The impact of the COVID-19 pandemic on the use of Emergency Departments in Italy

Background

During 2020, COVID-19 had a diversified distribution in Italy, the first nation in Europe to experience the outbreak of the epidemic. This was linked to geographical differences in population density and distribution of healthcare facilities, including Emergency Departments (EDs). This study aims to assess the impact of the pandemic on ED utilization in 2020 across different subpopulations and geographical locations in Italy.

Methods

We used anonymized data from a survey conducted by the Italian National Institute of Statistics on 25,000 families to analyze the yearly rate of people who used EDs from 2015 to 2020. The rate of persons who accessed ED services in 2020 per 1,000 population was compared with those of the previous non-pandemic years.

Results

The number of people accessing EDs in 2020 was 32.3% lower, although this reduction was not uniform across the 21 regions / autonomous provinces. People aged 0-14 years experienced the highest reduction in ED visits. In 2020, low educational level people exhibited a steeper reduction in the use of EDs.

Conclusions

This study shows a significant drop in EDs use especially by children; the population section mostly affected by the effects of the pandemic. This study also confirms that education and socio-economic status are important determinants of ED use. The heterogeneous reduction in ED use across the regions of Italy highlights the need to further investigate the impact of this pattern on the health of the population, as well as to define adequate preparedness strategies to face future emergencies.

Trust and its relations to vaccine beliefs: a latent class analysis on 140,000 individuals worldwide

Background

Research shows that vaccine-related beliefs (i.e., about efficacy, safety, purpose) may reflect a host of within-person and contextual factors yielding homogeneous subgroups of individuals. This study aims to characterize distinct subgroups of people and identify ideal targets for tailored public health interventions to increase vaccine adherence.

Methods

Latent class analysis was used to derive subgroups based on unique response profiles using the 2019 Gallup survey of 140 countries (>140,000 individuals). We modeled a composite of vaccine beliefs as a distal outcome examining differences for the obtained classes, with and without covariates in the model.

Results

A 5-class model fit best with classes distinguished primarily on whether individuals possessed or sought personal knowledge about science, medicine, and health, whether they trusted science, scientists and have confidence in the healthcare system. The lowest levels of vaccine beliefs were reported by a class not endorsing any of these indicators and the highest levels by a class endorsing all the indicators (p < 0.001). Age class showed a U-shaped relation with vaccine beliefs, while higher educational level (p = 0.025), higher subjective income (p = 0.006) and employment (p < 0.001) were related to higher vaccine beliefs. Country-level income was moderately related to class membership and vaccine beliefs were higher in lower-income countries (p < 0.001).

Conclusions

Our findings suggest that more work is needed to improve trust in science and medical providers. Tailored interventions grounded in a community-based and empowering approach with the collaboration of multiple stakeholders seems to be needed to improve vaccination rates. This can only be achieved when individuals trust science, scientists and healthcare providers and accrue the necessary wisdom to make good healthcare decisions that affect not only themselves but their fellow citizens.

Key messages

• Efforts to alter vaccine beliefs should touch on where people access information on science and health, the processes that build trust, and their belief whether science improves well-being.

• Public health interventions should focus on reassuring individuals that science and health workers are benevolent. An essential first step in the health worker-patient relations is building trust.

The impact of the SARS-CoV-2 pandemic on cause-specific- mortality: a systematic literature review

Background

Although investigating the patterns of COVID-19 excess mortality (EM) is relevant, understanding the effects of the pandemic on cause-specific mortality is even crucial and should also be assessed, as this metric allows for a more detailed analysis of the true impact of the pandemic. The aim of this systematic literature review is to estimate the impact of the pandemic on different causes of death, providing a quantitative and qualitative analysis of the phenomenon.

Methods

We searched MEDLINE to identify studies that reported cause-specific mortality during the COVID-19 pandemic. We adopted several inclusion criteria: original article; assessed at least one cause-specific mortality during the pandemic; assessed causes of deaths using the ICD-10 classification; reporting of at least one of the following outcomes: cause-specific mortality estimates or cause-specific EM; full-length articles. Several relevant data were extracted (e.g. publication year, data stratification, territory, country income level, all-cause EM, and cause-specific mortality, etc.).

Results

The search identified 548 articles. After title, abstract and full-text screening, we extracted relevant data from the final set of 14 articles. Cause-specific mortality was reported using different units of measurement. Only 9 studies reported the statistical significance and/or confidence intervals. The most frequently analyzed causes of death were cardiovascular diseases (n = 11), cancer (n = 7), diabetes (n = 6), and suicide (n = 5). We found very heterogeneous patterns of cause-specific mortality, for all the specific causes of deaths, except for suicide and road accident.

Conclusions

The impact of the pandemic on cause-specific deaths has been very heterogeneous and the analyses conducted so far are not exhaustive. We advocate for the urgent need to find a consensus to define uniform methodological approaches to establish the true burden of the COVID-19 pandemic on non-COVID-19 mortality.

Key messages

• We reviewed the body of literature to estimate the impact of the COVID-19 pandemic on different causes of death, and to provide a quantitative and qualitative analysis of the phenomenon.

• We did not identify unique patterns of cause-specific mortality due to too varied approaches in terms of disease classification and coding, and methodologies used for estimating mortality.

Perceived quality and willingness to continue using telemedicine services in patients with diabetes

Background

Plenty of literature reported the applicability and usefulness of telemedicine and teleassistance (TMTA) services in the management of diabetes and other chronic conditions. Specifically, TMTA proved to be effective for conditions that require radical lifestyle modifications, tailored pharmacological interventions, and periodic monitoring of clinical health status. The purpose of this study is to investigate the individual and contextual determinants of the perceived quality (PQ) of the telemedicine and teleassistance (TMTA) services and the willingness to continue (WC) with them among patients with diabetes using TMTA during the COVID-19 pandemic in one large region of Italy (Emilia-Romagna).

Methods

A structured survey was administered to patients with type 1 and 2 diabetes who used TMTA services during the first wave of the COVID-19 pandemic. The questionnaire was comprised of questions on TMTA service experience and participants’ socio-demographic characteristics. Multiple regression models investigated the independent factors associated with PQ (score 1-100) and WC (yes/no).

Results

The final analysis included 569 patients with diabetes (54.7% female), with an average age of 58.1 years. TMTA services’ PQ and WC were high. A higher education (OR = 1.83; 95%CI 1.04, 3.31) and being unemployed (OR = 2.57; 95%CI 1.17, 6.02) were factors associated with an increased WC. Older age was negatively related to PQ (b = −3.6; 95%CI −6.8, −0.29). Perceived support from TMTA service was positively associated with PQ (b = 10.1; 95%CI 5.1, 15) and WC (OR = 2.03; 95%CI 1.07, 3.85). Perceived increase in disease self-management was positively associated with PQ (b = 5.3; 95%CI 0.24, 10) and WC (OR = 7.11; 95%CI 4.04, 12.8).

Conclusions

Our study identified several determinants of PQ and WC. These socio-demographic and patient-perception related factors should be considered in the implementation of care pathways integrating in-person visits with TMTA services.

Key messages

• Socio-demographic factors play a crucial role in TMTA acceptance and should be taken into due consideration when implementing health pathways integrating in-person visits with TMTA services.

• Health workers should always try to improve patients’ self-management skills and should always make patients feel supported. This is also true in the digital health era.

Semi-Automatic Knowledge Extraction from COVID-19 Scientific Literature: the COKE Project

Background

The COVID-19 pandemic highlighted the importance of rapidly updating scientific information. However, the guidelines’ drafting process is highly time- and resource-consuming. The COKE Project aims to accelerate and streamline the extraction and synthesis of scientific evidence. To do so, the Project used deep learning to implement a semi-automated system that enhances the systematic literature review processes. We aim to show some preliminary results on the automatic classification of abstract sentences in papers related to COVID-19.

Methods

The tool is based on Natural Language Processing algorithms to detect and classify PICO elements and medical terms and organize abstracts accordingly. We built a BERT + bi-LSTM language model. The tool was trained on a corpus of 24,668 abstracts unrelated to COVID-19. We assessed the tool performance in a specific topic related to COVID-19 that has not been covered during training. To carry out manual validation, we randomly selected 50 abstracts. Abstract sentences were classified by 2 domain experts into 7 types: Aim (A), Participants (P), Intervention (I), Outcome (O), Method (M), Results (R), and Conclusion (C). The performance of the tool was compared with that of the experts in terms of precision, recall, and F1.

Results

The classifier proved to have a 76% overall accuracy. Precision, recall, and F1 were above 75% for all types of sentences except I, M, and P.

Conclusions

The results indicate a promising ability of the semi-automated classifier to predict expert-validated labels on abstracts of different topics. Our proposed tool is expected to significantly reduce the effort for producing medical guidelines and therefore have a strong, positive impact, particularly in emergency scenarios. The COKE Project also represents a call-to-action for similar initiatives, aimed at enhancing the information extraction process in medicine.

Key messages

• A rapidly changing healthcare requires fast decisions supported by scientific evidence. This is not compatible with the human limits in cognitive skills that reduce the ability to extract information.

• The COKE Project aims to speed up the creation of healthcare guidelines, semi-automating parts of the workflow, and supporting the human-performed process of extracting and analyzing contents.

Association between economic growth, mortality and healthcare spending in 31 high-income countries

Background

During the last decades, countries' healthcare spending has grown continuously, becoming a major expenditure item and threatening the overall sustainability of healthcare systems. Plenty of literature shows conflicting evidence about the relationship between economic variations and measurable health outcomes. This study aims to investigate the association between GDP, population mortality and healthcare spending in OECD high-income countries.

Methods

We conducted a cross-sectional study using panel data across 31 high-income countries from 2000 to 2017. Socioeconomic data for every year and each country were extracted from WHO and OECD Database. The association between current healthcare expenditure (CHE), GDP and mortality rate (MR) was investigated through a random-effects model. To control for possible reverse causality, we adopted a test of Granger causality for heterogeneous panel data models.

Results

The results of the random-effects model show that the MR has no statistically significant effect on CHE. We found no statistically significant association between countries' MR and GDP when the latter is the dependent variable. Our results show that an increase in GDP is associated with a significant increase of CHE (b = 0.066, p < 0.001) and CHE is significantly associated with an increase in GDP (b = 3.188, p < 0.001). The Granger causality analysis shows a unidirectional association between MR and CHE, with MR influencing CHE, albeit with a small statistical significance (p = 0.045). Between GDP and CHE, the causality is bidirectional, while between GDP and MR we found no causality.

Conclusions

In this study, we found a strong two-way relationship between GDP and CHE, both in the causality analysis and in the random-effect panel model. Our analysis highlights the economic multiplier effect of CHE. In the debate on the optimal allocation of resources often resulting from economic crises, this evidence should be taken into due consideration.

Key messages

Policymakers worldwide need to recognize the economic impact of healthcare spending when allocating financial resources. Spending on health leads to economic growth. In light of the current health-economy dichotomy, it is important to produce robust scientific evidence supporting healthcare spending.

Small-scale spatial analysis shows the specular distribution of excess mortality between the first and second wave of the COVID-19 pandemic in Italy

OBJECTIVES

The objective of the study is to compare excess mortality (EM) patterns and spatial correlation between the first and second wave of the pandemic in Lombardy, the Italian region that paid an extremely high COVID-19-related mortality toll in March and April 2020.

STUDY DESIGN

We conducted a longitudinal study using municipality-level mortality data.

METHODS

We investigated the patterns and spatial correlation of EM of men aged ≥75 years during the first two pandemic waves (March-April 2020 vs November 2020) of COVID-19, using the mortality data released by the Italian National Institute of Statistics. EM was estimated at the municipality level to accurately detect the critical areas within the region.

RESULTS

The areas that were mostly hit during the first wave of COVID-19 were generally spared by the second wave: EM of men aged ≥75 years in the municipality of Bergamo plummeted from +472% in March and April to -13% in November, and in Cremona the variation was from +344% to -19%. Conversely, in November 2020 EM was higher in some areas that had been protected in the first wave of the pandemic. Spatial correlation widely corroborates these findings, as large sections of the hot spots of EM detected in the first wave of the pandemic changed into cold spots in the second wave, and vice versa.

CONCLUSIONS

Our results reveal the specular distribution of EM between the first and second wave of the pandemic, which may entail the consequences of social distancing measures and individual behaviors, local management strategies, 'harvesting' of the frailer population and, possibly, acquired immune protection. In conclusion, our findings support the need for continuous monitoring and analysis of mortality data using detailed spatial resolution.

Patient-reported outcomes in patients undergoing elective arthroplasty: the PaRIS-IOR study

Background

The number of hip and knee arthroplasties continues to rise worldwide. The Organization for Economic Cooperation and Development has launched the PaRIS Initiative for the systematic collection of Patient Reported Outcome Measures (PROMs) in patients undergoing elective hip and knee arthroplasty. The Rizzoli Orthopedic Institute (IOR) was selected as a pilot center for the Initiative (PaRIS-IOR study), because it hosts the Registry of Orthopedic Prosthetic Implants (RIPO). The objective of PaRIS-IOR study is to investigate the characteristics and temporal trend of PROMs in relation to the type of surgical intervention and patient profile. Here we report the preliminary results of the first study year.

Methods

The PaRIS-IOR is a prospective, single site, cohort study started on January 1st 2019 that consists of the administration of Euro Quality 5 Dimensions (EQ-5D), Hip disability and Osteoarthritis Outcome Score and Knee injury and Osteoarthritis Outcome Score Physical function Short-form (HOOS-PS, KOOS-PS) questionnaires to patients on the list for elective arthroplasty. Questionnaires data are linked with those routinely collected by the RIPO and regional administrative data, in order to track patients' medical history.

Results

The study population consists of 1,413 patients. Patients undergoing knee arthroplasty (n = 393) were older (68.4 vs 60.2 years; p < 0.001), and had a higher prevalence of obesity (41.6 vs 22.6%; p < 0.001) than patients undergoing hip arthroplasty (n = 1020). Female and obese patients reported a worse perceived health status both in the EQ-5D (p < 0.001) and in the HOOS-PS and KOOS-PS (p < 0.001). Among patients who underwent knee surgery, the younger ones reported a poorer perceived health in the general and the specific questionnaires.

Conclusions

The PaRIS-IOR study has potential important implications in targeting the factors affecting patient-reported functional outcomes and quality of life after joint arthroplasty.

Key messages

The PaRIS-IOR study underscores the poorer perception of health status in female and obese patients undergoing arthroplasty and in younger patients undergoing knee surgery. The routine adoption of PROMs may support surgeons in the management of patients undergoing hip and knee arthroplasty and policy-makers in improving healthcare quality in orthopedics.

Early scientific response to COVID-19 epidemic: a scientometric perspective

Background

The recent COVID-19 epidemic is showing how the response of the scientific literature is fundamental in the first days following the onset of a new epidemic. Quantifying which studies have a greatest impact can help researchers and policymakers in controlling the epidemic. The aim of this study is to describe the early scientific production in response to the COVID-19 epidemic through a scientometric analysis.

Methods

The study consisted of: 1) review of the scientific literature produced in the 30 days since the first paper related to COVID-19 has been published on Pubmed; 2) Identification of papers' Digital Object Identifiers (DOI) and analysis of related metrics with the construction of a 'Computed Impact Score' (CIS) that represents a unifying score over heterogeneous bibliometric indicators. The CIS takes into account all the bibliometric indicators both traditional (i.e. counting of citations) and alternative (i.e. altmetrics). In this study we use the altmetrics provided by Plum Analytics (PlumX). All bibliometric indicators for the selected papers have been collected by using their corresponding DOIs as the key for querying Scopus API, which integrates PlumX. On top of those indicators we compute the CIS. The papers with higher CIS are discussed and presented.

Results

239 papers have been included in the study. A threshold for CIS of t = 1.04 (i.e.95% quantile) allowed us to record 8 papers as potentially impactful. The 8 papers are: 6 case reports, 1 methodological study, 1 editorial. First authors come from China (n = 6), USA (n = 1) and Germany (n = 1). The main topics are: case/s description (n = 5), outbreak investigation (n = 2) and 1 genomic study.

Conclusions

The early response of the scientific literature during an epidemic does not follow a pre-established pattern. Tracing the traditional and non-traditional metrics measures of papers can help to understand and evaluate the impact of literature on the scientific community and general population.

Key messages

The dynamic of the scientific community represents an important aspect of the early response to the onset of a new epidemic, which must be studied also to increase systems’ preparedness.

In a connected digital world, tracing metrics measures of scientific papers can identify those with the greatest impact and help professionals to correctly inform the population.

Crowdfunding for unmet medical needs: the case of CAR-T and Gofundme

Background

Crowdfunding (CF) is the practice of financing a project by raising money from a large number of people. Many patients use online CF platforms to fund medical needs, whether unmet by their healthcare service - therefore to be sought elsewhere -, or when unable to afford them. CAR-T (Chimeric antigen receptor T-cells) is an innovative therapy approved to treat several types of lymphoma and with potential to treat many other cancers. CAR-T is available in most countries through clinical trials only and its diffusion is limited by high costs. Gofundme is a CF platform ’leader in online medical fundraising’. The objective of this study is to shed some light on the phenomenon of CF for CAR-T therapy, describing the campaigns started on Gofundme.

Methods

We extracted data from CAR-T campaigns started in Europe and publicly available on Gofundme until March 2019. Data related to each campaign has been analyzed and reported through descriptive analyses.

Results

Since 2017, 26 CAR-T treatment campaigns have been started. Due to the privacy policy of the platform, we were able to retrieve data from only 12 of them; 3 campaigns were closed, thus not disclosing enough data to be included. Nine campaigns were studied: 4 from Italy, 4 from the UK, 1 from Spain. The United States were the main destination. The median campaign goal was 180k€. The number of campaign shares on social media and the percentage of goal raised seemed to be linked.

Conclusions

CF is unquestionably a good expression of the Internet: it channels empathy towards important causes, providing tangible help. However, when applied to healthcare - especially to experimental treatments -, several questions arise. Patients affected by treatment resistant cancers may be prone trying new treatments to keep the hope alive, even when indication is missing or scientific evidence is lacking. Policymakers should monitor healthcare related CF campaigns, both for equity and safety reasons.

Key messages

Policymaker should monitor healthcare related CF campaigns, both for equity and safety reasons. Healthcare related crowdfunding campaigns could be interpreted as an indicator of unmet medical needs.

Developing a new predictor of health expenditure: preliminary results from a primary healthcare setting

OBJECTIVES

Risk adjustment is a widely used tool for health expenditure prediction and control. Early approaches for estimating health expenditure were based on patient demographic variables alone, whereas more recent models incorporate patient information, such as chronic medical conditions, clinical diagnoses, and self-reported health status. Many studies have investigated the health expenditure predictive capacity of single demographic, morbidity, or health-related quality of life measures, but the best models prove to be those that include them all. The aim of this study was to develop an index that combines measures of perceived health and disease severity and to compare its efficacy in predicting health expenditure with that of the measures taken individually.

STUDY DESIGN

This is a linked cross-sectional study.

METHODS

In 2009 and 2010, the health-related quality of life questionnaire SF-36 (8 scales, two indices: Physical Component Summary [PCS] and Mental Component Summary [MCS]) was distributed to 886 patients of general practitioners in the Province of Siena, Italy. Severity of diseases was calculated for each patient using the Charlson Index (CH-I) and Cumulative Illness Rating Scale Severity Index (CIRS-SI). Siena Local Health Unit 2012 data on health expenditure were obtained for each patient. Multivariate linear regression was applied to test the performance of severity (CH-I, CIRS-SI) and perceived health (PCS and MCS) measures in predicting health expenditure. The indexes that predicted health expenditure best were then combined in a new tool, and its expenditure predictive capacity was tested.

RESULTS

The best health expenditure predictors proved to be PCS and SI (R² = 0.15 and R² = 0.17, respectively). When combined in a new index (PCS-SI), better predictive capacity of health expenditure was obtained than with the two single measures separately (R² = 0.19).

CONCLUSIONS

A multidimensional indicator proved to be a better predictor of healthcare expenditure than single health measures.

Development of an international comorbidity education framework

CONTEXT

The increasing number of people living with multiple chronic conditions in addition to an index condition has become an international healthcare priority. Health education curricula have been developed alongside single condition frameworks in health service policy and practice and need redesigning to incorporate optimal management of multiple conditions.

AIM

Our aims were to evaluate current teaching and learning about comorbidity care amongst the global population of healthcare students from different disciplines and to develop an International Comorbidity Education Framework (ICEF) for incorporating comorbidity concepts into health education.

METHODS

We surveyed nursing, medical and pharmacy students from England, India, Italy and Sweden to evaluate their understanding of comorbidity care. A list of core comorbidity content was constructed by an international group of higher education academics and clinicians from the same disciplines, by searching current curricula and analysing clinical frameworks and the student survey data. This list was used to develop the International Comorbidity Education Framework.

RESULTS

The survey sample consisted of 917 students from England (42%), India (48%), Italy (8%) and Sweden (2%). The majority of students across all disciplines said that they lacked knowledge, training and confidence in comorbidity care and were unable to identify specific teaching on comorbidities. All student groups wanted further comorbidity training. The health education institution representatives found no specific references to comorbidity in current health education curricula. Current clinical frameworks were used to develop an agreed list of core comorbidity content and hence an International Comorbidity Education Framework.

CONCLUSIONS

Based on consultation with academics and clinicians and on student feedback we developed an International Comorbidity Education Framework to promote the integration of comorbidity concepts into current healthcare curricula.

The potential for pocket parks to increase physical activity

PURPOSE

To assess the use of new pocket parks in low-income neighborhoods.

DESIGN

The design of the study was a quasi-experimental post-test only comparison.

SETTING

Los Angeles, California, was the setting for the study.

SUBJECTS

Subjects were park users and residents living within .5 mile of three pocket parks and 15 neighborhood parks.

INTERVENTION

The creation of pocket parks.

MEASURES

We used the System of Observing Play and Recreation in Communities (SOPARC) tool to measure park use and park-based physical activity, and then surveyed park users and residents about their park use.

ANALYSIS

We surveyed 392 and 432 household members within .5 mile of the three pocket parks before and after park construction, respectively, as well as 71 pocket park users, and compared them to 992 neighborhood park users and 342 residents living within .5 mile of other neighborhood parks. We compared pocket park use to playground area use in the larger neighborhood parks. We used descriptive statistics and generalized estimating equations for the analysis.

RESULTS

Overall, pocket park use compared favorably in promoting moderate-to-vigorous physical activity with that of existing playground space in nearby parks, and they were cost-effective at $0.73/MET hour (metabolic equivalent hour) gained. Pocket park visitors walked an average of .25 miles to get to a park.

CONCLUSIONS

Pocket parks, when perceived as attractive and safe destinations, may increase physical activity by encouraging families with children to walk there. Additional strategies and programs may be needed to encourage more residents to use these parks.

Use of neighbourhood parks: does socio-economic status matter? A four-city study

OBJECTIVES

To determine if neighbourhood socio-economic status (SES) is associated with park use and park-based physical activity.

STUDY DESIGN

Cross-sectional study.

METHODS

The use and characteristics of 24 neighbourhood parks in Albuquerque, Chapel Hill/Durham, Columbus and Philadelphia were observed systematically in three seasons (spring, summer and autumn), with nearly 36,000 park users observed. Twelve parks were in high-poverty neighbourhoods and 12 parks were in low-poverty neighbourhoods. In total, 3559 park users and 3815 local residents were surveyed. Park incivilities were assessed and park administrators were interviewed about management practices.

RESULTS

The size and number of facilities in parks in high-poverty neighbourhoods were similar to those in parks in low-poverty neighbourhoods, but the former had more hours of programming. Neighbourhood poverty level, perception of safety and the presence of incivilities were not associated with the number of park users observed. However, programmed activities and the number of activity facilities were strongly correlated with park use and energy expended in the park.

CONCLUSIONS

The finding that park programming is the most important correlate of park use and park-based physical activity suggests that there are considerable opportunities for facilitating physical activity among populations of both high- and low-poverty areas.

Trauma Exposure in Anxious Primary Care Patients

The present study examined rates of trauma exposure, clinical characteristics associated with trauma exposure, and the effect of trauma exposure on treatment outcome in a large sample of primary care patients without posttraumatic stress disorder (PTSD). Individuals without PTSD (N = 1263) treated as part of the CALM program (Roy-Byrne et al., 2010) were assessed for presence of trauma exposure. Those with and without trauma exposure were compared on baseline demographic and diagnostic information, symptom severity, and responder status six months after beginning treatment. Trauma-exposed individuals (N = 662, 53%) were more likely to meet diagnostic criteria for Obsessive Compulsive Disorder and had higher levels of somatic symptoms at baseline. Individuals with and without trauma exposure did not differ significantly on severity of anxiety, depression, or mental health functioning at baseline. Trauma exposure did not significantly impact treatment response. Findings suggest that adverse effects of trauma exposure in those without PTSD may include OCD and somatic anxiety symptoms. Treatment did not appear to be adversely impacted by trauma exposure. Thus, although trauma exposure is prevalent in primary care samples, results suggest that treatment of the presenting anxiety disorder is effective irrespective of trauma history.

Quality of and patient satisfaction with primary health care for anxiety disorders

BACKGROUND

Most patients with anxiety disorders receive their care from primary care practitioners (PCPs). The purpose of this study was to evaluate quality of and patient satisfaction with primary health care for anxiety disorders.

METHOD

A survey was performed among 1,004 outpatients with anxiety disorders (diagnosed according to DSM-IV) referred by their PCPs from 17 primary care clinical settings (3 of which were university-affiliated) in 4 regions of the United States for participation in the Coordinated Anxiety Learning and Management (CALM) study, a therapeutic trial. Participating research institutions were the University of Washington at Seattle, the University of California at San Diego and Los Angeles, and the University of Arkansas for Medical Sciences at Little Rock. Enrollment took place between June 2006 and April 2008. Patients were contacted by telephone after enrollment to provide information about previous care received (during the 6 months prior to referral) and satisfaction with that care. Quality-of-care indicators were self-reported type, dose, and duration of antianxiety medication treatment and self-reported psychotherapy with cognitive-behavioral therapy (CBT) elements.

RESULTS

A total of 576 patients (57.4%) had received an appropriate antianxiety medication in the previous 6 months, but only 289 patients (29.4% of 983 who answered this question) had received the medication at adequate dose for at least 2 months. A total of 465 patients (46.3%) had received some counseling with at least 1 element of CBT, but only 213 patients (21.2%) had received counseling with a strong (3+ elements) CBT focus. Overall, 416 patients (41.4%) had received quality pharmacotherapy or psychotherapy, and 81 patients (8.1%) had received both. Only 432 patients (44.8% of 964 who answered this question) were at least somewhat satisfied with their mental health care. Receipt of quality psychotherapy was the sole positive predictor (adjusted odds ratio = 2.71; 95% CI, 1.94-3.80; P < .0005) of satisfaction with mental health care for anxiety. Moreover, there was a dose-response relationship between the number of CBT elements consistently delivered and satisfaction with care (test for trend, z = 4.06, P < .0005).

CONCLUSIONS

Despite recognition of these patients' anxiety disorders and referral by their PCPs to an anxiety treatment study, fewer than half of the patients had in the prior 6 months received quality pharmacologic and/or psychosocial mental health care. Receipt of CBT-oriented, quality psychosocial (but not pharmacologic) care showed a strong dose-response relationship with satisfaction with mental health care.

Functioning and disability levels in primary care out-patients with one or more anxiety disorders

BACKGROUND

Anxiety disorders are the most prevalent mental health disorders and are associated with substantial disability and reduced well-being. It is unknown whether the relative impact of different anxiety disorders is due to the anxiety disorder itself or to the co-occurrence with other anxiety disorders. This study compared the functional impact of combinations of anxiety disorders in primary care out-patients.

METHOD

A total of 1004 patients with panic disorder (PD), generalized anxiety disorder (GAD), social anxiety disorder (SAD) or post-traumatic stress disorder (PTSD) provided data on their mental and physical functioning, and disability. Multivariate regressions compared functional levels for patients with different numbers and combinations of disorders.

RESULTS

Of the patients, 42% had one anxiety disorder only, 38% two, 16% three and 3% all four. There were few relative differences in functioning among patients with only one anxiety disorder, although those with SAD were most restricted in their work, social and home activities and those with GAD were the least impaired. Functioning levels tended to deteriorate as co-morbidity increased.

CONCLUSIONS

Of the four anxiety disorders examined, GAD appears to be the least disabling, although they all have more in common than in distinction when it comes to functional impairment. A focus on unique effects of specific anxiety disorders is inadequate, as it fails to address the more pervasive impairment associated with multiple anxiety disorders, which is the modal presentation in primary care.

Bayesian inference in a hidden stochastic two-compartment model for feline hematopoiesis

In this paper, we describe a hidden two-compartment stochastic process used to model the kinetics of feline hematopoietic stem cells (HSCs) in continuous time. Because of the experimental design and data collection scheme, the inferential task presents numerous challenges. While the hematopoietic process evolves in continuous time, the observations are collected only at discrete irregular times and are a probabilistic function of the state of the process. In addition, the animals go through an experimental procedure such that their reserve of HSCs is severely depleted at the start of the observation period. This impedes any approximation of the hematopoietic process with a continuous state-space process (normal approximation of the transition probabilities would be inaccurate when the state of the process, i.e. the number of stem cells, is small). We implement a Markov chain Monte Carlo algorithm that allows us to estimate the posterior distribution of the parameters of the hematopoietic process while maintaining its state-space discrete (i.e. without using any approximation). We show the performance of the algorithm on simulated data. Finally, we apply the algorithm to data on multiple experimental cats and provide estimates of the rates of the fates of feline HSCs. The obtained estimates are in agreement with the estimates obtained with different methods published in the medical literature. However, the proposed approach makes a more efficient use of the data and hence the parameter estimates are much more accurate than the one obtained with the methods previously proposed.

In vivo kinetics of murine hemopoietic stem cells

We used stochastic modeling and computer simulation to study the replication, apoptosis, and differentiation of murine hemopoietic stem cells (HSCs) in vivo. This approach allows description of the behavior of an unobserved population (ie, HSCs) on the basis of the behavior of observed progeny cells (ie, granulocytes and lymphocytes). The results of previous limiting-dilution, competitive-repopulation studies in 44 mice were compared with the results of simulated transplantation studies to identify parameters that led to comparable outcomes. Using this approach, we estimated that murine HSCs replicate (on average) once every 2.5 weeks and that the frequency of murine HSCs is 8 per 10(5) nucleated marrow cells. If it is assumed that short-term repopulating cells are distinct from HSCs, that they contribute to hemopoiesis early after transplantation, and that they are independently regulated, a frequency of 4 HSCs per 10(5) nucleated marrow cells also allows simulations that best approximate the observed data. When stochastic modeling and computer simulation were applied to limiting-dilution, autologous-transplantation studies in cats heterozygous for glucose-6-phosphate-dehydrogenase, different estimates of HSC replication rate (1 per 8.3-10 weeks) and frequency (6 per 10(7) cells) were derived. Therefore, it appears that these parameters vary inversely with increased longevity, size, or both. An implication of these data is that human HSCs may be less frequent and replicate more slowly. These findings on cell kinetics have several implications.