Sex Differences in Cardiovascular Disease-Related Hospitalization and Mortality in Japan　- Analysis of Health Records From a Nationwide Claim-Based Database, the Japanese Registry of All Cardiac and Vascular Disease (JROAD).

BACKGROUND: The prevalence of cardiovascular disease (CVD) is rising in Japan with its aging population, but there is a lack of epidemiological data on sex differences in CVD, including acute coronary syndrome (ACS), acute heart failure (AHF), and acute aortic disease.Methods and Results: This retrospective study analyzed data from 1,349,017 patients (January 2012-December 2020) using the Japanese Registry Of All Cardiac and Vascular Diseases database. ACS patients were youngest on average (70.5±12.9 years) and had the lowest female proportion (28.9%). AHF patients had the oldest mean age (79.7±12.0 years) and the highest proportion of females (48.0%). Acute aortic disease had the highest in-hospital mortality (26.1%), followed by AHF (11.5%) and ACS (8.9%). Sex-based mortality differences were notable in acute aortic disease, with higher male mortality in Stanford Type A acute aortic dissection (AAD) with surgery (males: 14.2% vs. females: 10.4%, P<0.001) and similar rates in Type B AAD (males: 6.2% vs. females: 7.9%, P=0.52). Aging was a universal risk factor for in-hospital mortality. Female sex was a risk factor for ACS and acute aortic disease but not for AHF or Types A and B AAD. CONCLUSIONS: Sex-based disparities in the CVD-related hospitalization and mortality within the Japanese national population have been highlighted for the first time, indicating the importance of sex-specific strategies in the management and understanding of these conditions.

Decoding cardiogenic shock: assessing shock index and its variants as prognostic indicators for in-hospital mortality.

BACKGROUND: Cardiogenic shock (CS) is associated with high in-hospital mortality. Objective assessment of its severity and prognosis is paramount for timely therapeutic interventions. This study aimed to evaluate the efficacy of the shock index (SI) and its variants as prognostic indicators for in-hospital mortality. METHODS: A retrospective study involving 1282 CS patients were evaluated. Baseline patient characteristics, clinical trajectory, hospital outcomes, and shock indices were collected and analysed. Receiver operating characteristic (ROC) curves were employed to determine the predictive accuracy of shock indices in predicting in-hospital mortality. RESULTS: Of those evaluated, 866 (67.6%) survived until discharge. Non-survivors were older (66.0 ± 13.7 vs. 57.4 ± 16.2, P < 0.001), had a higher incidence of cardiac risk factors, and were more likely to present with acute coronary syndrome (33.4% vs. 16.1%, P < 0.001) and out-of-hospital cardiac arrest (11.3% vs. 5.3%, P < 0.001). All mean shock indices were significantly higher in non-survivors compared with survivors. ROC curves demonstrated that adjusted shock index (ASI), age-modified shock index (AMSI), and shock index-C (SIC) had the highest predictive accuracy for in-hospital mortality, with AUC values of 0.654, 0.667, and 0.659, respectively. Subgroup analysis revealed that SIC had good predictive ability in patients with STEMI (AUC: 0.714) and ACS (AUC: 0.696) while AMSI and ASI were notably predictive in the OHCA group (AUC: 0.707 and 0.701, respectively). CONCLUSIONS: Shock index and its variants, especially ASI, AMSI, and SIC, may be helpful in predicting in-hospital mortality in CS patients. Their application could guide clinicians in upfront risk stratification. SIC, ASI, and AMSI show potential in predicting in-hospital mortality in specific CS subsets (STEMI and OHCA). This is the first study to evaluate SI and its variants in CS patients.

The impact of smoking on third-degree atrioventricular block outcomes: A propensity-matched analysis.

Background: Third-degree atrioventricular (AV) blocks are rare but cause significant symptoms and require immediate intervention. Coronary artery disease (CAD) is felt to be the most common etiology. Although smoking is a prominent risk factor for CAD, there is a paucity of data assessing the direct effect of smoking on third-degree AV block. Methods: We performed a retrospective cohort study on adult-weighted admissions in 2019-2020 with a primary diagnosis of third-degree AV block and a history of smoking using the National Inpatient Sample (NIS) database. In-hospital mortality, rates of pacemaker insertion, cardiogenic shock, cardiac arrest, acute kidney injury (AKI), stroke, tracheal intubation, mechanical ventilation, mechanical circulatory support, vasopressor use, length of stay (LOS), and total hospitalization costs were analyzed using regression analysis. We performed a secondary analysis using propensity score matching to confirm the results. Results: A total of 77,650 admissions met inclusion criteria (33,625 females [43.3 %], 58,315. Caucasians [75 %], 7030 African American [9 %], 6155 Hispanic [7.9 %]; mean [SD] age 75.4.[10.2] years) before propensity matching. A total of 29,380 (37.8 %) patients with AV block were smokers.A total of 5560 patients with and without a history of smoking were matched for the analysis. Smokers had.decreased odds of mortality (aOR, 0.59; CI, 0.44-0.78; p < 0.001), cardiogenic shock, cardiac arrest, tracheal intubation, mechanical ventilation, shorter LOS, and lower total hospital costs in both the multivariable regression and propensity-matched analyses. Conclusion: Third-degree AV block had lower in-hospital mortality, cardiogenic shock, cardiac arrest, LOS, and total hospitalization cost in patients with smoking history.

Association between ambulance station case volume and clinical outcomes in moderate to severe trauma.

Objectives: The effect of the case volume of emergency medical services (EMS) on the clinical outcomes of trauma is uncertain. The purpose of this study was to evaluate the association between the case volume of an ambulance station and clinical outcomes in moderate to severe trauma patients.Methods: Adult trauma patients with injury severity scores greater than 8 who were transported by the EMS between 2018 and 2019 were analyzed. The main exposure was the annual case volume of moderate to severe trauma at the ambulance station where the patient-transporting ambulance was based: low-volume (less than 60 cases), intermediate-volume (between 60 and 89 cases), and high-volume (equal or greater than 90 cases). The primary outcome was in-hospital mortality. Multilevel multivariable logistic regression analysis was conducted to calculate adjusted odds ratios (AORs) and 95% confidence intervals (CIs), with the high-volume group used as the reference.Results: In total, 21,498 trauma patients were analyzed. The high-volume group exhibited lower in-hospital mortality, 447 (9.0%), compared to 867 (14.1%) in the intermediate-volume group and 1,458 (14.1%) in the low-volume group. There was a significantly higher odds of in-hospital mortality: low-volume group (AOR 95% CI: 1.20 (0.95-1.51)) and intermediate-volume group (AOR 95% CI: 1.29 (1.02-1.64)) when compared to the high-volume group.Conclusions: The case volume at an ambulance station is associated with in-hospital mortality in patients with moderate to severe trauma. These results should be considered when constructing an EMS system and education program for prehospital trauma care.

Continuous patient state attention model for addressing irregularity in electronic health records.

BACKGROUND: Irregular time series (ITS) are common in healthcare as patient data is recorded in an electronic health record (EHR) system as per clinical guidelines/requirements but not for research and depends on a patient's health status. Due to irregularity, it is challenging to develop machine learning techniques to uncover vast intelligence hidden in EHR big data, without losing performance on downstream patient outcome prediction tasks. METHODS: In this paper, we propose Perceiver, a cross-attention-based transformer variant that is computationally efficient and can handle long sequences of time series in healthcare. We further develop continuous patient state attention models, using Perceiver and transformer to deal with ITS in EHR. The continuous patient state models utilise neural ordinary differential equations to learn patient health dynamics, i.e., patient health trajectory from observed irregular time steps, which enables them to sample patient state at any time. RESULTS: The proposed models' performance on in-hospital mortality prediction task on PhysioNet-2012 challenge and MIMIC-III datasets is examined. Perceiver model either outperforms or performs at par with baselines, and reduces computations by about nine times when compared to the transformer model, with no significant loss of performance. Experiments to examine irregularity in healthcare reveal that continuous patient state models outperform baselines. Moreover, the predictive uncertainty of the model is used to refer extremely uncertain cases to clinicians, which enhances the model's performance. Code is publicly available and verified at https://codeocean.com/capsule/4587224 . CONCLUSIONS: Perceiver presents a computationally efficient potential alternative for processing long sequences of time series in healthcare, and the continuous patient state attention models outperform the traditional and advanced techniques to handle irregularity in the time series. Moreover, the predictive uncertainty of the model helps in the development of transparent and trustworthy systems, which can be utilised as per the availability of clinicians.

Malignant tumor increases the risk of all causes in-hospital mortality in critically ill patients with ischemic stroke: analysis of the MIMIC-IV database.

BACKGROUND: Ischemic stroke (IS) and malignant tumor (MT) have high morbidity and mortality rates worldwide, and several associations exist between them. This study aimed to determine the effect of MT on hospital mortality in patients with IS. METHODS: Based on their MT status, participants with IS in the Medical Information Mart for Intensive Care IV (MIMIC-IV) were divided into two groups. The primary outcome was in-hospital all causes mortality. Kaplan-Meier survival analysis was performed to evaluate the intergroup in-hospital mortality, and three Cox regression models were used to determine the association between MT and in-hospital mortality. RESULTS: A total of 1605 participants (749 males and 856 females) were included in the study. The mean age was 72.030 ± 15.463 years. Of these, 257 (16%) patients died in the hospital. Kaplan-Meier analysis showed that the MT group had a significantly lower possibility of in-hospital survival than the non-MT group. In the unadjusted model, in-hospital mortality among MT patients had a higher odds ratio (OR) of 1.905 (95% CI, 1.320-2.748; P < 0.001) than the non-MT group. After adjusting for basic information, vital signs, and laboratory data, MT was also associated with increased in-hospital mortality (OR = 1.844, 95% CI: 1.255-2.708; P = 0.002). CONCLUSIONS: Among the patients with IS, the risk of all causes in-hospital mortality was higher for MT than for patients non-MT. This finding can assist clinicians in more accurately assessing prognosis and making informed treatment decisions.

Comparative performance of intensive care mortality prediction models based on manually curated versus automatically extracted electronic health record data.

INTRODUCTION: Benchmarking intensive care units for audit and feedback is frequently based on comparing actual mortality versus predicted mortality. Traditionally, mortality prediction models rely on a limited number of input variables and significant manual data entry and curation. Using automatically extracted electronic health record data may be a promising alternative. However, adequate data on comparative performance between these approaches is currently lacking. METHODS: The AmsterdamUMCdb intensive care database was used to construct a baseline APACHE IV in-hospital mortality model based on data typically available through manual data curation. Subsequently, new in-hospital mortality models were systematically developed and evaluated. New models differed with respect to the extent of automatic variable extraction, classification method, recalibration usage and the size of collection window. RESULTS: A total of 13 models were developed based on data from 5,077 admissions divided into a train (80%) and test (20%) cohort. Adding variables or extending collection windows only marginally improved discrimination and calibration. An XGBoost model using only automatically extracted variables, and therefore no acute or chronic diagnoses, was the best performing automated model with an AUC of 0.89 and a Brier score of 0.10. DISCUSSION: Performance of intensive care mortality prediction models based on manually curated versus automatically extracted electronic health record data is similar. Importantly, our results suggest that variables typically requiring manual curation, such as diagnosis at admission and comorbidities, may not be necessary for accurate mortality prediction. These proof-of-concept results require replication using multi-centre data.

Usefulness of the qSOFA score for predicting hospital mortality in cancer patients.

BACKGROUND: The quick Sequential Sepsis-related Organ Failure Assessment (qSOFA) is a score that has been proposed to quickly identify patients at higher risk of death. OBJECTIVE: To describe the usefulness of the qSOFA score to predict in-hospital mortality in cancer patients. MATERIAL AND METHODS: Cross-sectional study carried out between January 2021 and December 2022. Hospital mortality was the dependent variable. The area under the ROC curve (AUC) was calculated to determine the discriminative ability of qSOFA to predict in-hospital mortality. RESULTS: A total of 587 cancer patients were included. A qSOFA score higher than 1 obtained a sensitivity of 57.2%, specificity of 78.5%, a positive predictive value of 55.4% and negative predictive value of 79.7%. The AUC of qSOFA for predicting in-hospital mortality was 0.70. In-hospital mortality of patients with qSOFA scores of 2 and 3 points was 52.7 and 64.4%, respectively. In-hospital mortality was 31.9% (187/587). CONCLUSION: qSOFA showed acceptable discriminative ability for predicting in-hospital mortality in cancer patients.

ANTECEDENTES: El quick Sequential Sepsis-related Organ Failure Assessment (qSOFA) es una puntuación propuesta para identificar de forma rápida a pacientes con mayor probabilidad de morir. OBJETIVO: Describir la utilidad de la puntuación qSOFA para predecir mortalidad hospitalaria en pacientes con cáncer. MATERIAL Y MÉTODOS: Estudio transversal realizado entre enero de 2021 y diciembre de 2022. La mortalidad hospitalaria fue la variable dependiente. Se calculó el área bajo la curva ROC (ABC) para determinar la capacidad discriminativa de qSOFA para predecir mortalidad hospitalaria. RESULTADOS: Se incluyeron 587 pacientes con cáncer. La puntuación qSOFA < 1 obtuvo una sensibilidad de 57.2 %, una especificidad de 78.5 %, un valor predictivo positivo de 55.4 % y un valor predictivo negativo de 79.7 %. El ABC de qSOFA para predecir mortalidad hospitalaria fue de 0.70. La mortalidad hospitalaria de los pacientes con qSOFA de 2 y 3 puntos fue de 52.7 y 64.4 %, respectivamente. La mortalidad hospitalaria fue de 31.9 % (187/587). CONCLUSIÓN: qSOFA mostró capacidad discriminativa aceptable para predecir mortalidad hospitalaria en pacientes con cáncer.

Hospital-acquired bacterial pneumonia in critically ill patients: from research to clinical practice.

INTRODUCTION: Hospital-acquired pneumonia (HAP) represents a significant cause of mortality among critically ill patients admitted to Intensive Care Units (ICUs). Timely and precise diagnosis is imperative to enhance therapeutic efficacy and patient outcomes. However, the diagnostic process is challenged by test limitations and a wide-ranging list of differential diagnoses, particularly in patients exhibiting escalating oxygen requirements, leukocytosis, and increased secretions. AREAS COVERED: This narrative review aims to update diagnostic modalities, facilitating the prompt identification of nosocomial pneumonia while guiding, developing, and assessing therapeutic interventions. A comprehensive literature review was conducted utilizing the MEDLINE/PubMed database from 2013 to April 2024. EXPERT OPINION: An integrated approach that integrates clinical, microbiological, and imaging tools is paramount. Progress in diagnostic techniques, including novel molecular methods, the expanding utilization and accuracy of bedside ultrasound, and the emergence of Artificial Intelligence, coupled with an improved comprehension of lung microbiota and host-pathogen interactions, continues to enhance our capability to accurately and swiftly identify HAP and its causative agents. This advancement enables the refinement of treatment strategies and facilitates the implementation of precision medicine approaches.

Case volume and specialization in critically ill emergency patients: a nationwide cohort study in Japanese ICUs.

BACKGROUND: Previous studies have explored the association between the number of cases and patient outcomes for critical illnesses such as sepsis and trauma, as well as various surgeries, with the expectation that a higher number of cases would have a more favorable effect on patient outcomes. The aim of this study was to elucidate the association among intensive care unit (ICU) case volume, specialization, and patient outcomes in critically ill emergency patients and to determine how ICU case volumes and specializations impact the outcomes of these patients in Japanese ICUs. METHODS: Utilizing data from the Japanese Intensive Care PAtient Database (JIPAD) from April 2015 to March 2021, this retrospective cohort study was conducted in 80 ICUs across Japan and included 72,214 emergency patients aged ≥ 16 years. The primary outcome measure was in-hospital mortality, and the secondary outcomes encompassed ICU mortality, 28-day mortality, ventilator-free days, and the lengths of ICU and hospital stays. Bayesian hierarchical generalized linear mixed models were used to adjust for patient- and ICU-level variables. RESULTS: This study revealed a significant association between a higher ICU case volume and decreased in-hospital mortality. In particular, ICUs with a higher percentage (> 75%) of emergency patients showed more pronounced effects, with the odds ratios for in-hospital mortality in the higher case volume quartiles (Q2, Q3, and Q4) being 0.92 (95% credible interval [CI]: 0.88-0.96), 0.70 (95% CI: 0.67-0.73), and 0.78 (95% CI: 0.73-0.83), respectively, compared with the lowest quartile (Q1). Similar trends were observed for various secondary outcomes. CONCLUSIONS: Higher ICU case volumes were significantly associated with lower in-hospital mortality rates in Japanese ICUs predominantly treating critically ill emergency patients. These findings emphasize the importance of ICU specialization and highlight the potential benefits of centralized care for critically ill emergency patients. These findings are potential insights for improving health care policy in Japan and may be valuable in emergency care settings in other countries with similar healthcare systems, after careful consideration of contextual differences.

Comparative Analysis of Modified BT Shunt and Central Shunt in Pediatric Patients.

INTRODUCTION: Cyanotic congenital heart diseases constitute 40-45% of all congenital heart diseases. In patients who are not suitable for primary repair, modified BT (MBT) shunt and central shunt (CS) procedures are still frequently used. METHODS: This study included 62 pediatric patients who underwent MBT shunt or CS via median sternotomy. Patients' demographic, echocardiographic, operative, and postoperative data were collected retrospectively. The patients were classified as single ventricle and bi-ventricle according to their cardiac anatomy, and the presence of prematurity and heterotaxy was noted. Procedure details of the patients who underwent endovascular intervention prior to the surgery were investigated, and operation data were accessed from the surgery notes. Data regarding postoperative follow-ups were obtained and comparatively analyzed. RESULTS: Of the total 62 patients, 32 (51.6%) were newborns and 16 (25.8%) had a body weight < 3 kg. MBT shunt was applied to 48 patients (77.4%), while CS was applied to 14 patients (22.6%). There was no significant difference between the two surgical procedures in terms of requirement for urgent shunt or cardiopulmonary bypass, additional simultaneous surgical intervention, need for high postoperative inotropes, and in-hospital mortality (P>0.05). The rate of congestive heart failure in patients with in-hospital mortality was determined as 66.7% and it was significantly higher than in patients without heart failure (P<0.001). CONCLUSION: MBT shunt and CS are still frequently used in cyanotic patients. The use of small-diameter shunts, particularly when centrally located, can prevent the onset of congestive heart failure and lower mortality.

Intentionally self-injured patients have lower mortality when treated at trauma centers versus non-trauma centers in South Korea.

Objective: This study investigated the characteristics and survival rates of patients with intentional severe trauma (self-harm or suicide) who were transported to either a regional trauma center (TC) or a non-TC facility. Methods: This retrospective, national, population-based, observational, case-control study included patients who sustained intentional severe trauma and had an abnormal Revised Trauma Score at the injury site between January 2018 and December 2019. The data were a community-based severe trauma survey based on data collected from severe injury and multiple casualty patients transported by 119 emergency medical services (EMS), distributed by the Korea Disease Control and Prevention Agency. The treatment hospitals were divided into two types, TC and non-TCs, and several variables, including in-hospital mortality, were compared. Propensity score matching (PSM) was used to mitigate the influence of confounding variables on the survival outcomes. Results: Among the 3864 patients, 872 and 2992 visited TC and non-TC facilities, respectively. The injury severity did not differ significantly between patients treated at TCs and non-TCs (TC, 9; non-TC, 9; p=0.104). However, compared with those treated at non-TCs, patients treated at TCs had a higher rate of surgery or transcatheter arterial embolization (14.2% vs 38.4%; p<0.001) and a higher admission rate to the emergency department (34.4% vs 60.6%; p<0.001). After PSM, 872 patients from both groups were analyzed. Patients treated at TCs exhibited a higher overall survival rate than those treated at non-TCs (76.1% vs 66.9%; p<0.001), and multiple variable logistic regression analysis demonstrated that the causes of injury and transport to the TC were significantly associated. Conclusion: Using Korean EMS data, the results of this study revealed that initial transport to TCs was associated with reduced mortality rates. However, considering the limitations of using data from only 2 years and the retrospective design, further research is warranted. Study type: Retrospective national, population-based observational case-control study. Level of evidence: Level III.

Postoperative intensive care allocation and mortality in high-risk surgical patients: evidence from a low- and middle-income country cohort.

BACKGROUND: The escalation of surgeries for high-risk patients in Low- and Middle-Income Countries (LMICs) lacks evidence on the positive impact of Intensive Care Unit (ICU) admission and lacks universal criteria for allocation. This study explores the link between postoperative ICU allocation and mortality in high-risk patients within a LMIC. Additionally, it assesses the Ex-Care risk model's utility in guiding postoperative allocation decisions. METHODS: A secondary analysis was conducted in a cohort of high-risk surgical patients from a 800-bed university-affiliated teaching hospital in Southern Brazil (July 2017 to January 2020). Inclusion criteria encompassed 1431 inpatients with Ex-Care Model-assessed all-cause postoperative 30-day mortality risk exceeding 5%. The study compared 30-day mortality outcomes between those allocated to the ICU and the Postanesthetic Care Unit (PACU). Outcomes were also assessed based on Ex-Care risk model classes. RESULTS: Among 1431 high-risk patients, 250 (17.47%) were directed to the ICU, resulting in 28% in-hospital 30-day mortality, compared to 8.9% in the PACU. However, ICU allocation showed no independent effect on mortality (RR = 0.91; 95% CI 0.68‒1.20). Patients in the highest Ex-Care risk class (Class IV) exhibited a substantial association with mortality (RR = 2.11; 95% CI 1.54-2.90) and were more frequently admitted to the ICU (23.3% vs. 13.1%). CONCLUSION: Patients in the highest Ex-Care risk class and those with complications faced elevated mortality risk, irrespective of allocation. Addressing the unmet need for adaptable postoperative care for high-risk patients outside the ICU is crucial in LMICs. Further research is essential to refine criteria and elucidate the utility of risk assessment tools like the Ex-Care model in assisting allocation decisions.

Hidden Dangers of Frailty: Higher Mortality, Complications and Costs in Acute Pancreatitis.

BACKGROUND: Frailty is a clinically recognizable state of increased vulnerability due to age-related decline in reserve and function across multiple physiologic systems that compromises the ability to cope with acute stress. As frailty is being identified as an important risk factor in outcomes of gastrointestinal pathologies, we aimed to assess outcomes in patients with acute pancreatitis within this cohort. METHOD: We conducted a retrospective study using the Nationwide Inpatient Sample (NIS) database. ICD-10 codes were used to inquire for patients admitted with acute pancreatitis between September 2015 through 2017. ICD-10 codes corresponding to the Hospital Frailty Risk Score (HFRS) were used to divide the study sample into 2 cohorts: low risk (< 5 points) and intermediate or high risk (> 5 points). To calculate the points, we fitted a logistic regression model that included membership of the frail group as the binary dependent variable (frail vs. non-frail) and the set of ICD-10 codes as binary predictor variables (1 = present, 0 = absent for each code). To simplify the calculation and interpretation, we multiplied regression coefficients by five to create a points system, so that a certain number of points are awarded for each ICD-10 code and added together to create the final frailty risk score. Multivariate regression analysis was performed to find adjusted mortality. RESULTS: Out of a total of 1,267,744 patients admitted with acute pancreatitis, 728,953 (57.5%) were identified as intermediate and high risk (> 5 points) (study cohort) and 538,781 (42.5%) as low risk (< 5 points). The mean age in the study cohort was 64.8 ± 12.6 and that in the low-risk group was 58.6 ± 9.5. Most of the patients in both groups were males and Caucasians; Medicare was the predominant insurance provider. A majority of the admissions in both groups were in an urban teaching hospital and were emergency. (Table 1). The primary outcome was in-hospital mortality which was significantly higher in the study cohort as compared to the low-risk group (4.3% vs. 2.5%, p < 0.0001). The age-adjusted Odds ratio of mortality was 1.72(95% CI (Confidence Interval) 1.65-1.80, p < 0.05). When compared between the two groups; median length of stay (6 vs. 4); hospitalization cost ($14,412 vs. $10,193), disposition to a skilled nursing facility (SNF) (17.1% vs. 8.6%) and need for home health care (HHC) was significantly higher in the study cohort. Complications like septicemia, septic shock, and acute kidney injury were also higher in the study group (Table 2). Table 1 Baseline demographics of the cohort Characteristics Acute pancreatitis with High HES Frailty score (> 5, intermediate + high) Acute pancreatitis with low HES Frailty score (< 5) P-value N = 1,267,744 N = 728,953 (57.5%) N = 538,781 (42.5%) Age  Mean years (Mean ± SD) 64.8 ± 12.6 58.6 ± 9.5 < 0.001 Gender < 0.001  Male 59.1% 52.3%  Female 40.9% 47.7% *Missing-475 Age groups < 0.001  18-44 3.7% 14.3%  45-64 48% 52.9%  65-84 32.2% 28.7%  ≥ 85 16.1% 4.1% Race < 0.001  Caucasians 67.4% 61.9%  African Americans 9.6% 16.8%  Others 23% 21.3% *Missing-10 Insurance type < 0.001  Medicare 40.9% 36.3%  Medicaid 17.2% 24.3%  Private 31.8% 27.9%  Other 9.9% 11.4% *Missing-75 Active smoking 32.7% 37.9% 0.005 Biliary Stone 36.2% 16.7% < 0.001 Admission Type < 0.001  Emergent 93.7% 94.3%  Elective 6.3% 5.7% *Missing-2880 Hospital ownership/control < 0.001  Rural 7.8% 10%  Urban nonteaching 26.3% 26.6%  Urban teaching 65.9% 63.4% Table 2 Outcomes Outcomes Acute pancreatitis with High HES Frailty score (> 5, intermediate + high) Acute pancreatitis with low HES Frailty score (< 5) P-value In-hospital mortality *Missing-920 4.3% 2.5% < .0001 1.72(1.65-1.80) < .0001 Length of stay, days (Median,IQR) 6(3-8) 4(2-6) < .0001 Total hospitalization cost, $ (Median,IQR) 14,412(8843-20,216) 10,193(6840-13,842) < .0001 In-Hospital Complications  ARDS 0.4% 0.3% 0.08  Ventilator dependence respiratory failure 0.23% 0.29% 0.25  Septicemia 15.2% 9.6% < .0001  Septic Shock 6.1% 2.9% < .0001  AKI 24.8% 14.9% < .0001 Disposition < .0001  Discharge to home 58.9% 74.9%  Transfer other: includes  Skilled Nursing Facility (SNF), Intermediate Care Facility (ICF), and another type of facility 17.1% 8.6%  Home health care 11.5% 8.1%  Against medical advice (AMA) 1.6% 3.4% *Missing-920 CONCLUSION: Using frailty as a construct to identify those who are at greater risk for adverse outcomes, can help formulate interventions to target individualized reversible factors to improve outcomes in patients with acute pancreatitis. Future large-scale prospective studies are warranted to understand the dynamic and longitudinal relationship between pancreatitis and frailty.

Prediction of Initial CRP/Albumin Ratio on In-Hospital Mortality in Isolated Traumatic Brain Injury Patients.

The CRP/albumin ratio (CAR) is a mortality predictor in intensive care unit (ICU) patients. The aim of the current study was to investigate the ability of CAR to predict in-hospital mortality (IHM) in patients with isolated traumatic brain injury (iTBI). We performed a retrospective analysis including 200 patients with iTBI admitted to our neurosurgical intensive care unit (NICU) between September 2014 and December 2016. Serum biomarkers, demographic and radiological data, several ICU scores, and cardiopulmonary parameters were analyzed. The rate of IHM was 27.5% (55/200) and significantly associated with a higher AIS head score (p < 0.0001), a lower albumin level (p < 0.0001), and the necessity of a higher level of inspiratory oxygen fraction (p = 0.002). Furthermore, advanced age (odds ratio [OR] = 0.953, 95% confidence interval [CI] = 0.927-0.981, p = 0.001), a lower GCS score (OR = 1.347, 95% CI = 1.203-1.509, p < 0.0001), a higher level of lactate (OR = 0.506, 95% CI = 0.353-0.725, p < 0.0001), a higher CAR (OR = 0.547, 95% CI = 0.316-0.945, p = 0.031) and a higher norepinephrine application rate (OR = 0.000, 95% CI 0.000-0.090, p = 0.016) were identified as independent predictors of IHM. ROC analysis showed an association between IHM and a CAR cut-off value of >0.38 (Youden index 0.073, sensitivity: 27.9, specificity: 64.8, p = 0.044). We could identify a CAR > 0.38 as a new independent predictor for IHM in patients with iTBI.

Behind the Hospital Ward: In-Hospital Mortality of Type 2 Diabetes Mellitus Patients in Indonesia (Analysis of National Health Insurance Claim Sample Data).

The rising global prevalence of diabetes mellitus, a chronic metabolic disorder, poses significant challenges to healthcare systems worldwide. This study examined in-hospital mortality among patients diagnosed with non-insulin-dependent diabetes mellitus (NIDDM) of ICD-10, or Type 2 Diabetes Mellitus (T2DM), in Indonesia, utilizing hospital claims data spanning from 2017 to 2022 obtained from the Indonesia Health Social Security Agency or Badan Penyelenggara Jaminan Sosial (BPJS) Kesehatan. The analysis, which included 610,809 hospitalized T2DM patients, revealed an in-hospital mortality rate of 6.6%. Factors contributing to an elevated risk of mortality included advanced age, the presence of comorbidities, and severe complications. Additionally, patients receiving health subsidies and those treated in government hospitals were found to have higher mortality risks. Geographic disparities were observed, highlighting variations in healthcare outcomes across different regions. Notably, the complication of ketoacidosis emerged as the most significant risk factor for in-hospital mortality, with an odds ratio (OR) of 10.86, underscoring the critical need for prompt intervention and thorough management of complications to improve patient outcomes.

Care fragmentation and readmission mortality and length of stay before and during the COVID-19 pandemic: data from the National Readmissions Database, 2018-2020.

IMPORTANCE: A quarter of all 30-day readmissions involve fragmented care, where patients return to a different hospital than their original admission; these readmissions are associated with increased in-hospital mortality and longer lengths-of-stay (LOS). The stress on healthcare systems at the beginning of the COVID-19 pandemic could worsen care fragmentation and related outcomes. OBJECTIVE: To compare fragmented readmissions in 2020 versus 2018-2019 and assess whether mortality and LOS in fragmented readmissions differed in the two time periods. DESIGN: Observational study SETTING: National Readmissions Database (NRD), 2018-2020 PARTICIPANTS: All adults (> 18 y/o) with 30-day readmissions MAIN OUTCOMES AND MEASURES: We examined the percentage of fragmented readmissions over 2018-2020. Using unadjusted and adjusted logistic and linear regressions, we estimated the associations between fragmented readmissions and in-hospital mortality and LOS. RESULTS: 24.0-25.7% of readmissions in 2018-2020 and 27.3%-31.0% of readmissions for COVID-19 were fragmented. 2018-2019 fragmented readmissions were associated with 18-20% higher odds of in-hospital mortality compared to nonfragmented readmissions. Fragmented readmissions for COVID-19 were associated with an 18% increase in in-hospital mortality (AOR 1.18, 95% CI 1.12, 1.24). The LOS of fragmented readmissions in March-November 2018-2019 were on average 0.81 days longer, while fragmented readmissions between March-November of 2020 were associated with a 0.88-1.03 day longer LOS. CONCLUSIONS AND RELEVANCE: A key limitation is that the NRD does not contain information on several patient/hospital-level factors that may be associated with the outcomes of interest. We observed increased fragmentation during COVID-19, but its impact on in-hospital mortality and LOS remained consistent with previous years.

Effects of a medical admission unit on in-hospital patient flow and clinical outcomes.

BACKGROUND: the burden of acute complex patients, increasingly older and poli-pathological, accessing to Emergency Departments (ED) leads up hospital overcrowding and the outlying phenomenon. These issues highlight the need for new adequate patients' management strategies. The aim of this study is to analyse the effects on in-hospital patient flow and clinical outcomes of a high-technology and time-limited Medical Admission Unit (MAU) run by internists. METHODS: all consecutive patients admitted to MAU from Dec-2017 to Nov-2019 were included in the study. The admissions number from ED and hospitalization rate, the overall in-hospital mortality rate in medical department, the total days of hospitalization and the overall outliers bed days were compared to those from the previous two years. RESULTS: 2162 patients were admitted in MAU, 2085(95.6%) from ED, 476(22.0%) were directly discharged, 88(4.1%) died and 1598(73.9%) were transferred to other wards, with a median in-MAU time of stay of 64.5 [0.2-344.2] hours. Comparing the 24 months before, despite the increase in admissions/year from ED in medical department (3842 ± 106 in Dec2015-Nov2017 vs 4062 ± 100 in Dec2017-Nov2019, p<0.001), the number of the outlier bed days has been reduced, especially in surgical department (11.46 ± 6.25% in Dec2015-Nov2017 vs 6.39 ± 3.08% in Dec2017-Nov2019, p=0.001), and mortality in medical area has dropped from 8.74 ± 0.37% to 7.29 ± 0.57%, p<0.001. CONCLUSIONS: over two years, a patient-centred and problem-oriented approach in a medical admission buffer unit run by internists has ensured a constant flow of acute patients with positive effects on clinical risk and quality of care reducing medical outliers and in-hospital mortality.

Real-world evidence of survival benefit of remdesivir: study of 419 propensity score-matched patients hospitalized over the alpha and delta waves of COVID-19 in New Orleans, LA.

Background: The direct acting antiviral remdesivir (RDV) has shown promising results in randomized clinical trials. This study is a unique report of real clinical practice RDV administration for COVID-19 from alpha through delta variant circulation in New Orleans, Louisiana (NOLA). Patients in NOLA have among US worst pre-COVID health outcomes, and the region was an early epicenter for severe COVID. Methods: Data were directly extracted from electronic medical records through REACHnet. Of 9,106 adults with COVID, 1,928 were admitted to inpatient care within 7 days of diagnosis. The propensity score is based upon 22 selected covariates, related to both RDV assignment and outcome of interest. RDV and non-RDV patients were matched 1:1 with replacement, by location and calendar period of admission. Primary and secondary endpoints were, death from any cause and inpatient discharge, within 28 and 14 days after inpatient admission. Results: Of 448 patients treated with RDV, 419 (94%) were successfully matched to a non-RDV patient. 145 (35%) patients received RDV for < 5 days, 235 (56%) for 5 days, and 39 (9%) for > 5 days. 96% of those on RDV received it within 2 days of admission. RDV was more frequently prescribed in patients with pneumonia (standardized difference: 0.75), respiratory failure, hypoxemia, or dependence on supplemental oxygen (0.69), and obesity (0.35) within 5 days prior to RDV initiation or corresponding day in non-RDV patients (index day). RDV patients were numerically more likely to be on steroids within 5 days prior to index day (86 vs. 82%) and within 7 days after inpatient admission (96 vs. 87%). RDV was significantly associated with lower risk of death within 14 days after admission (hazard ratio [HR]: 0.37, 95% CI: 0.19 to 0.69, p = 0.002) but not within 28 days (HR: 0.62, 95% CI: 0.36 to 1.07, p = 0.08). Discharge within 14 days of admission was significantly more likely for RDV patients (p < 0.001) and numerically more likely within 28 days after admission (p = 0.06). Conclusion: Overall, our findings support recommendation of RDV administration for COVID-19 in a highly comorbid, highly impoverished population representative of both Black and White subjects in the US Gulf South.

DASC-21 score and the risk of in-hospital death in elderly patients with heart failure.

AIM: We investigated whether the Dementia Assessment Sheet for Community-based Integrated Care System-21 Items (DASC-21), a questionnaire that assesses cognitive function, including activities of daily living (ADL), was predictive of in-hospital death and prolonged hospital stay in elderly patients hospitalized for heart failure. METHODS: We retrospectively assessed the DASC-21 score at the time of admission, in-hospital death, length of hospital stay, and change in the Barthel index in 399 patients hospitalized for heart failure between 2016 and 2019. RESULTS: The mean patient age was 85.8 ± 7.7 years (61.3% women). The median DASC-21 score was 38 (64.7% higher than 31). On multivariate logistic regression analysis, a higher DASC-21 score was associated with an increased risk of in-hospital death (odds ratio [OR] = 1.045 per 1 point increase, 95% confidence interval [CI]: 1.010-1.081, P = 0.012), even after adjusting for confounding factors, including atrial fibrillation, ejection fraction, and B-type natriuretic peptide. Difficulties (3 or 4) with the self-management of medication in instrumental ADL inside the home (OR = 3.28, 95% CI: 1.05-10.28, P = 0.042), toileting (OR = 3.66, 95% CI: 1.19-11.29, P = 0.024), grooming (OR = 6.47, 95% CI: 2.00-20.96, P = 0.002), eating (OR = 7.96, 95% CI: 2.49-25.45, P < 0.001), and mobility in physical ADL (OR = 5.99, 95% CI: 1.85-19.35, P = 0.003) were identified as risk factors for in-hospital death. Patients in the highest tertile of the DASC-21 score had a significantly longer hospital stay (P = 0.006) and a greater reduction in the Barthel index (P < 0.001). CONCLUSIONS: In elderly patients hospitalized for heart failure, higher DASC-21 scores were associated with an increased risk of in-hospital death, prolonged hospital stay, and impaired ADL. Geriatr Gerontol Int 2024; 24: 546-553.