cardiovascular disease is seen in LMIC populations. Hypertension (HTN), diabetes mellitus (DM), ischaemic heart disease (IHD) and myocardial injury have been variably associated with adverse COVID-19 outcomes. A systematic comparison of their impact on specific COVID-19 outcomes is lacking. We quantified the impact of DM, HTN, IHD and myocardial injury on six adverse COVID-19 outcomes: death, acute respiratory distress syndrome (ARDS), invasive mechanical ventilation (IMV), admission to intensive care (ITUadm), acute kidney injury (AKI) and severe COVID-19 disease (SCov), in an unvaccinated population. Methodology: We included studies published between 1st December 2019 and 16th July 2020 with extractable data on patients ≥18 years of age with suspected or confirmed SARS-CoV-2 infection. Odds ratios (OR) for the association between DM, HTN, IHD and myocardial injury with each of six COVID-19 outcomes were measured. Results: We included 110 studies comprising 48,809 COVID-19 patients. Myocardial injury had the strongest association for all six adverse COVID-19 outcomes [death: OR 8.85 95% CI (8.08-9.68), ARDS: 5.70 (4.48-7.24), IMV: 3.42 (2.92-4.01), ITUadm: 4.85 (3.94-6.05), AKI: 10.49 (6.55-16.78), SCov: 5.10 (4.26-6.05)]. HTN and DM were also significantly associated with death, ARDS, ITUadm, AKI and SCov. There was substantial heterogeneity in the results, partly explained by differences in age, gender, geographical region and recruitment period. Conclusion: COVID-19 patients with myocardial injury are at substantially greater risk of death, severe disease and other adverse outcomes. Weaker, yet significant associations are present in patients with HTN, DM and IHD. Quantifying these associations is important for risk stratification, resource allocation and urgency in vaccinating these populations. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, registration no: CRD42020201435 and CRD42020201443.

Machine Learning Algorithms in Application to COVID-19 Severity Prediction in Patients

Uzbekistan as well as the rest of the world faces the third wave of COVID-19 and uses machine learning algorithms to predict the adverse outcome during the admission of new patients. We collected the dataset of 1145 patients admitted to the Republican Center for Emergency Medicine. We use different machine learning models to predict the COVID-19 severe course. This study uses feature selection procedures based on statistical tests and the elimination of linearly dependent features. The resulting multilayer perceptron yields a ROC AUC of 86.9% on the test set outperforming other machine learning algorithms and several competing works. The model relies on easily collected features without blood laboratory testing. It increases an availability of the reliable risk prediction to developing countries. © 2022, Springer Nature Switzerland AG.

Stillbirth in COVID-19 Affected Pregnancies: A Double Whammy for the Mother.

Introduction Pregnant women represent a high-risk group especially during the COVID-19 pandemic, suffering at the expense of pandemic restrictions and landing up in adverse maternofetal outcomes including stillbirth. Fetal demise along with COVID-19 disease acts as a double blow to these mothers. Literature is still limited on its impact on maternofetal outcomes. Methods A prospective, observational study was conducted in a tertiary care hospital in Delhi, India from April 15, 2020 to April 14, 2021, wherein all pregnant mothers with SARS-CoV-2 infection in the hospital who delivered a stillborn baby were enrolled and analyzed for incidence of stillbirth. These women were evaluated for risk factors and causes for stillbirth. Results Out of 15859 deliveries in the institute, there were 330 viable births among COVID-19 affected pregnancies. The incidence of stillbirth was 7.2% (24/330). The institutional delivery rate fell by 43% during the pandemic. The majority of cases were unbooked, from rural areas and of low socioeconomic status (p<0.01). The most significant risk factor and cause for stillbirth was an associated comorbidity (75%, p<0.001), notably severe forms of hypertensive disorders of pregnancy (HDP, 41.6%, p=0.002), followed by preterm labour (58.3%) and preterm premature rupture of membranes (PPROM, 29.1%, p<0.001). HDP remained the main cause of macerated stillbirths while maternal fever (50%, p<0.001) was the main cause of fresh stillbirth. Major modifiable factors were lack of awareness of when to seek care (83.3%), financial reasons (75%), commutation problems (87.5%), distance to hospitals (50%) and delayed referral (41.6%). Conclusion Improved policy-making, with an emphasis on telemedicine, COVID-19 preparedness alongside amped up vaccination and healthcare workers training will help reduce adverse maternofetal outcomes.