Low TSH and low T3 hormone levels as a prognostic for mortality in COVID-19 intensive care patients.

Introduction: Coronavirus diasease 2019 (COVID-19) can cause both pulmonary and systemic inflammation, potentially determining multi-organ dysfunction. The thyroid gland is a neuroendocrine organ that plays an important role in regulating immunity and metabolism. Low serum levels of thyroid hormones are common in critical disease situations. The association between low thyroid hormone levels and mortality in COVID-19 intensive care patients has yet to be studied. Aim: The aim of this study is to compare thyroid hormone levels between patients in the general intensive care unit (ICU) to patients in the COVID-19 ICU. Methods: This was a retrospective comparative study of 210 patients who were hospitalized at Ziv Medical Center in the general ICU and in the COVID-19 ICU. Clinical and demographic data were collected from patient's electronic medical records. Results: Serum thyroid hormone levels of Thyroid Simulating Hormone (TSH), T4, and T3 were significantly lower in COVID-19 intensive care unit patients compared to the patients from the general intensive care unit (p < 0.05). The mortality rate in the COVID-19 ICU (44.4%) was higher compared to that in the general ICU (27.3%) (p < 0.05). No significant statistical difference was observed between the two groups in terms of gender and recorded comorbidities of diabetes mellitus, cerebral vascular accident, kidney disease, and cancer. Conclusions: Low serum thyroid hormone levels-T3, T4, and TSH-in COVID-19 ICU patients are associated with higher mortality and could possibly be used as a prognostic factor for mortality among COVID-19 ICU patients. Thyroid hormone levels should be a part in the routine evaluation of COVID-19 ICU patients.

The potential of tailed amplicons for SARS-CoV-2 detection in Nucleic Acid Lateral Flow Assays.

Nucleic Acid Lateral Flow Assays (NALFAs) are a promising solution for the point-of-care detection of viruses like SARS-CoV-2. However, they show some drawbacks, such as the great dependency on the use of antibodies and the need for post-amplification protocols that enable the preparation of amplicons for effective readings, as well as low sensitivity. Here, we developed amplicons of a specific SARS-CoV-2 gene tailed with single-strand DNA (ssDNA) sequences to hybridize with DNA probes immobilized on the NALFA strips, thus overcoming the aforementioned problems. Results have shown that tailed primers have not compromised the amplification efficiency and allowed the correct detection of the amplicons in the lateral flow strip. This approach has presented a limit of detection (LOD) of 25 RNA copies /reaction mix (1 copy/µL) and the test of cross-reactivity with other related viruses has not shown any cross-reactivity. Twenty clinical samples were evaluated by NALFA and simultaneously compared with the gold standard RT-qPCR protocol, originating equal results. Although the number of clinical specimens tested being relatively small, this indicates a sensitivity and specificity both of 100%. In short, an alternative NALFA was successfully implemented, rendering an accurate route for SARS-CoV-2 diagnosis, compatible with low-resource settings.

Logistic regression analysis of the value of biomarkers, clinical symptoms, and imaging examinations in COVID-19 for SARS-CoV-2 nucleic acid detection.

The detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) nucleic acid detection provides a direct basis for diagnosing Coronavirus Disease 2019. However, nucleic acid test false-negative results are common in practice and may lead to missed diagnosis. Certain biomarkers, clinical symptoms, and imaging examinations are related to SARS-CoV-2 nucleic acid detection and potential predictors. We examined nucleic acid test results, biomarkers, clinical symptoms, and imaging examination data for 116 confirmed cases and asymptomatic infections in Zhuhai, China. Patients were divided into nucleic acid-positive and -false-negative groups. Predictive values of biomarkers, symptoms, and imaging for the nucleic acid-positive rate were calculated by Least Absolute Shrinkage and Selection Operators regression analysis and binary logistic regression analysis, and areas under the curve of these indicators were calculated. Hemoglobin (OR = 1.018, 95% CI: 1.006-1.030; P = .004) was higher in the respiratory tract-positive group than the nucleic acid-negative group, but platelets (OR = 0.996, 95% CI: 0.993-0.999; P = .021) and eosinophils (OR = 0.013, 95% CI: 0.001-0.253; P = .004) were lower; areas under the curve were 0.563, 0.614, and 0.642, respectively. Some biomarkers can predict SARS-CoV-2 viral nucleic acid detection rates in Coronavirus Disease 2019 and are potential auxiliary diagnostic tests.

Is it possible to identify COVID-19 infection-related biomarkers during pregnancy?: A prospective study in Turkish population.

The coronavirus disease 2019 (COVID-19) has raised concerns about the potential complications it may cause in pregnant women. Therefore, biomarkers that can predict the course of COVID-19 in pregnant women may be of great benefit as they would provide valuable insights into the prognosis and, thus, the management of the disease. In this context, the objective of this study is to identify the biomarkers that can predict COVID-19 progression in pregnant women, focusing on composite hemogram parameters and systemic inflammatory and spike markers. The population of this single-center prospective case-control study consisted of all consecutive pregnant women with single healthy fetuses who tested positive for COVID-19 and who were admitted to Bakirköy Dr Sadi Konuk Training and Research Hospital in Istanbul, Turkey, a COVID-19 referral hospital, between April 2020 and March 2021, with an obstetric indication, during their second or third trimester. The control group consisted of consecutive pregnant women with a single healthy fetus who were admitted to the same hospital within the same date range, had demographic and obstetric characteristics matching the patient group, but tested negative for COVID-19. The patient and control groups were compared in terms of platelet-to-lymphocyte ratio (PLR), platelet-to-neutrophil ratio (PNR), and neutrophil-to-lymphocyte ratio (NLR), and systemic inflammatory and spike markers, including C-reactive protein (CRP), interleukin-6 (IL-6), interleukin-10 (IL-10), cluster of differentiation 26 (CD26), and B7 homolog 4 (B7H4). There were 45 (51.1%) and 43 (48.8%) pregnant women in the patient and control groups, respectively. There was no significant difference between the groups in demographic and obstetric characteristics (P > .05). The PNR, PLR, and CRP values were significantly higher in the patient group than in the control group (P < .05). On the other hand, there was no significant difference between the groups in IL-6, IL-10, CD26, and B7H4 levels (P > .05). The findings of our study showed that specific inflammatory markers, such as CRP, PLR, and PNR, can potentially predict the course of COVID-19 in pregnant women. However, more comprehensive, well-controlled studies are needed to corroborate our study's findings and investigate other potential inflammatory markers.

Development and evaluation of a lyophilization protocol for colorimetric RT-LAMP diagnostic assay for COVID-19.

Molecular diagnostics involving nucleic acids (DNA and RNA) are regarded as extremely functional tools. During the 2020 global health crisis, efforts intensified to optimize the production and delivery of molecular diagnostic kits for detecting SARS-CoV-2. During this period, RT-LAMP emerged as a significant focus. However, the thermolability of the reagents used in this technique necessitates special low-temperature infrastructure for transport, storage, and conservation. These requirements limit distribution capacity and necessitate cost-increasing adaptations. Consequently, this report details the development of a lyophilization protocol for reagents in a colorimetric RT-LAMP diagnostic kit to detect SARS-CoV-2, facilitating room-temperature transport and storage. We conducted tests to identify the ideal excipients that maintain the molecular integrity of the reagents and ensure their stability during room-temperature storage and transport. The optimal condition identified involved adding 5% PEG 8000 and 75 mM trehalose to the RT-LAMP reaction, which enabled stability at room temperature for up to 28 days and yielded an analytical and diagnostic sensitivity and specificity of 83.33% and 90%, respectively, for detecting SARS-CoV-2. This study presents the results of a lyophilized colorimetric RT-LAMP COVID-19 detection assay with diagnostic sensitivity and specificity comparable to RT-qPCR, particularly in samples with high viral load.

Maximally informative feature selection using Information Imbalance: Application to COVID-19 severity prediction.

Clinical databases typically include, for each patient, many heterogeneous features, for example blood exams, the clinical history before the onset of the disease, the evolution of the symptoms, the results of imaging exams, and many others. We here propose to exploit a recently developed statistical approach, the Information Imbalance, to compare different subsets of patient features and automatically select the set of features that is maximally informative for a given clinical purpose, especially in minority classes. We adapt the Information Imbalance approach to work in a clinical framework, where patient features are often categorical and are generally available only for a fraction of the patients. We apply this algorithm to a data set of ∼ 1300 patients treated for COVID-19 in Udine hospital before October 2021. Using this approach, we find combinations of features which, if used in combination, are maximally informative of the clinical fate and of the severity of the disease. The optimal number of features, which is determined automatically, turns out to be between 10 and 15. These features can be measured at admission. The approach can be used also if the features are available only for a fraction of the patients, does not require imputation and, importantly, is able to automatically select features with small inter-feature correlation. Clinical insights deriving from this study are also discussed.

Faecal shedding of SARS-CoV-2 from patients with asymptomatic and mild COVID-19 without gastrointestinal symptoms in Ghana.

OBJECTIVE: In this study, we sought to determine whether faecal shedding occurs among SARS-COV-2 positive Ghanaians, as reported elsewhere. Hence we assayed for SARS-COV-2 in the stools of 48 SARS-COV-2 confirmed patients at the Ho Municipal Hospital in Ghana. RESULTS: Of the 48 COVID-19 patients, 45 (93.8%) had positive tests for SARS-CoV-2 faecal shedding. About 60% reported no respiratory symptoms, while only 2% (1 patient) reported gastrointestinal (GI) symptoms in the form of nausea. Other symptoms reported included headache (57.9%), weakness (57.9%), cough (52.6%), blocked/runny nose (47.4%), fever (31.6%), sore throat (31.6%), and shortness of breath (21.1%). One person complained of nausea (5.3%) Semi-quantitative comparison of the SARS COV-2 viral loads in matched respiratory and faecal samples using the cycle threshold (CT) values revealed no statistical differences. Furthermore, the duration between collection of respiratory and faecal samples did not have any direct influence on the differences in the CT values. This suggests that treatment and use of sewage for environmental surveillance of SARS COV-2 could be a potential public health countermeasure.

[VASCULAR OPHTHALMIC MANIFESTATIONS IN COVID-19 PATIENTS].

INTRODUCTION: Although COVID-19 is mainly a respiratory disease, recent evidence has emerged of vascular and procoagulant pathologies even in young and otherwise healthy individuals. Ophthalmic manifestations include, among others, visual impairment due to arteritic and venous retinal obstructions, which at times precedes other aspects of the disease. We present two atypical cases of internal carotid dissection (ICAD) and review the different ocular symptoms of ICAD and its association with the COVID-19 pandemic. BACKGROUND: A 43-year-old otherwise healthy man was referred to the Emergency Department with a headache and monocular blurring of vision. A recent fever (2 weeks prior) was noted on anamnesis, in light of absence of available positive PCR test during the illness period, clinical suspicion of COVID-19 was assumed. An initial ophthalmic evaluation found a mild optic nerve function impairment with preserved visual acuity. Computed tomography (CT) showed sinusitis, and an initial diagnosis was made of mild optic neuropathy secondary to sphenoid sinusitis. A few hours after admission, the patient reported deterioration of symptoms and examination revealed no light perception in his right eye and pale edematous optic nerve. Urgent magnetic resonance angiography (MRA) demonstrated right ICAD with no additional findings. The second patient, a 43-year-old man developed an acute event of strabismus, left limb paralysis, and speech difficulties while on a hospital visit for his son. The patient underwent CT of the brain which demonstrated extensive infarction following the distribution of his right cerebral artery. Continued investigation using computed tomography angiography (CTA) demonstrated a dissection of the right internal carotid artery. The patient was positive for COVID-19. DISCUSSION: In this review, we discuss 2 cases of carotid artery dissection presenting with an acute ocular complaint in two otherwise healthy young individuals. Events were suspected to have been provoked by COVID-19 infection. The pathogenesis and mechanisms behind COVID-19 induced coagulopathy are not clear, and several mechanisms have been proposed including endothelial damage and dysfunction. The virus is thought to enter endothelial cells and lead to a pathological procoagulant state. Awareness should be drawn to uncommon signs especially in young adults. Clotting issues can arise and should be treated quickly as they might be life and vision threatening.

Collection and transportation of SARS-CoV-2 and influenza A virus diagnostic samples: Optimizing the usage of guanidine-based chaotropic salts for enhanced biosafety and viral genome preservation.

Many virus lysis/transport buffers used in molecular diagnostics, including the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA, contain guanidine-based chaotropic salts, primarily guanidine hydrochloride (GuHCl) or guanidine isothiocyanate (GITC). Although the virucidal effects of GuHCl and GITC alone against some enveloped viruses have been established, standardized data on their optimum virucidal concentrations against SARS-CoV-2 and effects on viral RNA stability are scarce. Thus, we aimed to determine the optimum virucidal concentrations of GuHCl and GITC against SARS-CoV-2 compared to influenza A virus (IAV), another enveloped respiratory virus. We also evaluated the effectiveness of viral RNA stabilization at the determined optimum virucidal concentrations under high-temperature conditions (35°C) using virus-specific real-time reverse transcription polymerase chain reaction. Both viruses were potently inactivated by 1.0 M GITC and 2.5 M GuHCl, but the GuHCl concentration for efficient SARS-CoV-2 inactivation was slightly higher than that for IAV inactivation. GITC showed better viral RNA stability than GuHCl at the optimum virucidal concentrations. An increased concentration of GuHCl or GITC increased viral RNA degradation at 35°C. Our findings highlight the need to standardize GuHCl and GITC concentrations in virus lysis/transport buffers and the potential application of these guanidine-based salts alone as virus inactivation solutions in SARS-CoV-2 and IAV molecular diagnostics.

Analyzing factors affecting positivity in drive-through COVID-19 testing: a cross-sectional study.

BACKGROUND: Demand for COVID-19 testing prompted the implementation of drive-through testing systems. However, limited research has examined factors influencing testing positivity in this setting. METHODS: From October 2020 to March 2023, a total of 1,341 patients, along with their clinical information, were referred from local clinics to the Sasebo City COVID-19 drive-through PCR center for testing. Association between clinical information or factors related to the drive-through center and testing results was analyzed by Fisher's exact test and logistic regression models. RESULTS: Individuals testing positive exhibited higher frequencies of upper respiratory symptoms; cough (OR 1.5 (95% CI 1.2-1.8), p < 0.001, q = 0.005), sore throat (OR 2.4 (95% CI 1.9-3.0), p < 0.001, q < 0.001), runny nose (OR 1.4 (95% CI 1.1-1.8), p = 0.002, q = 0.009), and systemic symptoms; fever (OR 1.5 (95% CI 1.1-2.0), p = 0.006, q = 0.02), headache (OR 1.9 (95% CI 1.4-2.5), p < 0.001, q < 0.001), and joint pain (OR 2.7 (95% CI 1.8-4.1), p < 0.001, q < 0.001). Conversely, gastrointestinal symptoms; diarrhea (OR 0.2 (95% CI 0.1-0.4), p < 0.001, q < 0.001) and nausea (OR 0.3 (95% CI 0.1-0.6), p < 0.001, q < 0.001) were less prevalent among positives. During omicron strain predominant period, higher testing positivity rate (OR 20 (95% CI 13-31), p < 0.001) and shorter period from symptom onset to testing (3.2 vs. 6.0 days, p < 0.001) were observed compared to pre-omicron period. Besides symptoms, contact history with infected persons at home (OR 4.5 (95% CI 3.1-6.5), p < 0.001, q < 0.001) and in office or school (OR 2.9 (95% CI 2.1-4.1), p < 0.001, q < 0.001), as well as the number of sample collection experiences by collectors (B 7.2 (95% CI 2.8-12), p = 0.002) were also associated with testing results. CONCLUSIONS: These findings underscore the importance of factors related to drive-through centers, especially contact history interviews and sample collection skills, for achieving higher rates of COVID-19 testing positivity. They also contribute to enhanced preparedness for next infectious disease pandemics.

Clinical characteristics of liver transplant recipients with COVID-19 and analysis of risk factors for the severe disease.

INTRODUCTION: Liver transplant (LT) recipients were at a high risk of infection during the coronavirus disease 2019 (COVID-19) pandemic. Our purpose was to compare the clinical characteristics of severe and non-severe groups of LT recipients with COVID-19, and to analyze their risk factors for severe disease. METHODOLOGY: 79 LT recipients with COVID-19 were divided into a non-severe group (n = 60) and a severe group (n = 19), and differences in clinical characteristics, laboratory tests, and chest computed tomography (CT) performance were analyzed. Logistic regression was used to identify risk factors with severe COVID-19. Receiver operating characteristic (ROC) curves were plotted and the area under curve (AUC) values were calculated to assess the predictive value for severe COVID-19. RESULTS: Age was statistically different (p < 0.001) between the two groups. The difference in neutrophil-to-lymphocyte ratio (NLR), serum creatinine (Scr), D-dimer, urea, C-reactive protein (CRP), lactate dehydrogenase (LDH), and the number of lung segments involved in inflammation between the two groups were statistically significant (p < 0.05). The results revealed that age (OR = 1.255, 95% CI 1.079-1.460), NLR (OR = 1.172, 95% CI 1.019-1.348), and Scr (OR = 1.041, 95% CI 1.016-1.066) were independent risk factors for severe COVID-19. The ROC results showed that high values for age, NLR and Scr predicted severe COVID-19, with AUC values of 0.775, 0.841 and 0.820, respectively, and 0.925 for the three factors combined. CONCLUSIONS: Advanced age, and elevated NLR and Scr are independent risk factors for severe COVID-19 in LT recipients.

Accuracy of the Verbal Autopsy questionnaire in the diagnosis of COVID-19 deaths in a Brazilian capital.

The Verbal Autopsy (VA) is a questionnaire about the circumstances surrounding a death. It was widely used in Brazil to assist in postmortem diagnoses and investigate excess mortality during the Coronavirus Disease 2019 (COVID-19) pandemic. This study aimed to determine the accuracy of investigating acute respiratory distress syndrome (ARDS) using VA. This is a cross-sectional study with prospective data collected from January 2020 to August 2021 at the Death Verification Service of Sao Luis city, Brazil. VA was performed for suspected COVID-19 deaths, and one day of the week was randomly chosen to collect samples from patients without suspected COVID-19. Two swabs were collected after death and subjected to reverse transcription-polymerase chain reaction (RT-PCR) for SARS-CoV-2 detection. Of the 250 cases included, the VA questionnaire identified COVID-19-related ARDS in 67.2% (52.98% were positive for COVID-19). The sensitivity of the VA questionnaire was 0.53 (0.45-0.61), the specificity was 0.75 (0.64-0.84), the positive predictive value was 0.81 (0.72-0.88), and the negative predictive value was 0.44 (0.36-0.53). The VA had a lower-than-expected accuracy for detecting COVID-19 deaths; however, because it is an easily accessible and cost-effective tool, it can be combined with more accurate methods to improve its performance.

Hematological Parameters and Comorbidities in COVID-19: Insights into Clinical Profiles and Outcome Predictors.

BACKGROUND: The global pandemic, known as the coronavirus disease 2019 (COVID-19) and caused by the severe acute respiratory syndrome, coronavirus 2 (SARS-CoV-2), poses a significant threat, particularly to individuals with comorbidities such as hypertension, chronic obstructive pulmonary disease (COPD), diabetes, HIV, cardiovascular disease (CVD), and cancer. METHODS: This descriptive retrospective study investigates the impact of comorbidities on COVID-19-positive patients. The study includes individuals that were tested positive for SARS-CoV-2 via polymerase chain reaction at the Security Forces Hospital, Makkah, KSA, between February, 2022, and June, 2022. A total of 208 patients (107 males, 101 females) were examined, and the laboratory results revealed normal parameters. RESULTS: An analysis indicates that 86.5% of the patients were discharged, 2.9% remained hospitalized, and 10.6% succumbed to the disease, indicating a 10.6% mortality rate among comorbid COVID-19-positive patients. Notably, the study identifies specific comorbidities (chronic kidney disease, diabetes mellitus, hypertension) and changes in laboratory parameters (red blood cells, hemoglobin, C-reactive protein, white blood cells, ferritin, D-dimer, ALT, troponin, LDH, neutrophils) associated with ICU admission during hospitalization. CONCLUSIONS: This study underscores the critical impact of comorbidities, such as chronic kidney disease, diabetes, and hypertension, on the clinical outcomes of COVID-19-positive patients. The identification of specific laboratory parameters linked with ICU admission provides valuable insights for risk stratification and tailored management strategies.

SARS-CoV-2 Infection Increases High Risk Rate of Down Syndrome Screening Test by Reducing Alpha-Fetoprotein.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been a significant global health issue in recent years. Numerous studies indicate that COVID-19 during pregnancy is associated with an increased likelihood of pregnancy complications. Additionally, pregnancy itself is known to elevate the risk of severe SARS-CoV-2 infection. To explore the potential impact of SARS-CoV-2 infection on the probability of Down syndrome in fetuses, we conducted serological testing of Down syndrome markers in pregnant women who had contracted the virus. METHODS: Serological experiments were conducted utilizing a particle chemiluminescence test. The cohort of pregnant women was categorized into three groups: a control group with no infection, a group infected with SARS-CoV-2 Omicron within the first six weeks of gestation, and a group infected beyond the sixth week of gestation. RESULTS: In the group of individuals infected within 6 gestational weeks, the infection resulted in a decrease in alpha-fetoprotein (AFP) levels and a higher positive rate of Down syndrome screening tests (p ˂ 0.05). However, in this study, SARS-CoV-2 infection did not lead to an increase in the occurrence of Down syndrome in the fetus. The positive rate of women infected beyond 6 gestational weeks was slightly higher than the non-infected group (6.2% vs. 5.7%), but these differences were not statistically significant (p > 0.05). Within the group infected beyond 6 gestational weeks, there was, compared to the control group, a decrease in free beta human chorionic gonadotropin (ß-hCG) levels (p < 0.05). CONCLUSIONS: This study presents a novel investigation into the impact of SARS-CoV-2 infection on AFP and ß-hCG levels. It has been observed that pregnant women who contract SARS-CoV-2 may exhibit an increased likelihood of positive results in serum tests conducted for Down syndrome screening. However, it is important to note that the occurrence of Down syndrome in the developing fetus does not appear to be elevated. To validate these findings, additional research involving larger and diverse cohorts is necessary.

Strategic Retesting to Reduce False Positive SARS-CoV-2 PCR Test Results.

BACKGROUND: Nucleic acid amplification testing is the gold standard for SARS-CoV-2 diagnostics, although it may produce a certain number of false positive results. There has not been much published about the characteristics of false positive results. In this study, based on retesting, specimens that initially tested positive for SARS-CoV-2 were classified as true or false positive groups to characterize the distribution of cycle threshold (CT) values for N1 and N2 targets and number of targets detected for each group. METHODS: Specimens that were positive for N-gene on retesting and accompanied with S-gene were identified as true positives (true positive based on retesting, rTP), while specimens that retested negative were classified as false positives (false positive based on retesting, rFP). RESULTS: Of the specimens retested, 85/127 (66.9%) were rFP, 16/47 (34.0%) specimens with both N1 and N2 targets initially detected were rFP, and the CT values for each target was higher in rFP than in rTP. ROC curve analysis showed that optimal cutoff values of CT to differentiate between rTP and rFP were 34.8 for N1 and 33.0 for N2. With the optimal cutoff values of CT for each target, out of the 24 specimens that were positive for both N1 and N2 targets and classified as rTP, 23 (95.8%) were correctly identified as true positives. rFP specimens had a single N1 target in 52/61 (85.2%) and a single N2 target in 17/19 (89.5%). Notably, no true positive results were obtained from any specimens with only N2 target detected. CONCLUSIONS: These results suggest that retesting should be performed for positive results with a CT value greater than optimal cutoff value for each target or with a single N1 target amplified, considering the possibility of a false positive. This may provide guidance on indications to perform retesting to minimize the number of false positives.

Contributing Factors Affecting the Length of Hospital Stay among Febrile Patients with Omicron Reported in Suzhou.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has had global attention with regard to the urgent challenging threat to global public health. Currently, the novel Omicron variant is showing rapid transmission across the world, which appears to be more contagious than the previous variants of COVID-19. Early recognition of disease is critical for patients' prognosis. Fever is the most common symptom. We evaluated the clinical characteristics of febrile patients with COVID-19 reported in Suzhou and explored the predictors for a longer duration of hospitalization in febrile patients. METHODS: This retrospective study was carried out in 146 Omicron variant infected patients confirmed by nucleic acid tests in the Affiliated Infectious Hospital of Soochow University between February 13, 2022 and March 2, 2022. Data of febrile and afebrile laboratory-confirmed patients on hospital admission in Suzhou were collected and compared. According to the median length of stay (LOS), febrile cases were divided into short and long LOS groups. Then the predictive factors for a prolonged duration of hospitalization were analyzed using logistic regression methods. Receiver Operating Characteristic (ROC) Curve analysis was used to analyze the effectiveness of the risk factors for prolonged duration of hospitalization in febrile COVID-19 patients. RESULTS: Of the 146 discharged patients in our study, 112 patients (76.7%) caught a fever. Compared to afebrile Omicron patients, febrile patients showed a significantly longer duration of hospitalization (15.00 (5.80) vs. 13.00 (6.00), p = 0.002). Taking the median LOS (15 days) as the dividing point, 64 febrile cases were assigned to the short LOS group and the rest to the long LOS group. The long LOS group had a longer virus shedding duration than the short LOS group (18.42 ± 2.86 vs. 11.94 ± 2.50 days, p < 0.001). Compared to short LOS febrile patients, long LOS patients were older (44.88 ± 21.36 vs. 30.89 ± 17.95 years, p < 0.001) and showed a higher proportion of greater than 60 years old (33.3% vs. 9.4%, p = 0.002; Supplemental Table S2). Febrile patients with long LOS also showed a higher proportion of hypertension (25% vs. 6.3%, p = 0.005) and higher levels of cTnI (5.00 (3.00) vs. 4.00 (2.00) µg/L, p = 0.025). The multivariate analysis indicated that virus shedding duration (OR 2.369, 95% CI 1.684 - 3.333, p < 0.001) was the independent risk factor associated with long-term hospital stay in febrile patients with Omicron. Furthermore, ROC Curve analysis revealed that the area under the curve (AUC) for virus shedding duration to diagnose prolonged duration of hospitalization in febrile COVID-19 patients was 0.951 (95% CI 0.913 - 0.989). The cutoff point was set at 14.5 days. CONCLUSIONS: More than half of the non-severe patients exposed to the new Omicron variant had symptoms of fever. In total, 42.86% of the febrile patients were discharged within 15 days since hospital admission. Febrile Omicron cases took a longer duration of hospitalization compared to afebrile patients, and virus shedding duration (OR 2.369, 95% CI 1.684 - 3.333, p < 0.001) was probably a predictive factor for long-term hospital stays.

A Prediction Model for Prolonged Hospital Length of Stay (ProLOS) in Coronavirus Disease 2019 (COVID-19) Patients.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). With the normalization of COVID-19 globally, it is crucial to construct a prediction model that enables clinicians to identify patients at risk for ProLOS based on demographics and serum inflammatory biomarkers. METHODS: The study included hospitalized patients with a confirmed diagnosis of COVID-19. These patients were randomly grouped into a training (80%) and a test (20%) cohort. The LASSO regression and ten-fold cross-validation method were applied to filter variables. The training cohort utilized multifactorial logistic regression analyses to identify the independent factors of ProLOS in COVID-19 patients. A 4-variable nomogram was created for clinical use. ROC curves were plotted, and the area under the curve (AUC) was calculated to evaluate the model's discrimination; calibration analysis was planned to assess the validity of the nomogram, and decision curve analysis (DCA) was used to evaluate the clinical usefulness of the model. RESULTS: The results showed that among 310 patients with COVID-19, 80 had extended hospitalization (80/310). Four independent risk factors for COVID-19 patients were identified: age, coexisting chronic respiratory diseases, white blood cell count (WBC), and serum albumin (ALB). A nomogram based on these variables was created. The AUC in the training cohort was 0.808 (95% CI: 0.75 - 0.8671), and the AUC in the test cohort was 0.815 (95% CI: 0.7031 - 0.9282). The model demonstrates good calibration and can be used with threshold probabilities ranging from 0% to 100% to obtain clinical net benefits. CONCLUSIONS: A predictive model has been created to accurately predict whether the hospitalization duration of COVID-19 patients will be prolonged. This model incorporates serum WBC, ALB levels, age, and the presence of chronic respiratory system diseases.

Feature fusion method for pulmonary tuberculosis patient detection based on cough sound.

Since the COVID-19, cough sounds have been widely used for screening purposes. Intelligent analysis techniques have proven to be effective in detecting respiratory diseases. In 2021, there were up to 10 million TB-infected patients worldwide, with an annual growth rate of 4.5%. Most of the patients were from economically underdeveloped regions and countries. The PPD test, a common screening method in the community, has a sensitivity of as low as 77%. Although IGRA and Xpert MTB/RIF offer high specificity and sensitivity, their cost makes them less accessible. In this study, we proposed a feature fusion model-based cough sound classification method for primary TB screening in communities. Data were collected from hospitals using smart phones, including 230 cough sounds from 70 patients with TB and 226 cough sounds from 74 healthy subjects. We employed Bi-LSTM and Bi-GRU recurrent neural networks to analyze five traditional feature sets including the Mel frequency cepstrum coefficient (MFCC), zero-crossing rate (ZCR), short-time energy, root mean square, and chroma_cens. The incorporation of features extracted from the speech spectrogram by 2D convolution training into the Bi-LSTM model enhanced the classification results. With traditional futures, the best TB patient detection result was achieved with the Bi-LSTM model, with 93.99% accuracy, 93.93% specificity, and 92.39% sensitivity. When combined with a speech spectrogram, the classification results showed 96.33% accuracy, 94.99% specificity, and 98.13% sensitivity. Our findings underscore that traditional features and deep features have good complementarity when fused using Bi LSTM modelling, which outperforms existing PPD detection methods in terms of both efficiency and accuracy.

Efficient detection of nitric oxide a biomarker associated with COVID19 via N, P co-doped C60 fullerene: a computational study.

CONTEXT: Coronavirus (COVID-19) is a novel respiratory viral infection, causing a relatively large number of deaths especially in people who underly lung diseases such as chronic obstructive pulmonary and asthma, and humans are still suffering from the limited testing capacity. In this article, a solution is proposed for the detection of COVID-19 viral infections through the analysis of exhaled breath gasses, i.e., nitric oxide, a prominent biomarker released by respiratory epithelial, as a non-invasive and time-saving approach. Here, we designed a novel and low-cost N and P co-doped C60 fullerene-based breathalyzer for the detection of NO gas exhaled from the respiratory epithelial cells. This breathalyzer shows a quick response to the detection of NO gas by directly converting NO to NO2 without passing any energy barrier (0 kcal/mol activation energy). The recovery time of breathalyzer is very short (0.98 × 103 s), whereas it is highly selective for NO sensing in the mixture of CO2 and H2O gasses. The study provides an idea for the synthesis of low-cost (compared to previously reported Au atom decorated nanostructure and metal-based breathalyzer), efficient, and highly selective N and P co-doped C60 fullerene-based breathalyzer for COVID-19 detection. METHODS: The geometries of N and P-doped systems and gas molecules are simulated using spin-polarized density functional theory calculations.