Cause Of In-hospital Death Research Articles

Risk factors of thromboembolic events in patients with scrub typhus.

Thromboembolic events are a well-recognized cause of in-hospital deaths of patients with infectious diseases. However, thromboembolic events in patients with scrub typhus, caused by Orientia tsutsugamushi have rarely been reported. This study aimed to assess risk factors associated with thromboembolic events in patients with scrub typhus. All 93 scrub typhus patients' diagnoses were confirmed serologically or by positive nested polymerase chain reaction (PCR). The clinical and laboratory findings from 12 scrub typhus patients with thromboembolic events and 81 scrub typhus patients with nonthromboembolic events were retrospectively studied. To determine the factors implicated in thromboembolic events, we performed multivariate logistic regression analysis using the six independent factors identified by the univariate analysis. The mean age of the patients in the thromboembolic group was 76.4 years (median, 76 years), and in nonthromboembolic group it was 64.6 years (median, 65 years) (P<0·001). Thromboembolic events were observed in 12 patients. These events included acute coronary syndrome (n = 5), acute limb ischemia (n = 4), ischemic stroke (n = 1), deep vein thrombosis combined with pulmonary thromboembolism (n = 1), and left common iliac artery aneurysm with a thrombus (n = 1). According to multivariate analysis, the following four factors were significantly associated with the thromboembolic events: 1) treatment with rifampin (OR = 57.6; CI 1.2-2700.3), 2) Taguchi genotype (OR = 41.5, P = 0.028; CI 1.5-1154.6), 3) atrial fibrillation (OR = 9.4, P = 0.034; CI 1.2-74.0), and 4) age (OR = 1.1, P = 0.046; CI 1.0-1.3). Our study suggests that clinicians should be cautious when managing patients with scrub typhus to avoid the development of thromboembolic events, especially in patients with risk factors such as treatment with rifampin, Taguchi genotype, atrial fibrillation, and advanced age.

Sex-specific prediction of cardiogenic shock after acute coronary syndromes: the SEX-SHOCK score.

Cardiogenic shock (CS) remains the primary cause of in-hospital death after acute coronary syndromes (ACS), with its plateauing mortality rates approaching 50%. To test novel interventions, personalized risk prediction is essential. The ORBI (Observatoire Régional Breton sur l'Infarctus) score represents the first-of-its-kind risk score to predict in-hospital CS in ACS patients undergoing percutaneous coronary intervention (PCI). However, its sex-specific performance remains unknown, and refined risk prediction strategies are warranted. This multinational study included a total of 53 537 ACS patients without CS on admission undergoing PCI. Following sex-specific evaluation of ORBI, regression and machine-learning models were used for variable selection and risk prediction. By combining best-performing models with highest-ranked predictors, SEX-SHOCK was developed, and internally and externally validated. The ORBI score showed lower discriminative performance for the prediction of CS in females than males in Swiss (area under the receiver operating characteristic curve [95% confidence interval]: 0.78 [0.76-0.81] vs. 0.81 [0.79-0.83]; P =.048) and French ACS patients (0.77 [0.74-0.81] vs. 0.84 [0.81-0.86]; P = .002). The newly developed SEX-SHOCK score, now incorporating ST-segment elevation, creatinine, C-reactive protein, and left ventricular ejection fraction, outperformed ORBI in both sexes (females: 0.81 [0.78-0.83]; males: 0.83 [0.82-0.85]; P < .001), which prevailed following internal and external validation in RICO (females: 0.82 [0.79-0.85]; males: 0.88 [0.86-0.89]; P < .001) and SPUM-ACS (females: 0.83 [0.77-0.90], P = .004; males: 0.83 [0.80-0.87], P = .001). The ORBI score showed modest sex-specific performance. The novel SEX-SHOCK score provides superior performance in females and males across the entire spectrum of ACS, thus providing a basis for future interventional trials and contemporary ACS management.

Pediatric crush-related acute kidney injury and risk factors: asingle center experience.

Crush injury, the most important trauma complicationencountered in earthquake victims, occurs as a result of prolonged compression of muscle mass. Crush syndrome, resultingfrom crushinjury, and acute kidney injury (AKI) are the most common causes of in-hospital deaths after earthquakes. The aim of this study is to convey our experience afterthe devastating Turkey-Syria earthquake and to identify the risk factors of crush syndrome and crush-related AKI. Of the 1134 children admitted to the emergency department, 265 with crush injury were included the study. Demographic information, laboratory and clinical data of the patients were retrospectively analyzed. Mean age of the patientswas 10.3 ± 4.9years (134 femalesand131 males). The median time spent under the rubble was 20h. Crush syndrome developed in 135 (50.9%). Patients with crush syndrome were older and had higher body weight, respectively (p = 0.014, p = 0.044). Acute kidney injury was present in 157 (59.2%) patients. Thirty-two patients (12.1%) received kidney replacement therapy (KRT). The risk factors for the development of AKI Stage 3 were crush syndrome, abdominal trauma, and age. This disaster taught us the importance of establishing in advancea national emergency disaster plan. Older pediatric earthquake victims with multiple trauma and severe crush syndrome should be closely followed-up for development of AKI and, if necessary, started on dialysis. Timely access to medical care, early fluid resuscitation, and effective use of dialysis treatment are essential.

Neurologic complications in patients receiving aortic versus subclavian versus femoral arterial cannulation for post-cardiotomy extracorporeal life support: results of the PELS observational multicenter study

BackgroundCerebral perfusion may change depending on arterial cannulation site and may affect the incidence of neurologic adverse events in post-cardiotomy extracorporeal life support (ECLS). The current study compares patients' neurologic outcomes with three commonly used arterial cannulation strategies (aortic vs. subclavian/axillary vs. femoral artery) to evaluate if each ECLS configuration is associated with different rates of neurologic complications.MethodsThis retrospective, multicenter (34 centers), observational study included adults requiring post-cardiotomy ECLS between January 2000 and December 2020 present in the Post-Cardiotomy Extracorporeal Life Support (PELS) Study database. Patients with Aortic, Subclavian/Axillary and Femoral cannulation were compared on the incidence of a composite neurological end-point (ischemic stroke, cerebral hemorrhage, brain edema). Secondary outcomes were overall in-hospital mortality, neurologic complications as cause of in-hospital death, and post-operative minor neurologic complications (seizures). Association between cannulation and neurological outcomes were investigated through linear mixed-effects models.ResultsThis study included 1897 patients comprising 26.5% Aortic (n = 503), 20.9% Subclavian/Axillary (n = 397) and 52.6% Femoral (n = 997) cannulations. The Subclavian/Axillary group featured a more frequent history of hypertension, smoking, diabetes, previous myocardial infarction, dialysis, peripheral artery disease and previous stroke. Neuro-monitoring was used infrequently in all groups. Major neurologic complications were more frequent in Subclavian/Axillary (Aortic: n = 79, 15.8%; Subclavian/Axillary: n = 78, 19.6%; Femoral: n = 118, 11.9%; p < 0.001) also after mixed-effects model adjustment (OR 1.53 [95% CI 1.02–2.31], p = 0.041). Seizures were more common in Subclavian/Axillary (n = 13, 3.4%) than Aortic (n = 9, 1.8%) and Femoral cannulation (n = 12, 1.3%, p = 0.036). In-hospital mortality was higher after Aortic cannulation (Aortic: n = 344, 68.4%, Subclavian/Axillary: n = 223, 56.2%, Femoral: n = 587, 58.9%, p < 0.001), as shown by Kaplan–Meier curves. Anyhow, neurologic cause of death (Aortic: n = 12, 3.9%, Subclavian/Axillary: n = 14, 6.6%, Femoral: n = 28, 5.0%, p = 0.433) was similar.ConclusionsIn this analysis of the PELS Study, Subclavian/Axillary cannulation was associated with higher rates of major neurologic complications and seizures. In-hospital mortality was higher after Aortic cannulation, despite no significant differences in incidence of neurological cause of death in these patients. These results encourage vigilance for neurologic complications and neuromonitoring use in patients on ECLS, especially with Subclavian/Axillary cannulation.Graphical abstract

A Preclinical Model of Sepsis-Induced Myopathy with Disuse in Mice.

Sepsis is a major cause of in-hospital deaths. Improvements in treatment result in a greater number of sepsis survivors. Approximately 75% of the survivors develop muscle weakness and atrophy, increasing the incidence of hospital readmissions and mortality. However, the available preclinical models of sepsis do not address skeletal muscle disuse, a key component for the development of sepsis-induced myopathy. Our objective in this protocol is to provide a step-by-step guideline for a mouse model that reproduces the clinical setting experienced by a bedridden septic patient. Male C57Bl/6 mice were used to develop this model. Mice underwent cecal ligation and puncture (CLP) to induce sepsis. Four days post-CLP, mice were subjected to hindlimb suspension (HLS) for seven days. Results were compared with sham-matched surgeries and/or animals with normal ambulation (NA). Muscles were dissected for in vitro muscle mechanics and morphological assessments. The model results in marked muscle atrophy and weakness, a similar phenotype observed in septic patients. The model represents a platform for testing potential therapeutic strategies for the mitigation of sepsis-induced myopathy.

Epidemiological analysis of in patients with sepsis in a large tertiary general hospital in Southwest China

To analyze the epidemiological characteristics of hospitalized patients diagnosed with sepsis in a large class III general hospital in Southwest China in a period of 2 years, and to explore the risk factors related to death in patients with sepsis. A retrospective study was conducted to select patients with sepsis admitted to Sichuan Provincial People's Hospital from September 1, 2021 to August 31, 2023, and general characteristics such as gender, age, discharge diagnosis, discharge department, hospitalization cost, length of stay, and prognosis during hospitalization were collected. The baseline of two groups of patients was compared, and the risk factors of in-hospital cause of death in patients with sepsis were analyzed by multivariate Logistic regression. A total of 3 568 patients with sepsis were included with median age of 58 (35, 74) years old. Of all patients, there were 2 147 males (60.17%). The median length of hospitalization was 13 (8, 24) days, and the median hospitalization cost was 3.98 (1.87, 8.83) ten thousand yuan. The departments with more than 100 cases of sepsis in 2 years were central intensive care unit (ICU), pediatrics department, nephrology department, emergency medicine department, emergency intensive care unit (EICU), infectious department, respiratory medicine department, hematology department, neonatal care unit and emergency surgical department. A total of 1 210 patients (33.91%) admitted to ICU (including central ICU and EICU). The hospitalization cost of ICU patients were higher [6.7 (3.1, 15.5) ten thousand yuan], the hospitalization duration was longer [9 (3, 17) days], and the mortality was higher [35.29% (427/1 210)]. Among 3 568 patients with sepsis, 448 died and 3 120 survived during hospitalization. The age, male proportion and hospitalization cost of patients with sepsis in the death group were significantly higher than those in the survival group [age (years old): 75 (60, 86) vs. 57 (30, 71), male proportion: 67.86% (304/448) vs. 59.07% (1 843/3 120), hospitalization cost (ten thousand yuan): 6.7 (3.0, 16.9) vs. 3.7 (1.8, 8.1)], the ratio of diabetes mellitus was significantly lower than that of survival group [4.91% (22/448) vs. 10.45% (326/3 120)], the length of hospitalization was shorter than that of survival group [days: 10.0 (3.0, 19.0) vs. 13.0 (8.0, 24.0)], the differences were statistically significant (all P < 0.01). Multivariate Logistic regression analysis showed that male [odds ratio (OR) = 0.75, 95% confidence interval (95%CI) was 0.59-0.96], elder (OR = 1.04, 95%CI was 1.03-1.05) and diabetes (OR = 0.32, 95%CI was 0.19-0.54) were independent risk factors for in-hospital death in patients with sepsis (all P < 0.05). Sepsis is a heavy burden in Southwest China, especially for ICU, with high mortality, high hospitalization costs, and heavy economic burden on patients and society. Male, elder and diabetes were independent risk factors for in-hospital death of sepsis patients.

Infections as a “cause of death” in patients with cancer: Need improved focus to improve outcomes?

e23281 Background: Infectious diseases are a significant contributor to both morbidity and mortality in cancer patients. Cancer's impact on the immune system and the immunosuppressive effect of its treatment make patients more susceptible to infection. Furthermore, cancer's involvement of multiple organs increases the risk of infection. It is crucial to consider causes of death beyond cancer when evaluating overall survival, as effective treatment alone is not sufficient. We conducted a study to investigate infection as a cause of in-hospital death among cancer patients in a tertiary hospital. Methods: We collected data on the causes of death for all patients with cancer who passed away in our hospital in 2022 and 2023. This included detailed medical histories, investigation charts, and test results related to infections. Infections were defined as those listed as the cause of death in the hospital records. We had access to data on age, sex, primary tumor site, and laboratory test results related to infections. Infections were identified through microbiological cultures and PCR panels for bacteria, fungi, and viruses. Percentages were used to analyze standard statistical variables. Results: The death toll for the year period amounted to 113 individuals, which included 77 males and 36 females, with ages ranging from 16 to 88 and a mean of 63.2 years, with a median of 64 years. Among the 91 patients with classifiable stages, 86% had metastatic disease. Many of the patients, amounting to 75%, were suspected or confirmed to have contracted an infection at the time of death. In 69/113 (61%) cases, the infections were confirmed through laboratory and radiological tests. Out of 90 patients in whom cultures and infection PCR tests were sent, 53/90 (59%) showed positive microbiology reports, and 37/90 (41%) had negative microbiological culture reports. Among the 41 patients with positive microbiology culture reports, 41% had blood culture positivity but no localizing signs, 34% had lung infections, 15% had both lung and blood culture positivity, and around 8% had urological origins of infection. Around 60% of the patients had bacterial infections, while approximately 4% had documented fungal infections. No cases of viral infections were recorded. Half of the patients, or 50%, were directly admitted to the Intensive Care Unit (ICU) during their last admission, while the remaining 50% were transferred from the ward to the ICU. Infection as a cause of death was attributed to 81/113 (71.6%) of the patients. Conclusions: Infectious diseases appear to be a major cause of death. Its control may play a significant role in reducing the overall survival and improving quality of life. Increased focus on detection and intervention to manage infections could substantially add to desirable endpoints in oncology. Therefore, there is an urgent need to focus on the management of infections.

Identifying prognostic factors for survival in intensive care unit patients with SIRS or sepsis by machine learning analysis on electronic health records.

Systemic inflammatory response syndrome (SIRS) and sepsis are the most common causes of in-hospital death. However, the characteristics associated with the improvement in the patient conditions during the ICU stay were not fully elucidated for each population as well as the possible differences between the two. The aim of this study is to highlight the differences between the prognostic clinical features for the survival of patients diagnosed with SIRS and those of patients diagnosed with sepsis by using a multi-variable predictive modeling approach with a reduced set of easily available measurements collected at the admission to the intensive care unit (ICU). Data were collected from 1,257 patients (816 non-sepsis SIRS and 441 sepsis) admitted to the ICU. We compared the performance of five machine learning models in predicting patient survival. Matthews correlation coefficient (MCC) was used to evaluate model performances and feature importance, and by applying Monte Carlo stratified Cross-Validation. Extreme Gradient Boosting (MCC = 0.489) and Logistic Regression (MCC = 0.533) achieved the highest results for SIRS and sepsis cohorts, respectively. In order of importance, APACHE II, mean platelet volume (MPV), eosinophil counts (EoC), and C-reactive protein (CRP) showed higher importance for predicting sepsis patient survival, whereas, SOFA, APACHE II, platelet counts (PLTC), and CRP obtained higher importance in the SIRS cohort. By using complete blood count parameters as predictors of ICU patient survival, machine learning models can accurately predict the survival of SIRS and sepsis ICU patients. Interestingly, feature importance highlights the role of CRP and APACHE II in both SIRS and sepsis populations. In addition, MPV and EoC are shown to be important features for the sepsis population only, whereas SOFA and PLTC have higher importance for SIRS patients.

Long-term outcome in new onset refractory status epilepticus: a retrospective study

BackgroundNew onset refractory status epilepticus (NORSE) is a neurologic emergency without an immediately identifiable cause. The complicated and long ICU stay of the patients can lead to perceiving a prolongation of therapies as futile. However, a recovery is possible even in severe cases. This retrospective study investigates ICU treatments, short- and long-term outcome and ethical decisions of a case series of patients with NORSE.MethodsOverall, 283 adults were admitted with status epilepticus (SE) to the Neurocritical Care Unit of the University Hospital Zurich, Switzerland, between 01.2010 and 12.2022. Of them, 25 had a NORSE. We collected demographic, clinical, therapeutic and outcome data. Descriptive statistics was performed.ResultsMost patients were female (68%), previously healthy (Charlson comorbidity index 1 [0–4]) and relatively young (54 ± 17 years). 96% presented with super-refractory SE. Despite extensive workup, the majority (68%) of cases remained cryptogenic. Most patients had a long and complicated ICU stay. The in-hospital mortality was 36% (n = 9). The mortality at last available follow-up was 56% (n = 14) on average 30 months after ICU admission. The cause of in-hospital death for 89% (n = 8) of the patients was the withholding/withdrawing of therapies. Medical staff except for one patient triggered the decision. The end of life (EOL) decision was taken 29 [12–51] days after the ICU admission. Death occurred on day 6 [1–8.5] after the decision was taken. The functional outcome improved over time for 13/16 (81%) hospital survivors (median mRS at hospital discharge 4 [3.75–5] vs. median mRS at last available follow-up 2 [1.75–3], p < 0.001).ConclusionsOur data suggest that the long-term outcome can still be favorable in NORSE survivors, despite a prolonged and complicated ICU stay. Clinicians should be careful in taking EOL decisions to avoid the risk of a self-fulfilling prophecy. Our results encourage clinicians to continue treatment even in initially refractory cases.

Leading Causes of In-Hospital Death of Older Patients of Different Age Groups in Shanghai.

Despite great achievements in clinical medicine, the in-hospital mortality of older patients remains high. How to reduce the in-hospital mortality of older inpatients is of great clinical value in clinical practice. This study is to analyze the leading causes of in-hospital death of older inpatients of different ages in Shanghai. An observational study was conducted in Shanghai. A total of 3894 older inpatients (≥60 years old) were investigated. According to the age stratification standard of World Health Organization, they were divided into young older patients group (aged 60 to 74), old older patients group (aged 75 to 89) and very old patients group (aged ≥90). Diseases of in-hospital death of older inpatients in different age groups were classified according to the 10th edition of the International Classification of Diseases. Constituent ratio of causes of in-hospital death in each group was analyzed. The constituent ratio of pulmonary infection had the highest rate of in-hospital death in older patients. The constituent ratio of lung malignant tumors had the highest rate of in-hospital death in young older patients. The constituent ratio of pulmonary infection had the highest rate of in-hospital death in old older patients. The constituent ratio of pulmonary infection had the highest rate of in-hospital death in very old patients. The leading cause of in-hospital death of young older patients group was lung malignant tumor. The leading cause of in-hospital death of old older patients group and very older patients group was pulmonary infection. Great importance should be attached to the prevention of lung tumor and lung infection in the elderly. Results of this study will provide a basis for health administrative departments to formulate corresponding health-care policies for older patients.

Medical versus surgical causes of death following colorectal resection: a Queensland Audit of Surgical Mortality (QASM) study.

The causes of death following colorectal resection remain poorly explored. Few studies have addressed whether early post-operative mortality is predominantly caused by a patient's medical co-morbidities, or from factors pertaining to the presenting surgical disease process itself. This study analyses data from the Queensland audit of surgical mortality (QASM) to report the causes of in-hospital death following colorectal resection, identifies whether these were due to either medical or surgical factors, and determines the patient characteristics associated with a medical cause of death. Through analysis of QASM Surgical Case Forms, the causes of in-hospital death were determined in 750 patients who died in Queensland following colorectal resection between January 2010 and December 2020. Deaths were attributed to a specific medical or surgical cause, with multivariate analysis used to identify independent risk factors associated with a medical cause of death. In total, 395 patients (52.7%) died due to surgical causes and 355 (47.3%) died due to medical causes. Respiratory co-morbidities (OR 1.832, 95% CI: 1.267-2.650), advanced malignancy (OR 1.814, 95% CI: 1.262-2.607), neurological co-morbidities (OR 1.794, 95% CI: 1.168-2.757) and advanced age (OR 1.430, 95% CI: 1.013-2.017) were independent risk factors associated with increased risk of a medical cause of death. Even in the absence of complicating surgical factors, a significant number of patients died in hospital following colorectal resection due to their underlying co-morbidities. Multi-disciplinary models of care which allow for the early recognition and treatment of medical complications may reduce post-operative mortality in these patients.

Venous Thromboembolism Prophylaxis in Medical and Surgical Patients - What's Our Reality?

Venous thromboembolism (VTE) includes pulmonary embolism (PE), deep vein thrombosis (DVT) in lower limbs, and thrombosis in rare locations. VTE is a common cardiovascular disease, being the leading preventable cause of in-hospital death. Both surgical and acute medical patients have an elevated risk of developing VTE. VTE risk assessment is essential to identify patients who might benefit from VTE prophylaxis accurately. Clinical data on risk factors and prophylaxis in Portugal are scarce. We aimed to determine the proportion of at-risk patients who received prophylaxis and the incidence of bleeding events. We also intended to study the rate of VTE in a cohort of medical and surgical patients during the hospitalization period and three months after discharge. During one week in 2020, adults admitted for more than 72hr to a medical or surgical ward were included. The study excluded patients with a diagnosis of VTE three months before hospitalization and who were either chronically receiving anticoagulation therapy or had started it 48 hours after admission. Risk assessments were based on the Padua Prediction Score (PPS) for medical patients and the Caprini Risk Assessment Model (CRAM) for surgical patients. We used CHEST guidelines, 9th edition, to determine the adequacy of the prophylactic method. A total of 123 patients were analyzed, 18.7% of which tested positive for SARS-CoV-2. VTE risk in surgical patients was categorized as very low or low (16.6%), moderate (37.5%), and high (43.8%), according to the CRAM. Risk in medical patients was categorized as low (60.0%) or high (40.0%) according to the PPS. We estimated that VTE chemoprophylaxis was overused in about 30.0% of patients vs. 7.0% who were at risk and did not receive appropriate chemoprophylaxis. The rate of thromboembolic events was 4.1% (n=5), 2 of which happened after discharge. Two of these patients were under VTE prophylaxis during hospitalization. Major bleeding occurred in 2.4% of patients (n=3). A significant number of hospitalized patients are deemed to be at risk for VTE, making appropriate prophylaxis essential. The results emphasize the insufficient management of VTE prophylaxis.

In-Hospital Mortality from Spondylodiscitis: Insights from a Single-Center Retrospective Study

(1) Background: There is a marked proportion of spondylodiscitis patients who die during the early stage of the disease despite the applied therapy. This study investigates this early mortality and explores the associated risk factors. (2) Methods: We conducted a retrospective analysis of spondylodiscitis patients treated at our Level I spine center between 1 January 2018 and 31 December 2022. (3) Results: Among 430 patients, 32 (7.4%) died during their hospital stay, with a median time of 28.5 days (range: 2.0–84.0 days). Six of these patients (18.75%) did not undergo surgery due to dire clinical conditions or death prior to scheduled surgery. Identified causes of in-hospital death included multiorgan failure (n = 15), acute bone marrow failure (2), cardiac failure (4), liver failure (2), acute respiratory failure (2), acute renal failure (1), and concomitant oncological disease (1). In a simple logistic regression analysis, advanced age (p = 0.0006), diabetes mellitus (p = 0.0002), previous steroid medication (p = 0.0279), Charlson Comorbidity Index (p &lt; 0.0001), and GFR level at admission (p = 0.0008) were significant risk factors for in-hospital death. In a multiple logistic regression analysis, advanced age (p = 0.0038), diabetes mellitus (p = 0.0002), and previous steroid medication (p = 0.0281) remained significant. (4) Conclusions: Despite immediate treatment, a subset of spondylodiscitis patients experience early mortality. Particular attention should be given to elderly patients and those with diabetes or a history of steroid medication, as they face an elevated risk of a rapidly progressing and fatal disease.

Abstract 12610: Outcomes of Patients With Cancer and Acute Myocardial Infarction-Associated Cardiogenic Shock Managed With Temporary Mechanical Circulatory Support

Introduction: Cardiogenic shock (CS) is a leading cause of in-hospital death among patients with acute myocardial infarction (AMI). Temporary mechanical circulatory support (tMCS) is used in AMI-CS and may improve end-organ perfusion at the risk of bleeding/thrombosis. Patients with cancer are at high risk of AMI and CS and are at risk of bleeding and thrombosis. However, there is limited data on the outcomes of patients with cancer and AMI-CS managed with tMCS. Methods: Adult patients with AMI-CS managed with tMCS from January 2006 to December 2018 with and without cancer were identified within the National Inpatient Sample. Propensity score matching (PSM) was performed to match 1 cancer patient to 10 non-cancer controls. Primary outcome was in-hospital death and secondary outcomes were major bleeding and thrombotic complications. Temporal trends of tMCS use in cancer patients were investigated. Results: Patient characteristics after PSM are described in Table. After PSM, 1,287 individuals with and 12,870 without cancer were included. Patient characteristics were well-balanced between cancer and non-cancer groups after PSM. After PSM, there was no difference in death (OR 1.00, 95% CI 0.88 - 1.13) or thrombotic complications (OR 1.10, 95% CI 0.91 - 1.34) between patients with and without cancer. Patients with cancer had higher risk of major bleeding (OR 1.29, 95% CI 1.15 - 1.46). Conclusions: Among patients hospitalized for AMI-CS managed with tMCS, cancer was associated with increased major bleeding but similar mortality and thrombotic risk. Future investigation is needed in order to further characterize and improve outcomes for this increasingly common patient population.

A-155 Unlocking the Complete Blood Count: Derivation of a Single-Panel Laboratory Test That Includes Monocyte Distribution Width to Create a Universal Sepsis Screening Tool

Abstract Background Sepsis is the leading cause of in-hospital death. Outcome improvement requires rapid detection and early antimicrobial therapy. The complete blood count (CBC) is ordered for more than two-thirds of all patients in the emergency department (ED). Individual CBC components have limited utility for sepsis screening due to low specificity and sensitivity. We sought to create a reliable sepsis screening tool by combining components of the CBC differential. Methods In this single-center retrospective cohort study, all adult patients who had a CBC with differential performed within 6 h of ED arrival during a 20-month period were eligible for inclusion. Repeat ED visits by the same patient were excluded. Our primary outcome was manifestation of sepsis within 72 h of ED arrival, detected from timestamped electronic health records using a previously validated electronic phenotype based on Sepsis-3 consensus criteria. Multivariable logistic regression was performed to identify individual components of the CBC differential that were independently associated with our outcome and to identify optimal cutoffs for discretization. Odds ratios were used to assign weights to each component and to derive a 10-point system for scoring likelihood of sepsis. Results 34 864 patients were included; 1306 (3.7%) met sepsis outcome criteria within 72 h of ED arrival and 181 (0.5%) had septic shock. White blood cell (WBC) count, monocyte distribution width (MDW), and the neutrophil to lymphocyte count ratio were found to predict sepsis. As shown in the figure, there was a linear relationship between our CBC infection severity index and likelihood of developing sepsis and septic shock. Patients with a high risk score (8 or above) had a greater than one in four chance of developing sepsis within 72 h. Conclusion A simple ten-point index derived from the most commonly used laboratory panel in medicine reliably estimated likelihood of developing sepsis.

Prediction of bleeding in patients being considered for venous thromboembolism prophylaxis

BackgroundVenous thromboembolism (pulmonary embolism and deep vein thrombosis) is an important preventable cause of in-hospital death. Prophylaxis with low doses of anticoagulants reduces the incidence of venous thromboembolism but can also cause bleeding. It is, therefore, important to stratify the risk of bleeding for hospitalized patients when considering pharmacologic prophylaxis. The IMPROVE (international medical prevention registry on venous thromboembolism) and Consensus risk assessment models (RAMs) are the two tools available for such patients. Few studies have evaluated their ability to predict bleeding in a large, unselected cohort of patients. We assessed the ability of the IMPROVE and Consensus bleeding RAMs to predict bleeding within 90 days of hospitalization in a comprehensive analysis encompassing all hospitalized patients, regardless of surgical vs nonsurgical status. MethodsWe analyzed consecutive first hospital admissions of 1,228,448 unique surgical and nonsurgical patients to 1298 Veterans Affairs facilities nationwide between January 2016 and December 2021. IMPROVE and Consensus scores were generated using data from a repository of their common electronic medical records. We assessed the ability of the two RAMs to predict bleeding within 90 days of admission. We used area under the receiver operating characteristic curves to determine the prediction of bleeding by each RAM. ResultsOf 1,228,448 hospitalized patients, 324,959 (26.5%) were surgical and 903,489 (73.5%) were nonsurgical. Of these patients, 68,372 (5.6%) had a bleeding event within 90 days of admission. The Consensus RAM scores ranged from −5.60 to −1.21 (median, −4.93; interquartile range, −5.60 to −4.93). The IMPROVE RAM scores ranged from 0 to 22 (median, 3.5; interquartile range, 2.5-5). Both showed good calibration, with higher scores associated with higher bleeding rates. The ability of both RAMs to predict 90-day bleeding was low (area under the receiver operating characteristic curve 0.61 for the IMPROVE RAM and 0.59 for the Consensus RAM). The predictive ability was also low at 30 and 60 days for surgical and nonsurgical patients, patients receiving prophylactic, therapeutic, or no anticoagulation, and patients hospitalized for ≥72 hours. Prediction was also low across different bleeding outcomes (ie, any bleeding, gastrointestinal bleeding, nongastrointestinal bleeding, and bleeding or death). ConclusionsIn this large, unselected, nationwide cohort of surgical and nonsurgical hospital admissions, increasing IMPROVE and Consensus bleeding RAM scores were associated with increasing bleeding rates. However, both RAMs had low ability to predict bleeding at 0 to 90 days after admission. Thus, the currently available RAMs require modification and rigorous reevaluation before they can be applied universally.

Assessment of Bleeding Risk in Patients Being Considered for VTE Pharmacoprophylaxis in a Large Nationwide Cohort

More than 100,000 patients are hospitalized in the United States each day. Half of all venous thromboembolism (VTE) events occur in hospitalized patients. Hospital-related pulmonary embolism was declared the leading preventable cause of in-hospital death by the US Surgeon General, Centers for Disease Control and Prevention, and Centers for Medicare and Medicaid Services. Risk-stratification and targeted-prophylaxis are keys to prevention. Pharmacoprophylaxis is highly effective, though with an increased risk of bleeding. Therefore, decisions for VTE prophylaxis must balance the predicted risk of VTE against the predicted risk of bleeding in individual patients. While there are several risk assessment models (RAMs) to predict the risk of VTE, there are only two RAMs proposed to predict bleeding from pharmacoprophylaxis and neither has been validated in a large, unselected cohort of general hospitalized patients. We analyzed all consecutive unique hospital admissions of surgical and nonsurgical patients at all 1298 VA facilities nationwide between January 2016 and December 2021. IMPROVE and Consensus RAM scores were generated using data from a repository of the unified national VA electronic medical record. We assessed the predictive ability of the RAMs for bleeding within 30, 60, and 90 days after admission and compared their performance in surgical and nonsurgical patients by computing the areas under their respective receiver operating-characteristic curves (AUC). We analyzed 1,228,448 patients; 26.5% (n = 324,959) surgical and 73.5% (n = 903,489) nonsurgical. 68,372 (5.6%) patients had major bleeding (as defined by the International Society on Thrombosis and Hemostasis) within 90 days postadmission (surgical 5.0%, nonsurgical 5.8%). IMPROVE scores ranged from 0 to 22 (median, 3.5; interquartile range, 2.5-5.0); Consensus scores ranged from −5.60 to −1.21 (medina, −4.93; interquartile range, −5.60 to −4.93). Higher scores were associated with higher bleeding rates, however, the ability of either RAM to predict 90-day bleeding was no better than a coin toss (AUCs: IMPROVE, 0.61: Consensus, 0.59), and was similarly low at 30 and 60 days postadmission (Table). Both RAMs performed better in surgical vs nonsurgical patients (AUCs: IMPROVE, 0.64 vs 0.61; P < .001; Consensus, 0.63 vs 0.58; P < .001) (Figure). In this first known validation study evaluating existing RAMs for bleeding from pharmacoprophylaxis in an unselected cohort, increasing scores correlated with bleeding rates; though both RAMs had low predictive ability for major bleeding postadmission. Both RAMs predicted bleeding better in surgical vs nonsurgical patients, but the differences were of limited clinical importance. Further studies are urgently required to improve existing bleeding RAMs to facilitate systematic decision-making for VTE prophylaxis in hospitalized patients.TableArea under receiver operating characteristic curves (AUC) for the IMPROVE and Consensus Bleeding risk assessment models (RAMs) at different follow-up intervalsTime from hospital admission, daysImprove bleeding RAMConsensus bleeding RAMAUC (95% confidence intervals)P valueAUC (95% confidence intervals)P value0-300.62 (0.62-0.62)<.0010.61 (0.60-0.61)<.0010-600.62 (0.61-0.62).0720.60 (0.60-0.60).0120-900.61 (0.61-0.62)1.00(ref)0.59 (0.59-0.60)1.00(ref) Open table in a new tab

Interventional therapies for pulmonary embolism.

Pulmonary embolism (PE) is the leading cause of in-hospital death and the third most frequent cause of cardiovascular death. The clinical presentation of PE is variable, and choosing the appropriate treatment for individual patients can be challenging. Traditionally, treatment of PE has involved a choice of anticoagulation, thrombolysis or surgery; however, a range of percutaneous interventional technologies have been developed that are under investigation in patients with intermediate-high-risk or high-risk PE. These interventional technologies include catheter-directed thrombolysis (with or without ultrasound assistance), aspiration thrombectomy and combinations of the aforementioned principles. These interventional treatment options might lead to a more rapid improvement in right ventricular function and pulmonary and/or systemic haemodynamics in particular patients. However, evidence from randomized controlled trials on the safety and efficacy of these interventions compared with conservative therapies is lacking. In this Review, we discuss the underlying pathophysiology of PE, provide assistance with decision-making on patient selection and critically appraise the available clinical evidence on interventional, catheter-based approaches for PE treatment. Finally, we discussfuture perspectives and unmet needs.

Reasons for Hospitalization and All-Cause Mortality for Adults with Sarcoidosis

PurposeSarcoidosis is a multisystem immune disease with a high rate of hospitalization. There is a paucity of large population-based studies on sarcoid inpatients. We aimed to examine the reasons for hospitalizations and mortality of adult sarcoid patients utilizing the National Inpatient Sample (NIS) database. MethodsAdult hospitalizations in 2016-2019 NIS database with sarcoidosis (ICD-10 code D86) were analyzed. The “reason for hospitalization” and “reason for in-hospital death” were divided into 19 organ system/disease categories based on their principal ICD-10 hospital billing diagnosis. ResultsAmong the 330,470 sarcoid hospitalizations, cardiovascular (20.4%) and respiratory (16.9%) diagnoses were the most common reasons for hospitalization. The most common individual diagnoses were sepsis and pneumonia. In-hospital death occurred in 2.4% of sarcoid hospitalizations. The most common reasons for death were infectious (30%), cardiovascular (20.7%), and respiratory (20.3%) diagnoses. The most common individual diagnoses in the deceased group were sepsis and respiratory failure. Finally, the sarcoid group had a higher frequency of complications including arrhythmias/heart blocks, heart failure, cranial neuropathies, hypercalcemia, iridocyclitis, myocarditis, and myositis. Sarcoid inpatients had longer length of stay (4 vs 3 days; p < .001) and higher median total hospital charges ($36,865 vs $31,742; p < .001). ConclusionsThe most common reasons for sarcoid hospitalizations were cardiovascular and respiratory. Nearly 1 in 40 hospitalizations resulted in death, with most common complications being conduction abnormalities and heart failure. The most common causes of in-hospital death were sepsis and respiratory failure. Sarcoid hospitalizations had 16% higher total hospital charges compared to nonsarcoid inpatients.

Machine Learning for Early Outcome Prediction in Septic Patients in the Emergency Department

Background: Sepsis is one of the major causes of in-hospital death, and is frequent in patients presenting to the emergency department (ED). Early identification of high-risk septic patients is critical. Machine learning (ML) techniques have been proposed for identification and prognostication of ED septic patients, but these models often lack pre-hospital data and lack validation against early sepsis identification scores (such as qSOFA) and scores for critically ill patients (SOFA, APACHE II). Methods We conducted an electronic health record (EHR) study to test whether interpretable and scalable ML models predict mortality in septic ED patients and compared their performance with clinical scores. Consecutive adult septic patients admitted to ED over 18 months were included. We built ML models, ranging from a simple-classifier model, to unbalanced and balanced logistic regression, and random forest, and compared their performance to qSOFA, SOFA, and APACHE II scores. Results: We included 425 sepsis patients after screening 38,500 EHR for sepsis criteria. Overall mortality was 15.2% and peaked in patients coming from retirement homes (38%). Random forest, like balanced (0.811) and unbalanced logistic regression (0.863), identified patients at risk of mortality (0.813). All ML models outperformed qSOFA, APACHE II, and SOFA scores. Age, mean arterial pressure, and serum sodium were major mortality predictors. Conclusions: We confirmed that random forest models outperform previous models, including qSOFA, SOFA, and APACHE II, in identifying septic patients at higher mortality risk, while maintaining good interpretability. Machine learning models may gain further adoption in the future with increasing diffusion and granularity of EHR data, yielding the advantage of increased scalability compared to standard statistical techniques.