Gender Differences in Hospital Outcomes among COVID-19 Hospitalizations.

OBJECTIVES: Many epidemiological studies have shown that coronavirus disease 2019 (COVID-19) disproportionately affects males, compared with females, although other studies show that there were no such differences. The aim of the present study was to assess differences in the prevalence of hospitalizations and in-hospital outcomes between the sexes, using a larger administrative database. METHODS: We used the 2020 California State Inpatient Database for this retrospective analysis. International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis code U07.1 was used to identify COVID-19 hospitalizations. These hospitalizations were subsequently stratified by male and female sex. Diagnosis and procedures were identified using the International Classification of Diseases, Tenth Revision, Clinical Modification codes. The primary outcome of the study was hospitalization rate, and secondary outcomes were in-hospital mortality, prolonged length of stay, vasopressor use, mechanical ventilation, and intensive care unit (ICU) admission. RESULTS: There were 95,180 COVID-19 hospitalizations among patients 18 years and older, 52,465 (55.1%) of which were among men and 42,715 (44.9%) were among women. In-hospital mortality (12.4% vs 10.1%), prolonged length of hospital stays (30.6% vs 25.8%), vasopressor use (2.6% vs 1.6%), mechanical ventilation (11.8% vs 8.0%), and ICU admission rates (11.4% versus 7.8%) were significantly higher among male compared with female hospitalizations. Conditional logistic regression analysis showed that the odds of mortality (odds ratio [OR] 1.38, 95% confidence interval [CI] 1.38-1.44), hospital lengths of stay (OR 1.35, 95% CI 1.31-1.39), vasopressor use (OR 1.59, 95% CI 1.51-1.66), mechanical ventilation (OR 1.62, 95% CI 1.47-1.78), and ICU admission rates (OR 1.58, 95% CI 1.51-1.66) were significantly higher among male hospitalizations. CONCLUSION: Our findings show that male sex is an independent and strong risk factor associated with COVID-19 severity.

Healthcare expenditure trends among adult stroke patients in the United States, 2011-2020.

BACKGROUND: In the US, between 2018 and 2019, approximately $57 billion were expended on stroke and related conditions. The aim of this study was to understand trends in direct healthcare expenditures among stroke patients using novel cost estimation methods and a nationally representative database. METHODS: This study was a retrospective analysis of 193,003 adults, ≥18 years of age, using the Medical Expenditure Panel Survey during 2009-2016. Manning and Mullahy's two-part model were used to calculate adjusted mean and incremental medical expenditures after adjusting for covariates. RESULTS: The mean (Standard Deviation) direct annual healthcare expenditure among stroke patients was $16,979.0 ($16,222.0- $17,736.0) and was nearly 3 times greater than non-stroke participants which were $5,039.7 ($4,951.0-$5,128.5) and were mainly spent on inpatient services, prescription medications, and office-based visits. Stroke patients had an additional healthcare expenditure of $4096.0 (3543.9, 4648.1) per person per year, compared to participants without stroke after adjusting for covariates (P<0.001). The total mean annual direct healthcare expenditure for stroke survivors increased from $16,142.0 (15,017.0-17,267.0) in 2007-2008 to $16,979.0 (16,222.0-17,736.0) in 2015-2016. CONCLUSION: Our study showed that stroke survivors had significantly greater healthcare expenses, compared to non-stroke individuals, mainly due to higher expenditures on inpatient services, prescription drugs, and office visits. These findings are concerning because the prevalence of stroke is projected to increase due to aging population and increased survival rates.

Engaging biological oscillators through second messenger pathways permits emergence of a robust gastric slow-wave during peristalsis.

Peristalsis, the coordinated contraction-relaxation of the muscles of the stomach is important for normal gastric motility and is impaired in motility disorders. Coordinated electrical depolarizations that originate and propagate within a network of interconnected layers of interstitial cells of Cajal (ICC) and smooth muscle (SM) cells of the stomach wall as a slow-wave, underly peristalsis. Normally, the gastric slow-wave oscillates with a single period and uniform rostrocaudal lag, exhibiting network entrainment. Understanding of the integrative role of neurotransmission and intercellular coupling in the propagation of an entrained gastric slow-wave, important for understanding motility disorders, however, remains incomplete. Using a computational framework constituted of a novel gastric motility network (GMN) model we address the hypothesis that engaging biological oscillators (i.e., ICCs) by constitutive gap junction coupling mechanisms and enteric neural innervation activated signals can confer a robust entrained gastric slow-wave. We demonstrate that while a decreasing enteric neural innervation gradient that modulates the intracellular IP3 concentration in the ICCs can guide the aboral slow-wave propagation essential for peristalsis, engaging ICCs by recruiting the exchange of second messengers (inositol trisphosphate (IP3) and Ca2+) ensures a robust entrained longitudinal slow-wave, even in the presence of biological variability in electrical coupling strengths. Our GMN with the distinct intercellular coupling in conjunction with the intracellular feedback pathways and a rostrocaudal enteric neural innervation gradient allows gastric slow waves to oscillate with a moderate range of frequencies and to propagate with a broad range of velocities, thus preventing decoupling observed in motility disorders. Overall, the findings provide a mechanistic explanation for the emergence of decoupled slow waves associated with motility impairments of the stomach, offer directions for future experiments and theoretical work, and can potentially aid in the design of new interventional pharmacological and neuromodulation device treatments for addressing gastric motility disorders.

First 30 Days Wound-Related Complications in Young Smokers Following Primary Achilles Repair.

The Achilles tendon is frequently injured in the young to middle aged population. Previous studies have shown that there is an increased risk of delay in postsurgical wound healing amongst tobacco smoking patients with Achilles tendon injury. This study utilized the American College of Surgeons National Surgical Quality Improvement Project (ACS-NSQIP) database. We included patients between the ages of 18 and 35 years who underwent primary Achilles tendon repair between years 2011 and 2020. The procedure type (with or without graft, CPT 27650 and 27652), patient demographics, and comorbidities were included. Primary outcomes of interest were 30-day readmission, minor complications, outcomes related to wound healing (wound disruption, superficial surgical site infection, deep incisional surgical site infection, organ-space site infections) and reoperations within 30 days of index surgery. A total of 1944 patients met the inclusion criteria for this study. One thousand six hundred and fifty-nine patients were nonsmokers, while 285 were smokers. Logistic regression showed no differences between smokers and nonsmokers (reference group) for 30-day readmission, reoperation, and minor complications. However, Black non-Hispanic patients were found to be 0.3 times (95% confidence interval: 0.1, 0.98) as likely to develop minor complications as compared to the White non-Hispanic patients. Wound-related complications after Achilles tendon repair remain low in younger (18-35 years) patients. When comparing clinical outcomes between nonsmokers and smokers, we found no statistically significant difference in this retrospective study.

Prevalence and effects of acute myocardial infarction on hospital outcomes among COVID-19 patients.

BACKGROUND: Acute myocardial infarction (AMI) is one of the most lethal complications of COVID-19 hospitalization. In this study, we looked for the occurrence of AMI and its effects on hospital outcomes among COVID-19 patients. METHODS: Data from the 2020 California State Inpatient Database was used retrospectively. All COVID-19 hospitalizations with age ≥ 18 years were included in the analyses. Adverse hospital outcomes included in-hospital mortality, prolonged length of stay (LOS), vasopressor use, mechanical ventilation, and ICU admission. Prolonged LOS was defined as any hospital LOS ≥ 75th percentile. Multivariate logistic regression analyses were used to understand the strength of associations after adjusting for cofactors. RESULTS: Our analysis had 94 114 COVID-19 hospitalizations, and 1548 (1.6%) had AMI. Mortality (43.2% vs. 10.8%, P  < 0.001), prolonged LOS (39.9% vs. 28.2%, P  < 0.001), vasopressor use (7.8% vs. 2.1%, P  < 0.001), mechanical ventilation (35.0% vs. 9.7%, P  < 0.001), and ICU admission (33.0% vs. 9.4%, P  < 0.001) were significantly higher among COVID-19 hospitalizations with AMI. The odds of adverse outcomes such as mortality (aOR 3.90, 95% CI: 3.48-4.36), prolonged LOS (aOR 1.23, 95% CI: 1.10-1.37), vasopressor use (aOR 3.71, 95% CI: 3.30-4.17), mechanical ventilation (aOR 2.71, 95% CI: 2.21-3.32), and ICU admission (aOR 3.51, 95% CI: 3.12-3.96) were significantly more among COVID-19 hospitalizations with AMI. CONCLUSION: Despite the very low prevalence of AMI among COVID-19 hospitalizations, the study showed a substantially greater risk of adverse hospital outcomes and mortality. COVID-19 patients with AMI should be aggressively treated to improve hospital outcomes.

Prevalence and trends of perioperative major adverse cardiovascular and cerebrovascular events during cancer surgeries.

Major adverse cardiovascular and cerebrovascular events (MACCE) is an important cause of morbidity and mortality during perioperative period. In this study, we looked for national trends in perioperative MACCE and its components as well as cancer types associated with high rates of perioperative MACCE during major cancer surgeries. This study was a retrospective analysis of the National Inpatient Sample, 2005-2014. Hospitalizations for surgeries of prostate, bladder, esophagus, pancreas, lung, liver, colorectal, and breast among patients 40 years and greater were included in the analysis. MACCE was defined as a composite measure that included in-hospital all-cause mortality, acute myocardial infarction (AMI), and ischemic stroke. A total of 2,854,810 hospitalizations for major surgeries were included in this study. Of these, 67,316 (2.4%) had perioperative MACCE. Trends of perioperative MACCE showed that it decreased significantly for AMI, death and any MACCE, while stroke did not significantly change during the study period. Logistic regression analysis for perioperative MACCE by cancer types showed that surgeries for esophagus, pancreas, lung, liver, and colorectal cancers had significantly greater odds for perioperative MACCE. The surgeries identified to have greater risks for MACCE in this study could be risk stratified for better informed decision-making and management.

Difference in 30-Day Readmission Rates After Laparoscopic Sleeve Gastrectomy Versus Laparoscopic Roux-En-Y Gastric Bypass: a Propensity Score Matched Study Using ACS NSQIP Data (2015-2019).

PURPOSE: There are very few studies that have compared the short-term outcomes of laparoscopic Roux-en-Y gastric bypass (LRYGB) and laparoscopic sleeve gastrectomy (LSG). Among short-term outcomes, hospital readmission after these procedures is an area for quality enhancement and cost reduction. In this study, we compared 30-day readmission rates after LSG and LRYGB through analyzing a nationalized dataset. In addition, we identified the reasons of readmission. MATERIALS AND METHODS: The current study was a retrospective analysis of data from National Surgical Quality Improvement Program (NSQIP) All adult patients, ≥ 18 years of age and who had LSG or LRYGB during 2014 to 2019 were included. Current Procedural Terminology (CPT) codes were used to identify the procedures. Multivariate logistic regressions were used to calculate propensity score adjusted odds ratios (ORs) for all cause 30-day re-admissions. RESULTS: There were 109,900 patients who underwent laparoscopic bariatric surgeries (67.5% LSG and 32.5% LRYGB). Readmissions were reported in 4168 (3.8%) of the patients and were more common among RYGB recipients compared to LSG (5.6% versus 2.9%, P < 0.001). The odds of 30-day readmissions were significantly higher among LRYGB group compared to LSG group (AOR, 2.20; 95% CI; 1.83, 2.64). In addition, variables such as age, chronic obstructive pulmonary disease, hypertension, bleeding disorders, blood urea nitrogen, SGOT, alkaline phosphatase, hematocrit, and operation time were significantly predicting readmission rates. CONCLUSIONS: Readmission rates were significantly higher among those receiving LRYGB, compared to LSG. Readmission was also affected by many patient factors. The factors could help patients and providers to make informed decisions for selecting appropriate procedures.

Association Between Frailty, 30-day Unplanned Readmission and Mortality After Hospitalization for Heart Failure: Results From the Nationwide Readmissions Database.

Objectives: This study examined how frailty in traditional risk-adjusted models could improve the predictability of unplanned 30-day readmission and mortality among heart failure patients. Methods: This study was a retrospective analysis of Nationwide Readmissions Database data collected during the years 2010-2018. All patients ≥65 years who had a principal diagnosis of heart failure were included in the analysis. The Johns Hopkins Adjusted Clinical Groups frailty-defining diagnosis indicator was used to identify frail patients. Results: There was a total of 819,854 patients admitted for heart failure during the study period. Among them, 63,302 (7.7%) were frail. In the regression analysis, the risk of all-cause 30-day readmission (OR, 1.18; 95% CI, 1.14-1.22) and in-hospital mortality (OR, 1.52; 95% CI, 1.40-1.66) were higher in patients with frailty. Discussion: Inclusion of frailty in comorbidity-based risk-prediction models significantly improved the predictability of unplanned 30-day readmission and in-hospital mortality.

Racial difference in mortality among COVID-19 hospitalizations in California.

In the US, racial disparities in hospital outcomes are well documented. We explored whether race was associated with all-cause in-hospital mortality and intensive care unit (ICU) admission among COVID-19 patients in California. This was a retrospective analysis of California State Inpatient Database during 2020. Hospitalizations ≥ 18 years of age for COVID-19 were included. Cox proportional hazards with mixed effects were used for associations between race and in-hospital mortality. Logistic regression was used for the association between race and ICU admission. Among 87,934 COVID-19 hospitalizations, majority were Hispanics (56.5%), followed by White (27.3%), Asian, Pacific Islander, Native American (9.9%), and Black (6.3%). Cox regression showed higher mortality risk among Hispanics, compared to Whites (hazard ratio, 0.91; 95% CI 0.87-0.96), Blacks (hazard ratio, 0.87; 95% CI 0.79-0.94), and Asian, Pacific Islander, Native American (hazard ratio, 0.89; 95% CI 0.83-0.95). Logistic regression showed that the odds of ICU admission were significantly higher among Hispanics, compared to Whites (OR, 1.70; 95% CI 1.67-1.74), Blacks (OR, 1.70; 95% CI 1.64-1.78), and Asian, Pacific Islander, Native American (OR, 1.82; 95% CI 1.76-1.89). We found significant disparities in mortality among COVID-19 hospitalizations in California. Hispanics were the worst affected with the highest mortality and ICU admission rates.

Effect of Frailty on Hospital Outcomes Among Pediatric Cancer Patients in the United States: Results From the National Inpatient Sample.

BACKGROUND: Studies on frailty among pediatric patients with cancer are scarce. In this study, we sought to understand the effects of frailty on hospital outcomes in pediatric patients with cancer. METHODS: This retrospective study used data collected and stored in the Nationwide Inpatient Sample (NIS) between 2005 and 2014. These were hospitalized patients and hence represented the sickest group of patients. Frailty was measured using the frailty definition diagnostic indicator by Johns Hopkins Adjusted Clinical Groups. RESULTS: Of 187,835 pediatric cancer hospitalizations included in this analysis, 11,497 (6.1%) were frail. The average hospitalization costs were $86,910 among frail and $40,358 for nonfrail patients. In propensity score matching analysis, the odds of in-hospital mortality (odds ratio, 2.08; 95% CI, 1.71-2.52) and length of stay (odds ratio, 3.76; 95% CI, 3.46-4.09) were significantly greater for frail patients. The findings of our study suggest that frailty is a crucial clinical factor to be considered when treating pediatric cancer patients in a hospital setting. CONCLUSIONS: These findings highlight the need for further research on frailty-based risk stratification and individualized interventions that could improve outcomes in frail pediatric cancer patients. The adaptation and validation of a frailty-defining diagnostic tool in the pediatric population is a high priority in the field.

Burden of maternal and fetal outcomes among pregnant cancer survivors during delivery hospitalizations in the United States.

Existing studies on pregnancy-related outcomes among cancer survivors are limited by sample size or specificity of the cancer type. This study estimated the burden of adverse maternal and fetal outcomes among pregnant cancer survivors using a national database. This study was a retrospective analysis of National Inpatient Sample collected during 2010-2014. Multivariate regression models were used to calculate odds ratios for maternal and fetal outcomes. The study included a weighted sample of 64,506 pregnant cancer survivors and 18,687,217 pregnant women without cancer. Pregnant cancer survivors had significantly higher odds for death during delivery hospitalization, compared to pregnant women without cancer (58 versus 5 deaths per 100,000 pregnancies). They also had higher odds of severe maternal morbidity (aOR 2.00 [95% CI 1.66-2.41]), cesarean section (aOR 1.27 [95% CI 1.19-1.37]), labor induction (aOR 1.17 [95% CI 1.07-1.29]), pre-eclampsia (aOR 1.18 [95% CI 1.02-1.36]), preterm labor (aOR 1.55 [95% CI 1.36-1.76]), chorioamnionitis (aOR 1.45 [95% CI 1.15-1.82]), postpartum infection (aOR 1.68 [95% CI 1.21-2.33]), venous thromboembolism (aOR 3.62 [95% CI 2.69-4.88]), and decreased fetal movements (aOR 1.67 [95% CI 1.13-2.46]). This study showed that pregnancy among cancer survivors constitutes a high-risk condition requiring advanced care and collective efforts from multiple subspecialties.

A Brief Overview of Adaptive Designs for Phase I Cancer Trials.

Phase I studies are used to estimate the dose-toxicity profile of the drugs and to select appropriate doses for successive studies. However, literature on statistical methods used for phase I studies are extensive. The objective of this review is to provide a concise summary of existing and emerging techniques for selecting dosages that are appropriate for phase I cancer trials. Many advanced statistical studies have proposed novel and robust methods for adaptive designs that have shown significant advantages over conventional dose finding methods. An increasing number of phase I cancer trials use adaptive designs, particularly during the early phases of the study. In this review, we described nonparametric and algorithm-based designs such as traditional 3 + 3, accelerated titration, Bayesian algorithm-based design, up-and-down design, and isotonic design. In addition, we also described parametric model-based designs such as continual reassessment method, escalation with overdose control, and Bayesian decision theoretic and optimal design. Ongoing studies have been continuously focusing on improving and refining the existing models as well as developing newer methods. This study would help readers to assimilate core concepts and compare different phase I statistical methods under one banner. Nevertheless, other evolving methods require future reviews.

Impact of COVID-19 on Intracranial Meningioma Resection: Results from California State Inpatient Database.

PURPOSE: To assess the effects of COVID-19 on hospitalizations for intracranial meningioma resection using a large database. METHODS: We conducted a retrospective analysis of the California State Inpatient Database (SID) 2019 and 2020. All adult (18 years or older) hospitalizations were included for the analysis. The primary outcomes were trends in hospitalization for intracranial meningioma resection between 2019 and 2020. Secondary outcomes were Clavien-Dindo grade IV complications, in-hospital mortality, and prolonged length of stay, which was defined as length of stay ≥75 percentile. RESULTS: There were 3,173,333 and 2,866,161 hospitalizations in 2019 and 2020, respectively (relative decrease, 9.7%), of which 921 and 788 underwent intracranial meningioma resection (relative decrease, 14.4%). In 2020, there were 94,114 admissions for COVID-19 treatment. Logistic regression analysis showed that year in which intracranial meningioma resection was performed did not show significant association with Clavien-Dindo grade IV complications and in-hospital mortality (OR, 1.23, 95% CI: 0.78-1.94) and prolonged length of stay (OR, 1.05, 95% CI: 0.84-1.32). CONCLUSION: Our findings show that neurosurgery practice in the US successfully adapted to the unforeseen challenges posed by COVD-19 and ensured the best quality of care to the patients.

Hospital Outcomes among COVID-19 Hospitalizations with Acute Ischemic Stroke: Cross-Sectional Study Results from California State Inpatient Database.

Coronavirus disease 2019 (COVID-19) could be a risk factor for acute ischemic stroke (AIS) due to the altered coagulation process and hyperinflammation. This study examined the risk factors, clinical profile, and hospital outcomes of COVID-19 hospitalizations with AIS. This study was a retrospective analysis of data from California State Inpatient Database (SID) during 2019 and 2020. COVID-19 hospitalizations with age ≥ 18 years during 2020 and a historical cohort without COVID-19 from 2019 were included in the analysis. The primary outcomes studied were in-hospital mortality and discharge to destinations other than home. There were 91,420 COVID-19 hospitalizations, of which, 1027 (1.1%) had AIS. The historical control cohort included 58,083 AIS hospitalizations without COVID-19. Conditional logistic regression analysis showed that the odds of in-hospital mortality, discharge to destinations other than home, DVT, pulmonary embolism, septic shock, and mechanical ventilation were significantly higher among COVID-19 hospitalizations with AIS, compared to those without AIS. The odds of in-hospital mortality, DVT, pulmonary embolism, septic shock, mechanical ventilation, and respiratory failure were significantly higher among COVID-19 hospitalizations with AIS, compared to AIS hospitalizations without COVID-19. Although the prevalence of AIS was low among COVID-19 hospitalizations, it was associated with higher mortality and greater rates of discharges to destinations other than home.

Hospital Outcomes Among COVID-19 Hospitalizations With Myocarditis from the California State Inpatient Database.

Many case reports have indicated that myocarditis could be a prognostic factor for predicting morbidity and mortality among patients with COVID-19. In this study, using a large database we examined the association between myocarditis among COVID-19 hospitalizations and in-hospital mortality and other adverse hospital outcomes. The present study was a retrospective analysis of data collected in the California State Inpatient Database during 2020. All hospitalizations for COVID-19 were included in the analysis and grouped into those with and without myocarditis. The outcomes were in-hospital mortality, cardiac arrest, cardiogenic shock, mechanical ventilation, and acute respiratory distress syndrome. Propensity score matching, followed by conditional logistic regression, was performed to find the association between myocarditis and outcomes. Among 164,417 COVID-19 hospitalizations, 578 (0.4%) were with myocarditis. After propensity score matching, the rate of in-hospital mortality was significantly higher among COVID-19 hospitalizations with myocarditis (30.0% vs 17.5%, p <0.001). Survival analysis with log-rank test showed that 30-day survival rates were significantly lower among those with myocarditis (39.5% vs 46.3%, p <0.001). Conditional logistic regression analysis showed that the odds of cardiac arrest (odds ratio [OR] 1.90, 95% confidence interval [CI] 1.16 to 3.14), cardiogenic shock (OR 4.13, 95% CI 2.14 to 7.99), mechanical ventilation (OR 3.30, 95% CI 2.47 to 4.41), and acute respiratory distress syndrome (OR 2.49, 95% CI 1.70 to 3.66) were significantly higher among those with myocarditis. Myocarditis was associated with greater rates of in-hospital mortality and adverse hospital outcomes among patients with COVID-19, and early suspicion is important for prompt diagnosis and management.