Google Search Activity and Heart Failure: Analysis of the US Population's Interest in Heart Failure and Its Correlation with Heart Failure-Associated Mortality.
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ABSTRACT:
SUBMITTER: Sheth A
PROVIDER: S-EPMC8772295 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background Follow-up in a nurse-led heart failure ( HF ) clinic is recommended in HF guidelines, but its association with outcomes remains controversial, with previous studies including few and highly selected patients. Thus, large analyses of "real-world" samples are needed. Aims were to assess: (1) independent predictors of and (2) prognosis associated with planned referral to nurse-led HF clinics. Methods and Results We analyzed data from the SwedeHF (Swedish HF Registry) using multivariable logistic regressions to identify independent predictors of planned referral to a nurse-led HF clinic and multivariable Cox regressions to test associations between planned referral and outcomes (all-cause death, HF hospitalization, and their composite). Of 40 992 patients, 39% were planned to be referred to a follow-up in a nurse-led HF clinic. Independent characteristics associated with planned referral were shorter duration of HF , clinical markers of more-severe HF, such as lower ejection fraction, higher New York Heart Association class and N-terminal pro-B-type natriuretic peptide, and lower blood pressure, as well as cohabitating versus living alone, male sex, fewer comorbidities, and more use of HF treatments. After adjustments, planned referral to a nurse-led HF clinic was associated with reduced mortality and mortality/ HF hospitalization, but not HF hospitalization alone. Conclusions In this nation-wide registry, 39% of our identified HF cohort was planned to be referred to a nurse-led HF clinic. Planned referral reflected more-severe HF , but also sex- and family-related factors, and it was independently associated with lower risk of death, but not of HF hospitalization.
| S-EPMC6585319 | biostudies-literature
Project description:BackgroundIn the absence of vaccines and established treatments, nonpharmaceutical interventions (NPIs) are fundamental tools to control coronavirus disease (COVID-19) transmission. NPIs require public interest to be successful. In the United States, there is a lack of published research on the factors that influence public interest in COVID-19. Using Google Trends, we examined the US level of public interest in COVID-19 and how it correlated to testing and with other countries.ObjectiveThe aim of this study was to determine how public interest in COVID-19 in the United States changed over time and the key factors that drove this change, such as testing. US public interest in COVID-19 was compared to that in countries that have been more successful in their containment and mitigation strategies.MethodsIn this retrospective study, Google Trends was used to analyze the volume of internet searches within the United States relating to COVID-19, focusing on dates between December 31, 2019, and March 24, 2020. The volume of internet searches related to COVID-19 was compared to that in other countries.ResultsThroughout January and February 2020, there was limited search interest in COVID-19 within the United States. Interest declined for the first 21 days of February. A similar decline was seen in geographical regions that were later found to be experiencing undetected community transmission in February. Between March 9 and March 12, 2020, there was a rapid rise in search interest. This rise in search interest was positively correlated with the rise of positive tests for SARS-CoV-2 (6.3, 95% CI -2.9 to 9.7; P<.001). Within the United States, it took 52 days for search interest to rise substantially after the first positive case; in countries with more successful outbreak control, search interest rose in less than 15 days.ConclusionsContainment and mitigation strategies require public interest to be successful. The initial level of COVID-19 public interest in the United States was limited and even decreased during a time when containment and mitigation strategies were being established. A lack of public interest in COVID-19 existed in the United States when containment and mitigation policies were in place. Based on our analysis, it is clear that US policy makers need to develop novel methods of communicating COVID-19 public health initiatives.
| S-EPMC7371405 | biostudies-literature
Project description:Reliable forecasts of influenza-associated hospitalizations during seasonal outbreaks can help health systems better prepare for patient surges. Within the USA, public health surveillance systems collect and distribute near real-time weekly hospitalization rates, a key observational metric that makes real-time forecast of this outcome possible. In this paper, we describe a method to forecast hospitalization rates using a population level transmission model in combination with a data assimilation technique. Using this method, we generated retrospective forecasts of hospitalization rates for five age groups and the overall population during five seasons in the USA and quantified forecast accuracy for both near-term and seasonal targets. Additionally, we describe methods to correct for under-reporting of hospitalization rates (backcast) and to estimate hospitalization rates from publicly available online search trends data (nowcast). Forecasts based on surveillance rates alone were reasonably accurate in predicting peak hospitalization rates (within ± 25% of the actual peak rate, three weeks before peak). The error in predicting rates one to four weeks ahead, remained constant for the duration of the seasons, even during periods of increased influenza incidence. An improvement in forecast quality across all age groups, seasons and targets was observed when backcasts and nowcasts supplemented surveillance data. These results suggest that the model-inference framework can provide reasonably accurate real-time forecasts of influenza hospitalizations; backcasts and nowcasts offer a way to improve system tolerance to observational errors.
| S-EPMC6597779 | biostudies-literature
Project description:The Middle East respiratory syndrome coronavirus (MERS-CoV) was exported to Korea in 2015, resulting in a threat to neighboring nations. We evaluated the possibility of using a digital surveillance system based on web searches and social media data to monitor this MERS outbreak. We collected the number of daily laboratory-confirmed MERS cases and quarantined cases from May 11, 2015 to June 26, 2015 using the Korean government MERS portal. The daily trends observed via Google search and Twitter during the same time period were also ascertained using Google Trends and Topsy. Correlations among the data were then examined using Spearman correlation analysis. We found high correlations (>0.7) between Google search and Twitter results and the number of confirmed MERS cases for the previous three days using only four simple keywords: "MERS", "" ("MERS (in Korean)"), "" ("MERS symptoms (in Korean)"), and "" ("MERS hospital (in Korean)"). Additionally, we found high correlations between the Google search and Twitter results and the number of quarantined cases using the above keywords. This study demonstrates the possibility of using a digital surveillance system to monitor the outbreak of MERS.
| S-EPMC5011762 | biostudies-literature
Project description:The Morbidity and Mortality Weekly Reports of the U.S. Centers for Disease Control and Prevention document a raw proxy for counts of pertussis cases in the U.S., and the Project Tycho (PT) database provides an improved source of these weekly data. These data are limited because of reporting delays, variation in state-level surveillance practices, and changes over time in diagnosis methods. We aim to assess whether Google Trends (GT) search data track pertussis incidence relative to PT data and if sociodemographic characteristics explain some variation in the accuracy of state-level models. GT and PT data were used to construct auto-correlation corrected linear models for pertussis incidence in 2004-2011 for the entire U.S. and each individual state. The national model resulted in a moderate correlation (adjusted R2?=?0.2369, p?<?0.05), and state models tracked PT data for some but not all states. Sociodemographic variables explained approximately 30% of the variation in performance of individual state-level models. The significant correlation between GT models and public health data suggests that GT is a potentially useful pertussis surveillance tool. However, the variable accuracy of this tool by state suggests GT surveillance cannot be applied in a uniform manner across geographic sub-regions.
| S-EPMC6930253 | biostudies-literature
Project description:Hemographic indices have been associated with clinical outcomes in patients with chronic heart failure. We therefore investigated the prognostic values of hemographic indices in patients hospitalized for acute heart failure (AHF). Patients hospitalized primarily for AHF were drawn from an intramural registry. Hemographic indices, including white blood cell counts, neutrophil counts, neutrophil-to-lymphocyte ratio, reciprocal of lymphocyte (RL) and platelet-to-lymphocyte ratio were recorded. Among a total of 1923 participants (mean age 76?±?12 years, 68% men), 875 patients died during a mean follow-up of 28.6?±?20.7 months. Except for white blood cell counts, all the other hemographic indices were related to mortality, independently. In a forward stepwise Cox regression analysis among hemographic indices, RL was the strongest predictor (HR and 95% CI per-1SD:1.166,1.097-1.240) for mortality, after accounting for confounders. However, conditioned on the survivals, the hemographic indices were independently related to mortality within 3 years of follow-up, rather than beyond. Hemographic indices were independent risk factors of mortality in patients hospitalized for AHF, especially in patients with impaired left ventricular systolic function. As an acute presentation of inflammation, hemographic indices might be useful to identify subjects at risk of mortality soon after the index hospitalization.
| S-EPMC5736628 | biostudies-literature
Project description:Acute heart failure (AHF) emerges either de novo or from worsening of chronic heart failure (CHF). The aim of the present study was to evaluate the association between worsening of CHF and mortality in AHF patients. Out of 152 included AHF patients, 47 (30.9%) were de novo AHF patients and 105 (69%) were AHF patients with worsening of CHF. The proportion dying in hospital (19.0% vs. 4.3%, p = 0.023) and within 3 months after hospitalization (36.6% vs. 6.7%, p < 0.001) was significantly higher in AHF patients with worsening of CHF. Logistic regression analyses also showed a significant positive association of AHF emerging as worsening of CHF with hospital mortality [odds ratio (OR) and 95% confidence interval (CI): 5.29 (1.46-34.10), p = 0.029] and 3-month mortality [8.09 (2.70-35.03), p = 0.001]. While the association with hospital mortality was no longer significant after adjusting for comorbidities and clinical as well as laboratory parameters known to be associated with mortality in heart failure patients, the association with 3-month mortality remained significant. We conclude that compared to de novo AHF, AHF evolved from worsening of CHF is a more severe condition and is associated with increased mortality.
| S-EPMC6018547 | biostudies-literature
Project description:Whether heart rate upon discharge following hospitalization for heart failure is associated with long-term adverse outcomes and whether this association differs between patients with sinus rhythm (SR) and atrial fibrillation (AF) have not been well studied. We conducted a retrospective cohort study from clinical registry data linked to Medicare claims for 46 217 patients participating in Get With The Guidelines(®)-Heart Failure. Cox proportional-hazards models were used to estimate the association between discharge heart rate and all-cause mortality, all-cause readmission, and the composite outcome of mortality/readmission through 1 year. For SR and AF patients with heart rate ≥75, the association between heart rate and mortality (expressed as hazard ratio [HR] per 10 beats-per-minute increment) was significant at 0 to 30 days (SR: HR 1.30, 95% CI 1.22 to 1.39; AF: HR 1.23, 95% CI 1.16 to 1.29) and 31 to 365 days (SR: HR 1.15, 95% CI 1.12 to 1.20; AF: HR 1.05, 95% CI 1.01 to 1.08). Similar associations between heart rate and all-cause readmission and the composite outcome were obtained for SR and AF patients from 0 to 30 days but only in the composite outcome for SR patients over the longer term. The HR from 0 to 30 days exceeded that from 31 to 365 days for both SR and AF patients. At heart rates <75, an association was significant for mortality only for both SR and AF patients. Among older patients hospitalized with heart failure, higher discharge heart rate was associated with increased risks of death and rehospitalization, with higher risk in the first 30 days and for SR compared with AF.
| S-EPMC4579947 | biostudies-literature
Project description:Portfolio diversification and active risk management are essential parts of financial analysis which became even more crucial (and questioned) during and after the years of the Global Financial Crisis. We propose a novel approach to portfolio diversification using the information of searched items on Google Trends. The diversification is based on an idea that popularity of a stock measured by search queries is correlated with the stock riskiness. We penalize the popular stocks by assigning them lower portfolio weights and we bring forward the less popular, or peripheral, stocks to decrease the total riskiness of the portfolio. Our results indicate that such strategy dominates both the benchmark index and the uniformly weighted portfolio both in-sample and out-of-sample.
| S-EPMC3776958 | biostudies-other
Project description: Not available
| S-EPMC5788329 | biostudies-literature