scholarly journals Differentiating COVID-19 and dengue from other febrile illnesses in co-epidemics: Development and internal validation of COVIDENGUE scores

2021 ◽  
Author(s):  
Patrick Gerardin ◽  
Olivier Maillard ◽  
Lea Bruneau ◽  
Frederic Accot ◽  
Florian Legrand ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Multinomial Logistic Regression ◽  
Characteristic Curve ◽  
Severe Dengue ◽  
Delayed Presentation ◽  
Upper Respiratory Tract ◽  
Discriminative Ability ◽  
Internal Validation ◽  
Logistic Regression Models ◽  
Testing Center

Background. In a retrospective cohort study, we previously distinguished the factors associated with coronavirus 2019 (COVID-19) or dengue from those associated with other febrile illnesses (OFIs). In this study, we developed a scoring system to discriminate both infectious diseases. Methods. Predictors of both infections were sought using multinomial logistic regression models (OFIs as controls) in all subjects suspected of COVID-19 who attended the SARS-CoV-2 testing center of Saint-Pierre teaching hospital, Reunion Island, between March 23 and May 10, 2020. Two COVIDENGUE scores were developed and internally validated by bootstrapping for predicting each infection after weighting the odd ratios according to a predefined rule. The discriminative ability of each score was assessed using the area under the receiver operating characteristic curve (AUC). Their calibration was assessed using goodness-of-fit statistics. Results. Over 49 days, 80 COVID-19, 60 non-severe dengue and 872 OFI cases were diagnosed. The translation of the best fit model yielded two COVIDENGUE scores composed of 11 criteria: contact with a COVID-19 positive case (+3 points for COVID-19; 0 point for dengue), return from travel abroad within 15 days (+3/-1), previous individual episode of dengue (+1/+3), active smoking (-3/0), body ache (0/+5), cough (0/-2), upper respiratory tract infection symptoms (-1/-1), anosmia (+7/-1), headache (0/+5), retro-orbital pain (-1/+5), and delayed presentation (>3 days) to hospital (+1/0). The AUC was of 0.79 (95%CI 0.76-0.82) for COVID-19 score and of 0.88 (95%CI 0.85-0.90) for dengue score. Calibration was satisfactory for COVID-19 score and excellent for dengue score. For predicting COVID-19, sensitivity was of 97% at the 0-point cut-off and specificity approximated 99% at the 10-point cut-off. For predicting dengue, sensitivity approximated 97% at the 3-point cut-off and specificity 98% at the 11-point cut-off. Conclusions. In conclusion, the COVIDENGUE scores proved discriminant to differentiate COVID-19 and dengue from other febrile illnesses in the context of SARS-CoV-2 testing center during a co-epidemic. Further studies are needed to validate or refine these scores in other settings.

scholarly journals Distinguishing non severe cases of dengue from COVID-19 in the context of co-epidemics: A cohort study in a SARS-CoV-2 testing center on Reunion island

2021 ◽  
Vol 15 (4) ◽  
pp. e0008879
Author(s):  
Antoine Joubert ◽  
Fanny Andry ◽  
Antoine Bertolotti ◽  
Frédéric Accot ◽  
Yatrika Koumar ◽  
...  
Keyword(s):  
Cohort Study ◽  
Multinomial Logistic Regression ◽  
University Hospital ◽  
Severe Dengue ◽  
Nasopharyngeal Swab ◽  
Delayed Presentation ◽  
Reunion Island ◽  
Upper Respiratory Tract ◽  
Réunion Island ◽  
Testing Center

Background As coronavirus 2019 (COVID-19) is spreading globally, several countries are handling dengue epidemics. As both infections are deemed to share similarities at presentation, it would be useful to distinguish COVID-19 from dengue in the context of co-epidemics. Hence, we performed a retrospective cohort study to identify predictors of both infections. Methodology/Principal findings All the subjects suspected of COVID-19 between March 23 and May 10, 2020, were screened for COVID-19 within the testing center of the University hospital of Saint-Pierre, Reunion island. The screening consisted in a questionnaire surveyed in face-to-face, a nasopharyngeal swab specimen for the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) reverse transcription polymerase chain-reaction and a rapid diagnostic orientation test for dengue. Factors independently associated with COVID-19 or with dengue were sought using multinomial logistic regression models, taking other febrile illnesses (OFIs) as controls. Adjusted Odds ratios (OR) and 95% Confidence Intervals (95%CI) were assessed. Over a two-month study period, we diagnosed 80 COVID-19, 61 non-severe dengue and 872 OFIs cases eligible to multivariate analysis. Among these, we identified delayed presentation (>3 days) since symptom onset (Odds ratio 1.91, 95% confidence interval 1.07–3.39), contact with a COVID-19 positive case (OR 3.81, 95%CI 2.21–6.55) and anosmia (OR 7.80, 95%CI 4.20–14.49) as independent predictors of COVID-19, body ache (OR 6.17, 95%CI 2.69–14.14), headache (OR 5.03, 95%CI 1.88–13.44) and retro-orbital pain (OR 5.55, 95%CI 2.51–12.28) as independent predictors of dengue, while smoking was less likely observed with COVID-19 (OR 0.27, 95%CI 0.09–0.79) and upper respiratory tract infection symptoms were associated with OFIs. Conclusions/Significance Although prone to potential biases, these data suggest that non-severe dengue may be more symptomatic than COVID-19 in a co-epidemic setting with higher dengue attack rates. At clinical presentation, nine basic clinical and epidemiological indicators may help to distinguish COVID-19 or dengue from each other and other febrile illnesses.

scholarly journals Distinguishing non severe cases of dengue from COVID-19 in the context of co-epidemics: a cohort study in a SARS-CoV-2 testing center on Reunion island

2020 ◽  
Author(s):  
Antoine Joubert ◽  
Fanny Andry ◽  
Antoine Bertolotti ◽  
Frédéric Accot ◽  
Yatrika Koumar ◽  
...  
Keyword(s):  
Cohort Study ◽  
Multinomial Logistic Regression ◽  
University Hospital ◽  
Severe Dengue ◽  
Delayed Presentation ◽  
Reunion Island ◽  
Orbital Pain ◽  
Réunion Island ◽  
Testing Center ◽  
Body Ache

AbstractBackgroundAs coronavirus (COVID-19) is spreading globally, several countries are handling dengue epidemics. As both infections are deemed to share similarities at presentation, it would be useful to distinguish COVID-19 from dengue in the context of co-epidemics. In this aim, we performed a cohort study to identify predictors of both infections.MethodsAll the subjects suspected of COVID-19 between March 23 and May 10, 2020, were screened for COVID-19 within the testing center of the University hospital of Saint-Pierre, Reunion island. The screening consisted in a questionnaire surveyed in face-to-face, a nasopharyngeal swab specimen for the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) reverse transcription polymerase chain-reaction and a rapid diagnostic orientation test for dengue. Factors independently associated with COVID-19 or with dengue were sought using multinomial logistic regression models, taking other febrile illnesses (OFIs) as controls.ResultsOver a two-month study period, we identified among 80 COVID-19, 60 non-severe dengue and 872 OFIs cases, delayed presentation (>3 days) since symptom onset (Odds ratio 1.89, 95% confidence interval 1.4-3.40), contact with a COVID-19 positive case (OR 3.81, 95%CI 2.12-6.82) and anosmia (OR 8.27, 95%CI 4.39-15.54) as independent predictors of COVID-19, body ache (OR 6.83, 95%CI 2.84-16.41), headache (OR 5.38, 95%CI 1.81-15.94) and retro-orbital pain (OR 7.45, 95%CI 3.17-17.50) as independent predictors of dengue, while smoking was less likely observed with COVID-19 (OR 0.27, 95%CI 0.10-0.74).ConclusionsAlthough prone to potential biases, these data suggest that non-severe dengue may be more symptomatic than COVID-19 in a co-epidemic setting with higher dengue attack rates.40-word summary of the article’s main pointIn the COVID-19 dengue co-epidemic setting of Reunion island, dengue was found more symptomatic than COVID-19 and associated with body ache, headache and retro-orbital pain, while COVID-19 was found associated with contact, anosmia, delayed presentation and absence of active smoking.

scholarly journals Noninvasive Estimation of Hydration Status in Athletes Using Wearable Sensors and a Data-Driven Approach Based on Orthostatic Changes

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4469
Author(s):  
Fahad Kamran ◽  
Victor C. Le ◽  
Adam Frischknecht ◽  
Jenna Wiens ◽  
Kathleen H. Sienko
Keyword(s):  
Characteristic Curve ◽  
Wearable Sensors ◽  
Fluid Replacement ◽  
Data Driven ◽  
Hydration Status ◽  
Bodyweight Loss ◽  
Discriminative Ability ◽  
Logistic Regression Models ◽  
Data Driven Approach ◽  
Similar Accuracy

Dehydration beyond 2% bodyweight loss should be monitored to reduce the risk of heat-related injuries during exercise. However, assessments of hydration in athletic settings can be limited in their accuracy and accessibility. In this study, we sought to develop a data-driven noninvasive approach to measure hydration status, leveraging wearable sensors and normal orthostatic movements. Twenty participants (10 males, 25.0 ± 6.6 years; 10 females, 27.8 ± 4.3 years) completed two exercise sessions in a heated environment: one session was completed without fluid replacement. Before and after exercise, participants performed 12 postural movements that varied in length (up to 2 min). Logistic regression models were trained to estimate dehydration status given their heart rate responses to these postural movements. The area under the receiver operating characteristic curve (AUROC) was used to parameterize the model’s discriminative ability. Models achieved an AUROC of 0.79 (IQR: 0.75, 0.91) when discriminating 2% bodyweight loss. The AUROC for the longer supine-to-stand postural movements and shorter toe-touches were similar (0.89, IQR: 0.89, 1.00). Shorter orthostatic tests achieved similar accuracy to clinical tests. The findings suggest that data from wearable sensors can be used to accurately estimate mild dehydration in athletes. In practice, this method may provide an additional measurement for early intervention of severe dehydration.

scholarly journals Prevalence and determinants of diabetes and prediabetes in southwestern Iran: the Khuzestan comprehensive health study (KCHS)

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sanam Hariri ◽  
Zahra Rahimi ◽  
Nahid Hashemi-Madani ◽  
Seyyed Ali Mard ◽  
Farnaz Hashemi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Family History ◽  
Waist Circumference ◽  
Multinomial Logistic Regression ◽  
Fasting Blood Glucose ◽  
Health Study ◽  
Khuzestan Province ◽  
Logistic Regression Models ◽  
Relative Risks ◽  
Southwestern Iran

Background The Middle East and North Africa (MENA) is postulated to have the highest increase in the prevalence of diabetes by 2030; however, studies on the epidemiology of diabetes are rather limited across the region, including in Iran. Methods This study was conducted between 2016 and 2018 among Iranian adults aged 20 to 65 years residing in Khuzestan province, southwestern Iran. Diabetes was defined as the fasting blood glucose (FBG) level of 126 mg/dl or higher, and/or taking antidiabetic medications, and/or self-declared diabetes. Prediabetes was defined as FBG 100 to 125 mg/dl. Multinomial logistic regression models were used to examine the association of multiple risk factors that attained significance on the outcome. Results Overall, 30,498 participants were recruited; the mean (±SD) age was 41.6 (±11.9) years. The prevalence of prediabetes and diabetes were 30.8 and 15.3%, respectively. We found a similar prevalence of diabetes in both sexes, although it was higher among illiterates, urban residents, married people, and smokers. Participants aged 50–65 and those with Body Mass Index (BMI) 30 kg/m2 or higher were more likely to be affected by diabetes [RR: 20.5 (18.1,23.3) and 3.2 (3.0,3.6)]. Hypertension [RR: 5.1 (4.7,5.5)], waist circumference (WC) equal or more than 90 cm [RR: 3.6 (3.3,3.9)], and family history [RR: 2.3 (2.2,2.5)] were also significantly associated with diabetes. For prediabetes, the main risk factors were age 50 to 65 years [RR: 2.6 (2.4,2.8)], BMI 30 kg/m2 or higher [RR: 1.9 (1.8,2.0)], hypertension and WC of 90 cm or higher [RR: 1.7 (1.6,1.8)]. The adjusted relative risks for all variables were higher in females than males, with the exception of family history for both conditions and waist circumference for prediabetes. Conclusions Prediabetes and diabetes are prevalent in southwestern Iran. The major determinants are older age, obesity, and the presence of hypertension. Further interventions are required to escalate diabetes prevention and diagnosis in high-risk areas across Iran.

scholarly journals Transitions in hookah (Waterpipe) smoking by U.S. sexual minority adults between 2013 and 2015: the population assessment of tobacco and health study wave 1 and wave 2

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mary Rezk-Hanna ◽  
Ian W. Holloway ◽  
Joy Toyama ◽  
Umme Shefa Warda ◽  
Lorree Catherine Berteau ◽  
...  
Keyword(s):  
Multinomial Logistic Regression ◽  
Health Study ◽  
Chi Square ◽  
Population Assessment ◽  
Logistic Regression Models ◽  
Global Epidemic ◽  
Product Use ◽  
Hookah Smoking ◽  
Nationally Representative ◽  
And Gender

Abstract Background Tobacco smoking using a hookah (i.e., waterpipe) is a global epidemic. While evidence suggests that sexual minorities (SM) have higher odds of hookah use compared to heterosexuals, little is known about their hookah use patterns and transitions. We sought to examine transitions between hookah smoking and use of other tobacco and electronic (e-) products among SM adults aged 18 years of age and older versus their heterosexual counterparts. Methods We analyzed nationally representative data of ever and current hookah smokers from Wave 1 (2013–2014; ever use n = 1014 SM and n = 9462 heterosexuals; current use n = 144 SM and n = 910 heterosexuals) and Wave 2 (2014–2015; ever use n = 901 SM and n = 8049 heterosexuals; current use n = 117 SM and n = 602 heterosexuals) of the Population Assessment of Tobacco and Health Study. Comparisons between groups and gender subgroups within SM identity groups were determined with Rao-Scott chi-square tests and multivariable survey-weighted multinomial logistic regression models were estimated for transition patterns and initiation of electronic product use in Wave 2. Results Ever and current hookah smoking among SM adults (ever use Wave 1: 29% and Wave 2: 31%; current use Wave 1: 4% and Wave 2: 3%) was higher than heterosexuals (ever use Wave 1: 16% and Wave 2: 16%; current use Wave 1: 1% and Wave 2: 1%; both p < 0.0001). Among SM adults who reported hookah use at Wave 1, 46% quit hookah use at Wave 2; 39% continued hookah use and did not transition to other products while 36% of heterosexual adults quit hookah use at Wave 2 and 36% continued hookah use and did not transition to other products. Compared with heterosexuals, SM adults reported higher use of hookah plus e-products (Wave 2 usage increased by 65 and 83%, respectively). Conclusions Compared to heterosexuals, in addition to higher rates of hookah smoking, higher percentages of SM adults transitioned to hookah plus e-product use between 2013 and 2015. Results have implications for stronger efforts to increase awareness of the harmful effects of hookah as well as vaping, specifically tailored among SM communities.

Estimated fetal weight and severe neonatal outcomes in preterm prelabor rupture of membranes

2020 ◽  
Vol 48 (7) ◽  
pp. 687-693 ◽  
Author(s):  
Jose R. Duncan ◽  
Katherine M. Dorsett ◽  
Michael M. Aziz ◽  
Zoran Bursac ◽  
Mario A. Cleves ◽  
...  
Keyword(s):  
Characteristic Curve ◽  
Neonatal Outcomes ◽  
Fetal Weight ◽  
Clinical Tool ◽  
Logistic Regression Models ◽  
Clinical Variables ◽  
Prognostic Accuracy ◽  
Prediction Probability ◽  
Prelabor Rupture Of Membranes ◽  
Estimated Fetal Weight

AbstractObjectivesOur aim was to study the association of clinical variables obtainable before delivery for severe neonatal outcomes (SNO) and develop a clinical tool to calculate the prediction probability of SNO in preterm prelabor rupture of membranes (PPROM).MethodsThis was a prospective study from October 2015 to May 2018. We included singleton pregnancies with PPROM and an estimated fetal weight (EFW) two weeks before delivery. We excluded those with fetal anomalies or fetal death. We examined the association between SNO and variables obtainable before delivery such as gestational age (GA) at PPROM, EFW, gender, race, body mass index, chorioamnioitis. SNO was defined as having at least one of the following: respiratory distress syndrome, intraventricular hemorrhage, necrotizing enterocolitis, neonatal sepsis, or neonatal death. The most parsimonious logistic regression models was constructed using the best subset selection model approach, and receiver operator curves were utilized to evaluate the prognostic accuracy of these clinical variables for SNO.ResultsWe included 106 pregnancies, 42 had SNO (39.6%). The EFW (area under the receiver operating characteristic curve [AUC]=0.88) and GA at PPROM (AUC=0.83) were significant predictors of SNO. The addition of any of the other variables did not improve the predictive probability of EFW for the prediction of SNO.ConclusionsThe EFW had the strongest association with SNO in in our study among variables obtainable before delivery. Other variables had no significant effect on the prediction probability of the EFW. Our findings should be validated in larger studies.

scholarly journals Food insecurity and its association with changes in nutritional habits among adults during the COVID-19 confinement measures in Belgium

2020 ◽  
pp. 1-7
Author(s):  
Stefanie Vandevijvere ◽  
Karin De Ridder ◽  
Sabine Drieskens ◽  
Rana Charafeddine ◽  
Finaba Berete ◽  
...  
Keyword(s):  
Food Insecurity ◽  
Multinomial Logistic Regression ◽  
Soft Drink ◽  
Household Composition ◽  
Healthy Diet ◽  
Cross Sectional ◽  
Nutritional Habits ◽  
Logistic Regression Models ◽  
Soft Drink Consumption ◽  
Snack Consumption

Abstract Objective: To assess food insecurity and its association with changes in nutritional habits among Belgian adults during confinement due to COVID-19. Design: Three cross-sectional online health surveys were conducted during March–May 2020. Multinomial logistic regression models were used to determine associations between self-reported changes in fruit, vegetable, soft drink and sweet and salted snack consumption or weight as dependent variables and food insecurity indicators as independent variables, adjusted for gender, household composition, educational attainment and household income. Setting: Belgium. Participants: In total, 8640 adults recruited by convenience sampling. Results: About 10·4 % of Belgians often or sometimes feared food shortages, 5·0 % were often or sometimes short of food without money to buy more and 10·3 % often or sometimes could not afford to eat a healthy diet during confinement. These percentages were highest among single-parent families (26·7, 14·4 and 23·4 %, respectively). Adults who often or sometimes feared that food would run out during confinement had significantly higher odds of decreased v. unchanged fruits (3·53; 95 % CI = 2·06, 6·05) and vegetables (5·42; 95 % CI = 2·90, 10·11) consumption and significantly higher odds of increased v. unchanged soft drink consumption (3·79; 95 % CI = 2·20, 6·54). Similar results were found for adults who often or sometimes ran out of food and for adults who often or sometimes were not able to afford a healthy diet. Conclusion: Food insecurity during the COVID-19 confinement measures in Belgium was associated with adverse changes in most dietary behaviours. A strong government response is needed to tackle malnutrition and food insecurity to protect public health from ongoing and future pandemics.

scholarly journals Correlates of Transitions in Food Insecurity Status during the Early Stages of the COVID-19 Pandemic among Ethnically Diverse Households in Central Texas

Nutrients ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 2597
Author(s):  
Kathryn M. Janda ◽  
Nalini Ranjit ◽  
Deborah Salvo ◽  
Aida Nielsen ◽  
Pablo Lemoine ◽  
...  
Keyword(s):  
Food Insecurity ◽  
Food Availability ◽  
Low Income ◽  
Food Access ◽  
Multinomial Logistic Regression ◽  
Related Factors ◽  
Logistic Regression Models ◽  
Early Stages ◽  
Central Texas ◽  
June July

Food insecurity increased substantially in the USA during the early stages of the 2020 COVID-19 pandemic. The purpose of this study was to identify potential sociodemographic and food access-related factors that were associated with continuing or transitioning into food insecurity in a diverse population. An electronic survey was completed by 367 households living in low-income communities in Central Texas during June–July 2020. Multinomial logistic regression models were developed to examine the associations among food insecurity transitions during COVID-19 and various sociodemographic and food access-related factors, including race/ethnicity, children in the household, loss of employment/wages, language, and issues with food availability, accessibility, affordability, and stability during the pandemic. Sociodemographic and food access-related factors associated with staying or becoming newly food insecure were similar but not identical. Having children in the household, changes in employment/wages, changing shopping location due to food availability, accessibility and/or affordability issues, issues with food availability, and stability of food supply were associated with becoming newly food insecure and staying food insecure during the pandemic. Identifying as Latino and/or Black was associated with staying food insecure during COVID-19. These findings suggest that the COVID-19 pandemic did not create new food insecurity disparities. Rather, the pandemic exacerbated pre-existing disparities.

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