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1.
Frontiers in Surgery ; 9, 2022.
Article in English | Web of Science | ID: covidwho-2109898

ABSTRACT

Background: Healthcare seeking behavior has been widely impacted due to the restricted movements of individuals during the Coronavirus disease-19 (COVID-19) pandemic. This study aims to perform risk stratification in patients requiring timely intervention during the recovery periods. Methods: Operation notes of acute appendicitis (AA) patients within a hospital were analyzed during three six-month periods (23 January-23 July in 2019, 2020, and 2021, respectively). Patient data were collected retrospectively including demographics, pre-emergency status, perioperative information, postoperative outcomes, and follow-up results. Results: 321 patients were included in this study, with 111, 86, and 124 patients in 2019, 2020, and 2021 groups, respectively. The median age of patients decreased by 4 years in 2020 as compared to that in 2019. The proportion of pre-hospitalization symptoms duration of more than 48 h in the 2020 group was higher (36.05% in 2020 vs. 22.52% in 2019). Length of hospital stay (LOS) in 2020 was shorter than it was during the same period in 2019 (4.77 vs. 5.64) and LOS in 2021 was shorter than in 2019 (4.13 vs. 5.64). Compared to the lockdown period, the proportion of patients with recurrent AA was higher in the post-lockdown period (15.1% vs. 27.4%). The median age was 34 years (vaccinated) vs. 37 years (unvaccinated). Logistic regression suggests that elevated C-reactive protein (CRP) (OR = 1.018, CI = 1.010-1.028), white cell count (WBC) (OR = 1.207, CI = 1.079-1.350), female (OR = 2.958, CI = 1.286-6.802), recurrent (OR = 3.865, CI = 1.149-12.997), and fecalith (OR = 2.308, CI = 1.007-5.289) were associated with complicated appendicitis (CA). Conclusion: The lockdown measures during the COVID-19 epidemic are shown to be correlated with a reduction in the proportion of AA patients who underwent surgery, particularly in older adults. Risk factors for CA include elevated CRP, WBC, female, recurrent, and fecalith.

2.
2022 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2022 ; 2022-August, 2022.
Article in English | Scopus | ID: covidwho-2107814

ABSTRACT

The Covid-19 pandemic has caused large scale of people in danger of infection and death during early outbreak period. Precise screening of the new coronal virus through PCR (Polymerase Chain Reaction) testing on the nasal or oral sample becomes very critical for epidemic control. This study proposes the idea of using a robotic remote manipulation platform for oral and nasal specimen collection operated by medical staffs. The oral cavity image was captured by a compact camera and then displayed on the human machine interface for the medical staffs to confirm the target region for sample collection. The wiping action of the robot was accomplished with a force control with force sensing the contact force between the cotton swab and soft tissue. A prototype of the swabbing robot has been implemented to verify the feasibility and safety of the remote robot-assisted specimen collection. © 2022 IEEE.

3.
Microbiol Spectr ; : e0392322, 2022 Nov 08.
Article in English | MEDLINE | ID: covidwho-2108239

ABSTRACT

In November 2021, the World Health Organization declared the Omicron variant (B.1.1.519) a variant of concern. Since then, worries have been expressed regarding the ability of usual diagnostic tests to detect the Omicron variant. In addition, some recently published data suggested that the salivary reverse transcription (RT)-PCR might perform better than the current gold standard, nasopharyngeal (NP) RT-PCR. In this study, we aimed to compare the sensitivities of nasopharyngeal and saliva RT-PCR and assess the diagnostic performances of rapid antigen testing (RAT) in nasopharyngeal and saliva samples. We conducted a prospective clinical study among symptomatic health care professionals consulting the occupational health service of our hospital for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) screening and hospitalized patients in internal medicine/intensive care wards screened for SARS-CoV-2 with COVID-19-compatible symptoms. A composite outcome considering NP PCR and/or saliva PCR was used as a reference standard to define COVID-19 cases. A total of 475 paired NP/saliva specimens have been collected with a positivity rate of 40% (n = 192). NP and salivary RT-PCR exhibited sensitivities of 98% (95% CI, 94 to 99%) and 87% (95% CI, 81 to 91%), respectively, for outpatients (n = 453) and 94% (95% CI, 72 to 99%) and 69% (95% CI, 44 to 86%), respectively, for hospitalized patients (n = 22). Nasopharyngeal rapid antigen testing exhibited much lower diagnostic performances (sensitivity of 66% and 31% for outpatients and inpatients, respectively), while saliva RAT showed a sensitivity of less than 5% in both groups. Nasopharyngeal RT-PCR testing remains the gold standard for SARS-CoV-2 Omicron variant screening. Salivary RT-PCR can be used as an alternative in case of contraindication to perform NP sampling. The use of RAT should be limited to settings where access to molecular diagnostic methods is lacking. IMPORTANCE The Omicron variant of concern spread rapidly since it was first reported in November 2021 and currently accounts for the vast majority of new infections worldwide. Recent reports suggest that saliva sampling might outweigh nasopharyngeal sampling for the diagnosis of the Omicron variant. Nevertheless, data investigating the best diagnostic strategy specifically for the Omicron variant of concern remain scarce. This study fills this gap in current knowledge and elucidates the question of which strategy to use in which patient. It provides a new basis for further improving COVID-19 screening programs and managing patients suspected to have COVID-19.

4.
Open Forum Infect Dis ; 9(11): ofac509, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2107552

ABSTRACT

Background: Rapid diagnostic and prognostic tests for coronavirus disease (COVID-19) are urgently required. We aimed to evaluate the diagnostic and prognostic ability of breath analysis using gas chromatography-ion mobility spectrometry (GC-IMS) in hospitalized patients with COVID-19. Methods: Between February and May 2021, we took 1 breath sample for analysis using GC-IMS from participants who were admitted to the hospital for COVID-19, participants who were admitted to the hospital for other respiratory infections, and symptom-free controls, at the University Hospitals of Leicester NHS Trust, United Kingdom. Demographic, clinical, and radiological data, including requirement for continuous positive airway pressure (CPAP) ventilation as a marker for severe disease in the COVID-19 group, were collected. Results: A total of 113 participants were recruited into the study. Seventy-two (64%) were diagnosed with COVID-19, 20 (18%) were diagnosed with another respiratory infection, and 21 (19%) were healthy controls. Differentiation between participants with COVID-19 and those with other respiratory tract infections with GC-IMS was highly accurate (sensitivity/specificity, 0.80/0.88; area under the receiver operating characteristics curve [AUROC], 0.85; 95% CI, 0.74-0.96). GC-IMS was also moderately accurate at identifying those who subsequently required CPAP (sensitivity/specificity, 0.62/0.80; AUROC, 0.70; 95% CI, 0.53-0.87). Conclusions: GC-IMS shows promise as both a diagnostic tool and a predictor of prognosis in hospitalized patients with COVID-19 and should be assessed further in larger studies.

5.
Healthcare (Basel) ; 10(10)2022 Sep 28.
Article in English | MEDLINE | ID: covidwho-2110001

ABSTRACT

Within the ever-growing healthcare industry, dental informatics is a burgeoning field of study. One of the major obstacles to the health care system's transformation is obtaining knowledge and insightful data from complex, high-dimensional, and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, heterogeneous, poorly documented, and generally unstructured electronic health records, imaging, sensor data, and text. There were still certain restrictions even after many current techniques were used to extract more robust and useful elements from the data for analysis. New effective paradigms for building end-to-end learning models from complex data are provided by the most recent deep learning technology breakthroughs. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for dental informatics problems and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to some drawbacks and the need for better technique development and provide new perspectives about this exciting new development in the field.

6.
Diagnostics (Basel) ; 12(11)2022 Nov 09.
Article in English | MEDLINE | ID: covidwho-2109978

ABSTRACT

In this paper, we propose a new Modified Laplacian Vector Median Filter (MLVMF) for real-time denoising complex images corrupted by "salt and pepper" impulsive noise. The method consists of two rounds with three steps each: the first round starts with the identification of pixels that may be contaminated by noise using a Modified Laplacian Filter. Then, corrupted pixels pass a neighborhood-based validation test. Finally, the Vector Median Filter is used to replace noisy pixels. The MLVMF uses a 5 × 5 window to observe the intensity variations around each pixel of the image with a rotation step of π/8 while the classic Laplacian filters often use rotation steps of π/2 or π/4. We see better identification of noise-corrupted pixels thanks to this rotation step refinement. Despite this advantage, a high percentage of the impulsive noise may cause two or more corrupted pixels (with the same intensity) to collide, preventing the identification of noise-corrupted pixels. A second round is then necessary using a second set of filters, still based on the Laplacian operator, but allowing focusing only on the collision phenomenon. To validate our method, MLVMF is firstly tested on standard images, with a noise percentage varying from 3% to 30%. Obtained performances in terms of processing time, as well as image restoration quality through the PSNR (Peak Signal to Noise Ratio) and the NCD (Normalized Color Difference) metrics, are compared to the performances of VMF (Vector Median Filter), VMRHF (Vector Median-Rational Hybrid Filter), and MSMF (Modified Switching Median Filter). A second test is performed on several noisy chest x-ray images used in cardiovascular disease diagnosis as well as COVID-19 diagnosis. The proposed method shows a very good quality of restoration on this type of image, particularly when the percentage of noise is high. The MLVMF provides a high PSNR value of 5.5% and a low NCD value of 18.2%. Finally, an optimized Field-Programmable Gate Array (FPGA) design is proposed to implement the proposed method for real-time processing. The proposed hardware implementation allows an execution time equal to 9 ms per 256 × 256 color image.

8.
Front Med (Lausanne) ; 9: 1016008, 2022.
Article in English | MEDLINE | ID: covidwho-2109789
9.
OpenNano ; : 100104, 2022.
Article in English | ScienceDirect | ID: covidwho-2105672

ABSTRACT

Early diagnosis is essential for effective illness treatment, but traditional diagnostic approaches inevitably have major downsides. Recent advancements in nanoparticle-based biosensors have created new opportunities for accelerating diagnosis. High surface area, exceptional sensitivity, high specificity, and optical characteristics of metal and metal oxide nanoparticles have made it possible to detect a variety of health conditions and diseases immediately, including cancer, viral infection, biomarkers, and in-vivo imaging. Metal nanoparticles may be produced in a variety of ways, enabling the creation of innovative tools for chemical and biological sensing targets. The utilization of various metal nano-formulations, metal oxide nanoplatforms, and their composites in the early identification of illnesses is reported and summarized in this review. Additionally, the challenging corners in the use of metal oxide-based nano-scale diagnostic technologies in clinical applications are highlighted. The current work is believed to serve as a roadmap for in-depth research on inorganic nanomedicine, both in-vitro and in-vivo diagnosis of diseases and illnesses, especially pandemic infections like COVID-19.

10.
Microelectronic Engineering ; : 111912, 2022.
Article in English | ScienceDirect | ID: covidwho-2105585

ABSTRACT

COVID-19 has spread worldwide, and early detection has been the key to controlling its propagation and preventing severe cases. However, diagnostic devices must be developed using different strategies, to avoid a shortage of supplies needed for tests' fabrication caused by their large demand in pandemic situations. Furthermore, some tropical and subtropical countries are also facing epidemics of Dengue and Zika, viruses with similar symptoms in early stages, and cross-reactivity with serological tests. Herein, we reported a qualitative immunosensor based on capacitive detection of spike proteins of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19. The sensor device exhibited a good signal-to-noise ratio (SNR), in 1 kHz frequency, with an absolute value of capacitance variation significantly smaller for Dengue and Zika NS1 proteins (;ΔC; = 1.5 ± 1.0 nF and 1.8 ± 1.0 nF, respectively) than for the spike protein (;ΔC; = 7.0 ± 1.8 nF). Under the optimized conditions, the established biosensor is able to indicate that the sample contains target proteins when ;ΔC; > 3.8 nF, as determined by the cut-off value (CO). This immunosensor was developed using interdigitated electrodes which require a measurement system with a simple electrical circuit that can be miniaturized to enable point-of-care detection, offering an alternative for COVID-19 diagnosis, especially in areas where there is also a co-incidence of Zika and Dengue.

11.
Gene Rep ; 20: 100756, 2020 Sep.
Article in English | MEDLINE | ID: covidwho-2104964

ABSTRACT

The new SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) belongs to the family of coronaviruses, and it is a new strain of coronavirus that has not been previously identified in humans. It causes a contagious disease, which affects the respiratory system and can lead to severe complications in some cases. This virus was detected in China, then rapidly spread to almost all countries. Because of their complexity and the malignancy of the symptoms, they remain a center of interest for researchers. Herein, we provide a review in terms of transmission, clinical presentation, diagnosis, and treatment options in clinical trials of COVID-19 (coronavirus disease 2019), because readers need to update themselves regularly, and there is still much more to know about it.

12.
J Breath Res ; 17(1)2022 11 24.
Article in English | MEDLINE | ID: covidwho-2107282

ABSTRACT

The spread of coronavirus disease 2019 (COVID-19) results in an increasing incidence and mortality. The typical diagnosis technique for severe acute respiratory syndrome coronavirus 2 infection is reverse transcription polymerase chain reaction, which is relatively expensive, time-consuming, professional, and suffered from false-negative results. A reliable, non-invasive diagnosis method is in urgent need for the rapid screening of COVID-19 patients and controlling the epidemic. Here we constructed an intelligent system based on the volatile organic compound (VOC) biomarkers in human breath combined with machine learning models. The VOC profiles of 122 breath samples (65 of COVID-19 infections and 57 of controls) were identified with a portable gas chromatograph-mass spectrometer. Among them, eight VOCs exhibited significant differences (p< 0.001) between the COVID-19 and the control groups. The cross-validation algorithm optimized support vector machine (SVM) model was employed for the prediction of COVID-19 infection. The proposed SVM model performed a powerful capability in discriminating COVID-19 patients from healthy controls, with an accuracy of 97.3%, a sensitivity of 100%, a specificity of 94.1%, and a precision of 95.2%, and anF1 score of 97.6%. The SVM model was also compared with other common machine models, including artificial neural network,k-nearest neighbor, and logistic regression, and demonstrated obvious superiority in the prediction of COVID-19 infection. Furthermore, user-friendly software was developed based on the optimized SVM model. The developed intelligent platform based on breath analysis provides a new strategy for the point-of-care screening of COVID and shows great potential in clinical application.


Subject(s)
COVID-19 , Volatile Organic Compounds , Humans , Breath Tests/methods , Volatile Organic Compounds/analysis , Support Vector Machine , Biomarkers/analysis
13.
J Allergy Clin Immunol ; 150(5): 1059-1073, 2022 11.
Article in English | MEDLINE | ID: covidwho-2105179

ABSTRACT

BACKGROUND: Most severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals are asymptomatic or only exhibit mild disease. In about 10% of cases, the infection leads to hypoxemic pneumonia, although it is much more rare in children. OBJECTIVE: We evaluated 31 young patients aged 0.5 to 19 years who had preexisting inborn errors of immunity (IEI) but lacked a molecular diagnosis and were later diagnosed with coronavirus disease 2019 (COVID-19) complications. METHODS: Genetic evaluation by whole-exome sequencing was performed in all patients. SARS-CoV-2-specific antibodies, autoantibodies against type I IFN (IFN-I), and inflammatory factors in plasma were measured. We also reviewed COVID-19 disease severity/outcome in reported IEI patients. RESULTS: A potential genetic cause of the IEI was identified in 28 patients (90.3%), including mutations that may affect IFN signaling, T- and B-cell function, the inflammasome, and the complement system. From tested patients 65.5% had detectable virus-specific antibodies, and 6.8% had autoantibodies neutralizing IFN-I. Five patients (16.1%) fulfilled the diagnostic criteria of multisystem inflammatory syndrome in children. Eleven patients (35.4%) died of COVID-19 complications. All together, at least 381 IEI children with COVID-19 have been reported in the literature to date. Although many patients with asymptomatic or mild disease may not have been reported, severe presentation of COVID-19 was observed in 23.6% of the published cases, and the mortality rate was 8.7%. CONCLUSIONS: Young patients with preexisting IEI may have higher mortality than children without IEI when infected with SARS-CoV-2. Elucidating the genetic basis of IEI patients with severe/critical COVID-19 may help to develop better strategies for prevention and treatment of severe COVID-19 disease and complications in pediatric patients.


Subject(s)
COVID-19 , Humans , Child , COVID-19/genetics , SARS-CoV-2 , Antibodies, Viral , Autoantibodies
14.
Comput Biol Med ; 150: 106165, 2022 Oct 05.
Article in English | MEDLINE | ID: covidwho-2104646

ABSTRACT

OBJECTIVE: To develop a two-step machine learning (ML) based model to diagnose and predict involvement of lungs in COVID-19 and non COVID-19 pneumonia patients using CT chest radiomic features. METHODS: Three hundred CT scans (3-classes: 100 COVID-19, 100 pneumonia, and 100 healthy subjects) were enrolled in this study. Diagnostic task included 3-class classification. Severity prediction score for COVID-19 and pneumonia was considered as mild (0-25%), moderate (26-50%), and severe (>50%). Whole lungs were segmented utilizing deep learning-based segmentation. Altogether, 107 features including shape, first-order histogram, second and high order texture features were extracted. Pearson correlation coefficient (PCC≥90%) followed by different features selection algorithms were employed. ML-based supervised algorithms (Naïve Bays, Support Vector Machine, Bagging, Random Forest, K-nearest neighbors, Decision Tree and Ensemble Meta voting) were utilized. The optimal model was selected based on precision, recall and area-under-curve (AUC) by randomizing the training/validation, followed by testing using the test set. RESULTS: Nine pertinent features (2 shape, 1 first-order, and 6 second-order) were obtained after features selection for both phases. In diagnostic task, the performance of 3-class classification using Random Forest was 0.909±0.026, 0.907±0.056, 0.902±0.044, 0.939±0.031, and 0.982±0.010 for precision, recall, F1-score, accuracy, and AUC, respectively. The severity prediction task using Random Forest achieved 0.868±0.123 precision, 0.865±0.121 recall, 0.853±0.139 F1-score, 0.934±0.024 accuracy, and 0.969±0.022 AUC. CONCLUSION: The two-phase ML-based model accurately classified COVID-19 and pneumonia patients using CT radiomics, and adequately predicted severity of lungs involvement. This 2-steps model showed great potential in assessing COVID-19 CT images towards improved management of patients.

15.
Comput Biol Med ; 150: 106149, 2022 Sep 29.
Article in English | MEDLINE | ID: covidwho-2104645

ABSTRACT

The diagnosis of Coronavirus Disease 2019 (COVID-19) exploiting machine learning algorithms based on chest computed tomography (CT) images has become an important technology. Though many excellent computer-aided methods leveraging CT images have been designed, they do not possess sufficiently high recognition accuracy. Besides, these methods entail vast amounts of training data, which might be difficult to be satisfied in some real-world applications. To address these two issues, this paper proposes a novel COVID-19 recognition system based on CT images, which has high recognition accuracy, while only requiring a small amount of training data. Specifically, the system possesses the following three improvements: 1) Data: a novel redesigned BCELoss that incorporates Label Smoothing, Focal Loss, and Label Weighting Regularization (LSFLLW-R) technique for optimizing the solution space and preventing overfitting, 2) Model: a backbone network processed by two-phase contrastive self-supervised learning for classifying multiple labels, and 3) Method: a decision-fusing ensemble learning method for getting a more stable system, with balanced metric values. Our proposed system is evaluated on the small-scale expanded COVID-CT dataset, achieving an accuracy of 94.3%, a precision of 94.1%, a recall (sensitivity) of 93.4%, an F1-score of 94.7%, and an Area Under the Curve (AUC) of 98.9%, for COVID-19 diagnosis, respectively. These experimental results verify that our system can not only identify pathological locations effectively, but also achieve better performance in terms of accuracy, generalizability, and stability, compared with several other state-of-the-art COVID-19 diagnosis methods.

16.
Clin Microbiol Infect ; 2022 Nov 11.
Article in English | MEDLINE | ID: covidwho-2104617

ABSTRACT

OBJECTIVES: We aimed to investigate the real-life performance of the rapid antigen test (RAT) in the context of a primary healthcare setting, including symptomatic and asymptomatic individuals that sought diagnostic during a Omicron infection wave. METHODS: We prospectively accessed the performance of the DPP® SARS-CoV-2 Antigen test in the context of an omicron-dominant real-life setting. We evaluated 347 unselected individuals (all-comers) from a public testing center in Brazil, performing the RAT diagnosis at point-of-care with fresh samples. The combinatory result from two distinct RT-qPCR methods was employed as reference and 13 samples with discordant PCR results were excluded. RESULTS: The assessment of the rapid test in 67 PCR-positive and 265 negative samples revealed an overall sensitivity of 80.5% (CI95% = 69.1 - 89.2%), specificity of 99.2% (CI95% = 97.3 - 99.1%) and positive/negative predictive values higher than 95%. However, we observed that the sensitivity was dependent on the viral load (sensitivity in Ct<31 = 93.7%, CI = 82.8 - 98.7%; Ct>31 = 47.4%, CI = 24.4 - 71.1%). The positive samples evaluated in the study were Omicron (BA.1/BA.1.1) by whole-genome sequencing (n=40) and multiplex RT-qPCR (n=17). CONCLUSIONS: Altogether, the data obtained from a real-life prospective cohort supports that the RAT sensitivity for Omicron remains high and underscores the reliability of the test for COVID-19 diagnosis in settings with high disease prevalence and limited PCR testing capability.

17.
Laryngoscope Investigative Otolaryngology ; 2022.
Article in English | Web of Science | ID: covidwho-2103661

ABSTRACT

Objectives An increased incidence of acute invasive fungal sinusitis associated with the recent COVID-19 pandemic has been observed, which is considered a public health concern. This study aims to detect the incidence, risk factors, causative agents, clinical presentations, outcomes, and susceptibility rate of various antifungals. Methods In this cross-sectional cohort study, a total of 30 patients showing acute invasive fungal rhinosinusitis following a COVID-19 infection were investigated. Histopathological biopsies, culture identification, and molecular confirmation of the causative agents were conducted. The demographic data, risk factors, clinical presentations, treatment regimen and its outcomes, and efficacy of antifungals were listed and analyzed. Results A total of 30 cases with a mean age of 59.6 +/- 11.9 years were included. Diabetes mellitus was the most recorded comorbidity with a rate of 86.7%, whereas most of the patients received corticosteroids. The mycological examination confirmed the existence of Mucor (Rhizopus oryzae) and Aspergillus (Aspergillus niger) in 96.7% and 3.3% of the cases, respectively. Various stages of sinonasal involvement (ethmoid, maxillary, sphenoid, and inferior turbinate) represented 100%, 83.3%, 66.7%, and 86.7% of the cases, respectively. Headache and facial pain, ophthalmoplegia, visual loss, and blindness represented 100%, 66.7%, 90%, and 53.3% of the cases, respectively. All the cases were simultaneously treated with surgical debridement and amphotericin B. Moreover, R. oryzae was susceptible to it, whereas A. niger was sensitive to voriconazole, resulting in a survival rate of 86.7% (26/30). The R. oryzae and A. niger isolates were proven to be sensitive to acetic acid, ethyl alcohol, formalin, and isopropyl alcohol. Conclusions In patients with COVID-19, the diagnosis of acute invasive fungal sinusitis and prompt treatment with antifungal medicine and surgical debridement are important in achieving better outcomes and survival rates. Level of Evidence 4

18.
Infect Dis Ther ; 2022 Nov 04.
Article in English | MEDLINE | ID: covidwho-2104150

ABSTRACT

INTRODUCTION: In the current COVID-19 pandemic, clinicians require a manageable set of decisive parameters that can be used to (i) rapidly identify SARS-CoV-2 positive patients, (ii) identify patients with a high risk of a fatal outcome on hospital admission, and (iii) recognize longitudinal warning signs of a possible fatal outcome. METHODS: This comparative study was performed in 515 patients in the Maria Sklodowska-Curie Specialty Voivodeship Hospital in Zgierz, Poland. The study groups comprised 314 patients with COVID-like symptoms who tested negative and 201 patients who tested positive for SARS-CoV-2 infection; of the latter, 72 patients with COVID-19 died and 129 were released from hospital. Data on which we trained several machine learning (ML) models included clinical findings on admission and during hospitalization, symptoms, epidemiological risk, and reported comorbidities and medications. RESULTS: We identified a set of eight on-admission parameters: white blood cells, antibody-synthesizing lymphocytes, ratios of basophils/lymphocytes, platelets/neutrophils, and monocytes/lymphocytes, procalcitonin, creatinine, and C-reactive protein. The medical decision tree built using these parameters differentiated between SARS-CoV-2 positive and negative patients with up to 90-100% accuracy. Patients with COVID-19 who on hospital admission were older, had higher procalcitonin, C-reactive protein, and troponin I levels together with lower hemoglobin and platelets/neutrophils ratio were found to be at highest risk of death from COVID-19. Furthermore, we identified longitudinal patterns in C-reactive protein, white blood cells, and D dimer that predicted the disease outcome. CONCLUSIONS: Our study provides sets of easily obtainable parameters that allow one to assess the status of a patient with SARS-CoV-2 infection, and the risk of a fatal disease outcome on hospital admission and during the course of the disease.

19.
J Maxillofac Oral Surg ; : 1-9, 2022 Nov 01.
Article in English | MEDLINE | ID: covidwho-2104136

ABSTRACT

Aim: To perform site-based comparative analysis for samples collected from the nasal region and oral cavity subjected to microscopic detection of fungal hyphae in KOH mount in a group of patients with rhinomaxillary mucormycosis. Methodology: Forty patients fulfilled eligibility criteria. The diagnostic outcome of detection of fungal hyphae from the KOH samples obtained was the primary endpoint of the study. Based on this, the samples were grouped into three groups viz-oral, nasal and both. The secondary outcome was to check if there was any diagnostic delay in these three groups of patients. Results: The mean number of days for delayed diagnosis for oral site involvement was 56.33 ± 37.53, for nasal involvement was 32.86 ± 19.53 and for both oral and nasal involvement was 22.00 ± 12.94. This difference was statistically significant at p = 0.03. The mean delay in diagnosis was significantly less when both oral and nasal regions are involved as compared to the only oral region involved at P = 0.01. Conclusion: To avoid the chance of delayed diagnosis or false-negative results, it is best to collect samples from both nasal tissues and the most representative site in the dentoalveolar segment depending on the extensiveness of the disease.

20.
Rev Med Virol ; : e2404, 2022 Nov 04.
Article in English | MEDLINE | ID: covidwho-2103712

ABSTRACT

The multi-country outbreak of monkeypox virus (MPXV) infection, while the coronavirus disease 2019 pandemic is still an ongoing issue, has caused a new challenge. The re-emergence of MPXV and the rising incidence in non-endemic countries is turning into an upcoming threat to global health. Hence, rapid identification of the virus with appropriate methodology with the lowest false results plays a critical role in estimating the global extent of the crisis and providing preventive measures. This review summarised the main applicable strategies for primary detection and confirmation of MPXV and highlighted available data in biosafety, requirements, standard operating procedures, specimen collection, transportation and storage of clinical samples, and waste disposal of the viral agent. Also, various assays including molecular techniques, immunoassays, histopathological methods, electron microscopy, genomic sequencing, and cell culture have been illustrated. Moreover, we reflected on current knowledge of the advantages and disadvantages of each approach.

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