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1.
Scand J Trauma Resusc Emerg Med ; 28(1): 106, 2020 Oct 27.
Article in English | MEDLINE | ID: covidwho-2098375

ABSTRACT

BACKGROUND: Novel coronavirus disease 2019 (COVID-19) is a global public health emergency. Here, we developed and validated a practical model based on the data from a multi-center cohort in China for early identification and prediction of which patients will be admitted to the intensive care unit (ICU). METHODS: Data of 1087 patients with laboratory-confirmed COVID-19 were collected from 49 sites between January 2 and February 28, 2020, in Sichuan and Wuhan. Patients were randomly categorized into the training and validation cohorts (7:3). The least absolute shrinkage and selection operator and logistic regression analyzes were used to develop the nomogram. The performance of the nomogram was evaluated for the C-index, calibration, discrimination, and clinical usefulness. Further, the nomogram was externally validated in a different cohort. RESULTS: The individualized prediction nomogram included 6 predictors: age, respiratory rate, systolic blood pressure, smoking status, fever, and chronic kidney disease. The model demonstrated a high discriminative ability in the training cohort (C-index = 0.829), which was confirmed in the external validation cohort (C-index = 0.776). In addition, the calibration plots confirmed good concordance for predicting the risk of ICU admission. Decision curve analysis revealed that the prediction nomogram was clinically useful. CONCLUSION: We established an early prediction model incorporating clinical characteristics that could be quickly obtained on hospital admission, even in community health centers. This model can be conveniently used to predict the individual risk for ICU admission of patients with COVID-19 and optimize the use of limited resources.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Coronavirus Infections/therapy , Hospitalization , Intensive Care Units , Pneumonia, Viral/epidemiology , Pneumonia, Viral/therapy , Adult , Aged , COVID-19 , China , Coronavirus Infections/diagnosis , Female , Humans , Logistic Models , Male , Middle Aged , Nomograms , Pandemics , Pneumonia, Viral/diagnosis , Retrospective Studies , Risk Assessment , SARS-CoV-2
3.
Infect Control Hosp Epidemiol ; 41(8): 968-969, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-2096333

ABSTRACT

To inform the efficient allocation of testing resources, we evaluated the characteristics of those tested for COVID-19 to determine predictors of a positive test. Recent travel and exposure to a confirmed case were both highly predictive of positive testing. Symptom-based screening strategies alone may be inadequate to control the ongoing pandemic.


Subject(s)
Betacoronavirus/isolation & purification , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Polymerase Chain Reaction , Travel , Adult , Asymptomatic Infections , COVID-19 , COVID-19 Testing , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Female , Humans , Logistic Models , Male , Middle Aged , Minnesota , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Risk Assessment , SARS-CoV-2
4.
Medicina (Kaunas) ; 58(10)2022 Oct 21.
Article in English | MEDLINE | ID: covidwho-2082151

ABSTRACT

Little is known on the characteristics of headaches associated with coronavirus disease 2019 (COVID-19) in Indonesia. The objective of this study was to describe the characteristics of headache in post-COVID-19 patients, and its impact on the patients' quality of life (QoL), as well as to determine the associated determinants of the poor QoL. A cross-sectional study was conducted in Banda Aceh, Indonesia. The demographic characteristics, clinical symptoms of COVID-19, characteristics of headache, and the QoL were collected and assessed. Headache was diagnosed and characterized using the International Classification of Headache Disorders, version 3 (ICHD-3). QoL was assessed using a Short Form 36 Health Survey (SF-36) tool. A logistic regression model was used to investigate the associated determinants of poor QoL in post-COVID-19 patients. A total of 215 post-COVID-19 patients were included in the final analysis, and 21.4% (46/215) of them had a poor QoL due to headache following COVID-19. Those who were unemployed and who contracted COVID-19 less than three months prior to the study had higher odds of having poor QoL compared to those who were employed and who contracted COVID-19 more than three months prior to the study. Low QoL was also related to headache that occurred less than one month after recovering from COVID-19 (compared to that which occurred longer than one month after); had a high frequency; had a combination sensation of pulsating, pressing, fiery, and stabbing pain; had a high severity score; and had additional symptoms accompanying the headache. In conclusion, headache related to COVID-19 is associated with low QoL among post-COVID-19 patients. A guideline on prevention measures of headache on COVID-19 patients, therefore, needs to be established to avoid long-term consequences.


Subject(s)
COVID-19 , Quality of Life , Humans , COVID-19/complications , Cross-Sectional Studies , Headache/etiology , Logistic Models
5.
Int J Public Health ; 67: 1604958, 2022.
Article in English | MEDLINE | ID: covidwho-2065659

ABSTRACT

Objectives: This study aims to assess the trade-offs between vulnerability and efficiency attributes of contact tracing programmes based on preferences of COVID-19 contact tracing practitioners, researchers and other relevant stakeholders at the global level. Methods: We conducted an online discrete choice experiment (DCE). Respondents were recruited globally to explore preferences according to country income level and the prevailing epidemiology of COVID-19 in the local setting. The DCE attributes represented efficiency (timeliness, completeness, number of contacts), vulnerability (vulnerable population), cooperation and privacy. A mixed-logit model and latent class analysis were used. Results: The number of respondents was 181. Timeliness was the most important attribute regardless of country income level and COVID-19 epidemiological condition. Vulnerability of contacts was the second most important attribute for low-to-lower-middle-income countries and third for upper-middle-to-high income countries. When normalised against conditional relative importance of timeliness, conditional relative importance of vulnerability ranged from 0.38 to 0.42. Conclusion: Vulnerability and efficiency criteria were both considered to be important attributes of contact tracing programmes. However, the relative values placed on these criteria varied significantly between epidemiological and economic context.


Subject(s)
COVID-19 , Contact Tracing , COVID-19/epidemiology , COVID-19/prevention & control , Choice Behavior , Humans , Logistic Models , Patient Preference , Surveys and Questionnaires
6.
Int J Environ Res Public Health ; 19(19)2022 Sep 22.
Article in English | MEDLINE | ID: covidwho-2043724

ABSTRACT

The outbreak of the new COVID-19 disease is a serious health problem that has affected a large part of the world population, especially older adults and people who suffer from a previous comorbidity. In this work, we proposed a classifier model that allows for deciding whether or not a patient might suffer from the COVID-19 disease, considering spatio-temporal variables, physical characteristics of the patients and the presence of previous diseases. We used XGBoost to maximize the likelihood function of the multivariate logistic regression model. The estimated and observed values of percentage occurrence of cases were very similar, and indicated that the proposed model was suitable to predict new cases (AUC = 0.75). The main results revealed that patients without comorbidities are less likely to be COVID-19 positive, unlike people with diabetes, obesity and pneumonia. The distribution function by age group showed that, during the first and second wave of COVID-19, young people aged ≤20 were the least affected by the pandemic, while the most affected were people between 20 and 40 years, followed by adults older than 40 years. In the case of the third and fourth wave, there was an increased risk for young individuals (under 20 years), while older adults over 40 years decreased their chances of infection. Estimates of positive COVID cases with both the XGBoost-LR model and the multivariate logistic regression model were used to create maps to visualize the spatial distribution of positive cases across the country. Spatial analysis was carried out to determine, through the data, the main geographical areas where a greater number of positive cases occurred. The results showed that the areas most affected by COVID-19 were in the central and northern regions of Mexico.


Subject(s)
COVID-19 , Adolescent , Aged , COVID-19/epidemiology , Comorbidity , Humans , Logistic Models , Mexico/epidemiology , Pandemics
7.
Contemp Clin Trials ; 122: 106932, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2041608

ABSTRACT

BACKGROUND: Establishing equitable access to COVID-19 clinical trials is an important step in mitigating outcomes disparities. Historically, language has served as a barrier to equitable clinical trial participation. METHODS: A centralized research infrastructure was established at our institution to screen potential trial participants and to promote efficient and equitable access to COVID-19 clinical trials. Rates of eligibility and enrollment in COVID-19 clinical trials by primary language between April 9 and July 31, 2020 (during the first regional COVID-19 surge) were evaluated using logistic regression. Estimates were adjusted for potential confounders including age, sex, and time. RESULTS: A total of 1245 patients were admitted to the hospital with COVID-19 during the study period and screened for clinical trial eligibility. Among all screened patients, 487 (39%) had a non-English primary language. After adjustment, patients with a non-English primary language had 1.98 times higher odds (CI 1.51 to 2.59) of being eligible for 1 or more COVID-19 clinical trials. Among eligible patients, those with a non-English primary language had 1.83 times higher odds (CI 1.36 to 2.47) of enrolling in COVID-19 clinical trials than patients with English as the primary language. CONCULSION: These findings suggest that there are modifiable barriers that can be addressed to lessen the impact of language discordance on access to clinical trials and provide an opportunity to further investigate factors associated with clinical trial participation for patients whose primary language is not English.


Subject(s)
COVID-19 , Language , Humans , COVID-19/epidemiology , COVID-19/therapy , Retrospective Studies , Eligibility Determination , Logistic Models
8.
JAMA ; 328(8): 772-773, 2022 08 23.
Article in English | MEDLINE | ID: covidwho-2041181
9.
Public Health ; 211: 85-87, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-2036462

ABSTRACT

OBJECTIVE: To determine whether household contacts of confirmed cases of COVID-19 have an increased risk of hospitalisation or death. METHODS: We used the HOSTED data set of index cases of COVID-19 in England between June and November 2020, linked to Secondary Uses Service data on hospital episodes and Office for National Statistics' mortality data. Multivariable logistic regression models of the odds of household contacts being hospitalised or dying within six weeks of an index case, adjusted for case type, age, sex and calendar month were calculated. Excess risk was determined by comparing the first six weeks after the index case with 6-12 weeks after the index case in a survival analysis framework. RESULTS: Index cases were more likely to be hospitalised or die than either secondary cases or non-cases, having adjusted for age and sex. There was an increased risk of hospitalisation for non-cases (adjusted hazard ratio (aHR) 1.10; 95% confidence interval (CI) 1.04, 1.16) and of death (aHR 1.57; 95% CI 1.14, 2.16) in the first six weeks after an index case, compared to 6-12 weeks after. CONCLUSION: Risks of hospitalisation and mortality are predictably higher in cases compared to non-cases. The short-term increase in risks for non-case contacts following diagnosis of the index case may suggest incomplete case ascertainment among contacts, although this was relatively small.


Subject(s)
COVID-19 , Family Characteristics , Hospitalization , Humans , Logistic Models , SARS-CoV-2
10.
Int J Environ Res Public Health ; 19(18)2022 Sep 09.
Article in English | MEDLINE | ID: covidwho-2032926

ABSTRACT

This study compared levels of concern, spending, and use of external support by working status among older adults in the U.S. during the COVID-19 pandemic. It assessed whether work influences these variables related to wellness. Data from 2489 older adults from the 2020 U.S. Health and Retirement Study were analyzed using multiple linear and logistic regression. Older adults who worked had lower concerns about the pandemic (ß = -0.28, p = 0.048), were less likely to increase their spending (OR = 0.74, p = 0.041), and were less likely to use external support (OR = 0.50, p < 0.001). Use of external support increased with age (OR = 1.04, p < 0.001) and increased spending (OR = 1.32, p = 0.019). Married older adults were less likely to increase spending (OR = 0.75, p = 0.007) and had lower concerns toward COVID-19 (ß = -0.28, p = 0.011). Higher levels of concern were reported among women (ß = 0.31, p = 0.005) and participants who had friends or family members diagnosed with COVID-19 (ß = 0.51, p < 0.001). Women were more likely to use support (OR = 1.80, p < 0.001). Work appears to bolster older adult wellness outcomes.


Subject(s)
COVID-19 , Aged , COVID-19/epidemiology , Female , Humans , Logistic Models , Pandemics , Retirement
11.
J Public Health Manag Pract ; 28(6): 639-649, 2022.
Article in English | MEDLINE | ID: covidwho-2018363

ABSTRACT

CONTEXT: Considerable research has examined impacts of case investigation and contact tracing (CI/CT) programs on the spread of infectious diseases such as COVID-19, but there are few reports on factors affecting the ability of these programs to obtain interviews and acquire key information. OBJECTIVE: To investigate programmatic and case-specific factors associated with CI outcomes using data from the Public Health Institute's Tracing Health CI/CT program. Analyses were designed to detect variability in predictors of whether interviews and key information were obtained rather than quantify specific relationships. DESIGN: Logistic regression models examined variability in the predictive value of interview timeliness and respondent characteristics on outreach outcomes and interview results. SETTING AND PARTICIPANTS: Participants were members of a large California health care network with a positive laboratory test for COVID-19 and outreach from January 1 to July 31, 2021. MAIN OUTCOME MEASURES: The primary outcome was the result of outreach attempts: completed interview, refused interview, or failure to reach the infected person. Secondary outcomes considered whether respondents provided information on symptom onset, employment, and contact information or a reason for declining to provide information, and whether resource support was requested or accepted. RESULTS: Of 9391 eligible records, 65.6% were for completed interviews, 6.0% were refusals, and 28.3% were failed outreach. One-third of respondents (36.7%) provided information on contacts (mean = 0.97 contacts per respondent, 2.6 for those naming at least 1). Privacy concerns were the most common reasons for not providing contact information. Among respondent characteristics and interview timeliness, only race and number of symptoms showed statistically significant effects in all adjusted analyses. CONCLUSIONS: Significant variation existed in outreach outcomes by subject characteristics and interview timeliness. CI/CT programs carefully focused to characteristics and needs of specific communities will likely have the greatest impact on the spread of COVID-19 and other communicable diseases.


Subject(s)
COVID-19 , Contact Tracing , COVID-19/epidemiology , Contact Tracing/methods , Humans , Logistic Models , Program Evaluation , Public Health
12.
Sci Rep ; 12(1): 4109, 2022 03 08.
Article in English | MEDLINE | ID: covidwho-2004793

ABSTRACT

Preeclampsia and cardiovascular disease (CVD) share multiple features and risk factors. Circulating angiotensin-converting enzyme 2 (ACE2) is increased in CVD and mediates SARS-CoV-2 entry into host cells, causing COVID-19 infection. The role of ACE2 in preeclampsia pathophysiology is unknown. We hypothesized that circulating ACE2 is increased in mid-pregnancy in women later developing preeclampsia. We included 296 women later developing preeclampsia (cases) and 333 women with a continuous healthy pregnancy (controls). Circulating ACE2 was measured with an immunoassay based on proximity extension assay technology, with levels being expressed as relative quantification on a log2 scale. Median (interquartile range) ACE2 levels were higher in cases than in controls; 3.84 (3.50-4.24) vs. 3.72 (3.45-4.04), p = 0.002. Adjusted logistic regression models showed a 60% increased risk for later development of preeclampsia with one unit elevation of ACE2 (adjusted odds ratio (aOR) 1.60, 95% confidence intervals (CI) 1.17-2.18). Preterm preeclampsia (diagnosis before 37 gestational weeks, n = 97) seemed to have a stronger ACE2 association than term preeclampsia, n = 199 (aORs, 95% Cis 2.14, 1.15-3.96 and 1.52, 1.04-2.23, respectively). Circulating ACE2 is increased at mid-pregnancy in women later developing preeclampsia, particularly preterm preeclampsia. Thus, our finding indicates a partly shared pathophysiological pathway between preeclampsia and CVD.


Subject(s)
Angiotensin-Converting Enzyme 2/blood , Pre-Eclampsia/diagnosis , Adult , Body Mass Index , Cardiovascular Diseases/complications , Cardiovascular Diseases/pathology , Case-Control Studies , Female , Gestational Age , Hospitals, University , Humans , Logistic Models , Odds Ratio , Pre-Eclampsia/pathology , Pregnancy , Risk Factors , Sweden
13.
BMJ Open ; 12(8): e060799, 2022 08 18.
Article in English | MEDLINE | ID: covidwho-2001840

ABSTRACT

OBJECTIVES: This paper examines the relationship between individuals' perceptions of environmental quality and self-rated health (SRH) after controlling for dimensions of socioeconomic, demographic and healthy lifestyle variables. DESIGN: A cross-sectional survey. SETTING: The survey was conducted in Belait, an oil-rich and gas-rich district in Brunei Darussalam, from 17 October to 11 November 2019 and focused on the most populated subdistricts (Kuala Belait, Seria and Liang), where 97% of the people reside. PARTICIPANTS: A final sample of 1000 respondents aged 18 years and older were randomly selected from the population of the chosen subdistricts, with 95% CI and ±3 margin of error. Due to variable selection, only 673 respondents were available for analysis. OUTCOME MEASURES: SRH was dichotomised into 1 for good health and 0 otherwise. Perceptions of environmental quality included perceptions of the natural environment (air quality, marine quality, water supply, noise and olfactory pollution) and the social environment (crime). χ2 and logistic regression models were used to assess the relationship between individuals' perceived environmental quality and SRH. RESULTS: Most respondents perceived themselves with good SRH (72%). The adjusted logistic regression shows that perceptions of air quality (OR=2.20, 95% CI 1.15 to 4.22, p=0.018) and marine resources (OR=1.84, 95% CI 1.24 to 2.74, p=0.002) in their surrounding areas were significantly associated with good SRH. However, other environmental variables were insignificantly associated with SRH. Among the control variables, healthy lifestyle and employment had positive associations with good SRH (OR=3.89, 95% CI 1.96 to 7.71, p=0.000, for exercising 3-5 times a week; OR=1.72, 95% CI 1.09 to 2.71, p=0.021, for being employed). In addition, frequent physical exercise compensated for the negative health impact of environmental pollution. CONCLUSIONS: This study suggests that environmental quality has an important role in SRH. However, a healthy lifestyle measured with frequency of physical exercise seems to compensate for the adverse environmental effects on SRH.


Subject(s)
Health Status , Brunei/epidemiology , Cross-Sectional Studies , Humans , Logistic Models , Surveys and Questionnaires
14.
BMC Public Health ; 22(1): 1536, 2022 08 12.
Article in English | MEDLINE | ID: covidwho-1993348

ABSTRACT

BACKGROUND: Confusion of information has also colored the course of the Covid-19 pandemic in Indonesia. The study analyzes the relationship between media exposure and information clarity about Covid-19 in Indonesia. METHODS: The study collected extensive data (n = 5,397). The study determines information clarity about Covid-19 based on respondents' admissions. There were four types of media exposure analyzed: frequency of reading a newspaper/magazine, frequency of listening to a radio, frequency of watching television, and frequency of internet use. The study carried out a binary logistic regression test in the final stage. RESULTS: The results show read a newspaper/magazine every day is 1.670 times more likely than reading a newspaper/magazine > five days a week to get precise information about Covid-19. Reading a newspaper/magazine 2-3 days a week is 1.386 times more likely than reading a newspaper/magazine > five days a week to get precise information about Covid-19. Reading a newspaper/magazine 4-5 days a week is 1.470 times more likely than reading a newspaper/magazine > five days a week to get precise information about Covid-19. Watching television 2 to 3 days a week is 1.601 times more likely than watching television > five days a week to get clear details about Covid-19. Watching television 4 to 5 days a week are 1.452 times more likely than watching television > five days a week to get precise information about Covid-19. CONCLUSION: The study concluded two types of media exposure related to information clarity about Covid-19 in Indonesia: the frequency of reading newspapers and watching television.


Subject(s)
COVID-19 , Television , COVID-19/epidemiology , Humans , Indonesia/epidemiology , Logistic Models , Mass Media , Pandemics
15.
Can J Public Health ; 113(6): 878-886, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-1994670

ABSTRACT

OBJECTIVES: This study highlights how socioeconomic trends in the emergency department (ED) for low-acuity visits change with the onset of COVID-19, identifies societal inequities exacerbated by the pandemic, and demonstrates the geographical regions where these inequities occur. METHODS: We accessed 1,285,000 ED visits from 12 different facilities across New Brunswick from January 2017 to October 2020. Using a deprivation index developed by Statistics Canada as a measure of socioeconomic status, and controlling for additional factors, we perform a logistic regression to determine the influence of the COVID-19 pandemic on low-acuity visits of individuals from the most deprived quintile (Q5). We constructed a heat map of New Brunswick to highlight regions of high deprivation. RESULTS: The proportion of Q5 individuals in the ethnocultural composition domain accessing the ED for low-acuity visits increased from 22.91% to 24.72% with the onset of the pandemic. Our logistic regression showed the log odds of being considered Q5 in the ethnocultural composition domain when visiting the ED for a low-acuity reason increased by 6.3% if the visit occurred during the pandemic, and increased by 101.6% if the visit occurred in one of the 3 major regions of New Brunswick. CONCLUSION: Individuals visiting EDs for low-acuity reasons during the COVID-19 pandemic were more likely to be from the most diverse quintile in the ethnocultural domain, and the inequities were concentrated in the most urban regions in New Brunswick. This demonstrates that urban areas are where inequities are disproportionately faced for ethnically diverse individuals and demonstrates where policies could be focused.


RéSUMé: OBJECTIFS: Notre étude montre l'évolution des tendances socioéconomiques des visites aux services d'urgence (SU) pour des affections mineures avec l'apparition de la COVID-19 et indique les iniquités sociétales exacerbées par la pandémie et les régions géographiques où ces iniquités se manifestent. MéTHODE: Nous avons eu accès à 1 285 000 visites aux SU de 12 établissements du Nouveau-Brunswick entre janvier 2017 et octobre 2020. À l'aide d'un indice de défavorisation élaboré par Statistique Canada pour mesurer le statut socioéconomique et après avoir apporté des ajustements pour tenir compte des effets d'autres facteurs, nous avons effectué une analyse de régression logistique pour déterminer l'influence de la pandémie de COVID-19 sur les visites de personnes du quintile le plus défavorisé (Q5) pour des affections mineures. Nous avons construit une carte de densité du Nouveau-Brunswick pour représenter les régions très défavorisées. RéSULTATS: La proportion de personnes du Q5 dans le domaine de la composition ethnoculturelle ayant visité les SU pour des affections mineures est passée de 22,91 % à 24,72 % après le début de la pandémie. Selon notre analyse de régression logistique, la probabilité logarithmique pour une personne ayant visité les SU pour une affection mineure d'être considérée comme faisant partie du Q5 dans le domaine de la composition ethnoculturelle augmentait de 6,3 % si la visite avait eu lieu durant la pandémie, et elle augmentait de 101,6 % si la visite avait eu lieu dans l'une des trois grandes régions du Nouveau-Brunswick. CONCLUSION: Les personnes ayant visité les SU pour des affections mineures durant la pandémie de COVID-19 étaient plus susceptibles d'appartenir au quintile le plus diversifié dans le domaine ethnoculturel, et les iniquités étaient concentrées dans les régions les plus urbaines du Nouveau-Brunswick. L'étude démontre que c'est dans les agglomérations urbaines que les personnes d'origines ethniques diverses font face à des iniquités démesurées, et elle indique où les politiques pourraient être ciblées.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Pandemics , Emergency Service, Hospital , Social Class , Logistic Models , Retrospective Studies
16.
J Immigr Minor Health ; 24(6): 1590-1593, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-1990714

ABSTRACT

The coronavirus 2019 pandemic led to rapid expansion of outpatient telemedicine. We sought to characterize patient factors influencing outpatient teleneurology utilization at an urban safety-net hospital. We reviewed all neurology televisits scheduled between June 15, 2020 to April 15, 2021. We used the chi-squared test and multivariate logistic regression to characterize patient demographic factors associated with televisit completion and video use. Of 8875 scheduled televisit encounters, 7530 were completed successfully, 44% via video. Non-English speaking patients, Black patients, Latinx patients, and those with a zip code-linked annual income less than $50,000 were less likely to successfully complete a scheduled televisit. The same demographic groups other than Latinx ethnicity were also less likely to use the video option. Our study found unequal telehealth utilization based on patients' demographic factors. Currently declining telemedicine reimbursement rates asymmetrically affect audio-only visits, which may limit telehealth access for vulnerable patient populations.


Subject(s)
COVID-19 , Telemedicine , Humans , Pandemics , Safety-net Providers , Logistic Models
17.
J Nepal Health Res Counc ; 20(1): 33-40, 2022 Jun 02.
Article in English | MEDLINE | ID: covidwho-1988985

ABSTRACT

BACKGROUND: The utilization of institutional delivery services is pivotal to improve maternal health and reducing maternal mortality amid childbirth. But COVID-19 pandemic is posturing considerable challenges to maintain essential maternal and newborn health services. So study aims to assess the factors associated with the utilization of institutional delivery during the COVID -19 pandemic. METHODS: Data was collected from the 116 mothers of Kalika Municipality, Chitwan. The total enumerative sampling technique was used to include mothers who delivered a baby during lockdown (March 21 to August 21, 2020). Collected data were analysed by using descriptive and inferential statistics like chi-square test, logistic regression analysis. RESULTS: Out of 116 mothers, 76.6% had their delivery in the health facilities. Logistic regression analysis showed several factors associated with utilization of institutional delivery such as ethnicity, respondents education status, distance to the nearest health facility, fear of traveling, fear to visit health facility (AOR= 4.923; 95% CI =1.475-16.432, p=0.001),perception on the risk of covid-19 to mother, and intrauterine transmission of COVID-19 (AOR= 19 5.472;95% CI 1.35-22.175;p= 0.017) was found to be statistically significant with the utilization of institutional delivery during COVID-19 pandemic. CONCLUSIONS: Several factors have been associated with the utilization of institutional delivery during pandemic. Women preferred not to seek healthcare due to the fear of being infected, lack of awareness, and misperception about COVID-19 and pregnancy. Therefore, the concerned authority should need to deliver a separate message to the pregnant women for a regular check-up and deliver a baby at a hospital.


Subject(s)
COVID-19 , Maternal Health Services , COVID-19/epidemiology , Communicable Disease Control , Cross-Sectional Studies , Delivery, Obstetric , Female , Health Facilities , Humans , Infant, Newborn , Logistic Models , Nepal/epidemiology , Pandemics , Pregnancy , Prenatal Care
18.
J Neurooncol ; 158(3): 489-495, 2022 Jul.
Article in English | MEDLINE | ID: covidwho-1976838

ABSTRACT

PURPOSE: Terminated clinical trials are an inefficient use of financial, patient, and administrative resources. We reviewed ClinicalTrials.gov for completed and terminated clinical trials for glioblastoma multiforme (GBM) and compared reported characteristics of completed and terminated trials to identify factors associated with early trial termination. METHODS: ClinicalTrials.gov was queried to identify all completed and terminated GBM-related clinical trials. Trial characteristics were examined and the reason for trial termination was determined. Univariate analysis by Pearson's chi-square and a multivariate logistic regression were performed to identify independent predictors of early trial termination. RESULTS: We identified 886 completed and terminated GBM-related trials between 2003 and 2020. Of these, 175 (19.8%) were terminated prior to completion. The most common reason for termination was participant accrual difficulties, accounting for 63 (36.0%) terminated trials. Trial termination was associated with trials that reported a primary purpose of diagnosis relative to treatment (OR = 2.952, p = 0.001). CONCLUSION: Early termination of clinical trials investigating interventions for the treatment of GBM is associated with diagnostic trials relative to therapeutic trials. Patient accrual difficulties are the most commonly identified reason for early trial termination. Predictors of trial termination should be considered when designing GBM-related clinical trials to minimize the odds of early trial termination.


Subject(s)
Glioblastoma , Glioblastoma/therapy , Humans , Logistic Models , Research Design
19.
Front Public Health ; 10: 898254, 2022.
Article in English | MEDLINE | ID: covidwho-1952858

ABSTRACT

In this review, current studies on hospital readmission due to infection of COVID-19 were discussed, compared, and further evaluated in order to understand the current trends and progress in mitigation of hospital readmissions due to COVID-19. Boolean expression of ("COVID-19" OR "covid19" OR "covid" OR "coronavirus" OR "Sars-CoV-2") AND ("readmission" OR "re-admission" OR "rehospitalization" OR "rehospitalization") were used in five databases, namely Web of Science, Medline, Science Direct, Google Scholar and Scopus. From the search, a total of 253 articles were screened down to 26 articles. In overall, most of the research focus on readmission rates than mortality rate. On the readmission rate, the lowest is 4.2% by Ramos-Martínez et al. from Spain, and the highest is 19.9% by Donnelly et al. from the United States. Most of the research (n = 13) uses an inferential statistical approach in their studies, while only one uses a machine learning approach. The data size ranges from 79 to 126,137. However, there is no specific guide to set the most suitable data size for one research, and all results cannot be compared in terms of accuracy, as all research is regional studies and do not involve data from the multi region. The logistic regression is prevalent in the research on risk factors of readmission post-COVID-19 admission, despite each of the research coming out with different outcomes. From the word cloud, age is the most dominant risk factor of readmission, followed by diabetes, high length of stay, COPD, CKD, liver disease, metastatic disease, and CAD. A few future research directions has been proposed, including the utilization of machine learning in statistical analysis, investigation on dominant risk factors, experimental design on interventions to curb dominant risk factors and increase the scale of data collection from single centered to multi centered.


Subject(s)
COVID-19 , Patient Readmission , COVID-19/epidemiology , Humans , Logistic Models , Machine Learning , Risk Factors , United States
20.
Psychosom Med ; 83(4): 368-372, 2021 05 01.
Article in English | MEDLINE | ID: covidwho-1931979

ABSTRACT

OBJECTIVE: Infectious diseases can cause psychological changes in patients. This study aimed to evaluate the prevalence and related risk factors for anxiety and depression in patients with COVID-19. METHODS: A cross-sectional study was performed on patients with COVID-19 admitted to the Sino-French New City branch of Wuhan Tongji Hospital from January to February 2020. The Zung Self-Rating Anxiety and Depression Scales were used to evaluate the prevalence of anxiety and depression. Demographic, clinical, and sociological data were also collected. Multivariable logistic regression analysis was used to identify independent risk factors of anxiety and depression in patients with COVID-19. RESULTS: In the current study, 183 patients were enrolled (mean age = 53 ± 9 years; 41.1% women). The prevalences of anxiety and depression were 56.3% and 39.3%, respectively. Logistic regression analysis revealed that older age, female sex, being divorced or widowed, COVID-19 disease duration, renal disease, and depression were identified as independent risk factors for anxiety in patients with COVID-19. Factors that were associated with depression were female sex, being widowed, COVID-19 disease duration, and anxiety. CONCLUSIONS: This study demonstrates a high prevalence of anxiety and depression in patients with COVID-19 at the peak of the epidemic in Wuhan, China. The identification of demographic, clinical, and social factors may help identify health care professionals to provide psychological care as part of treatment for patients with COVID-19 and other life-threatening infectious diseases.


Subject(s)
Anxiety/epidemiology , COVID-19/psychology , Depression/epidemiology , Anxiety/etiology , COVID-19/complications , China/epidemiology , Cross-Sectional Studies , Depression/etiology , Female , Humans , Logistic Models , Male , Middle Aged , Prevalence , Psychiatric Status Rating Scales , Risk Factors
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