Information-motivation-behavioral guided nursing for stroke patients with pulmonary dysfunction:A randomized controlled trial

BACKGROUND Patients with stroke frequently experience pulmonary dysfunction.AIM To explore the effects of information-motivation-behavioral(IMB)skills modelbased nursing care on pulmonary function,blood gas indices,complication rates,and quality of life(QoL)in stroke patients with pulmonary dysfunction.METHODS We conducted a controlled study involving 120 stroke patients with pulmonary dysfunction.The control group received routine care,whereas the intervention group received IMB-model-based nursing care.Various parameters including pulmonary function,blood gas indices,complication rates,and QoL were assessed before and after the intervention.RESULTS Baseline data of the control and intervention groups were comparable.Post-intervention,the IMB model-based care group showed significant improvements in pulmonary function indicators,forced expiratory volume in 1 sec,forced vital capacity,and peak expiratory flow compared with the control group.Blood gas indices,such as arterial oxygen pressure and arterial oxygen saturation,increased significantly,and arterial carbon dioxide partial.pressure decreased significantly in the IMB model-based care group compared with the control group.The intervention group also had a lower complication rate(6.67%vs 23.33%)and higher QoL scores across all domains than the control group.CONCLUSION IMB model-based nursing care significantly enhanced pulmonary function,improved blood gas indices,reduced complication rates,and improved the QoL of stroke patients with pulmonary dysfunction.Further research is needed to validate these results and to assess the long-term efficacy and broader applicability of the model.

Sleep disturbances and predictors of nondeployability among active-duty army soldiers: an odds ratio analysis of medical healthcare data from fiscal year 2018

Background:The impact of sleep disorders on active-duty soldiers’medical readiness is not currently quantified.Patient data generated at military treatment facilities can be accessed to create research reports and thus can be used to estimate the prevalence of sleep disturbances and the role of sleep on overall health in service members.The current study aimed to quantify sleep-related health issues and their impact on health and nondeployability through the analysis of U.S.military healthcare records from fiscal year 2018(FY2018).Methods:Medical diagnosis information and deployability profiles(e-Profiles)were queried for all active-duty U.S.Army patients with a concurrent sleep disorder diagnosis receiving medical care within FY2018.Nondeployability was predicted from medical reasons for having an e-Profile(categorized as sleep,behavioral health,musculoskeletal,cardiometabolic,injury,or accident)using binomial logistic regression.Sleep e-Profiles were investigated as a moderator between other e-Profile categories and nondeployability.Results:Out of 582,031 soldiers,48.4%(n=281,738)had a sleep-related diagnosis in their healthcare records,9.7%(n=56,247)of soldiers had e-Profiles,and 1.9%(n=10,885)had a sleep e-Profile.Soldiers with sleep e-Profiles were more likely to have had a motor vehicle accident(p OR(prevalence odds ratio)=4.7,95%CI 2.63–8.39,P≤0.001)or work/duty-related injury(p OR=1.6,95%CI 1.32–1.94,P≤0.001).The likelihood of nondeployability was greater in soldiers with a sleep e-Profile and a musculoskeletal e-Profile(p OR=4.25,95%CI 3.75–4.81,P≤0.001)or work/dutyrelated injury(p OR=2.62,95%CI 1.63–4.21,P≤0.001).Conclusion:Nearly half of soldiers had a sleep disorder or sleep-related medical diagnosis in 2018,but their sleep problems are largely not profiled as limitations to medical readiness.Musculoskeletal issues and physical injury predict nondeployability,and nondeployability is more likely to occur in soldiers who have sleep e-Profiles in addition to these issues.Addressing sleep problems may prevent accidents and injuries that could render a soldier nondeployable.