Referral patterns and attitudes of Primary Care Physicians towards chiropractors

BACKGROUND: Despite the increasing usage and popularity of chiropractic care, there has been limited research conducted to examine the professional relationships between conventional trained primary care physicians (PCPs) and chiropractors (DCs). The objectives of our study were to contrast the intra-professional referral patterns among PCPs with referral patterns to DCs, and to identify predictors of PCP referral to DCs. METHODS: We mailed a survey instrument to all practicing PCPs in the state of Iowa. Descriptive statistics were used to summarize their responses. Multivariable logistic regression analyses were conducted to identify demographic factors associated with inter-professional referral behaviors. RESULTS: A total of 517 PCPs (33%) participated in the study. PCPs enjoyed strong intra-professional referral relationships with other PCPs. Although patients exhibited a great deal of interest in chiropractic care, PCPs were unlikely themselves to make formal referral relationships with DCs. PCPs in a private practice arrangement were more likely to exhibit positive referral attitudes towards DCs (p = 0.01). CONCLUSION: PCPs enjoy very good professional relationships with other PCPs. However, the lack of direct formalized referral relationships between PCPs and chiropractors has implications for efficiency, continuity, quality, and patient safety in the health care delivery system. Future research must focus on identifying facilitators and barriers for developing positive relationships between PCPs and chiropractors

Genomic reconstruction of the SARS-CoV-2 epidemic in England.

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3,4,5,6,7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease