Variability in non-core vaccination rates of dogs and cats in veterinary clinics across the United States

Vaccination guidelines for dogs and cats indicate that core vaccines (for dogs, rabies, distemper, adenovirus, parvovirus; for cats, feline parvovirus, herpes virus-1, calicivirus) are essential to maintain health, and that non-core vaccines be administered according to a clinician’s assessment of a pet’s risk of exposure and susceptibility to infection. A reliance on individual risk assessment introduces the potential for between-practice inconsistencies in non-core vaccine recommendations. A study was initiated to determine non-core vaccination rates of dogs (Leptospira, Borrelia burgdorferi, Bordetella bronchiseptica, canine influenza virus) and cats (feline leukemia virus) in patients current for core vaccines in veterinary practices across the United States. Transactional data for 5,531,866 dogs (1,670 practices) and 1,914,373 cats (1,661 practices) were retrieved from practice management systems for the period November 1, 2016 through January 1, 2020, deidentified and normalized. Non-core vaccination status was evaluated in 2,798,875 dogs and 788,772 cats that were core-vaccine current. Nationally, median clinic vaccination rates for dogs were highest for leptospirosis (70.5%) and B. bronchiseptica (68.7%), and much lower for canine influenza (4.8%). In Lyme-endemic states, the median clinic borreliosis vaccination rate was 51.8%. Feline leukemia median clinic vaccination rates were low for adult cats (34.6%) and for kittens and 1-year old cats (36.8%). Individual clinic vaccination rates ranged from 0 to 100% for leptospirosis, B. bronchiseptica and feline leukemia, 0–96% for canine influenza, and 0–94% for borreliosis. Wide variation in non-core vaccination rates between clinics in similar geographies indicates that factors other than disease risk are driving the use of non-core vaccines in pet dogs and cats, highlighting a need for veterinary practices to address gaps in patient protection. Failure to implement effective non-core vaccination strategies leaves susceptible dogs and cats unprotected against vaccine-preventable diseases.     

Orientation and mobility outcome measures

Despite orientation and mobility (O&M) being a significant factor determining quality of life of people with low vision or blindness, there are no gold standard measures or agreement on how to measure O&M performance. In the first part of this systematic review, an inventory of O&M outcome measures used by recent studies to assess the performance of orientation and/or mobility of adults with vision impairment (low vision and blindness) is presented. A wide variety of O&M outcome measures have been implemented in different fields of study, such as epidemiologic research and interventional studies evaluating training, assistive technology, vision rehabilitation and vision restoration. The most frequent aspect of outcome measures is efficiency such as time, distance, speed and percentage of preferred walking speed, followed by obstacle contacts and avoidance, and dis/orientation and veering. Other less commonly used aspects are target identification, safety and social interaction and self-reported outcome measures. Some studies employ sophisticated equipment to capture and analyse O&M performance in a laboratory setting, while others carry out their assessment in real-world indoor or outdoor environments. In the second part of this review, the appropriateness of implementing the identified outcome measures to assess O&M performance in clinical and functional O&M practice is evaluated. Nearly a half of these outcome measures meet all four criteria of face validity (either clinical or functional), responsiveness, reliability and feasibility and have the potential to be implemented in clinical or functional O&M practice. The findings of this review confirm the complicated and dynamic nature of O&M. Multiple measures are required in any evaluation of O&M performance to facilitate holistic assessment of O&M abilities and limitations of each individual.     

New frontiers in applied veterinary point‐of‐capture diagnostics: Toward early detection and control of zoonotic influenza

Among the chief limitations in achieving early detection and control of animal‐origin influenza of pandemic potential in high‐risk livestock populations is the existing lag time between sample collection and diagnostic result. Advances in molecular diagnostics are permitting deployment of affordable, rapid, highly sensitive, and specific point‐of‐capture assays, providing opportunities for targeted surveillance driving containment strategies with potentially compelling returns on investment. Interrupting disease transmission at source holds promise of disrupting cycles of animal‐origin influenza incursion to endemicity and limiting impact on animal production, food security, and public health. Adoption of new point‐of‐capture diagnostics should be undertaken in the context of promoting robust veterinary services systems and parallel support for operationalizing pre‐authorized plans and communication strategies that will ensure that the full potential of these new platforms is realized.     

2010—2016年重庆市中毒病例流行病学特征及影响因素分析

对2010年1月—2016年7月重庆市中毒救治指定医疗机构收治的2 497例中毒患者进行回顾性分析。结果显示，中毒患者中男性1 230例（49.3%）、女性1 267例（50.7%）；分布最多的3个年龄段依次是41~50岁（18.5%）、≤10岁（16.4%）和21~30岁（13.0%）；死亡16例，病死率0.6%。中毒类型构成排前三位的是细菌（33.8%）、化学品（32.2%）、植物（14.8%）。中毒预后多因素Logistic回归分析结果显示重度中毒患者结局死亡的可能性是轻度患者的1 102倍。提示重庆市应重点关注农村地区41~50岁人群的细菌、化学品、药物中毒，同时应该加强儿童中毒防控工作。     

Discordant Electrocardiogram Left Ventricular Wall Thickness and Strain Findings in Influenza Myocarditis

A 42‐year‐old man presented with a viral prodrome and tested positive for influenza A. He rapidly deteriorated developing cardiogenic shock, rhabdomyolysis, and acute kidney injury. Patient improved 1 week later with supportive measures including vasopressors, inotropes, and an intraaortic balloon pump. We report this case as it highlights the discordance between echocardiographic ventricular wall thickening as a result of myocardial edema, and electrocardiographic findings at presentation, with a reversal in findings at time of resolution. Additionally, there was some suggestion of a regional pattern to the reduced longitudinal strain.     

广西防城港市2017年活禽市场环境样本禽流感监测

目的 了解防城港市活禽市场环境禽流感病毒监测情况,为科学评判疫情并采取适当的防控措施提供理论依据。方法 2017年3—4月在全市活禽市场外环境采集笼具擦物、冼禽污水、禽粪、砧板擦物、禽类饮用水等标本,用荧光定量PCR法检测禽流感病毒FluA、H5、H9、H7核酸,并进行统计学分析。结果 采集全市36个活禽市场外环境标本1 855份,阳性393份,阳性率为21.19%,其中H5阳性28份,H7阳性2份,H9阳性198份,H5和H9混合阳性37份,其他亚型（FluA阳性,H5、H7、H9 阴性）128份;不同地区标本阳性率差异有统计学意义（P<0.05）;城区和乡镇市场采集的标本的阳性率差异无统计学意义。5种类型的标本中,洗禽污水的阳性率最高,其次是砧板擦物, 再次是禽类饮用水和笼具擦物,禽粪的阳性率最低,差异有统计学意义（P<0.05）。结论 防城港市活禽市场环境普遍存在高致病性禽流感病毒的污染,H9亚型是主要的病原体,采取了综合防控措施后,防城港市没有发生人间禽流感疫情。     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.