Evaluation of a New Zealand program to improve transition of care for older high risk adults

Transition interventions aim to improve care and reduce hospital readmissions but evaluations of these interventions have reported inconsistent results. We report on the evaluation of an intervention implemented in Auckland, New Zealand. Participants were people over the age of 65 who had an acute medical admission and were at high risk of readmission. The intervention included an improved discharge process and nurse telephone follow‐up soon after discharge. Outcomes were 28 day readmission rates and emergency attendances. The study is observational, using both interrupted times series and regression discontinuity designs. 5239 patients were treated over a one year period. There was no change in readmission rates or ED attendances or secondary outcomes. Not all patients received all components of the intervention. This transition intervention was not successful. Possible reasons for this and implications are discussed. Although non‐experimental methods were used, we believe the results are robust.     

Sporotrichosis masquerading as pyoderma gangrenosum: case report and review of 19 cases of sporotrichosis

We present the case of a 59-year-old woman who had large ulcerations on her right leg that were diagnosed initially as pyoderma gangrenosum and treated with three immunosuppressive agents (cyclosporin, prednisone and azathioprine) for 6 months. Results of a biopsy at 6 months showed numerous cigar-shaped bodies consistent with Sporothrix schenckii; identification was confirmed by tissue culture. A retrospective review was performed for all cases diagnosed as sporotrichosis from tissue culture or biopsy specimens at the Mayo Clinic. Nineteen cases were identified. The present case was the only one in which fungal organisms were visible on histological examination. The present case emphasizes the importance of making a definitive histological diagnosis in unusual ulcer cases or in suspected cases of pyoderma gangrenosum before the initiation of immunosuppressive therapy. The large number of cigar-shaped bodies in the tissue is a rare finding in sporothrix infection and has been reported in only two cases previously.     

Predicting prognosis in patients with stroke treated with intravenous alteplase through blood pressure changes: A machine learning-based approach

The use of machine learning (ML) in predicting disease prognosis has increased, and researchers have adopted different methods for variable selection to optimize early screening for AIS to determine its prognosis as soon as possible. We aimed to improve the understanding of the predictors of poor functional outcome at three months after discharge in AIS patients treated with intravenous thrombolysis and to construct a highly effective prognostic model to improve prediction accuracy. And four ML methods (random forest, support vector machine, naive Bayesian, and logistic regression) were used to screen and recombine the features for construction of an ML prognostic model. A total of 352 patients that had experienced AIS and had been treated with intravenous thrombolysis were recruited. The variables included in the model were NIHSS on admission, age, white blood cell count, percentage of neutrophils and triglyceride after thrombolysis, tirofiban, early neurological deterioration, early neurological improvement, and BP at each time point or period. The model's area under the curve for predicting 30-day modified Rankin scale was 0.790 with random forest, 0.542 with support vector machine, 0.411 with naive Bayesian, and 0.661 with logistic regression. The random forest model was shown to accurately evaluate the prognosis of AIS patients treated with intravenous thrombolysis, and therefore they may be helpful for accurate and personalized secondary prevention. The model offers improved prediction accuracy that may reduce rates of misdiagnosis and missed diagnosis in patients with AIS.