Fever and hypothermia do not affect the all-cause 30-day hospital readmission.

BACKGROUND: One of the goals of the Affordable Care Act is to decrease hospital readmissions. While widely adhered to, there is no published research to support the practice of delaying discharge if patients exhibit fever or hypothermia in the preceding 24 h, which is the focus of our study. METHODS: Retrospective analysis of the minimal (Tmin) and maximal (Tmax) body temperatures collected during the last 24 h before discharge of 19,038 inpatients. Fever was defined as Tmax >99.5F (+1SD from the mean Tmax) or >100.2F (+2SDs), and hypothermia as Tmin <97.1F (-1SD from the mean Tmin) or <96.7F (-2SDs). RESULTS: The overall readmission rate was 10.2% (highest for General Medicine and Pediatrics). The rate of readmission was not different between normothermic patients and those with abnormal body temperature, except for higher readmission rate (12.2%) for patients with fever at 1SD from Tmax compared with normothermic patients (9.96%). Neither fever nor hypothermia was associated with shorter time to readmission, except for fever at 2 SDs from Tmax (10.6 days) compared with normothermic patients (12.6 days). Surprisingly, univariate analysis revealed that higher Tmax and older age were associated with lower readmission probability. Both uni- and multivariate analysis showed that the presence of fever is associated with lower readmission probability. Evaluating 200 individual cases, the most common explanation for body temperature abnormality was infection and 90% of the preventable readmissions were due to infection. CONCLUSIONS: Abnormal body temperature 24 h prior to discharge was not useful for predicting the probability of readmission.

COVID-19 vaccination intention and behavior in a large, diverse, U.S. refugee population.

INTRODUCTION: Refugees often face increased risk of exposure to COVID-19 due to their disproportionate representation in the essential workforce and crowded household conditions. There is a paucity of data about risk factors for under-immunization for COVID-19 among refugees. METHODS: Refugees were surveyed in two phases that corresponded to before and after wide availability of COVID-19 vaccines. Participants were asked about their attitudes, and perceptions about COVID-19, previous acceptance of vaccines, sources utilized to obtain trusted health information, and intent to get vaccinated. The overall participant vulnerability was assessed using the social vulnerability index. In-depth semi-structured interviews were completed with key stakeholders through snowball sampling. RESULTS: Of 247 refugees, 244 agreed to participate in the initial survey. Among those, 140 (57.4%) intended to get vaccinated, 43 (17.6%) were unsure, and 61 (25%) did not intend to get vaccinated. In the follow up survey, all 215 who were reached, agreed to provide information about their vaccination status. Among those respondents, 141 (65.6%) were either vaccinated or expressed intent to do so, and 74 (34.4%) remained hesitant. We did not observe any significant correlation between socio-demographic variables, country of origin, and vaccination status/intent. Among those who initially intended to get vaccinated, nearly 1 in 5 changed their mind and decided to forego vaccination, and among those who initially did not plan getting vaccinated, 1 in 3 changed their mind and got vaccinated. Fears related to the vaccine, concerns that the vaccine is religiously prohibited, "wait and see" how others did with the vaccine, communication and transportation barriers were commonly cited as reason not to get vaccinated. CONCLUSIONS: Over a third of refugees in our study were hesitant to get vaccinated. Refugees desired additional education about the benefits and safety of vaccines along with easier access to vaccination clinics in their communities.

Integrated Care Management to Improve Diabetes Outcomes in Refugee and Immigrant Patients (I-Care).

Purpose: Refugee and immigrant patients face significant barriers to health care and are more likely to have poorly controlled chronic disease than the general U.S. population. I-Care aims to improve health equity for refugees and immigrants who face a disproportionate burden of chronic disease. Methods: Refugees and immigrants with uncontrolled diabetes and associated cardiovascular risk factors were enrolled in a care management program within an academic adult medicine clinic. The program utilized a care manager to coordinate care and services between designated primary care providers, affiliated clinical teams, and community partners. Health literacy, chronic disease parameters, and care utilization were assessed at enrollment and 8-12 months later. Results: A total of 50 refugees and immigrants were followed for 8 to 12 months. Clinical parameters found a reduced mean HbA1c from 9.32 to 8.60 (p=0.05) and reduced low-density lipoprotein mean from 96.22 to 86.60 (p=0.01). The frequency of normal blood pressures was 9 (18%) at enrollment and 16 (32%) at 1 year. The cumulative frequency of emergency room visits decreased from 66% to 36% and hospitalizations from 22% to 8%. Rates of comprehensive care monitoring, including monofilament testing and one-time ophthalmology visits, increased from 60% to 82% and from 32% to 42%, respectively. Cumulative frequency of interdisciplinary support engagement with pharmacy and nutrition visits increased from 58% to 78% and from 26% to 38%, respectively. Conclusion: This program highlights the importance of a multidisciplinary community-engaged care model that has demonstrated improvement in quality metrics and health care costs for refugees and immigrants.

A comparison of passive surveillance and active cluster-based surveillance for dengue fever in southern coastal Ecuador.

BACKGROUND: Dengue is a major emerging infectious disease, endemic throughout the tropics and subtropics, with approximately 2.5 billion people at risk globally. Active (AS) and passive surveillance (PS), when combined, can improve our understanding of dengue's complex disease dynamics to guide effective, targeted public health interventions. The objective of this study was to compare findings from the Ministry of Health (MoH) PS to a prospective AS arbovirus research study in Machala, Ecuador in 2014 and 2015. METHODS: Dengue cases in the PS system were compared to laboratory confirmed acute dengue illness cases that entered the AS study during the study period. Variables of interest included age class and sex. Outbreak detection curves by epidemiologic week, overall cumulative incidence and age-specific incidence proportions were calculated. Descriptive statistics were tabulated for all variables of interest. Chi-square tests were performed to compare demographic characteristics between the AS and PS data sets in 2014 and 2015. RESULTS: 177 and 245 cases were identified from 1/1/2014 to 12/31/2015 by PS and AS, respectively; nine cases appeared in both systems. AS identified a greater number of laboratory-confirmed cases in 2014, accounting for more than 60% of dengue cases in the study area. In 2015, the opposite trend was observed with PS identifying 60% of the dengue cases in the study area. Peak transmission time in laboratory confirmed dengue illness, as noted by AS and PS was similar in 2014, whereas earlier detection (7 weeks) was observed by AS in 2015. Younger patients were more frequently identified by PS, while older patients were identified more frequently by AS. The cumulative incidence proportion for laboratory confirmed dengue illness reported via PS to the MoH was 4.12 cases per 10,000 residents in 2014, and 2.21 cases per 10,000 residents in 2015. CONCLUSIONS: Each surveillance system captured distinct demographic subgroups within the Machala population, possibly due to differences in healthcare seeking behaviors, access to care, emerging threats of other viruses transmitted by the same mosquito vector and/or differences in clinical presentation. Integrating AS with pre-existing PS can aid in identifying additional cases in previously underdiagnosed subpopulations, improving our understanding of disease dynamics, and facilitating the implementation of timely public health interventions.

Severity Index for Suspected Arbovirus (SISA): Machine learning for accurate prediction of hospitalization in subjects suspected of arboviral infection.

BACKGROUND: Dengue, chikungunya, and Zika are arboviruses of major global health concern. Decisions regarding the clinical management of suspected arboviral infection are challenging in resource-limited settings, particularly when deciding on patient hospitalization. The objective of this study was to determine if hospitalization of individuals with suspected arboviral infections could be predicted using subject intake data. METHODOLOGY/PRINCIPAL FINDINGS: Two prediction models were developed using data from a surveillance study in Machala, a city in southern coastal Ecuador with a high burden of arboviral infections. Data were obtained from subjects who presented at sentinel medical centers with suspected arboviral infection (November 2013 to September 2017). The first prediction model-called the Severity Index for Suspected Arbovirus (SISA)-used only demographic and symptom data. The second prediction model-called the Severity Index for Suspected Arbovirus with Laboratory (SISAL)-incorporated laboratory data. These models were selected by comparing the prediction ability of seven machine learning algorithms; the area under the receiver operating characteristic curve from the prediction of a test dataset was used to select the final algorithm for each model. After eliminating those with missing data, the SISA dataset had 534 subjects, and the SISAL dataset had 98 subjects. For SISA, the best prediction algorithm was the generalized boosting model, with an AUC of 0.91. For SISAL, the best prediction algorithm was the elastic net with an AUC of 0.94. A sensitivity analysis revealed that SISA and SISAL are not directly comparable to one another. CONCLUSIONS/SIGNIFICANCE: Both SISA and SISAL were able to predict arbovirus hospitalization with a high degree of accuracy in our dataset. These algorithms will need to be tested and validated on new data from future patients. Machine learning is a powerful prediction tool and provides an excellent option for new management tools and clinical assessment of arboviral infection.

Lead Exposure in Newly Resettled Pediatric Refugees in Syracuse, NY.

Lead is a major environmental toxin that presents numerous health consequences for children. Refugee children are at a risk of lead poisoning post-resettlement due to urban housing and environmental inequalities stemming from lack of funding, legislation, and advocacy. This article addresses lead exposure upon arrival and post-resettlement in 705 refugee children (age 0-16 years) attending a university clinic in Syracuse, NY, a city with a large refugee population. 17% of the newly arrived children had elevated blood lead levels (BLLs) (≥ 5 µg/dL); 10% had elevated BLL upon follow-up; 8.3% of the children's follow-up elevated BLL were new exposures. 30% were found to have increased BLL at follow-up regardless of arrival status. An analysis of new exposures found a significant proportion of children would have been missed on routine screening that targets children < 2 years old. Primary prevention efforts are needed to prevent exposure and address risks to improve the health of all children locally, including newly resettled refugees.

Chagas Disease in Southern Coastal Ecuador: Coinfections with Arboviruses and a Comparison of Serological Assays for Chagas Disease Diagnosis.

Occurrence of Chagas disease and arbovirus coinfections is unknown, despite the vast co-endemic areas throughout the Americas. This study examined the proportion of individuals positive for Trypanosoma cruzi and coinfections with dengue, chikungunya, and Zika viruses in Machala, Ecuador (January 2014-December 2015). Chagas seropositivity was evaluated with five commercially available assays. Dengue infections were identified by nonstructural protein 1 rapid test and enzyme linked immunosorbent assay (ELISA), immunoglobulin M ELISA, and reverse transcription PCR (RT-PCR); chikungunya and Zika infections were identified by RT-PCR. Of 658 individuals, six were positive for T. cruzi (0.91%), including one T. cruzi/dengue coinfection and one T. cruzi/chikungunya/dengue coinfection. The clinical manifestations of coinfected individuals corresponded to severe dengue and dengue with warning signs, respectively. We observed discrepant results by using the Hemagen Chagas kit and the rapid test Chagas Detect Plus (false positives: 3.9% and 15.4%), highlighting the need to assess diagnostic assays in geographic regions with distinct taxonomic units of T. cruzi.

The Burden of Dengue Fever and Chikungunya in Southern Coastal Ecuador: Epidemiology, Clinical Presentation, and Phylogenetics from the First Two Years of a Prospective Study.

Here, we report the findings from the first 2 years (2014-2015) of an arbovirus surveillance study conducted in Machala, Ecuador, a dengue-endemic region. Patients with suspected dengue virus (DENV) infections (index cases, N = 324) were referred from five Ministry of Health clinical sites. A subset of DENV-positive index cases (N = 44) were selected, and individuals from the index household and four neighboring homes within 200 m were recruited (N = 400). Individuals who entered the study, other than the index cases, are referred to as associates. In 2014, 70.9% of index cases and 35.6% of associates had acute or recent DENV infections. In 2015, 28.3% of index cases and 12.8% of associates had acute or recent DENV infections. For every DENV infection captured by passive surveillance, we detected an additional three acute or recent DENV infections in associates. Of associates with acute DENV infections, 68% reported dengue-like symptoms, with the highest prevalence of symptomatic acute infections in children aged less than 10 years. The first chikungunya virus (CHIKV) infections were detected on epidemiological week 12 in 2015; 43.1% of index cases and 3.5% of associates had acute CHIKV infections. No Zika virus infections were detected. Phylogenetic analyses of isolates of DENV from 2014 revealed genetic relatedness and shared ancestry of DENV1, DENV2, and DENV4 genomes from Ecuador with those from Venezuela and Colombia, indicating the presence of viral flow between Ecuador and surrounding countries. Enhanced surveillance studies, such as this, provide high-resolution data on symptomatic and inapparent infections across the population.

Case Report: An Acute Chikungunya Infection and a Recent Secondary Dengue Infection in a Peripartum Case in Ecuador.

Dengue virus (DENV) and chikungunya virus (CHIKV) are transmitted by the same mosquito vectors and now co-circulate in many parts of the world; however, coinfections and serial infections are not often diagnosed or reported. A 38-week pregnant woman was admitted to the hospital with a diagnosis of suspected DENV and CHIKV in southern coastal Ecuador. The pregnancy was complicated by mild polyhydramnios and fetal tachycardia, and a healthy newborn was born. The patient was positive for a recent secondary DENV infection (Immunoglobulin M and Immunoglobulin G positive) and an acute CHIKV infection (real-time reverse transcriptase polymerase chain reaction positive) (Asian genotype). The newborn was not tested for either virus. This case resulted in a benign clinical course with a favorable pregnancy outcome.

Emotional Distress, Medical Utilization, and Disability Claims in Adult Refugees.

The refugee health screener-15 (RHS-15) is utilized as a diagnostic proxy for common mental disorders in refugees. Studies are needed to determine its clinical and social utility. A retrospective chart analysis of adult refugees compared RHS-15 scores to utilization of medical services and presence of disability claims. Refugees with negative, positive, and highly positive RHS-15 scores attended 3.1, 4.4, and 5.7 mean primary care visits and 1.6, 2.8, and 4.4 mean non-primary care visits, respectively (p < .000). The 11% (43/392) claiming disability were 5.1 times more likely to have a positive RHS-15 (OR 4.3, 95% CI 2.1-8.8). A positive RHS-15 was not predictive of a disability claim (19% PPV), and those with a negative RHS-15 were unlikely to claim disability (96% NPV). The RHS-15 score correlates with visit utilization. A positive score is not predictive of a subsequent disability claim.