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1.
J Clin Psychiatry ; 82(1)2020 12 08.
Article in English | MEDLINE | ID: covidwho-2066784

ABSTRACT

OBJECTIVE: To assess the prevalence of and risk factors for posttraumatic stress disorder (PTSD) in patients with COVID-19. METHODS: We conducted a cohort study between March and May 2020 at the Lille University Hospital (France), including all patients with laboratory-confirmed COVID-19. Psychological distress symptoms were measured 3 weeks after onset of COVID-19 symptoms using the Impact of Event Scale-6 items (IES-6). The evaluation of PTSD symptoms using the PTSD Checklist for DSM-5 (PCL-5) took place 1 month later. Bivariate analyses were performed to analyze the relationship between PCL-5 scores and the demographic and health variables. The significant variables were then introduced into a multivariable linear regression analysis to establish their relative contributions to the severity of PTSD symptoms. RESULTS: 180 patients were included in this study, and 138 patients completed the 2 evaluations. Among the 180 patients, 70.4% patients required hospitalization, and 30.7% were admitted to the intensive care unit. The prevalence of PTSD was 6.5%, and the predictive factors of PTSD included psychological distress at the onset of the illness and a stay in an intensive care unit. CONCLUSIONS: The prevalence of PTSD in patients with COVID-19 is not as high as that reported among patients during previous epidemics. Initial psychological responses were predictive of a PTSD diagnosis, even though most patients showing acute psychological distress (33.5% of the sample) improved in the following weeks. PTSD symptoms also increased following a stay in an intensive care unit. Future studies should assess the long-term consequences of COVID-19 on patients' mental health.


Subject(s)
COVID-19 , Hospitalization/statistics & numerical data , Intensive Care Units/statistics & numerical data , Psychological Distress , Stress Disorders, Post-Traumatic , Acute Disease , Adult , Aged , Aged, 80 and over , COVID-19/complications , COVID-19/epidemiology , COVID-19/psychology , COVID-19/therapy , Female , Follow-Up Studies , France/epidemiology , Humans , Male , Middle Aged , Prevalence , Severity of Illness Index , Stress Disorders, Post-Traumatic/diagnosis , Stress Disorders, Post-Traumatic/epidemiology , Stress Disorders, Post-Traumatic/etiology
2.
Salud Publica Mex ; 63(2, Mar-Abr): 160-162, 2021 Feb 27.
Article in Spanish | MEDLINE | ID: covidwho-1272146

ABSTRACT

OBJECTIVE: To describe a Covid-19 outbreak in a gerontological center in Mexico City. MATERIAL AND METHODS: Cross-sectional study in older adults. The association of risk factors for dying from Covid-19 was analyzed using a multiple logistic regression model. RESULTS: One hundred and two elders with an average age of 82.5 ± 8.8 years were included. Fifty-five (54%) tested positive and 47 (46%) were negative for the new coronavirus. Using the multiple logistic regression model, people with frailty had an OR of 11.6 of dying from Covid-19 compared to robust people (p-value = 0.024). CONCLUSION: The Covid-19 outbreak was initially caused by a resident of the center and spread by cross infection. In vulnerable populations, early detection, isolation, and follow-up of contacts should be carried out, as well as the identification of risk factors in order to reduce the spread and mortality caused by SARSCoV-2.


Subject(s)
COVID-19/epidemiology , Disease Outbreaks , Homes for the Aged , Aged , Aged, 80 and over , Cross-Sectional Studies , Female , Humans , Male , Mexico
3.
Sex Disabil ; 40(1): 3-20, 2022.
Article in English | MEDLINE | ID: covidwho-1881511

ABSTRACT

Multiple Sclerosis (MS) is a neurological condition which usually manifests between the ages of 20-40 years. This is a critical period for developing relationships, particularly romantic relationships. People with MS can experience sexual dysfunction, limb weakness, fatigue, pain, reduced mood and bladder/bowel dysfunction; potentially affecting their ability to participate in many meaningful activities, including those associated with romantic relationships, dating or engaging in sexual intercourse. Dating or starting romantic relationships can be difficult for people with physical disabilities as they can experience stigma, negative societal attitudes and the fear of requiring care from potential partners. Dating experiences of people with progressive conditions like MS have not been explored in detail. The aim of this study was to develop a rich understanding of how living with MS interacts with/influences dating and developing romantic relationships. The study used a descriptive phenomenological design and a purposive sampling strategy. Colaizzi's descriptive phenomenological method was used to analyze the data (Colaizzi, 1978). Five females and two males, aged 23-51, participated in two online focus groups. Dating with a diagnosis of MS is a highly personal phenomenon, characterized by individual differences in values and experiences. Core to the phenomenon was personal decision-making about disclosure of the diagnosis and ongoing adaptation to the fluctuating nature of the condition with partners in new/developing relationships. The findings will help health professionals working with adults with MS understand this important aspect of their lives.

4.
Crit Care Explor ; 2(6): e0154, 2020 Jun.
Article in English | MEDLINE | ID: covidwho-1795093

ABSTRACT

OBJECTIVE: As the severe acute respiratory syndrome-coronavirus-2 pandemic develops, assays to detect the virus and infection caused by it are needed for diagnosis and management. To describe to clinicians how each assay is performed, what each assay detects, and the benefits and limitations of each assay. DATA SOURCES: Published literature and internet. STUDY SELECTION: As well done, relevant and recent as possible. DATA EXTRACTION: Sources were read to extract data from them. DATA SYNTHESIS: Was synthesized by all coauthors. CONCLUSIONS: Available assays test for current or previous severe acute respiratory syndrome-coronavirus-2 infection. Nucleic acid assays such as quantitative, or real-time, polymerase chain reaction and loop-mediated isothermal amplification are ideal for acute diagnosis with polymerase chain reaction testing remaining the "gold standard" to diagnose acute infection by severe acute respiratory syndrome-coronavirus-2, specifically the presence of viral RNA. Assays that detect serum antibodies can theoretically diagnose both acute and remote infection but require time for the patient to develop immunity and may detect nonspecific antibodies. Antibody assays that quantitatively measure neutralizing antibodies are needed to test efficacy of convalescent plasma therapy but are more specialized.

5.
Nat Med ; 26(6): 845-848, 2020 06.
Article in English | MEDLINE | ID: covidwho-1641979

ABSTRACT

We report acute antibody responses to SARS-CoV-2 in 285 patients with COVID-19. Within 19 days after symptom onset, 100% of patients tested positive for antiviral immunoglobulin-G (IgG). Seroconversion for IgG and IgM occurred simultaneously or sequentially. Both IgG and IgM titers plateaued within 6 days after seroconversion. Serological testing may be helpful for the diagnosis of suspected patients with negative RT-PCR results and for the identification of asymptomatic infections.


Subject(s)
Antibodies, Viral/blood , Antibody Formation/drug effects , Betacoronavirus/pathogenicity , Coronavirus Infections/drug therapy , Pneumonia, Viral/drug therapy , Adult , Aged , Antibody Formation/immunology , Antiviral Agents/therapeutic use , Betacoronavirus/genetics , COVID-19 , Coronavirus Infections/blood , Coronavirus Infections/immunology , Coronavirus Infections/virology , Female , Humans , Immunoglobulin G/blood , Immunoglobulin M/blood , Male , Middle Aged , Pandemics/prevention & control , Pneumonia, Viral/blood , Pneumonia, Viral/immunology , Pneumonia, Viral/virology , SARS-CoV-2
6.
Clin Infect Dis ; 73(12): 2217-2225, 2021 12 16.
Article in English | MEDLINE | ID: covidwho-1595231

ABSTRACT

BACKGROUND: We investigated patients with potential severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection in the United States during May-July 2020. METHODS: We conducted case finding for patients with potential SARS-CoV-2 reinfection through the Emerging Infections Network. Cases reported were screened for laboratory and clinical findings of potential reinfection followed by requests for medical records and laboratory specimens. Available medical records were abstracted to characterize patient demographics, comorbidities, clinical course, and laboratory test results. Submitted specimens underwent further testing, including reverse transcription polymerase chain reaction (RT-PCR), viral culture, whole genome sequencing, subgenomic RNA PCR, and testing for anti-SARS-CoV-2 total antibody. RESULTS: Among 73 potential reinfection patients with available records, 30 patients had recurrent coronavirus disease 2019 (COVID-19) symptoms explained by alternative diagnoses with concurrent SARS-CoV-2 positive RT-PCR, 24 patients remained asymptomatic after recovery but had recurrent or persistent RT-PCR, and 19 patients had recurrent COVID-19 symptoms with concurrent SARS-CoV-2 positive RT-PCR but no alternative diagnoses. These 19 patients had symptom recurrence a median of 57 days after initial symptom onset (interquartile range: 47-76). Six of these patients had paired specimens available for further testing, but none had laboratory findings confirming reinfections. Testing of an additional 3 patients with recurrent symptoms and alternative diagnoses also did not confirm reinfection. CONCLUSIONS: We did not confirm SARS-CoV-2 reinfection within 90 days of the initial infection based on the clinical and laboratory characteristics of cases in this investigation. Our findings support current Centers for Disease Control and Prevention (CDC) guidance around quarantine and testing for patients who have recovered from COVID-19.


Subject(s)
COVID-19 , SARS-CoV-2 , Antibodies, Viral , Humans , Laboratories , Reinfection
7.
J Med Internet Res ; 23(2): e22841, 2021 02 23.
Article in English | MEDLINE | ID: covidwho-1574897

ABSTRACT

BACKGROUND: Misdiagnosis, arbitrary charges, annoying queues, and clinic waiting times among others are long-standing phenomena in the medical industry across the world. These factors can contribute to patient anxiety about misdiagnosis by clinicians. However, with the increasing growth in use of big data in biomedical and health care communities, the performance of artificial intelligence (Al) techniques of diagnosis is improving and can help avoid medical practice errors, including under the current circumstance of COVID-19. OBJECTIVE: This study aims to visualize and measure patients' heterogeneous preferences from various angles of AI diagnosis versus clinicians in the context of the COVID-19 epidemic in China. We also aim to illustrate the different decision-making factors of the latent class of a discrete choice experiment (DCE) and prospects for the application of AI techniques in judgment and management during the pandemic of SARS-CoV-2 and in the future. METHODS: A DCE approach was the main analysis method applied in this paper. Attributes from different dimensions were hypothesized: diagnostic method, outpatient waiting time, diagnosis time, accuracy, follow-up after diagnosis, and diagnostic expense. After that, a questionnaire is formed. With collected data from the DCE questionnaire, we apply Sawtooth software to construct a generalized multinomial logit (GMNL) model, mixed logit model, and latent class model with the data sets. Moreover, we calculate the variables' coefficients, standard error, P value, and odds ratio (OR) and form a utility report to present the importance and weighted percentage of attributes. RESULTS: A total of 55.8% of the respondents (428 out of 767) opted for AI diagnosis regardless of the description of the clinicians. In the GMNL model, we found that people prefer the 100% accuracy level the most (OR 4.548, 95% CI 4.048-5.110, P<.001). For the latent class model, the most acceptable model consists of 3 latent classes of respondents. The attributes with the most substantial effects and highest percentage weights are the accuracy (39.29% in general) and expense of diagnosis (21.69% in general), especially the preferences for the diagnosis "accuracy" attribute, which is constant across classes. For class 1 and class 3, people prefer the AI + clinicians method (class 1: OR 1.247, 95% CI 1.036-1.463, P<.001; class 3: OR 1.958, 95% CI 1.769-2.167, P<.001). For class 2, people prefer the AI method (OR 1.546, 95% CI 0.883-2.707, P=.37). The OR of levels of attributes increases with the increase of accuracy across all classes. CONCLUSIONS: Latent class analysis was prominent and useful in quantifying preferences for attributes of diagnosis choice. People's preferences for the "accuracy" and "diagnostic expenses" attributes are palpable. AI will have a potential market. However, accuracy and diagnosis expenses need to be taken into consideration.


Subject(s)
Artificial Intelligence , Diagnosis , Patient Preference , Physicians , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19 , China , Choice Behavior , Diagnostic Techniques and Procedures/economics , Female , Health Expenditures , Humans , Latent Class Analysis , Logistic Models , Male , Middle Aged , Pandemics , SARS-CoV-2 , Surveys and Questionnaires , Time Factors , Young Adult
8.
Surg Endosc ; 35(12): 6532-6538, 2021 12.
Article in English | MEDLINE | ID: covidwho-1530321

ABSTRACT

BACKGROUND: This study was aimed to develop a computer-aided diagnosis (CAD) system with deep-learning technique and to validate its efficiency on detecting the four categories of lesions such as polyps, advanced cancer, erosion/ulcer and varices at endoscopy. METHODS: A deep convolutional neural network (CNN) that consists of more than 50 layers were trained with a big dataset containing 327,121 white light images (WLI) of endoscopy from 117,005 cases collected from 2012 to 2017. Two CAD models were developed using images with or without annotation of the training dataset. The efficiency of the CAD system detecting the four categories of lesions was validated by another dataset containing consecutive cases from 2018 to 2019. RESULTS: A total of 1734 cases with 33,959 images were included in the validation datasets which containing lesions of polyps 1265, advanced cancer 500, erosion/ulcer 486, and varices 248. The CAD system developed in this study may detect polyps, advanced cancer, erosion/ulcer and varices as abnormality with the sensitivity of 88.3% and specificity of 90.3%, respectively, in 0.05 s. The training datasets with annotation may enhance either sensitivity or specificity about 20%, p = 0.000. The sensitivities and specificities for polyps, advanced cancer, erosion/ulcer and varices reached about 90%, respectively. The detect efficiency for the four categories of lesions reached to 89.7%. CONCLUSION: The CAD model for detection of multiple lesions in gastrointestinal lumen would be potentially developed into a double check along with real-time assessment and interpretation of the findings encountered by the endoscopists and may be a benefit to reduce the events of missing lesions.


Subject(s)
Artificial Intelligence , Neural Networks, Computer , Endoscopy, Gastrointestinal , Gastrointestinal Tract , Humans , Pilot Projects
9.
J Clin Microbiol ; 59(10): e0236020, 2021 09 20.
Article in English | MEDLINE | ID: covidwho-1486498

ABSTRACT

Efforts to control transmissible infectious diseases rely on the ability to screen large populations, ideally in community settings. These efforts can be limited by the requirement for invasive or logistically difficult collection of patient samples, such as blood, urine, stool, sputum, and nasopharyngeal swabs. Oral sampling is an appealing, noninvasive alternative that could greatly facilitate high-throughput sampling in community settings. Oral sampling has been described for the detection of dozens of human pathogens, including pathogens whose primary sites of infection are outside of the oral cavity, such as the respiratory pathogens Mycobacterium tuberculosis and SARS-CoV-2. Oral sampling can demonstrate active infections as well as resolving or previous infections, the latter through the detection of antibodies. Its potential applications are diverse, including improved diagnosis in special populations (e.g., children), population surveillance, and infectious disease screening. In this minireview, we address the use of oral samples for the detection of diseases that primarily manifest outside the oral cavity. Focusing on well-supported examples, we describe applications for such methods and highlight their potential advantages and limitations in medicine, public health, and research.


Subject(s)
COVID-19 , Communicable Diseases , Child , Communicable Diseases/diagnosis , Humans , SARS-CoV-2 , Specimen Handling , Sputum
10.
Int J Mol Sci ; 22(11)2021 May 31.
Article in English | MEDLINE | ID: covidwho-1477958

ABSTRACT

SARS-CoV-2/Coronavirus 2019 (COVID-19) is responsible for the pandemic, which started in December 2019. In addition to the typical respiratory symptoms, this virus also causes other severe complications, including neurological ones. In diagnostics, serological and polymerase chain reaction tests are useful not only in detecting past infections but can also predict the response to vaccination. It is now believed that an immune mechanism rather than direct viral neuroinvasion is responsible for neurological symptoms. For this reason, it is important to assess the presence of antibodies not only in the serum but also in the cerebrospinal fluid (CSF), especially in the case of neuro-COVID. A particular group of patients are people with multiple sclerosis (MS) whose disease-modifying drugs weaken the immune system and lead to an unpredictable serological response to SARS-CoV-2 infection. Based on available data, the article summarizes the current serological information concerning COVID-19 in CSF in patients with severe neurological complications and in those with MS.


Subject(s)
COVID-19 , Multiple Sclerosis , SARS-CoV-2/metabolism , COVID-19/blood , COVID-19/cerebrospinal fluid , COVID-19/therapy , Humans , Multiple Sclerosis/blood , Multiple Sclerosis/cerebrospinal fluid , Multiple Sclerosis/therapy , Multiple Sclerosis/virology
11.
Cochrane Database Syst Rev ; 5: CD013212, 2020 05 07.
Article in English | MEDLINE | ID: covidwho-1453527

ABSTRACT

BACKGROUND: Hypertension is a major public health challenge affecting more than one billion people worldwide; it disproportionately affects populations in low- and middle-income countries (LMICs), where health systems are generally weak. The increasing prevalence of hypertension is associated with population growth, ageing, genetic factors, and behavioural risk factors, such as excessive salt and fat consumption, physical inactivity, being overweight and obese, harmful alcohol consumption, and poor management of stress. Over the long term, hypertension leads to risk for cardiovascular events, such as heart disease, stroke, kidney failure, disability, and premature mortality. Cardiovascular events can be preventable when high-risk populations are targeted, for example, through population-wide screening strategies. When available resources are limited, taking a total risk approach whereby several risk factors of hypertension are taken into consideration (e.g. age, gender, lifestyle factors, diabetes, blood cholesterol) can enable more accurate targeting of high-risk groups. Targeting of high-risk groups can help reduce costs in that resources are not spent on the entire population. Early detection in the form of screening for hypertension (and associated risk factors) can help identify high-risk groups, which can result in timely treatment and management of risk factors. Ultimately, early detection can help reduce morbidity and mortality linked to it and can help contain health-related costs, for example, those associated with hospitalisation due to severe illness and poorly managed risk factors and comorbidities. OBJECTIVES: To assess the effectiveness of different screening strategies for hypertension (mass, targeted, or opportunistic) to reduce morbidity and mortality associated with hypertension. SEARCH METHODS: An Information Specialist searched the Cochrane Register of Studies (CRS-Web), the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, Latin American Caribbean Health Sciences Literature (LILACS) Bireme, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) without language, publication year, or publication status restrictions. The searches were conducted from inception until 9 April 2020. SELECTION CRITERIA: Randomised controlled trials (RCTs) and non-RCTs (NRCTs), that is, controlled before and after (CBA), interrupted time series (ITS), and prospective analytic cohort studies of healthy adolescents, adults, and elderly people participating in mass, targeted, or opportunistic screening of hypertension. DATA COLLECTION AND ANALYSIS: Screening of all retrieved studies was done in Covidence. A team of reviewers, in pairs, independently assessed titles and abstracts of identified studies and acquired full texts for studies that were potentially eligible. Studies were deemed to be eligible for full-text screening if two review authors agreed, or if consensus was reached through discussion with a third review author. It was planned that at least two review authors would independently extract data from included studies, assess risk of bias using pre-specified Cochrane criteria, and conduct a meta-analysis of sufficiently similar studies or present a narrative synthesis of the results. MAIN RESULTS: We screened 9335 titles and abstracts. We identified 54 potentially eligible studies for full-text screening. However, no studies met the eligibility criteria. AUTHORS' CONCLUSIONS: There is an implicit assumption that early detection of hypertension through screening can reduce the burden of morbidity and mortality, but this assumption has not been tested in rigorous research studies. High-quality evidence from RCTs or programmatic evidence from NRCTs on the effectiveness and costs or harms of different screening strategies for hypertension (mass, targeted, or opportunistic) to reduce hypertension-related morbidity and mortality is lacking.


Subject(s)
Hypertension/diagnosis , Early Diagnosis , Humans , Mass Screening
12.
Cells ; 10(5)2021 04 21.
Article in English | MEDLINE | ID: covidwho-1436054

ABSTRACT

Extracellular vesicles (EVs) refer to a heterogenous population of membrane-bound vesicles that are released by cells under physiological and pathological conditions. The detection of EVs in the majority of the bodily fluids, coupled with their diverse cargo comprising of DNA, RNA, lipids, and proteins, have led to the accumulated interests in leveraging these nanoparticles for diagnostic and therapeutic purposes. In particular, emerging studies have identified enhanced levels of a wide range of specific subclasses of non-coding RNAs (ncRNAs) in EVs, thereby suggesting the existence of highly selective and regulated molecular processes governing the sorting of these RNAs into EVs. Recent studies have also illustrated the functional relevance of these enriched ncRNAs in a variety of human diseases. This review summarizes the current state of knowledge on EV-ncRNAs, as well as their functions and significance in lung infection and injury. As a majority of the studies on EV-ncRNAs in lung diseases have focused on EV-microRNAs, we will particularly highlight the relevance of these molecules in the pathophysiology of these conditions, as well as their potential as novel biomarkers therein. We also outline the current challenges in the EV field amidst the tremendous efforts to propel the clinical utility of EVs for human diseases. The lack of published literature on the functional roles of other EV-ncRNA subtypes may in turn provide new avenues for future research to exploit their feasibility as novel diagnostic and therapeutic targets in human diseases.


Subject(s)
Extracellular Vesicles/physiology , Lung Injury/metabolism , Pneumonia, Bacterial/metabolism , Pneumonia, Viral/metabolism , RNA, Untranslated/physiology , Animals , Biomarkers/metabolism , Humans , Lung/metabolism , Lung/pathology
13.
Front Pharmacol ; 11: 588480, 2020.
Article in English | MEDLINE | ID: covidwho-1389229

ABSTRACT

Periodontitis is a complex multifactorial disease that can lead to destruction of tooth supporting tissues and subsequent tooth loss. The most recent global burden of disease studies highlight that severe periodontitis is one of the most prevalent chronic inflammatory conditions affecting humans. Periodontitis risk is attributed to genetics, host-microbiome and environmental factors. Empirical diagnostic and prognostic systems have yet to be validated in the field of periodontics. Early diagnosis and intervention prevents periodontitis progression in most patients. Increased susceptibility and suboptimal control of modifiable risk factors can result in poor response to therapy, and relapse. The chronic immune-inflammatory response to microbial biofilms at the tooth or dental implant surface is associated with systemic conditions such as cardiovascular disease, diabetes or gastrointestinal diseases. Oral fluid-based biomarkers have demonstrated easy accessibility and potential as diagnostics for oral and systemic diseases, including the identification of SARS-CoV-2 in saliva. Advances in biotechnology have led to innovations in lab-on-a-chip and biosensors to interface with oral-based biomarker assessment. This review highlights new developments in oral biomarker discovery and their validation for clinical application to advance precision oral medicine through improved diagnosis, prognosis and patient stratification. Their potential to improve clinical outcomes of periodontitis and associated chronic conditions will benefit the dental and overall public health.

14.
Gynecol Endocrinol ; 37(2): 157-161, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-1376255

ABSTRACT

In patients with endometriosis, ectopic endometrial tissues can escape from immune system control and survive in other tissues. The pathophysiology of endometriosis is still not fully understood. In this study, we aimed to clarify the pathophysiology of endometriosis, which is thought to be a benign but infiltrative cancer type, which has many similarities with cancer biology by determining PD-1 expression in patients with endometriosis. In this study, n = 73 cases who underwent surgery or examination at the Obstetrics and Gynecology Clinic of Sivas Cumhuriyet University Faculty of Medicine and diagnosed as endometriosis in the biopsy material taken with the pre-diagnosis of endometriosis constituted the patient group. The control group consisted of n = 64 healthy subjects without concomitant malignancy or chronic inflammatory disease. Venous whole blood samples were obtained from the study groups. PD-1 and PD-L1 levels were determined by the ELISA method from serum and plasma samples. PD-1 gene expression level was determined by RT-PCR. The PD-1 level was found to be approximately 350 ± 150 ng/L and 45 ± 17 ng/L in endometriosis and control group, respectively. While the PD-L1 level was approximately 760 ± 108 ng/L in the patients, this level was 140 ± 14 ng/L in the controls. According to the RT-PCR results, the expression of the PD-1 gene 10 times higher compared to the controls. Conclusion: The identified increase of PD-1 levels and gene expression in endometriosis groups show that immunotherapy may be used in the treatment of endometriosis.


Subject(s)
B7-H1 Antigen/blood , Endometriosis/blood , Programmed Cell Death 1 Receptor/blood , Case-Control Studies , Endometriosis/etiology , Female , Humans
15.
Intern Med J ; 51(8): 1236-1242, 2021 08.
Article in English | MEDLINE | ID: covidwho-1369321

ABSTRACT

BACKGROUND: Emerging evidence suggests an association between COVID-19 and acute pulmonary embolism (APE). AIMS: To assess the prevalence of APE in patients hospitalised for non-critical COVID-19 who presented clinical deterioration, and to investigate the association of clinical and biochemical variables with a confirmed diagnosis of APE in these subjects. METHODS: All consecutive patients admitted to the internal medicine department of a general hospital with a diagnosis of non-critical COVID-19, who performed a computer tomography pulmonary angiography (CTPA) for respiratory deterioration in April 2020, were included in this retrospective cohort study. RESULTS: Study populations: 41 subjects, median (interquartile range) age: 71.7 (63-76) years, CPTA confirmed APE = 8 (19.51%, 95% confidence interval (CI): 8.82-34.87%). Among patients with and without APE, no significant differences were found with regards symptoms, comorbidities, treatment, Wells score and outcomes. The optimal cut-off value of d-dimer for predicting APE was 2454 ng/mL, sensitivity (95% CI): 63 (24-91), specificity: 73 (54-87), positive predictive value: 36 (13-65), negative predictive value: 89 (71-98) and AUC: 0.62 (0.38-0.85). The standard and age-adjusted d-dimer cut-offs, and the Wells score ≥2 did not associate with confirmed APE, albeit a cut-off value of d-dimer = 2454 ng/mL showed an relative risk: 3.21; 95% CI: 0.92-13.97; P = 0.073. Heparin at anticoagulant doses was used in 70.73% of patients before performing CTPA. CONCLUSION: Among patients presenting pulmonary deterioration after hospitalisation for non-critical COVID-19, the prevalence of APE is high. Traditional diagnostic tools to identify high APE pre-test probability patients do not seem to be clinically useful. These results support the use of a high index of suspicion for performing CTPA to exclude or confirm APE as the most appropriate diagnostic approach in this clinical setting.


Subject(s)
COVID-19 , Pulmonary Embolism , Aged , Fibrin Fibrinogen Degradation Products , Hospitalization , Humans , Pulmonary Embolism/diagnostic imaging , Pulmonary Embolism/epidemiology , Retrospective Studies , SARS-CoV-2
16.
J Cancer ; 12(12): 3558-3565, 2021.
Article in English | MEDLINE | ID: covidwho-1355160

ABSTRACT

Purpose: Data are extremely limited with regards to the impact of COVID-19 on cancer patients. Our study explored the distinct clinical features of COVID-19 patients with cancer. Experimental Design: 189 COVID-19 patients, including 16 cancer patients and 173 patients without cancer, were recruited. Propensity score 1:4 matching (PSM) was performed between cancer patients and patients without cancer based on age, gender and comorbidities. Survival was calculated by the Kaplan-Meier method and the difference was compared by the log-rank test. Results: PSM analysis yielded 16 cancer patients and 64 propensity score-matched patients without cancer. Compared to patients without cancer, cancer patients tended to have leukopenia and elevated high-sensitivity C-reactive protein (hs-CRP) and procalcitonin. For those with critical COVID-19, cancer patients had an inferior survival than those without cancer. Also, cancer patients with severe/critical COVID-19 tended to be male and present with low SPO2 and albumin, and high hs-CRP, lactate dehydrogenase and blood urea nitrogen on admission compared to those with mild COVID-19. In terms of risk factors, recent cancer diagnosis (within 1 year of onset of COVID-19) and anti-tumor treatment within 3 months of COVID-19 diagnosis were associated with inferior survival. Conclusions: We found COVID-19 patients with cancer have distinct clinical features as compared to patients without cancer. Importantly, cancer patients with critical COVID-19 were found to have poorer outcomes compared to those without cancer. In the cancer cohort, patients with severe/critical COVID-19 presented with a distinct clinical profile from those with mild COVID-19; short cancer history and recent anti-cancer treatment were associated with inferior survival.

17.
J Am Dent Assoc ; 152(6): 425-433, 2021 06.
Article in English | MEDLINE | ID: covidwho-1338324

ABSTRACT

BACKGROUND: In 2020, the Centers for Disease Control and Prevention and the America Dental Association released COVID-19 infection control interim guidance for US dentists, advising the use of optimal personal protection equipment during aerosol-generating procedures. The aim of this longitudinal study was to determine the cumulative prevalence and incidence rates of COVID-19 among dentists and to assess their level of engagement in specific infection control practices. METHODS: US dentists were invited to participate in a monthly web-based survey from June through November 2020. Approximately one-third of initial respondents (n = 785) participated in all 6 surveys, and they were asked about COVID-19 testing received, symptoms experienced, and infection prevention procedures followed in their primary practice. RESULTS: Over a 6-month period, the cumulative COVID-19 infection prevalence rate was 2.6%, representing 57 dentists who ever received a diagnosis of COVID-19. The incidence rates ranged from 0.2% through 1.1% each month. The proportion of dentists tested for COVID-19 increased over time, as did the rate of dentists performing aerosol-generating procedures. Enhanced infection prevention and control strategies in the dental practice were reported by nearly every participant monthly, and rates of personal protection equipment optimization, such as changing masks after each patient, dropped over time. CONCLUSIONS: US dentists continue to show a high level of adherence to enhanced infection control procedures in response to the ongoing pandemic, resulting in low rates of cumulative prevalence of COVID-19. Dentists are showing adherence to a strict protocol for enhanced infection control, which should help protect their patients, their dental team members, and themselves. PRACTICAL IMPLICATIONS: COVID-19 infections among practicing dentists will likely remain low if dentists continue to adhere to guidance.


Subject(s)
COVID-19 Testing , COVID-19 , Dentists , Humans , Incidence , Longitudinal Studies , Prevalence , SARS-CoV-2 , Surveys and Questionnaires , United States/epidemiology
18.
JMIR Res Protoc ; 2021 Jun 04.
Article in English | MEDLINE | ID: covidwho-1323051

ABSTRACT

BACKGROUND: The COVID-19 pandemic has impacted lives significantly and greatly affected an already vulnerable population, college students, in relation to mental health and public safety. Social distancing and isolation have brought about challenges to student's mental health. Mobile health apps and wearable sensors may help to monitor students at risk for COVID-19 and support their mental well-being. OBJECTIVE: Through the use of a wearable sensor and smartphone-based survey completion, this study aimed to monitor students at risk for COVID-19. METHODS: We conducted a prospective study of students, undergraduate and graduate, at a public university in the Midwest. Students were instructed to download the Fitbit, Social Rhythms, and Roadmap 2.0 apps onto their personal mobile devices (Android or iOS). Subjects consented to provide up to 10 saliva samples during the study period. Surveys were administered through the Roadmap 2.0 app at five timepoints - at baseline, 1-month later, 2-months later, 3-months later, and at study completion. The surveys gathered information regarding demographics, COVID-19 diagnoses and symptoms, and mental health resilience, with the aim of documenting the impact of COVID-19 on the college student population. RESULTS: This study enrolled 2,158 college students between September 2020 and January 2021. Subjects are currently being followed on-study for one academic year. Data collection and analysis are ongoing. CONCLUSIONS: This study examined student health and well-being during the COVID-19 pandemic. It also assessed the feasibility of wearable sensor use and survey completion in a college student population, which may inform the role of our mobile health tools on student health and well-being. Finally, using wearable sensor data, biospecimen collection, and self-reported COVID-19 diagnosis, our results may provide key data towards the development of a model for the early prediction and detection of COVID-19. CLINICALTRIAL: ClinicalTrials.gov NCT04766788.

19.
Comput Math Methods Med ; 2021: 9998379, 2021.
Article in English | MEDLINE | ID: covidwho-1314186

ABSTRACT

In recent years, computerized biomedical imaging and analysis have become extremely promising, more interesting, and highly beneficial. They provide remarkable information in the diagnoses of skin lesions. There have been developments in modern diagnostic systems that can help detect melanoma in its early stages to save the lives of many people. There is also a significant growth in the design of computer-aided diagnosis (CAD) systems using advanced artificial intelligence. The purpose of the present research is to develop a system to diagnose skin cancer, one that will lead to a high level of detection of the skin cancer. The proposed system was developed using deep learning and traditional artificial intelligence machine learning algorithms. The dermoscopy images were collected from the PH2 and ISIC 2018 in order to examine the diagnose system. The developed system is divided into feature-based and deep leaning. The feature-based system was developed based on feature-extracting methods. In order to segment the lesion from dermoscopy images, the active contour method was proposed. These skin lesions were processed using hybrid feature extractions, namely, the Local Binary Pattern (LBP) and Gray Level Co-occurrence Matrix (GLCM) methods to extract the texture features. The obtained features were then processed using the artificial neural network (ANNs) algorithm. In the second system, the convolutional neural network (CNNs) algorithm was applied for the efficient classification of skin diseases; the CNNs were pretrained using large AlexNet and ResNet50 transfer learning models. The experimental results show that the proposed method outperformed the state-of-art methods for HP2 and ISIC 2018 datasets. Standard evaluation metrics like accuracy, specificity, sensitivity, precision, recall, and F-score were employed to evaluate the results of the two proposed systems. The ANN model achieved the highest accuracy for PH2 (97.50%) and ISIC 2018 (98.35%) compared with the CNN model. The evaluation and comparison, proposed systems for classification and detection of melanoma are presented.


Subject(s)
Diagnosis, Computer-Assisted/methods , Melanoma/diagnostic imaging , Skin Neoplasms/diagnostic imaging , Algorithms , Artificial Intelligence , Computational Biology , Databases, Factual/statistics & numerical data , Deep Learning , Dermoscopy , Diagnosis, Computer-Assisted/statistics & numerical data , Early Detection of Cancer/methods , Early Detection of Cancer/statistics & numerical data , Humans , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Image Interpretation, Computer-Assisted/statistics & numerical data , Neural Networks, Computer , Skin Diseases/classification , Skin Diseases/diagnostic imaging
20.
Genes Immun ; 22(3): 141-160, 2021 07.
Article in English | MEDLINE | ID: covidwho-1275909

ABSTRACT

When surveying the current literature on COVID-19, the "cytokine storm" is considered to be pathogenetically involved in its severe outcomes such as acute respiratory distress syndrome, systemic inflammatory response syndrome, and eventually multiple organ failure. In this review, the similar role of DAMPs is addressed, that is, of those molecules, which operate upstream of the inflammatory pathway by activating those cells, which ultimately release the cytokines. Given the still limited reports on their role in COVID-19, the emerging topic is extended to respiratory viral infections with focus on influenza. At first, a brief introduction is given on the function of various classes of activating DAMPs and counterbalancing suppressing DAMPs (SAMPs) in initiating controlled inflammation-promoting and inflammation-resolving defense responses upon infectious and sterile insults. It is stressed that the excessive emission of DAMPs upon severe injury uncovers their fateful property in triggering dysregulated life-threatening hyperinflammatory responses. Such a scenario may happen when the viral load is too high, for example, in the respiratory tract, "forcing" many virus-infected host cells to decide to commit "suicidal" regulated cell death (e.g., necroptosis, pyroptosis) associated with release of large amounts of DAMPs: an important topic of this review. Ironically, although the aim of this "suicidal" cell death is to save and restore organismal homeostasis, the intrinsic release of excessive amounts of DAMPs leads to those dysregulated hyperinflammatory responses-as typically involved in the pathogenesis of acute respiratory distress syndrome and systemic inflammatory response syndrome in respiratory viral infections. Consequently, as briefly outlined in this review, these molecules can be considered valuable diagnostic and prognostic biomarkers to monitor and evaluate the course of the viral disorder, in particular, to grasp the eventual transition precociously from a controlled defense response as observed in mild/moderate cases to a dysregulated life-threatening hyperinflammatory response as seen, for example, in severe/fatal COVID-19. Moreover, the pathogenetic involvement of these molecules qualifies them as relevant future therapeutic targets to prevent severe/ fatal outcomes. Finally, a theory is presented proposing that the superimposition of coronavirus-induced DAMPs with non-virus-induced DAMPs from other origins such as air pollution or high age may contribute to severe and fatal courses of coronavirus pneumonia.


Subject(s)
Alarmins/immunology , COVID-19/immunology , Cytokine Release Syndrome/immunology , Respiratory Distress Syndrome/immunology , SARS-CoV-2/immunology , Virus Diseases/immunology , Alarmins/metabolism , COVID-19/metabolism , COVID-19/virology , Cytokine Release Syndrome/metabolism , Cytokines/immunology , Cytokines/metabolism , Humans , Inflammation/immunology , Inflammation/metabolism , Models, Immunological , Respiratory Distress Syndrome/etiology , Respiratory Distress Syndrome/metabolism , SARS-CoV-2/physiology , Virus Diseases/complications , Virus Diseases/metabolism
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