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Case summary An 8-year-old neutered female domestic shorthair cat was referred with complaints of lethargy, anorexia, fever, tachypnoea and a pulmonary mass on thoracic radiography. Whole-body CT revealed the presence of a nodular lesion in the right caudal lobe of the lung. Fine-needle aspiration of the lung mass yielded purulent fluid and cytology showed a large number of mildly to moderately degenerated neutrophils with numerous cocci and bacilli, leading to the diagnosis of a lung abscess. Empirical administration of doxycycline and orbifloxacin was initiated on the day of referral. Bacterial culture and antibiotic susceptibility tests using the collected fluid sample detected two types of bacteria, which were susceptible to both antibiotics. The clinical signs of the cat improved after the initiation of treatment, and the antibiotics were discontinued 28 days later, after the lung lesions disappeared. No recurrence of lung abscess was observed until 588 days after the discontinuation of treatment. Relevance and novel information Only one case of a lung abscess has been previously reported in cats. Furthermore, while surgical resection is the most common treatment for lung abscesses in the field of veterinary medicine, this is the first report of successful treatment with antibiotic administration alone.

In both human and veterinary medicine, computed tomography (CT) volumetry provides a quantitative and accurate measure of liver volume. While CT volumetry is recognized as a useful method for assessing liver volume in dogs, a statistically significant reference interval for liver volume in dogs with no history of hepatic disease has not been reported. The purpose of the present study was to define a reference interval for liver volume with no history of hepatic disease using CT volumetry. Medical records from 2 June 2020 to 25 July 2022 were retrospectively reviewed, including 121 dogs that underwent abdominal CT scans and had no history of hepatic disease. Liver volumes were measured using CT volumetry and normalized by body weight. The median of normalized CT-based liver volume in 121 dogs was 22.2 cm3/kg. Based on these data, a weight-based reference interval lower limit of 11.1–15.5 (90% confidence interval [CI]) to an upper limit of 31.9–42.6 (90% CI) cm3/kg for CT-based liver volume was defined in dogs without hepatic disease. This study provides an accurate assessment of liver volume changes in dogs with various hepatic diseases.

Bidirectional patellar luxation (BPL) is a relatively rare form of patellar luxation, with limited information reported regarding breed predisposition and etiology. The purpose of this study was to describe the patient characteristics and radiographic measures of proximodistal patellar position associated with BPL in dogs in Japan, compared with dogs with medial patellar luxation (MPL). A retrospective medical record search of surgically corrected MPL and BPL dogs was performed, and breed, age, sex, body weight, and presence of the patella alta in the extended-stifle position were recorded. The ratio of the patellar ligament length to patella length (PLL/PL) and the ratio of the distance between the proximal pole of the patella and the femoral condyle to patella length (A/PL) were measured on stifle radiographs. A total of 35 dogs with BPL and 95 dogs with MPL were included. The BPL was most commonly present in Toy Poodles (odds ratio compared to MPL dogs: 7.05) in the present study. There were no significant differences in age, sex, or body weight between the BPL and MPL groups. Patella alta in the extended-stifle position was more common in the BPL group (23.4%) than in the MPL group (0.8%). However, there were no significant differences in PLL/PL or A/PL between the BPL and MPL groups. The study highlights BPL in different dog breeds in Japan, and suggests that the occurrence of BPL may be related to stifle extension. However, more research is needed to fully understand the etiology of BPL.

BackgroundDespite accumulating evidence concerning the association between daily step counts and mortality or disease risks, it is unclear whether daily step counts are associated with healthy life years.MethodsWe used the combined dataset of the Comprehensive Survey of Living Conditions and the National Health and Nutrition Survey conducted for a randomly sampled general population in Japan, 2019. Daily step counts were measured for 4957 adult participants. The associations of daily step counts with activity limitations in daily living and self-assessed health were evaluated using a multivariable logistic regression model. The bootstrap method was employed to mitigate uncertainties in estimating the threshold of daily step counts.ResultsThe median age was 60 (44–71) years, and 2592 (52.3%) were female. The median daily step counts were 5650 (3332–8452). The adjusted OR of activity limitations in daily living for the adjacent daily step counts was 0.27 (95% CI 0.26 to 0.27) for all ages and 0.25 (95% CI 0.25 to 0.26) for older adults at the lowest, with the thresholds of significant association at 9000 step counts. The OR of self-assessed unhealthy status was 0.45 (95% CI 0.44 to 0.46) for all ages and 0.42 (95% CI 0.41 to 0.43) for older adults at the lowest, with the thresholds at 11 000 step counts.ConclusionDaily step counts were significantly associated with activity limitations in daily living and self-assessed health as determinants of healthy life years, up to 9000 and 11 000 step counts, respectively. These results suggest a target of daily step counts to prolong healthy life years within health initiatives.

In some countries, including Japan-the leading country in terms of longevity, life expectancy has been increasing; meanwhile, healthy life years have not kept pace, necessitating an effective health policy to narrow the gap. The aim of this study is to develop a prediction model for healthy life years without activity limitations and deploy the model in a health policy to prolong healthy life years. The Comprehensive Survey of Living Conditions, a cross-sectional national survey of Japan, was conducted by the Japanese Ministry of Health, Labour and Welfare in 2013, 2016, and 2019. The data from 1,537,773 responders were used for modelling using machine learning. All participants were randomly split into training (n=1,383,995, 90%,) and test (n=153,778, 10%) subsets. Extreme gradient boosting classifier was implemented. Activity limitations were set as the target. Age, sex, and 40 types of diseases or injuries were included as features. Healthy life years without activity limitations were calculated by incorporating the predicted prevalence rate of activity limitations in a life table. For the wide utility of the model in individuals, we developed an application tool for the model. In the groups without (n=1,329,901) and with (n=207,872) activity limitations, the median age was 47 (IQR 30-64) and 69 (IQR 54-80) years, respectively (P<.001); female sex comprised 51.3% (n=681,794) in the group without activity limitations and 56.9% (n=118,339) in the group with activity limitations (P<.001). A total of 42 features were included in the feature set. Age had the highest impact on model accuracy, followed by depression or other mental diseases; back pain; bone fracture; other neurological disorders, pain, or paralysis; stroke, cerebral hemorrhage, or infarction; arthritis; Parkinson disease; dementia; and other injuries or burns. The model exhibited high performance with an area under the receiver operating characteristic curve of 0.846 (95% CI 0.842-0.849) with exact calibration for the average probability and fraction of positives. The prediction results were consistent with the observed values of healthy life years for both sexes in each year (range of difference between predictive and observed values: -0.89 to 0.16 in male and 0.61 to 1.23 in female respondents). We applied the prediction model to a regional health policy to prolong healthy life years by adjusting the representative predictors to a target prevalence rate. Additionally, we presented the health condition without activity limitations index, followed by the application development for individual health promotion. The prediction model will enable national or regional governments to establish an effective health promotion policy for risk prevention at the population and individual levels to prolong healthy life years. Further investigation is needed to validate the model's adaptability to various ethnicities and, in particular, to countries where the population exhibits a short life span.