Background. This research is aimed at establishing and internally validating the risk nomogram of insulin resistance (IR) in a Chinese population of patients with polycystic ovary syndrome (PCOS). Methods. We developed a predictive model based on a training dataset of 145 PCOS patients, and data were collected between March 2018 and May 2019. The least absolute shrinkage and selection operator regression model was used to optimize function selection for the insulin resistance risk model. Multivariable logistic regression analysis was used to construct a prediction model integrating the function selected in the regression model of the least absolute shrinkage and selection operator. The predicting model’s characteristics of prejudice, disease, and lifestyle were analyzed using the C-index, the calibration diagram, and the study of the decision curve. External validity was assessed using the validation of bootstrapping. Results. Predictors contained in the prediction nomogram included occupation, disease durations (years), BMI, current use of metformin, and activities. With a C-index of 0.739 (95 percent confidence interval: 0.644–0.830), the model showed good differentiation and proper calibration. In the interval validation, a high C-index value of 0.681 could still be achieved. Examination of the decision curve found that the IR nomogram was clinically useful when the intervention was determined at the 11 percent IR potential threshold. Conclusion. This novel IR nomogram incorporates occupation, disease durations (years), BMI, current use of metformin, and activities. This nomogram could be used to promote the estimation of individual IR risk in patients with PCOS.

Rationale: The standardization, individualization, and rationalization of intensive care and treatment for severe patients have improved. However, the combination of corona virus disease 2019 (COVID-19) and cerebral infarction presents new challenges beyond routine nursing care.Patient concerns and diagnoses: This paper examines the rehabilitation nursing of patients with both COVID-19 and cerebral infarction as an example. It is necessary to develop a nursing plan for COVID-19 patients and implement early rehabilitation nursing for cerebral infarction patients.Interventions: Timely rehabilitation nursing intervention is essential to enhance treatment outcomes and promote patient rehabilitation. After 20 days of rehabilitation nursing treatment, patients showed significant improvement in visual analogue scale score, drinking test, and upper and lower limb muscle strength.Outcomes: Treatment outcomes for complications, motor function, and daily activities also improved significantly.Lessons: Critical care and rehabilitation specialist care play a positive role in ensuring patient safety and improving their quality of life by adapting measures to local conditions and the timing of care.