In-Hospital Mortality Prediction Model for Critically Ill Older Adult Patients Transferred from the Emergency Department to the Intensive Care Unit

Purpose

Studies on the prognosis of critically ill older adult patients admitted to the emergency department (ED) but requiring immediate admission to the intensive care unit (ICU) remain limited. This study aimed to develop an in-hospital mortality prediction model for critically ill older adult patients transferred from the ED to the ICU.

Patients and Methods

The training cohort was taken from the Medical Information Mart for Intensive Care IV (version 2.2) database, and the external validation cohort was taken from the Affiliated Dongyang Hospital of Wenzhou Medical University. In the training cohort, class balance was addressed using Random Over Sampling Examples (ROSE). Univariate and multivariate Cox regression analyses were performed to identify independent risk factors. These were then integrated into the predictive nomogram. In the validation cohort, the predictive performance of the nomogram was evaluated using the area under the curve (AUC) of the receiver operating characteristic curve, calibration curve, clinical utility decision curve analysis (DCA), and clinical impact curve (CIC).

Results

In the ROSE-balanced training cohort, univariate and multivariate Cox regression analysis identified that age, sex, Glasgow coma scale score, malignant cancer, sepsis, use of mechanical ventilation, use of vasoactive agents, white blood cells, potassium, and creatinine were independent predictors of in-hospital mortality in critically ill older adult patients, and were included in the nomogram. The nomogram showed good predictive performance in the ROSE-balanced training cohort (AUC [95% confidence interval]: 0.792 [0.783-0.801]) and validation cohort (AUC [95% confidence interval]: 0.780 [0.727-0.834]). The calibration curves were well-fitted. DCA and CIC demonstrated that the nomogram has good clinical application value.

Conclusion

This study developed a predictive model for early prediction of in-hospital mortality in critically ill older adult patients transferred from the ED to the ICU, which was validated by external data and has good predictive performance.

Sarcopenia Imperils Postoperative Long-Term Survival in HCC Patients with Metabolic Dysfunction-Associated Fatty Liver Disease: A Propensity Score Matching Analysis

Background

Recent research has suggested that sarcopenia may have an impact on postoperative outcomes. The number of hepatocellular carcinoma (HCC) patients with metabolic dysfunction-associated fatty liver disease (MAFLD) has increased significantly over time. The main objective of this study was to investigate the impact of sarcopenia on the prognosis of HCC patients with MAFLD after hepatectomy.

Methods

A multivariate Cox proportional hazards model and a propensity score matching (PSM) analysis were conducted to ensure that the baseline characteristics were similar. Kaplan‒Meier survival curves were used to compare the prognosis of the two groups.

Results

This study involved 112 HCC patients with MAFLD undergoing hepatectomy. Sarcopenia was indicated as a risk factor for both recurrence-free survival (RFS) and overall survival (OS) in HCC patients with MAFLD after multivariate analysis (p=0.002 and 0.022, respectively). After conducting PSM analysis, Kaplan‒Meier survival curve analysis revealed significant differences in both the RFS and OS between the two groups (p=0.0002 and p=0.0047, respectively). All results showed that sarcopenia had a poor prognosis for HCC patients with MAFLD undergoing hepatectomy.

Conclusion

In summary, our study suggests that sarcopenia might be a risk factor for OS and RFS in HCC patients with MAFLD who underwent hepatectomy through multivariate analysis and PSM analysis. Sarcopenia imperils postoperative survival rates and this finding can guide clinical decision-making. For postoperative patients, preventing or treating sarcopenia can potentially improve survival outcomes for patients with HCC and MAFLD.

Impact of Promising Biomarkers on Severity and Outcome of Acute Pulmonary Embolism

Background

Acute pulmonary embolism (APE) is a common clinical condition. Its severity ranges from asymptomatic radiological findings to fatal obstructive shock. The potential circulating biomarkers have been studied to predict APE outcomes. This study aimed to explore their predictive power on prognosis in APE.

Material and Method

It was a prospective observational study between March 2008 and April 2010. All consecutive patients diagnosed with APE were categorized as massive/high-risk, submassive/moderate-risk, and non-massive/low-risk. Cardiac troponin T (cTnT), myoglobin, N-terminal pro-brain natriuretic peptide (NT-proBNP), heart-type fatty acid-binding protein (H-FABP), growth differentiation factor-15 (GDF-15), and D-dimer levels were measured.

Results

Of these patients, 14 (29.8%), 16 (34.0%), and 17 (36.2%) patients were categorized as low-risk, moderate-risk, and high risk-patients, respectively. There was no significant difference between the patient groups categorized based on the risk stratification in terms of demographic and clinical characteristics. The cTnT, myoglobin, HFABP, and D-dimer levels have also not differed significantly between the groups. There was a significant difference between the groups in respect of NT-proBNP and GDF-15 levels (p=0.009 and p=0.037, respectively). Nine (19.1%) patients had died by the 3rd-month follow-up. Adverse events were seen in 26 (55.3%) patients. GDF-15 had the highest area under the curve (AUC) value for predicting any adverse event (cut-off value=9.3 ng/mL, AUC=0.796, CI (confidence interval) 95%: 0.653-0.899). NT-ProBNP was determined as the best predictor for mortality (cut-off value=229.2 pg/mL, AUC=0.889, CI 95%: 0.756-0.964).

Conclusion

Higher levels of NT-proBNP and GDF-15 were found to be associated with more severe APE, worse outcomes, and mortality.

Factors and Outcomes Associated with Failed Noninvasive Positive Pressure Ventilation in Patients with Acute Respiratory Failure

Background

The decision guild for non-invasive positive pressure ventilation (NPPV) application in acute respiratory failure (ARF) patients still needs to work out.

Methods

Adult patients with acute hypoxemic or hypercapnic respiratory failure were recruited and treated with NPPV or primary invasive mechanical ventilation (IMV). Patients’ characteristic and clinical outcomes were recorded. Logistic regression models were used to estimate the adjusted odds ratio (aOR) and 95% confidence intervals for baseline characteristics and clinical outcomes. Subgroup analyses by reason behind successful NPPV were conducted to ascertain if any difference could influence the outcome.

Results

A total of 4525 ARF patients were recruited in our facility between year 2015 and 2017. After exclusion, 844 IMV patients, 66 patients with failed NPPV, and 74 patients with successful NPPV were enrolled. Statistical analysis showed APACHE II score (aOR = 0.93), time between admission and start NPPV (aOR = 0.92), and P/F ratio (aOR = 1.04) were associated with successful NPPV. When comparing with IMV patients, failed NPPV patients displayed a significantly lower APACHE II score, higher Glasgow Coma Scale, longer length of stay in hospital, longer duration of invasive ventilation, RCW/Home ventilator, and some comorbidities.

Conclusion

APACHE II score, time between admission and start NPPV, and PaO2 can be predictors for successful NPPV. The decision of NPPV application is critical as ARF patients with failed NPPV have various worse outcomes than patients receiving primary IMV.

Prevalence and Perception Among Saudi Arabian Population About Resharing of Information on Social Media Regarding Natural Remedies as Protective Measures Against COVID-19

INTRODUCTION

Ever since COVID-19 was declared as a global pandemic, there has been a prevalence of misinformation circulating online on social media platforms. In order to better tackle COVID-19 it is important to determine how the general population perceive the sharing of medical information on social media platforms. Based on this, the aim of the study is to analyse the perception of Saudi Arabian Health Care Workers' (HCWs) and Non-Health Care Workers' (NHCWs) regarding the sharing and resharing of medical information, whether true or false, on social media platforms regarding COVID-19.

METHODS

To achieve the aim of this study, the general objective is to identify the most commonly used Social Media Platforms, determine the proportion of the Saudi Arabian population who have participated in recirculating information in those social media platforms, and to analyse their perception of medical information sharing in social media platforms. This study was conducted using a quantitative research methodology. The measurement tool used for this study was an online survey conducted using Google Survey. A 10-item questionnaire was adopted and translated to Arabic to conduct the survey.

RESULTS

The total number of responses for the study were N=1249. The findings of the study indicate that Saudi Arabian general population understand the prevalence of unverified information, but are accepting of the practice of sharing information without evidence on social media platforms, with the belief that such information does not cause actual harm to the general public, but instead would be beneficial. WhatsApp was the most preferred social media platform for receiving and sharing information among participants, followed by Twitter and Snapchat.

CONCLUSION

The findings of this study indicate that the Saudi Arabian population are more wary than the global general population regarding misinformation online on social media platforms regarding COVID-19.