Time-series Study Research Articles

Tendência das internações por leishmaniose visceral na população brasileira, 2010-2019

Introduction: Visceral leishmaniasis (VL) is a serious parasitic disease with potential evolutionto death. Objective: analyze the trend of hospitalizations for VL in Brazil from 2010 to 2019. Methodology: this is an ecological study of time series, using data from the SUS Hospital Information System (SIH/SUS). The hospitalization rate per Brazilian state was calculated for each year in the selected period. The hospitalization rate trend was analyzed by Prais-Winsten regression using Stata 14.0. Results: In Brazil, 24,259 hospitalizations due to VL were registered between 2010 and 2019. The lowest number of cases occurred in the state of Amapá (4 cases), while the highest number occurred in the state of Maranhão (3,601 cases). Analyzing the hospitalization rates for VL, the highest rates were observed in the state of Tocantins and the lowest rates in Paraná (Table 2). There was an increasing trend of hospitalization for VL in the states of Paraíba, Pernambuco, Alagoas, Rio Grande do Sul and Goiás, and decreasing in the states of São Paulo, Mato Grosso, Mato Grosso do Sul and the Federal District. Conclusion: The trend of hospitalizations was increasing in five states of Brazil and decreasing in four of them. The other Brazilian states showed a stable trend.

Alcohol-related injury hospitalisations in relation to alcohol policy changes, Northern Territory, Australia, 2007-2022: A joinpoint regression analysis.

The Northern Territory (NT) of Australia has the highest rates of alcohol consumption and injury in the country. We aimed to: (i) describe the epidemiology of alcohol-related injury (ARI) hospitalisations in the NT; (ii) estimate the proportion of alcohol involvement in injury hospitalisations; and (iii) consider the influence of alcohol policies on ARI hospitalisation trends. We conducted a retrospective time-series study using coded hospitalisation data from NT public hospitals between 2007 and 2022. ARI hospitalisation was defined combining indicators for injury and acute alcohol use. We undertook descriptive analyses and calculated alcohol involvement against all injury hospitalisations. Annual percent changes (APC) were computed using joinpoint regression to examine the influence of alcohol policies on ARI hospitalisation trends by NT geographical regions (Central Australia and Top End). Alcohol use was associated with 22.6% of all injury hospitalisations. The most common cause of ARI hospitalisations was assault (46%). In Central Australia, a significant trend decline (APC -12.2; p = 0.011) was observed after 2017 following alcohol policies implemented between 2017 and 2018 (Banned Drinkers Register v2; Minimum Unit Price; and Police Auxiliary Liquor Inspectors). Consecutive years with the greatest decrease in Central Australia were 2013-2014 (APC -25.8) and 2018-2019 (APC -35.1); likely influenced by alcohol policies in effect at the time. In the Top End, a non-significant trend decline (APC -26.1; p = 0.186) was observed after 2020. Alcohol policies implemented between 2017 and 2018 were associated with reduced ARI hospitalisations in Central Australia. Alcohol policies that demonstrated reduced harm should be sustained.

Time-decay patterns and irregular disturbance: contrasting roles of abundant and rare microbial communities in dynamic coastal seawater.

The relative importance of rare and abundant taxa in microbial temporal patterns remains debated. Here, we identified taxonomically associated distinct diversity modes of abundant and rare subcommunities from a year-round time-series study in dynamic coastal seawater. We highlighted the significance of the rare subcommunity in maintaining community stability by serving as a repository to offer specialists driven by stochastic processes over time. The abundant subcommunity, by contrast, contributed mainly to temporal rhythmic variations. This study expands the current understanding of the temporal dynamics and stability of coastal microbial communities by revealing distinct variation patterns of subcommunities with different abundances.

Failed/difficult Intubation comparing between pre-COVID-19 and COVID-19 pandemic period using a national insurance claims database and information system of a university hospital

IntroductionEndotracheal intubation can be difficult or even fail under certain patient and anaesthesiologist conditions. During the COVID-19 pandemic a country-wide lockdown policy was enforced in Thailand which stipulated that anaesthesiologists wear personal protective equipment, powered air purifying respirator, or goggles and surgical/N95 mask during the intubation procedure. Thus, an anaesthesiologist’s vision is restricted and grip on the equipment less sure. Under these conditions, the incidence of difficult intubation was expected to increase.MethodsThis time-series study was based on the aggregated age- and sex-standardized monthly incidence of difficult intubation among all intubated patients whose data were recorded in the national insurance claims database and among patients recorded in the records of a university hospital from January 2018 to September 2022. Changes in incidence of difficult intubation following the implementation of a lockdown policy from 26 March 2020 during the COVID-19 pandemic were explored using negative binomial regression and interrupted linear regression time-series analysis.ResultsData of 922,274 individuals in the national database and 95,457 individuals in the university database were retrieved. The overall incidence of difficult intubation in both settings dropped by 25% following lockdown, significantly so in the national database (p < 0.001). At the point of interruption, a significant drop in level was evident in the national data (of 1.682 per thousand per month, P = 0.003) and a non-significant drop at the university level (of 1.118 per thousand per month, P = 0.304).DiscussionThe decreased incidence of difficult intubation during the lockdown period was contrary to expectation but might be related to the deployment solely of anaesthesiologists and more experienced anaesthetic staff using videolaryngoscopes during lockdown following the recommendation for intubation during respiratory disease pandemics.

The effect of heatwave and cold spell on cardiovascular disease mortality in central China, 2018-2022.

A time series study in Hunan province, central of China, from 2018 to 2022, was conducted to test the relationship between heatwave, cold spell and CVD mortality. According to different percentiles of daily mean temperatures and exposure duration, we built 9 kind of definitions for heatwave and cold spell. Distributed lag non-linear model was used to analyze the associations between heatwave, cold spell and CVD mortality, and the attributable fraction (AF) were estimated. The relative risks of CVD mortality associated with heatwave and cold spell varied depending on the definitions, ranging from 1.154 (95% CI: 1.148-1.160) to 1.229 (95% CI: 1.215-1.243) for heatwaves, and from 1.196 (95% CI: 1.192-1.201) to 1.290 (95% CI: 1.282-1.297) for cold spells. Under the definition of 95th percentile with ≥ 4-d duration (P95_4d), the total AF of CVD mortality attributable to heatwave was the largest at 8.43 (95% CI: 7.92-8.94). For the definition of 5th percentile with ≥ 3-d duration (P5_3d), the total AF attributable to cold spell was the largest at 12.96 (95% CI: 12.64-13.28). For heatwave and cold spell, higher CVD mortality risks were observed in females and the elderly over 75 years than males and young people. We found that both heatwave and cold spell could increase the mortality risk of CVD. The results highlight the importance of implementing warning systems for extreme temperature.

Exposure to air pollution and the risk of type II diabetes mellitus: a time-series study.

Environmental factors have been identified as primary risk factors for type 2 diabetes mellitus (T2DM). However, studies on the association between environmental factors and T2DM have mainly focused on morbidity and mortality, which do not fully reflect the disease burden stemming from air pollution. Therefore, we aimed to evaluate the correlation between air pollution and T2DM, including hospital length of stay (LOS) and costs. We collected data on patients with T2DM from three healthcare institutions in Xinxiang from 2016-2021. Data on particulate and gaseous pollutants in Xinxiang and daily meteorological data were collected from national databases. The distribution lag nonlinear model was used to evaluate the correlation between air pollution and the number of inpatients with T2DM, LOS, and hospital costs. Subgroup analyses were conducted to identify potential modifying factors. Overall, 13,797 patients with T2DM were included in our analysis. Within the cumulative lag of 7 days, with every increase of 1 mg/m3 of carbon monoxide (CO) and 10 μg/m3 of 2.5 microns particulate matter, nitrogen dioxide and ozone exhibited significant associations with an increase in diabetes hospitalization risk. CO exhibited adverse effects on LOS on most lag days. Moreover, hospital costs were significantly associated with the attributable fraction of LOS and hospital costs attributed to diabetes. Exposure to air pollutants increased T2DM risk, imposing significant economic and social burdens in Xinxiang, China. Implementing policies to reduce air pollutant exposure may decrease T2DM admissions, costs, and LOS.

Modification of the association between cold spells and cardiovascular disease by changes in natural gas prices: A nationwide time-series study

BackgroundAlthough the association between low ambient temperature and cardiovascular disease (CVD) is well-established, the effect of winter energy prices on this association remains unknown. AimThis ecological study aimed to investigate whether changes in natural gas prices (NGP), which account for a significant portion of winter energy prices in Korea, affect the association of cold spells with hospital admissions and mortality due to CVD. MethodsData from the National Health Insurance Service and Statistics Korea were used to determine the daily number of hospital admissions and mortality rates associated with CVD. From January 2012 to February 2017, the NGP continually increased by 24.1%. From January 2012 to December 2014 the NGP continually decreased by 32.6% owing to the Korea Gas Corporation’s management decisions, independent of external socioeconomic factors. We investigated the differences in the associations between cold spells and CVD-related outcomes in price-increasing and price-decreasing periods using a Poisson regression with a distributed lag nonlinear model. Cold spells were assessed on two consecutive days at the 5th percentile of the temperature for each region. ResultsThe meteorological factors and air pollution levels were similar between the two periods. The association between cold spells and hospital admissions due to CVD was stronger during the price-increasing period than during the price-decreasing period [ratio of cumulative relative risk (RRR) = 1.71, 95% confidence interval (CI): 1.31–2.22]. The difference in the association with mortality due to CVD between the two periods was not significant, although the point estimate remained >1 (RRR = 1.11, 95% CI: 0.90–1.38). ConclusionsChanges in energy prices may modify the cold spell-related CVD risk, possibly by inducing behavioral changes to manage energy expenditure. Policymakers should take into account the potential public health implications of changes in energy prices, alongside their economic effects.

Time series study of climate variables utilising a seasonal ARIMA technique for the Indian states of Punjab and Haryana

HighlightsTemperature and precipitation time series data from 1950 to 2020 were analyzed for the states of Haryana and Punjab.SARIMA models provided the most accurate temperature predictions for both states, though precipitation predictions in July were sometimes overestimated.SARIMA provided better results than machine learning-based models, with lower RMSE, AIC, and BIC values.Model forecasts can improve flood prediction, urban planning, and water resource management, benefiting scientists and decision-makers.

A Comparative Study of Time Series, Machine Learning, and Deep Learning Models for Forecasting Global Price of Wheat

A Comparative Study of Time Series, Machine Learning, and Deep Learning Models for Forecasting Global Price of Wheat

TEMPORAL ANALYSIS OF REPORTS OF INTERPERSONAL AND SELF-HARM VIOLENCE AGAINST THE ELDERLY IN BRAZIL

Violence against the elderly is an increasingly frequent phenomenon, both in developed and developing countries. In Brazil, in 2011, universal reporting of violence was implemented for some vulnerable groups, including the elderly. This study aims to describe the characteristics of reported cases and assess the trend in reporting of violence against the elderly in Brazil. A time series study of reported cases of violence against people aged 60 and over in Brazil between 2011 and 2023 was conducted. Between 2011 and 2023, 249,770 cases of violence against people aged 60 and over were reported in Brazil, of which 141,639 (56.7%) were women and 108,131 (43.3%) were men. Most of the violence occurred in the home (71.05%) and was classified as self-harm (13.79%). The use of physical force stands out (54.54%), followed by neglect/abandonment (28.52%). During this period, there was an increase in the reporting rates of violence against elderly people from 25.8 to 133.8 cases per 100,000 inhabitants (AAPC = 12.1), both for self-inflicted violence and interpersonal violence. In order to guarantee full citizenship for elderly people, health services must be alert to all forms of violence, establishing, in addition to reporting the case, access to comprehensive care, in addition to prevention actions.

Spatial and Temporal Analysis of Hospitalizations Due to Primary Care-Sensitive Conditions Related to Diabetes Mellitus in a State in the Northeast of Brazil.

Hospitalizations due to primary care-sensitive conditions (PCSCs) can be considered a proxy for the effectiveness of primary healthcare (PHC), especially diabetes mellitus (DM). The aim of this study was to analyze the temporal, spatial, and space-time patterns of PCSCs associated with DM in a state in Northeast Brazil from 2008 to 2022. An ecological and time-series study that included all records related to PCSCs-DM from the 75 municipalities of Sergipe was conducted. Segmented linear regression, global (I) and local (LISA) Moran indices, spatial scanning, Spearman correlation tests, bivariate I, and LISA were used in our analysis to examine the temporal trends and clusters of high spatial risk. Overall, 14,390 PCSCs-DM were recorded between 2008 and 2022. There was a higher prevalence of PCSCs-DM among women (53.75%) and individuals over 70 years old (57.60%). Temporal trends in PCSCs-DM were increasing with regard to the overall rate (AAPC: 2.39); males (AAPC: 3.15); age groups ≤ 19 years (AAPC: 6.13), 20-39 years (AAPC: 4.50), and 40-59 years (AAPC: 2.56); and 3 out of the 7 health regions. There was a positive spatial correlation between per capita income (I = -0.23; p = 0.004) and diabetic foot examination being performed by a nurse in a PHC (I = -0.18; p = 0.019) setting. The heterogeneous spatial distribution of DM hospitalizations demonstrated that this condition is a persistent public health problem in Sergipe.

The impact of air pollution on acute angle-closure glaucoma in Hefei, China, 2017-2022: a time-series study

The impact of air pollution on acute angle-closure glaucoma in Hefei, China, 2017-2022: a time-series study

Impact of the Diagnosis-Intervention Packet Payment Reform on Provider Behavior in China: A Controlled Interrupted Time Series Study.

China has developed a novel case-based payment method called the DiagnosisIntervention Packet (DIP) to regulate healthcare providers' behavior. G city, a metropolis in southeast China, has shifted its payment policy from fixed rate per admission to DIP under regional global budget since 2018. This study examined the immediate and trend changes in provider behavior after this payment reform. Discharge data in G city between 2016 and 2019 was used, covering more than 10 million inpatient cases in 320 hospitals. A counterfactual scenario was developed to assign insured and uninsured inpatients across the study period to specific DIP groups under consistent rules. Controlled interrupted time-series (ITS) analyses were performed, with uninsured inpatients as control. Outcomes included inpatient volume, average DIP weight (similar to case-mix index in Diagnosis-Related Groups), and two innovative indicators (average diagnostic weight and average treatment weight) to decompose the changes in DIP weight. Subgroup analyses were conducted for different hospital levels and 21 major disease categories. After the DIP reform, monthly trend of inpatient volume decreased (-1085.34, P=0.052), while monthly growth of average DIP weight increased (2.17, P=0.02). No significant changes in average diagnostic weight were observed. Monthly trend of average treatment weight increased (2.38, P=0.001) after the reform. Secondary and tertiary hospitals experienced insignificantly decreased inpatient volume and elevated average DIP weight, accompanied by negligible change in average diagnostic weight and significant increase in average treatment weight. Primary hospitals experienced reduced inpatient volume and stable average DIP weight, along with increase in average diagnostic weight and decrease in average treatment weight. By differentiated payments for severity, DIP induced hospitals to shift their focus from volume to weight of inpatients. Instead of diagnostic upcoding, hospitals responded to the DIP reform primarily by increasing treatment intensity. Primary hospitals may face financial risks under regional competition.

INTERNAÇÕES POR ANEMIA FERROPRIVA EM IDOSOS NO BRASIL ANTES, DURANTE E APÓS A PANDEMIA DE COVID-19

This research aimed to analyze hospitalizations for iron deficiency anemia in the elderly, before, during, and after the Covid-19 pandemic. This is an ecological time series study, using data from the Hospital Information System of the Unified Health System (SIH/SUS), using Prais-Winsten regression. In the period from 2017 to 2023, 42,805 hospitalizations for iron deficiency anemia in the elderly were reported in Brazil. The annual coefficient increased in the country during and after the Covid-19 pandemic, from 21 cases per 100 thousand elderly people in 2017 to 24 per 100 thousand in 2023, showing a stationary trend (-0.5%; p=0.176). The analysis of the hospitalization coefficient and the trend by region was increasing in the North (1.5%; p = 0.040) and Central-West (1.1%; p = 0.049) regions, and stationary in the other regions. Hospitalization and mortality rates were higher in males (22.8 to 26.0 cases/100,000; 7.4 to 6.58%), in the age group of 80 years or older (53.6 to 60.0 cases/100,000; 8.09 to 7.58%), and in emergency care (19.3 to 21.8/100,000; 6.96 to 6.54%). It is possible to conclude that hospitalizations for iron deficiency anemia in the elderly in the country increased, especially during and after the covid-19 pandemic, predominating among men over 80 years of age. Thus, health restrictions, reduced income, viral infection, low intake of iron-rich foods, and difficulties in accessing health services during the Covid-19 pandemic may have contributed to this increase. Thus, the importance of public policies aimed at the health, well-being and quality of life of the elderly population is emphasized, in order to reduce the rates of hospitalizations and mortality in the country.

Association between particulate matter exposure and acute ischemic stroke admissions in less-polluted areas: a time-series study using a distributed lag nonlinear model

Association between particulate matter exposure and acute ischemic stroke admissions in less-polluted areas: a time-series study using a distributed lag nonlinear model

Abstract 4116558: Navigator-driven Recommendations for Palliative Care Consults for Patients with Heart Failure and High Predicted Mortality

Background: Palliative care (PC) engagement can improve quality of life, reduce hospital costs, and enhance symptom control for individuals with heart failure (HF). For certain HF patients, PC can address symptoms and improve quality of life. However, referrals to PC often occur late, delaying benefits. Hypothesis: We hypothesize that a standardized recommendation for inpatient PC consultation will increase PC consultation rates and improve 30-day readmission without an impact on 30-day mortality rates. Methods: This interrupted time series study focused on high-risk HF patients at Atrium Health Wake Forest Baptist. The cohort included patients in the Golden Hearts Program, which is a local program to identify HF patients at elevated risk for 30-day readmissions and to accelerate resources to support their transitions. Baseline data were from patients 5 months before September 1, 2023, and the intervention group were from patients 5 months afterward. A standardized message recommending inpatient PC consultation was sent to attending physicians for patients with ESCAPE scores ≥4. Recommendations were also discussed at multidisciplinary rounds with senior residents. The primary outcomes were inpatient palliative care consultation and discharge to Hospice. Secondary outcomes were 30-day readmissions and 30-day mortality. Outcome measures were assessed post-discharge using Chi-square and T-test analyses. Results: The baseline group had 203 patients; the intervention group had 213. Post-intervention, PC consultation rates decreased from 12.3% to 8% (p=0.19), Discharge to hospice decreased from 2% to 0.9% (p=0.05), 30-day mortality decreased (8.4% vs 7%, p=0.74), and 30-day readmission dropped from 23.6% to 15% (p=0.04). The average length of stay remained 5.7 days in both groups. Limitations included provider buy-in and a limited time period. Conclusion: Though the intervention aimed at targeted PC consult recommendations for advanced HF patients led to reduced 30-day readmissions, there was a not a statistically significant impact on palliative care consultation or mortality.

Mortality from Hypertrophic Cardiomyopathy in Brazil-Historical Series.

Hypertrophic cardiomyopathy (HCM) is a relatively prevalent disease, primarily of a genetic etiology, affecting both sexes and characterized by left ventricular hypertrophy. However, limitations within healthcare systems, socioracial factors, and the issue of underdiagnosis hinder accurate mortality assessments in our region. This study, therefore, aimed to assess the mortality trends associated with HCM in Brazil from 2010 to 2020, with a focus on socioracial factors and healthcare disparities. This ecological, time-series study employed a quantitative approach based on secondary data from the Mortality System (SIM) developed by the Brazilian Ministry of Health. Mortality incidence and trend analyses were conducted using the average annual percent change (AAPC) and the annual percent change (APC). The results indicated a predominance of HCM-related deaths among white males aged 40 years and older. Additionally, an increasing trend in HCM-related mortality was observed among white and brown males and females aged 40 years and above from 2010 to 2018. Throughout the entire period covered in the study, the incidence of deaths due to HCM increased by 18.3% and 69.8% in the northeastern and southeastern regions. The findings suggest that health system managers should consider addressing the factors influencing HCM mortality and encourage the development and implementation of clinical protocols across healthcare institutions nationwide. Such protocols are recommended to facilitate early diagnosis and establish effective treatment strategies, ultimately aiming to improve the survival rates and quality of life for individuals affected by HCM.

The allocation and fairness of hospital pharmacist human resources in China: a time-series study

BackgroundTo address the rational use of medicines in healthcare institutions, the Chinese government enacted legislation for pharmacists in 2021, emphasizing the importance of pharmacists in medical services. The allocation and equity of pharmacist human resources in healthcare institutions directly affect people’s accessibility to pharmaceutical services. The study aims to analyze the supply and demand of pharmacist human resources in Chinese healthcare institutions and evaluate the equity of their distribution to provide a reference for the rational management of pharmacist resources.MethodsThis was a time-series study that was conducted using data obtained from Health and Health Statistical Yearbook that is performed every year by the National Health Commission of the People’s Republic of China. The study included 31 provinces, municipalities, and autonomous regions and 34,354 medical institutions in mainland China, which were classified into different economic regions based on their level of economic development. The study collected healthcare technicians and pharmacist data from national healthcare institutions between 2016 and 2020. The study evaluated the level of pharmacist human resource allocation using the health resource density index. The study explored the equity of pharmacist human resource allocation from two aspects: population and geographic area, using the Gini coefficient and Theil index.ResultsThe average annual growth rates of healthcare technical staff and pharmacists in Chinese medical institutions from 2016 to 2020 were 5.67% and 3.03%, respectively. The Gini coefficients of healthcare personnel resources based on population distribution were all below 0.119, while those based on geographical area were all above 0.655. The total Theil indexes of pharmacist human resources based on population distribution were all below 0.010, while those based on geographical area were all above 0.511. In addition, the contribution rates of the within-group Theil indexes of pharmacist human resources based on population and geographical area distributions to the total Theil index were all greater than or equal to 50%.ConclusionsThe allocation level of pharmacist human resources in China continues to improve, but there are differences in different economic development areas. Currently, allocation based on population shows equity, but allocation based on geographic area shows inequity. In the future, more attention should be paid to the geographic accessibility of pharmacist human resources, and resource allocation should consider both the population served and geographic area.

In Case You Haven't Heard…

Mondays and New Year's Day have the highest suicide risk according to new research, “Association of holidays and the day of the week with suicide risk: multi‐country, two‐stage, time series study,” published in The BMJ Oct. 23, according to a news release. An international research team used an advanced statistical technique called standardized two‐stage time series analysis to investigate suicide risk patterns. They analyzed data from 740 locations across 26 countries, gathered from the Multi‐country Multi‐city Collaborative Research Network database. This dataset comprised 1.7 million suicide cases, including daily suicide counts along with daily mean temperature data spanning from January 1971 to December 2019. The results revealed that suicide risk was highest on Mondays across all countries, though the effect of weekends varied. New Year's Day was associated with an increase in suicide risk in all countries, while Christmas showed a mixed pattern. Although there was an overall decreasing trend in suicide risk on other national holidays, the risk tended to increase after these holidays in most countries. Notably, the findings also showed that men are more vulnerable to variations related to the day of the week and New Year's Day compared to women. Researchers hope that this large‐scale study can lead to timely interventions, potentially saving countless lives.

Maximum-likelihood estimation of the Po-MDDRCINAR(p) model with analysis of a COVID-19 data

Integer-valued data are frequently encountered in time series studies. A pth-order mixed dependence-driven random coefficient integer-valued autoregressive time series model (Po-MDDRCINAR(p)) in view of binomial and negative binomial operators, where the innovation sequence follows a Poisson distribution, is investigated to provide meaningful theoretical explanations. Strict stationary and ergodicity of the model are demonstrated. Furthermore, the conditional least-squares and conditional maximum-likelihood methods are adopted to estimate the parameters, where the asymptotic characterization of the estimators is derived. Finite-sample properties of the conditional maximum-likelihood estimator are examined in relation to the widely used conditional least-squares estimator. The conclusion is that, if the Poisson assumption of the innovation sequence can be justified, conditional maximum-likelihood method performs better in terms of MADE and MSE. Finally, the practical performance of the model is illustrated by a set of COVID-19 data of suspected cases in China with a comparison with relevant models that exist so far in the literature.