Optimized Risk Score to Predict Mortality in Patients With Cardiogenic Shock in the Cardiac Intensive Care Unit

The association of the Sequential Organ Failure Assessment score at intensive care unit discharge with intensive care unit readmission in the cardiac intensive care unit

AIMS

Unplanned intensive care unit (ICU) readmissions contribute to increased morbidity, mortality, and healthcare costs. The severity of patient illness at ICU discharge may predict early ICU readmission. Thus, in this study, we investigated the association of cardiac ICU (CICU) discharge Sequential Organ Failure Assessment (SOFA) score with unplanned CICU readmission in patients admitted to the CICU.

METHODS AND RESULTS

We retrospectively reviewed the hospital medical records of 4659 patients who were admitted to the CICU from 2012 to 18. Sequential Organ Failure Assessment scores at CICU admission and discharge were obtained. The predictive performance of organ failure scoring was evaluated by using area under the receiver operating characteristic (AUROC) curves. The primary outcome was unplanned CICU readmission. Of the 3949 patients successfully discharged from the CICU, 184 (4.7%) had an unplanned CICU readmission or they experienced a deteriorated condition but died without being readmitted to the CICU (readmission group). The readmission group had significantly higher rates of organ failure in all organ systems at both CICU admission and discharge than the non-readmission group. The AUROC of the discharge SOFA score for CICU readmission was 0.731, showing good predictive performance. The AUROC of the discharge SOFA score was significantly greater than that of either the initial SOFA score (P = 0.020) or the Acute Physiology and Chronic Health Evaluation II score (P < 0.001). In the multivariable regression analysis, SOFA score, overweight or obese status, history of heart failure, and acute heart failure as reasons for ICU admission were independent predictors of unplanned ICU readmission during the same hospital stay.

CONCLUSION

The discharge SOFA score may identify patients at a higher risk of unplanned CICU readmission, enabling targeted interventions to reduce readmission rates and improve patient outcomes.

Development of an optimal short form of the GAD-7 scale with cross-cultural generalizability based on Riskslim

Despite the relatively small number of items in the GAD-7, fewer items are increasingly sought to shorten testing time in large-scale mental health screenings. As a result, short forms based on the GAD-7, the GAD-2, and GAD-mini, have become popular. However, the GAD-2 and GAD-mini have reported lower diagnostic accuracy in some cultural contexts, implying that a validated short-form version of the GAD-7 may be lacking in large-scale cross-cultural anxiety screening. Based on this, to develop an optimal short form of the GAD-7 with cross-cultural stability, we utilized seven GAD-7 datasets from six different countries, totaling 47,484 participants. Five 2 to 6 item short forms of the GAD were constructed using the Riskslim machine learning algorithm. We evaluated the diagnostic accuracy of the GAD-7 short forms in the training and test sets based on the coefficient of determination(R2) and area under the curve(AUC) metrics, and the results showed that GAD-R2 performed poorly in some cultures, and all of the 3 to 6 item short forms of the GAD performed good in cross-cultural diagnostic rates, with the GAD-R6 showing the highest diagnostic accuracy in all cultures; GAD-R3 outperformed GAD-R2, GAD-2, and GAD-mini in all cultures; GAD-R3 had higher generalizability across cultures and special populations; Given that the GAD-R3 was shorter and nearly as accurate as the GAD-R6, we recommend the use of the GAD-R3 in clinical studies and epidemiologic investigations. And we recommend the optimal actual cutoff value of 15 for GAD-R3. Overall, we recommend GAD-R3 as the short-form version of GAD-7 in cross-cultural studies. However, the 2-item GAD scale is also optimal for the short-form version in clinical practice.

Patent and Bibliometric Analysis of the Scientific Landscape of the Use of Pulse Oximeters and Their Prospects in the Field of Digital Medicine

This study conducted a comprehensive patent and bibliometric analysis to elucidate the evolving scientific landscape surrounding the development and application of pulse oximeters, including in the field of digital medicine. Utilizing data from the Lens database for the period of 2000-2023, we identified the United States, China, the Republic of Korea, Japan, Canada, Australia, Taiwan, and the United Kingdom as the predominant countries in patent issuance for pulse oximeter technology. Our bibliometric analysis revealed a consistent temporal trend in both the volume of publications and citations, underscoring the growing importance of pulse oximeters in digitally-enabled medical practice. Using the VOSviewer software(version 1.6.18), we discerned six primary research clusters: (1) measurement accuracy; (2) integration with the Internet of Things; (3) applicability across diverse pathologies; (4) telemedicine and mobile applications; (5) artificial intelligence and deep learning; and (6) utilization in anesthesiology, resuscitation, and intensive care departments. The findings of this study indicate the prospects for leveraging digital technologies in the use of pulse oximetry in various fields of medicine, with implications for advancing the understanding, diagnosis, prevention, and treatment of cardio-respiratory pathologies. The conducted patent and bibliometric analysis allowed the identification of technical solutions to reduce the risks associated with pulse oximetry: improving precision and validity, technically improved clinical diagnostic use, and the use of machine learning.