Effect of the Period From COVID-19 Symptom Onset to Confirmation on Disease Duration: Quantitative Analysis of Publicly Available Patient Data (Preprint)

BACKGROUND In general, early intervention in disease based on early diagnosis is considered to be very important for improving health outcomes. However, there is still insufficient evidence regarding how medical care that is based on the early diagnosis of confirmed cases can affect the outcome of COVID-19 treatment. OBJECTIVE We aimed to investigate the effect of the duration from the onset of clinical symptoms to confirmation of COVID-19 on the duration from the onset of symptoms to the resolution of COVID-19 (release from quarantine). METHODS For preliminary data collection, we performed data crawling to extract data from social networks, blogs, and official websites operated by local governments. We collected data from the 4002 confirmed cases in 33 cities reported up to May 31, 2020, for whom sex and age information could be verified. Subsequently, 2494 patients with unclear symptom onset dates and 1349 patients who had not been released or had no data about their release dates were excluded. Thus, 159 patients were finally included in this study. To investigate whether rapid confirmation reduces the prevalence period, we divided the duration from symptom onset to confirmation into quartiles of ≤1, ≤3, ≤6, and ≥7 days, respectively. We investigated the duration from symptom onset to release and that from confirmation to release according to these quartiles. Furthermore, we performed multiple regression analysis to investigate the effects of rapid confirmation after symptom onset on the treatment period, duration of prevalence, and duration until release from isolation. RESULTS We performed multiple regression analysis to investigate the association between rapid confirmation after symptom onset and the total prevalence period (faster release from isolation). The time from symptom onset to confirmation showed a negative association with the time from confirmation to release (<i>t</i>₁<i>=−</i>3.58; <i>P</i>&lt;.001) and a positive association with the time from symptom onset to release (<i>t</i>₁=5.86; <i>P</i>&lt;.001); these associations were statistically significant. CONCLUSIONS The duration from COVID-19 symptom onset to confirmation date is an important variable for predicting disease prevalence, and these results support the hypothesis that a short duration of symptom onset to confirmation can reduce the time from symptom onset to release.

Effect of Single Session of High Intensity Interval Exercise on Some Immune and Inflammatory Factors in Male Athletes and the Risk of Infection to Coronavirus

Introduction: High Intensity exercise is one of the effective factors on immune and inflammatory factors. The purpose of this study was to determine the single session of high intensity interval exercise (CrossFit) on levels of leukocytes, neutrophils, lymphocytes, monocytes, lactic acid and C- reactive protein (CRP) of male athletes to make decision for doing this exercise in coronavirus prevalence period. Methods: In this Causal-comparative study, 32 male athletes were selected as participants (with mean of age 26.9±4.7 year, height 177 ± 5 cm, weight 80.7±6.4 kg). Exercise session included a 400-meter running on treadmill, triple dead lift movement, pull-up (30 repetition), swing of kettlebell (30 kg) and throwing of 20 sand balls. Blood sampling, CBC and biochemistry auto analyzer tests were used for measuring leukocytes, lactic acid and CRP. In addition, ANOVA with repeated measure, Friedman, Wil-kaksun and Bonferroni post hoc tests were used to examine the differences between variables in resting position, post-exercise, and after modify the results by consideration of plasma volume changes using SPSS version 16 software. Results: The results showed significant increase in lactic acid (P<0.001), CRP (P=0.006), leukocytes (P<0.001) and lymphocytes (P=0.001), but the increase of monocytes was no significant (P=0.705). In addition, the results of study showed significant decrease in neutrophils (P=0.005) and plasma volume (P<0.001). Furthermore, the significant results of some indices were removed by consideration of plasma volume change (P>0.05). Conclusion: The single session of high intensity interval exercise makes disorder in immune and inflammation responses in athletes. Therefore, it has been suggested not to do intensive exercise at coronavirus prevalence period and consider enough time for recovery after high intensity exercise.

Epidemiology of Homelessness Among Veterans

Accurately estimating the incidence, prevalence, and composition of the population of Veterans who experience homelessness is important for planning and evaluating prevention and intervention strategies. However, several methodological considerations exist that are relevant to establishing and interpreting epidemiological estimates of homelessness among Veterans. These issues include the conceptual definition of homeless and Veteran status; the various time frames used in enumeration efforts and the implications of these time frames on resulting estimates; and the strengths and limitations of primary and administrative data sources. This chapter discusses methodological issues and present a national epidemiological estimates based on various sources and methodologies. Recent point prevalence, period prevalence, and incidence estimates are summarized, as are segmentation of estimates by demographic, geographic, and housing status characteristics, and trends over time. In the past decade, several indicators have suggested that homelessness among Veterans has decreased substantially. Since 2009, point-in-time estimates have declined nearly 50%, and 1-year estimates have declined by 11%. Despite these improvements, Veterans continue to be overrepresented among the population of homeless adults in the United States.

Abstract MP56: Misclassification of Incident Heart Failure Hospitalizations in Administrative Claims Data: The Atherosclerosis Risk in Communities (ARIC) Study.

Background: Estimation of disease incidence from administrative data requires an adequate look-back (prevalence) period to exclude pre-existing conditions from the incidence risk set. We characterized optimal lengths of the prevalence period to minimize misclassification of incident heart failure (HF) hospitalization, a proxy for incident HF. Methods: Data for participants of the ARIC Study (a prospective longitudinal cohort of 15,792 individuals sampled from 4 US communities) were linked with CMS Medicare claims from the years 2000-2012. We included only participants with >36 months of continuous CMS Medicare fee for service (FFS) enrollment. Each participant’s time-in-observation was divided into two phases. The first 36 months were the prevalence period. Observation time after an index date 36 months following the date of enrollment was the incidence period. HF hospitalizations were identified from CMS MedPAR records using ICD-9 code 428.xx in any position. Patients were classified as having a HF hospitalization in (a) both the prevalence and incidence periods, (b) in the prevalence period only, (c) in the incidence period only, or (d) neither. Incident HF was defined as the first HF hospitalization in the incidence period not preceded by a HF hospitalization in the prevalence period. The proportion of events misclassified as incident HF hospitalization was estimated from incremental reductions of the prevalence period to start 36, 30, 24, 18, 12, or 6 months before the index date. The impact of misclassification was estimated as differences in incidence per 1,000 patients at risk. Results: Of 11,054 ARIC participants enrolled in Medicare FFS, 9,568 met the study inclusion criteria. A total of 1,129 incident HF hospitalizations were identified based on the 36 month prevalence period, considered as the referent (incidence rate 118 HF hospitalizations per 1,000 patients at risk). Shortening the prevalence period to 24 months increased the HF incidence rate to 123 per 1,000, overestimating the number of incident HF hospitalizations by 4.2% while retaining over 90% of the sample. A 12 month prevalence period yielded an overestimation of the number of incident HF hospitalizations by 11% (incidence rate 129 per 1,000 patients at risk) while retaining 95% of the sample. Conclusions: Selection of too short of a prevalence period to define incident hospitalized HF from CMS Medicare claims data can introduce substantial misclassification. Consideration of several prevalence periods indicates that a 24 month prevalence period reduces the potential for bias in the estimation of incident hospitalized HF while retaining most observations.

Prevalence and distribution of pain in children

There has been a paucity of studies that have attempted to determine the prevalence and distribution of pain (acute or chronic) in large groups of infants and children across multiple settings. Rather, there is a preponderance of single-site studies that report local prevalence and distribution of paediatric pain data. Although one could extrapolate these results to gain a broader sense of pain in children, this approach would garner only a general estimate at best. Furthermore, studies of pain prevalence vary as to the pain and prevalence definitions used, the reporting period (i.e. point prevalence, period prevalence), and stratification by duration of involvement, which makes comparison of findings challenging. In this chapter, definitions of prevalence and acute and chronic pain will be clarified and used to explore the prevalence and distribution of pain in hospitals and in community health care settings for infants and children. Recommendations for clinical practice and future research will be proposed.

Comorbidity and Boundaries of Affective Disorders with Anxiety Disorders and Substance Misuse: Results of an International Task Force

Associations between affective disorders, anxiety disorders, and substance use disorders were examined in epidemiological studies conducted in Germany, Switzerland, Puerto Rico, and the mainland US. There was a remarkable degree of similarity across studies in the magnitude and type of specific disorders associated with the affective disorders. Comorbidity with affective disorders was greater for the anxiety disorders than for substance misuse. Panic disorder was the subtype of anxiety that was most highly comorbid with depression. Social phobia was the specific phobic type with the strongest association with the affective disorders. The magnitude of associations between substance misuse and affective disorders generally was quite low and less consistent across sites. No major differences were found in the patterns of comorbidity by gender or age group, affective subtype or prevalence period. The onset of anxiety disorders generally preceded that of depression, whereas alcohol misuse was equally likely to pre- or post-date the onset of affective disorders. Finally, comorbidity was associated with an elevation in treatment ratesacross all sites, confirming Berkson's paradox on an international level.