scholarly journals Incidence, duration and risk factors associated with missed opportunities to diagnose herpes simplex encephalitis: A population-based longitudinal study

2021 ◽  
Author(s):  
Aaron C Miller ◽  
Scott Koeneman ◽  
Alan T Arakkal ◽  
Joseph E Cavanaugh ◽  
Philip M Polgreen
Keyword(s):  
Risk Factors ◽  
Herpes Simplex ◽  
Herpes Simplex Encephalitis ◽  
Population Based ◽  
Missed Opportunities ◽  
Potential Risk Factors ◽  
Number Of Visits ◽  
Using Data ◽  
Missed Diagnostic Opportunities ◽  
Diagnostic Delays

Abstract Background Delays in diagnosing herpes simplex encephalitis (HSE) are associated with increased morbidity and mortality. The purpose of this paper is to determine the frequency and duration of diagnostic delays for HSE and risk factors for diagnostic delays. Methods Using data from the IBM Marketscan Databases, 2001-2017, we performed a retrospective cohort study of patients with HSE. We estimated the number of visits with HSE-related symptoms prior to diagnosis that would be expected to occur in the absence of delays and compared this estimate to the observed pattern of visits. Next, we used a simulation-based approach to compute the number of visits representing a delay, the number of missed diagnostic opportunities per case patient and the duration of delays. We also investigated potential risk factors for delays. Results We identified 2667 patients diagnosed with HSE. We estimated 45.9% (95% CI 43.6%-48.1%) of patients experienced at least one missed opportunity; 21.9% (95% CI 17.3%-26.3%) of these patients had delays lasting >7 days. Risk factors for delays included being seen only in the emergency department, age < 65, a history of sinusitis or schizophrenia. Conclusions Many patients with HSE experience multiple missed diagnostic opportunities prior to diagnosis.

scholarly journals Incidence, duration and risk factors associated with delayed and missed diagnostic opportunities related to tuberculosis: a population-based longitudinal study

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e045605
Author(s):  
Aaron C Miller ◽  
Alan T Arakkal ◽  
Scott Koeneman ◽  
Joeseph E Cavanaugh ◽  
Alicia K Gerke ◽  
...  
Keyword(s):  
Risk Factors ◽  
Pulmonary Tuberculosis ◽  
Diagnostic Delay ◽  
Secondary Outcome ◽  
Patient Specific ◽  
Missed Opportunities ◽  
Number Of Patients ◽  
Number Of Visits ◽  
Missed Diagnostic Opportunities ◽  
Missed Opportunity

ObjectivesMissed opportunities to diagnose tuberculosis are costly to patients and society. In this study, we (1) estimate the frequency and duration of diagnostic delays among patients with active pulmonary tuberculosis and (2) determine the risk factors for experiencing a diagnostic delay.DesignA retrospective cohort study of patients with tuberculosis using longitudinal healthcare encounters prior to diagnosis.SettingCommercially insured enrollees from the Commercial Claims and Encounters or Medicare Supplemental IBM Marketscan Research Databases, 2001–2017.ParticipantsAll patients diagnosed with, and receiving treatment for, pulmonary tuberculosis, enrolled at least 365 days prior to diagnosis.Primary and secondary outcome measuresWe estimated the number of visits with tuberculosis-related symptoms prior to diagnosis that would be expected to occur in the absence of delays and compared this estimate to the observed pattern. We computed the number of visits representing a delay and used a simulation-based approach to estimate the number of patients experiencing a delay, number of missed opportunities per patient and duration of delays (ie, time between diagnosis and earliest missed opportunity). We also explored risk factors for missed opportunities.ResultsWe identified 3371 patients diagnosed and treated for active tuberculosis that could be followed up for 1 year prior to diagnosis. We estimated 77.2% (95% CI 75.6% to 78.7%) of patients experienced at least one missed opportunity; of these patients, an average of 3.89 (95% CI 3.65 to 4.14) visits represented a missed opportunity, and the mean duration of delay was 31.66 days (95% CI 28.51 to 35.11). Risk factors for delays included outpatient or emergency department settings, weekend visits, patient age, influenza season presentation, history of chronic respiratory symptoms and prior fluoroquinolone use.ConclusionsMany patients with tuberculosis experience multiple missed diagnostic opportunities prior to diagnosis. Missed opportunities occur most commonly in outpatient settings and numerous patient-specific, environment-specific and setting-specific factors increase risk for delays.

Abstract P625: Rate of Hemorrhagic Transformation After Ischemic Stroke and Associated Risk Factors: The Greater Cincinnati/Northern Kentucky Stroke Study (GCNKSS)

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Robert J Stanton ◽  
Eleni Antzoulatos ◽  
Elisheva R Coleman ◽  
Felipe De Los Rios La Rosa ◽  
Stacie L Demel ◽  
...  
Keyword(s):  
Risk Factors ◽  
Ischemic Stroke ◽  
Case Fatality ◽  
Population Based ◽  
Hemorrhagic Transformation ◽  
Incidence Rates ◽  
Icd 10 ◽  
Potential Risk Factors ◽  
Adjusted Rate ◽  
Associated Risk Factors

Background: Hemorrhagic transformation (HT) of ischemic stroke can have devastating consequences, leading to longer hospitalizations, increased morbidity and mortality. We sought to identify the rate of HT in stroke patients not treated with tPA within a large, biracial population. Methods: The GCNKSS is a population-based stroke epidemiology study from five counties in the Greater Cincinnati region. During 2015, we captured all hospitalized strokes by screening ICD-9 codes 430-436 and ICD-10 codes I60-I68, and G45-46. Study nurses abstracted all potential cases and physicians adjudicated cases, including classifying the degree of HT. Patients treated with thrombolytics were excluded. Incidence rates per 100,000 and associated 95% confidence intervals (CI) were estimated for HT cases, age and sex adjusted to the 2000 US population. Multiple logistic regression was used to examine risk factors associated with HT. Results: In 2015, there were 2301 ischemic strokes included in the analysis. Of these 104 (4.5%) had HT; 23 (22.1%) symptomatic, 55 (52.9%) asymptomatic and 26 (25%) unknown. Documented reasons for not receiving tPA in these patients were: time (71, 68.3%), anticoagulant use (1, 1.0%), other (18,17.3%) and unknown (14, 13.5%), which were not significantly different compared to those without HT. Only 29/104 (18.3%) had HT classified as PH-1 or PH-2. The age, sex and race-adjusted rate of HT was 9.8 (7.9, 11.6) per 100,000. The table shows rates of potential risk factors and the adjusted odds of developing HT. 90 day all-cause case fatality for patients with HT was significantly higher, 27.9% vs. 15.7%, p<0.0001. Conclusion: We found that 4.5% of non-tPA treated IS patients had HT. These patients had more severe strokes, were more likely to have abnormal coagulation tests or anticoagulant use, and were more likely to die within 90 days. We also report the first population-based incidence rate of HT in non-tPA treated of 9.8/100,000, a rate similar to the incidence of SAH.

Abstract P249: Incident Sleep-Disordered Breathing is Associated with Obesity: Penn State Child Cohort

Circulation ◽  
2013 ◽  
Vol 127 (suppl_12) ◽  
Author(s):  
Edward O Bixler ◽  
Alexandros N Vgontzas ◽  
Duanping Liao ◽  
Susan Calhoun ◽  
Julio Fernandez-Mendoza ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Sleep Disordered Breathing ◽  
Population Sample ◽  
Population Based ◽  
Penn State ◽  
Potential Risk Factors ◽  
State Child ◽  
Disordered Breathing

Objectives: To study the epidemiology of sleep-disordered breathing (SDB) in adolescents, which has received little attention. Methods: The Penn State Child Cohort (PSCC) is a representative general population sample of 700 children aged 5-12 years. Our preliminary results are based on an average 8 year follow up of the initial 300 prospective subjects (~43%) from this ongoing cohort study. A logistic regression was used to assess the association between potential risk factors and incident SDB. Results: The mean age at the 8-year follow up examination was 17.2 ± 0.1 years, with an average BMI percentile of 66.6 ± 1.6 and 56.5% boys. At baseline 1.5% of this subsample had SDB, defined by Apnea Hypopnia Index (AHI > 5 /hour). Surprisingly, there was no persistence of SDB. Eight-year incident SDB was 10.5%. The average AHI in those with incident SDB was 12.7 with a maximum of 92.4. Incident SDB was similar for girls (7.8%) and boys (12.7%). Those with SDB were older than those without (18.7 vs 17.0 years, P<0.001) and girls with SDB were older than boys with SDB (20.0 vs 18.0 years, P=0.002). Those with incident SDB tended to have a greater change in BMI percentile (8.2 vs 1.8, P = 0.143) during the follow up and slightly higher minority representation (25.8% vs 21.9%, P=0.655). A logistic regression model identified three variables that were associated with incident SDB, controlling for baseline AHI: age (OR = 1.5 (1.3, 1.9) P<0.001), male (OR= 2.5 (1.11,10.00) P=0.021), and [[Unable to Display Character: &#8710;]]BMIPCT (OR=1.2(1.02, 1.5) P=0.032). Conclusion: In this population based sample of adolescents, the 8-year incidence of SDB was high (10.5%), whereas childhood SDB did not persist into adolescence. Further, the results indicate that risk factors for incident SDB in adolescents are age, male and the development of obesity.

scholarly journals Mood Disorders in Late Life: A Population-based Analysis of Prevalence, Risk Factors, and Consequences in Community-dwelling Older Adults in Ontario: Troubles de l’humeur en âge avancé : Une analyse dans la population de la prévalence, des facteurs de risque et des conséquences chez des adultes âgés vivant en milieu communautaire en Ontario

2020 ◽  
Vol 65 (9) ◽  
pp. 630-640
Author(s):  
Rachel Strauss ◽  
Paul Kurdyak ◽  
Richard H. Glazier
Keyword(s):  
Risk Factors ◽  
Mood Disorder ◽  
Mood Disorders ◽  
Potential Risk ◽  
Late Life ◽  
Population Based ◽  
Community Dwelling ◽  
Self Report ◽  
Term Care ◽  
Potential Risk Factors

Objective: Mental health issues in late life are a growing public health challenge as the population aged 65 and older rapidly increases worldwide. An updated understanding of the causes of mood disorders and their consequences in late life could guide interventions for this underrecognized and undertreated problem. We undertook a population-based analysis to quantify the prevalence of mood disorders in late life in Ontario, Canada, and to identify potential risk factors and consequences. Method: Individuals aged 65 or older participating in 4 cycles of a nationally representative survey were included. Self-report of a diagnosed mood disorder was used as the outcome measure. Using linked administrative data, we quantified associations between mood disorder and potential risk factors such as demographic/socioeconomic factors, substance use, and comorbidity. We also determined associations between mood disorders and 5-year outcomes including health service utilization and mortality. Results: The prevalence of mood disorders was 6.1% (4.9% among males, 7.1% among females). Statistically significant associations with mood disorders included younger age, female sex, food insecurity, chronic opioid use, smoking, and morbidity. Individuals with mood disorders had increased odds of all consequences examined, including placement in long-term care (adjusted odds ratio [OR] =2.28; 95% confidence interval [CI], 1.71 to 3.02) and death (adjusted OR = 1.35; 95% CI, 1.13 to 1.63). Conclusions: Mood disorders in late life were strongly correlated with demographic and social/behavioral factors, health care use, institutionalization, and mortality. Understanding these relationships provides a basis for potential interventions to reduce the occurrence of mood disorders in late life and their consequences.

One size fits all? Why we need more sophisticated analytical methods in the explanation of trajectories of cognition in older age and their potential risk factors

2009 ◽  
Vol 22 (2) ◽  
pp. 291-299 ◽  
Author(s):  
Graciela Muniz Terrera ◽  
Carol Brayne ◽  
Fiona Matthews ◽  
Keyword(s):  
Risk Factors ◽  
Cognitive Impairment ◽  
Cognitive Decline ◽  
Potential Risk ◽  
Analytical Methods ◽  
Cognitive Change ◽  
Population Based ◽  
Growth Mixture ◽  
Potential Risk Factors ◽  
Rate Of Decline

ABSTRACTBackground: Cognitive decline in old age varies among individuals. The identification of groups of individuals with similar patterns of cognitive change over time may improve our ability to see whether the effect of risk factors is consistent across groups.Methods: Whilst accounting for the missing data, growth mixture models (GMM) were fitted to data from four interview waves of a population-based longitudinal study of aging, the Cambridge City over 75 Cohort Study (CC75C). At all interviews global cognition was assessed using the Mini-mental State Examination (MMSE).Results: Three patterns were identified: a slow decline with age from a baseline of cognitive ability (41% of sample), an accelerating decline from a baseline of cognitive impairment (54% of sample) and a steep constant decline also from a baseline of cognitive impairment (5% of sample). Lower cognitive scores in those with less education were seen at baseline for the first two groups. Only in those with good performance and steady decline was the effect of education strong, with an increased rate of decline associated with poor education. Good mobility was associated with higher initial score in the group with accelerating change but not with rate of decline.Conclusion: Using these analytical methods it is possible to detect different patterns of cognitive change with age. In this investigation the effect of education differs with group. To understand the relationship of potential risk factors for cognitive decline, careful attention to dropout and appropriate analytical methods, in addition to long-term detailed studies of the population points, are required.

scholarly journals SARS-CoV-2 infection in pregnancy in Denmark - characteristics and outcomes after confirmed infection in pregnancy: a nationwide, prospective, population-based cohort study

2021 ◽  
Author(s):  
Anna JM Aabakke ◽  
Lone Krebs ◽  
Tanja G Petersen ◽  
Frank S Kjeldsen ◽  
Giulia Corn ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Hospital Admission ◽  
Severe Infection ◽  
Population Based ◽  
Neonatal Outcomes ◽  
Foreign Born ◽  
Hospitalised Patients ◽  
Using Data ◽  
In Pregnancy

Introduction Assessing the risk factors for and consequences of infection with SARS-CoV-2 during pregnancy is essential to guide clinical guidelines and care. Previous studies on the influence of SARS-CoV-2 infection in pregnancy have been among hospitalised patients, which may have exaggerated risk estimates of severe outcomes because all cases of SARS-CoV-2 infection in the pregnant population were not included. The objectives of this study were to identify risk factors for and outcomes after SARS-CoV-2 infection in pregnancy independent of severity of infection in a universally tested population, and to identify risk factors for and outcomes after severe infection requiring hospital admission. Material and Methods This was a prospective population-based cohort study in Denmark using data from the Danish National Patient Register and Danish Microbiology Database and prospectively registered data from medical records. We included all pregnancies between March 1 and October 31, 2020 and compared women with a positive SARS-CoV-2 test during pregnancy to non-infected pregnant women. Cases of SARS-CoV-2 infection in pregnancy were both identified prospectively and through register linkage to secure that all cases were identified and that cases were pregnant during infection. Main outcome measures were pregnancy, delivery, maternal, and neonatal outcomes. Severe infection was defined as hospital admission due to COVID-19. Results Among 82 682 pregnancies, 418 women had SARS-CoV-2 infection during pregnancy, corresponding to an incidence of 5.1 per 1000 pregnancies, 23 (5.5%) of which required hospital admission due to COVID-19. Risk factors for infection were asthma (OR 2.19 [1.41-3.41]) and being foreign born (OR 2.12 [1.70-2.64]). Risk factors for hospital admission due to COVID-19 included obesity (OR 2.74 [1.00-7.51]), smoking (OR 4.69 [1.58-13.90]), infection after gestational age (GA) 22 weeks (GA 22-27 weeks: OR 3.77 [1.16-12.29]; GA 28-36 weeks: OR 4.76 [1.60-14.12]) and having asthma (OR 4.53 [1.39-14.79]). We found no difference in any obstetric or neonatal outcomes. Conclusions Only 1 in 20 women with SARS-CoV-2 infection during pregnancy require admission to hospital due to COVID-19. And severe outcomes of SARS-CoV-2 infection in pregnancy are rare.

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