Is there a clinically significant seasonal component to hospital admissions for atrial fibrillation?

BACKGROUND: Atrial fibrillation is a common cardiac dysrhythmia, particularly in the elderly. Recent studies have indicated a statistically significant seasonal component to atrial fibrillation hospitalizations. METHODS: We conducted a retrospective population cohort study using time series analysis to evaluate seasonal patterns of atrial fibrillation hospitalizations for the province of Ontario for the years 1988 to 2001. Five different series methods were used to analyze the data, including spectral analysis, X11, R-Squared, autocorrelation function and monthly aggregation. RESULTS: This study found evidence of weak seasonality, most apparent at aggregate levels including both ages and sexes. There was dramatic increase in hospitalizations for atrial fibrillation over the years studied and an age dependent increase in rates per 100,000. Overall, the magnitude of seasonal difference between peak and trough months is in the order of 1.4 admissions per 100,000 population. The peaks for hospitalizations were predominantly in April, and the troughs in August. CONCLUSIONS: Our study confirms statistical evidence of seasonality for atrial fibrillation hospitalizations. This effect is small in absolute terms and likely not significant for policy or etiological research purposes

Simplicity within complexity: Seasonality and predictability of hospital admissions in the province of Ontario 1988–2001, a population-based analysis

BACKGROUND: Seasonality is a common feature of communicable diseases. Less well understood is whether seasonal patterns occur for non-communicable diseases. The overall effect of seasonal fluctuations on hospital admissions has not been systematically evaluated. METHODS: This study employed time series methods on a population based retrospective cohort of for the fifty two most common causes of hospital admissions in the province of Ontario from 1988–2001. Seasonal patterns were assessed by spectral analysis and autoregressive methods. Predictive models were fit with regression techniques. RESULTS: The results show that 33 of the 52 most common admission diagnoses are moderately or strongly seasonal in occurrence; 96.5% of the predicted values were within the 95% confidence interval, with 37 series having all values within the 95% confidence interval. CONCLUSION: The study shows that hospital admissions have systematic patterns that can be understood and predicted with reasonable accuracy. These findings have implications for understanding disease etiology and health care policy and planning

Autoregression as a means of assessing the strength of seasonality in a time series

BACKGROUND: The study of the seasonal variation of disease is receiving increasing attention from health researchers. Available statistical tests for seasonality typically indicate the presence or absence of statistically significant seasonality but do not provide a meaningful measure of its strength. METHODS: We propose the coefficient of determination of the autoregressive regression model fitted to the data ([Image: see text]) as a measure for quantifying the strength of the seasonality. The performance of the proposed statistic is assessed through a simulation study and using two data sets known to demonstrate statistically significant seasonality: atrial fibrillation and asthma hospitalizations in Ontario, Canada. RESULTS: The simulation results showed the power of the [Image: see text] in adequately quantifying the strength of the seasonality of the simulated observations for all models. In the atrial fibrillation and asthma datasets, while the statistical tests such as Bartlett's Kolmogorov-Smirnov (BKS) and Fisher's Kappa support statistical evidence of seasonality for both, the [Image: see text] quantifies the strength of that seasonality. Corroborating the visual evidence that asthma is more conspicuously seasonal than atrial fibrillation, the calculated [Image: see text] for atrial fibrillation indicates a weak to moderate seasonality ([Image: see text] = 0.44, 0.28 and 0.45 for both genders, males and females respectively), whereas for asthma, it indicates a strong seasonality ([Image: see text] = 0.82, 0.78 and 0.82 for both genders, male and female respectively). CONCLUSIONS: For the purposes of health services research, evidence of the statistical presence of seasonality is insufficient to determine the etiologic, clinical and policy relevance of findings. Measurement of the strength of the seasonal effect, as can be determined using the [Image: see text] technique, is also important in order to provide a robust sense of seasonality

Seasonality of primary care utilization for respiratory diseases in Ontario: A time-series analysis

<p>Abstract</p> <p>Background</p> <p>Respiratory diseases represent a significant burden in primary care. Determining the temporal variation of the overall burden of respiratory diseases on the health care system and their potential causes are keys to understanding disease dynamics in populations and can contribute to the rational management of health care resources.</p> <p>Methods</p> <p>A retrospective, cross-sectional time series analysis was used to assess the presence and strength of seasonal and temporal patterns in primary care visits for respiratory diseases in Ontario, Canada, for a 10-year period from January 1, 1992 to December 31, 2002. Data were extracted from the Ontario Health Insurance Plan database for people who had diagnosis codes for chronic obstructive pulmonary disease, asthma, pneumonia, or upper respiratory tract infections.</p> <p>Results</p> <p>The results illustrate a clear seasonal pattern in visits to primary care physicians for all respiratory conditions, with a threefold increase in visits during the winter. Age and sex-specific rates show marked increases in visits of young children and in female adults. Multivariate time series methods quantified the interactions among primary care visits, and Granger causality criterion test showed that the respiratory syncytial virus (RSV) and influenza virus influenced asthma (p = 0.0060), COPD (p = 0.0038), pneumonia (p = 0.0001), and respiratory diseases (p = 0.0001).</p> <p>Conclusion</p> <p>Primary care visits for respiratory diseases have clear predictable seasonal patterns, driven primarily by viral circulations. Winter visits are threefold higher than summer troughs, indicating a short-term surge on primary health service demands. These findings can aid in effective allocation of resources and services based on seasonal and specific population demands.</p

Sentinel monitoring of activity of out-of-hours services in Norway in 2007: an observational study

<p>Abstract</p> <p>Background</p> <p>In Norway, no valid activity statistics from the primary health care out-of-hours services or the pre-hospital emergency health care system have previously been available.</p> <p>Methods</p> <p>The National Centre for Emergency Primary Health Care has initiated an enterprise called "The Watchtowers" which consists of a representative sample of seven casualty clinics covering 18 Norwegian municipalities. The purpose of the project is to provide routine information over several years, which will enable monitoring, evaluation and comparison of the activities in the out-of-hours services. This paper presents data from 2007, the first full calendar year for the Watchtowers, analyzes some differences in user patterns for the seven casualty clinics involved, and estimates national figures for the use of casualty clinics and out-of-hours services in Norway.</p> <p>Results</p> <p>A total of 85 288 contacts were recorded during 2007 [399 per 1 000 inhabitants] of which 64 846 contacts were considered non-urgent [76.6%]. There were 53 467 consultations by a doctor [250 per 1 000], 8 073 telephone consultations by doctor [38 per 1 000], 2 783 home visits and call-outs by doctor [13 per 1000] and 20 502 contacts managed by nurses on their own [96 per 1000]. The most common mode of contact was by telephone. Women, young children and elderly had the highest rates of contact.</p> <p>Conclusion</p> <p>Norway has a high rate of contacts to the out-of-hours services compared with some other countries with available data. Valid national figures and future research of these services are important both for local services and policy makers.</p

A retrospective population based trend analysis on hospital admissions for lower respiratory illness among Swedish children from 1987 to 2000

BACKGROUND: Data relating to hospital admissions of very young children for wheezing illness have been conflicting. Our primary aim was to assess whether a previous increase in hospital admissions for lower respiratory illness had continued in young Swedish children. We have included re-admissions in our analyses in order to evaluate the burden of lower respiratory illness in very young children. We have also assessed whether changes in the labelling of symptoms have affected the time trend. METHODS: A retrospective, population based study was conducted to assess the time trend in admissions and re-admissions for lower respiratory illness. Data were obtained from the Swedish Hospital Discharge Register for all children with a first hospital admission before nine years of age, a total of 109,176 children. The register covers more than 98% of all hospital admissions in Sweden. The coding of diagnoses was based on ICD-9 from 1987 to 1996 and ICD-10 from 1997. RESULTS: The first admission rates declined significantly in children with a first admission after two years of age. However, an increasing admission trend was observed in children aged less than one year and 35% of first admissions occurred in this age group. The annual increase was 3.8% (95% CI 1.3–6.3) in boys and 5.0% (95% CI 2.4–7.6) in girls. A diagnostic shift appeared to occur when ICD-10 was introduced in 1997. The asthma and pneumonia admission rate in children aged less than one year levelled off, whereas the increase in admissions for bronchitis continued. The re-admission rates for asthma decreased and the probability of re-admission was higher in boys. National drug statistics demonstrated a substantial increase in the delivery of inhaled steroids to all age groups but most prescriptions occurred to children aged one year or more. CONCLUSION: Hospital admissions for lower respiratory illness are still increasing in children aged <1 year. Our findings are in line with other recent studies suggesting a change in the responsiveness to viral infections in very young children, but changes in admission criteria cannot be excluded. An increased use of inhaled steroids may have contributed to decreasing re-admission rates

Predictors of health decline in older adults with pneumonia: findings from the Community Acquired Pneumonia Impact Study

<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to identify predictors of health decline among older adults with clinically diagnosed community acquired pneumonia (CAP). It was hypothesized that older adults with CAP who had lower levels of social support would be more likely to report a decline in health.</p> <p>Methods</p> <p>A telephone survey was used to collect detailed information from older adults about their experiences with CAP. A broader determinants of health framework was used to guide data collection. This was a community wide study with participants being recruited from all radiology clinics in one Ontario community.</p> <p>Results</p> <p>The most important predictors of a health decline included: two symptoms (no energy; diaphoresis), two lifestyle variables (being very active; allowing people to smoke in their home), one quality of life variable (little difficulty in doing usual daily activities) and one social support variable (having siblings).</p> <p>Conclusions</p> <p>A multiplicity of factors was found to be associated with a decline in health among older adults with clinically diagnosed CAP. These findings may be useful to physicians, family caregivers and others for screening older adults and providing interventions to help ensure positive health outcomes.</p

Pneumonia and poverty: a prospective population-based study among children in Brazil

<p>Abstract</p> <p>Background</p> <p>Children in developing country suffer the highest burden of pneumonia. However, few studies have evaluated associations between poverty and pneumonia.</p> <p>Methods</p> <p>A prospective population-based study on pneumonia was carried out as part of the Latin America Epidemiological Assessment of Pneumococcus (LEAP study). Chest x-rays were obtained for children one to 35 months old with suspected pneumonia presenting to emergency care centers and hospital emergency rooms in Goiania, Brazil. Chest radiographs were evaluated according to WHO guidelines. Clustering of radiologically-confirmed pneumonia were evaluated using a Poisson-based spatial scan statistic. Associations between census socioeconomic indicators and pneumonia incidence rates were analyzed using generalized linear models.</p> <p>Results</p> <p>From May, 2007 to May, 2009, chest radiographs were obtained from 11 521 children with clinical pneumonia; 3955 episodes were classified as radiologically-confirmed. Incidence rates were significantly higher in very low income areas (4825.2 per 10⁵) compared to high income areas (1637.3 per 10⁵). Spatial analysis identified clustering of confirmed pneumonia in Western (RR 1.78; p = 0.001) and Southeast (RR 1.46; p = 0.001) regions of the city, and clustering of hospitalized pneumonia in the Western region (RR 1.69; p = 0.001). Lower income households and illiteracy were associated with pneumonia incidence.</p> <p>Conclusions</p> <p>In infants the risk of developing pneumonia is inversely associated with the head of household income and with the woman educational level. Areas with deprived socioeconomic conditions had higher incidence of pneumonia and should be targeted for high vaccination coverage.</p

Local Spatial and Temporal Processes of Influenza in Pennsylvania, USA: 2003–2009

Background: Influenza is a contagious respiratory disease responsible for annual seasonal epidemics in temperate climates. An understanding of how influenza spreads geographically and temporally within regions could result in improved public health prevention programs. The purpose of this study was to summarize the spatial and temporal spread of influenza using data obtained from the Pennsylvania Department of Health's influenza surveillance system. Methodology and Findings: We evaluated the spatial and temporal patterns of laboratory-confirmed influenza cases in Pennsylvania, United States from six influenza seasons (2003-2009). Using a test of spatial autocorrelation, local clusters of elevated risk were identified in the South Central region of the state. Multivariable logistic regression indicated that lower monthly precipitation levels during the influenza season (OR = 0.52, 95% CI: 0.28, 0.94), fewer residents over age 64 (OR = 0.27, 95% CI: 0.10, 0.73) and fewer residents with more than a high school education (OR = 0.76, 95% CI: 0.61, 0.95) were significantly associated with membership in this cluster. In addition, time series analysis revealed a temporal lag in the peak timing of the influenza B epidemic compared to the influenza A epidemic. Conclusions: These findings illustrate a distinct spatial cluster of cases in the South Central region of Pennsylvania. Further examination of the regional transmission dynamics within these clusters may be useful in planning public health influenza prevention programs. © 2012 Stark et al