Advancing the care of individuals with cancer through innovation & technology: Proceedings from the cardiology oncology innovation summit 2020 and 2021.

As cancer therapies increase in effectiveness and patients' life expectancies improve, balancing oncologic efficacy while reducing acute and long-term cardiovascular toxicities has become of paramount importance. To address this pressing need, the Cardiology Oncology Innovation Network (COIN) was formed to bring together domain experts with the overarching goal of collaboratively investigating, applying, and educating widely on various forms of innovation to improve the quality of life and cardiovascular healthcare of patients undergoing and surviving cancer therapies. The COIN mission pillars of innovation, collaboration, and education have been implemented with cross-collaboration among academic institutions, private and public establishments, and industry and technology companies. In this report, we summarize proceedings from the first two annual COIN summits (inaugural in 2020 and subsequent in 2021) including educational sessions on technological innovations for establishing best practices and aligning resources. Herein, we highlight emerging areas for innovation and defining unmet needs to further improve the outcome for cancer patients and survivors of all ages. Additionally, we provide actionable suggestions for advancing innovation, collaboration, and education in cardio-oncology in the digital era.

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.

Development of a Cancer Rehabilitation Dashboard to Collect Data on Physical Function in Cancer Patients and Survivors.

OBJECTIVE: The aim of the study is to describe the development of a cancer rehabilitation dashboard that collects data on physical function for cancer survivors in a cancer institute. METHODS: This project was conducted at the Miami Cancer Institute. The cancer rehabilitation dashboard was developed by a team of physicians, biostatistician, and medical informatics teams to record, report and track the physical function of cancer survivors. A multimodal approach to the measurement of physical function was used and included the Patient-Reported Outcome Measurement Information System-Physical Function short form, Patient-Reported Outcome Measurement Information System-Fatigue short form, Timed Up and Go Test, Sit-to-Stand Test in 30-sec test, four-stage balance test, and grip strength. To develop this system, a Cerner Power Form was developed based on the physical function data. To display the data, a dedicated flowsheet was developed and placed within the Oncology Viewpoint in Cerner Millennium. Thus, from inside any patient record, the flowsheet could easily be accessed by providers without leaving normal clinician workflows. Using native functionality, the data can also be shown in graphical format to facilitate dialog with patients and oncology teams. All patient data from the Cerner Power Form discrete task assays were integrated into an existing Oncology Data Warehouse for all patients. The data elements in the Cerner Power Form were identified in the electronic medical record system, loaded into the Oncology Data Warehouse, and related to the other source systems to develop reports and data visualizations such as the cancer rehabilitation dashboard. The cancer rehabilitation dashboard allows visualization of numerous parameters of physical function in cancer survivors evaluated and treated and their change over time. Rendered in Tableau, the cancer rehabilitation dashboard acts as a centralized, interactive data source to analyze and connect clinicians to near real-time data. RESULTS: The cancer rehabilitation dashboard was successfully developed and implemented into a cancer rehabilitation practice in a cancer institute and used to collect and track physical function data for cancer survivors receiving treatment and cancer survivors. This information has been used to direct the treatment plan and educate individual patients about the impact of the cancer and its treatment on physical function as well as oncology teams in a cancer institute. CONCLUSIONS: The cancer rehabilitation dashboard provides an insight into the physical function of cancer survivors receiving treatment and cancer survivors using both self-reported and objective metrics. It can be customized to suit the interests of clinicians and researchers wishing to improve the quality of life of this population.

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.

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.

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.

Adverse Outcomes in Hospitalizations for Amyloid-Related Heart Failure.

Transthyretin amyloid cardiomyopathy is being increasingly recognized as an important cause of heart failure (HF). In this study, we looked at adverse outcomes in hospitalizations with amyloid-related HF. This study was a retrospective analysis of the National Inpatient Sample data, collected from 2016 to 2019. Patients ≥41 years of age and admitted for HF were included in the study. In these hospitalizations, amyloid-related HF was identified through the International Classification of Diseases, Tenth Revision, Clinical Modification codes for amyloidosis. The primary outcome of the study was in-hospital mortality, whereas secondary outcomes were prolonged length of stay, mechanical ventilation, mechanical circulatory support, vasopressors use, and dispositions other than home. From 2016 to 2019, there were 4,705,274 HF hospitalizations, of which 16,955 (0.4%) had amyloid cardiomyopathy. In all HF hospitalizations, amyloid-related increased from 0.26% in 2016 to 0.46% in 2019 (relative increase, 76.9%, P for trend <0.001). Amyloid-related HF hospitalizations were more common in older, male, and Black patients. The odds of in-hospital mortality (odds ratio [OR], 1.29; 95% confidence interval [CI]: 1.11 to 1.38), prolonged hospital length (OR, 1.61; 95% CI: 1.49 to 1.73) and vasopressors use (OR, 1.59; 95% CI: 1.23 to 2.05) were significantly higher for amyloid-related hospitalizations. Amyloid-related HF hospitalizations are increasing substantially and are associated with adverse hospital outcomes. These hospitalizations were disproportionately higher for older, male, and Black patients. Amyloid-related HF is rare and underdiagnosed yet has several adverse outcomes. Hence, healthcare providers should be watchful of this condition for early identification and prompt management.

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.

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.

Recent Trends in Diabetes-Associated Hospitalizations in the United States.

The purpose of this study was to examine trends in diabetes-related hospitalizations over the period 2010 to 2019 using Nationwide Inpatient Sample (NIS) to facilitate informed policies regarding diabetes-related prevention and management. Between 2010 and 2019, there were 304 million hospitalizations above 18 years of age, of which 78 million were diabetes-associated hospitalizations. The overall population-adjusted diabetes hospitalizations significantly increased from 3079.0 to 3280.8 per 100,000 US population (relative increase, 6.6%, Ptrend < 0.028). Age-stratified analysis showed that hospitalizations significantly increased for 18−29 years (relative increase, 7.8%, Ptrend < 0.001) while age- and gender-stratified analysis showed that diabetes hospitalization significantly increased for 18−29-year males (relative increase, 18.1%, Ptrend < 0.001). Total hospitalization charge increased from 97.5 billion USD in 2010 to 132.0 billion USD in 2019 (relative increase, 35.4%, Ptrend < 0.001). Our study's findings suggest that diabetes-associated hospitalizations will continue to increase in the future because recent evidence indicates a reappearance of diabetes complications. It is important to screen, prevent, and control diabetes at a younger age based on the trends observed in our study.

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.

Effect of frailty on hospital outcomes among patients with cancer in the United States: Results from the National Inpatient Sample.

INTRODUCTION: To understand the effects of frailty on hospital outcomes such as in-hospital mortality, length of stay, and healthcare cost among patients with cancer using a nationally representative database. MATERIALS AND METHODS: This study was a retrospective observational analysis of Nationwide Inpatient Sample (NIS) data collected during 2005-2014. Participants included adult patients with cancer ≥45 years identified by International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes. 'Frail' versus 'non-frail' hospitalizations were determined using the Johns Hopkins Adjusted Clinical Groups (ACG) frailty-defining diagnosis indicator. Main outcome measures were in-hospital mortality, hospital length of stay, and hospitalization cost. We defined prolonged length of stay as hospital stay ≥75th percentile of the study sample. Propensity score match analysis was done to examine whether frailty was associated with length of stay and in-hospital mortality. RESULTS: There were 10,463,083 cancer hospitalizations during 2005-2014, of which 1,022,777 (9.8%) were frail. Patients having length of stay ≥8 days were significantly higher among frail group, compared to non-frail group (53.3% versus 25.3%, P < 0.001). Similarly, unadjusted mortality (12.0% versus 5.3%, P < 0.001) and hospitalization costs ($29,726 versus $18,595, P < 0.001) were significantly higher for frail patients. Nearly $28 billion was expended on hospitalization of frail patients with cancer during the study period. In propensity score match analysis, the odds of in-hospital mortality (odds ratio [OR], 1.54; 95% confidence interval [CI], 1.50-1.58) and length of stay (OR, 2.23; 95% CI, 2.18-2.27) were significantly greater for frail patients. DISCUSSION: Frailty was associated with adverse hospital outcomes such as increased length of stay, mortality, and hospitalization cost among all cancer types. Our findings could be valuable for frailty-based risk stratification of patients with cancer. Concerted efforts by the physiatrists, oncologists, and surgeons towards identifying frailty and incorporating it in risk estimation measures could help in optimizing management strategies for cancer.

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.

Obstetric outcomes during delivery hospitalizations among obese pregnant women in the United States.

The rates of both maternal and fetal adverse outcomes increase significantly with higher body mass index. The aim of this study was to calculate national estimates of adverse maternal and fetal outcomes and associated hospitalization cost among obese pregnant women using a national database. This study was a retrospective analysis of data retrieved from Nationwide Inpatient Sample database, collected during 2010-2014. The primary outcomes of this study were adverse maternal and fetal outcomes, hospital length of stay, and hospitalization cost. There was a total of 18,687,217 delivery-related hospitalizations, of which 1,048,323 were among obese women. Obese women were more likely to have cesarean deliveries (aOR 1.70, 95% CI 1.62-1.79) and labor inductions (aOR 1.51, 95% CI 1.42-1.60), greater length of stay after cesarean deliveries (aOR 1.14, 95% CI 1.08-1.36) and vaginal deliveries (aOR 1.48, 95% CI 1.23-1.77). They were also more likely to have pregnancy-related hypertension, preeclampsia, gestational diabetes, premature rupture of membranes, chorioamnionitis, venous thromboembolism, excessive fetal growth, and fetal distress. Obese pregnant women had significantly greater risk for adverse obstetrical outcomes, which substantially increased the hospital and economic burden. Risk stratification of pregnant patients based on obesity could also help obstetricians to make better clinical decisions and improve patient outcomes.

Stroke Genomics: Current Knowledge, Clinical Applications and Future Possibilities.

The pathophysiology of stoke involves many complex pathways and risk factors. Though there are several ongoing studies on stroke, treatment options are limited, and the prevalence of stroke is continuing to increase. Understanding the genomic variants and biological pathways associated with stroke could offer novel therapeutic alternatives in terms of drug targets and receptor modulations for newer treatment methods. It is challenging to identify individual causative mutations in a single gene because many alleles are responsible for minor effects. Therefore, multiple factorial analyses using single nucleotide polymorphisms (SNPs) could be used to gain new insight by identifying potential genetic risk factors. There are many studies, such as Genome-Wide Association Studies (GWAS) and Phenome-Wide Association Studies (PheWAS) which have identified numerous independent loci associated with stroke, which could be instrumental in developing newer drug targets and novel therapies. Additionally, using analytical techniques, such as meta-analysis and Mendelian randomization could help in evaluating stroke risk factors and determining treatment priorities. Combining SNPs into polygenic risk scores and lifestyle risk factors could detect stroke risk at a very young age and help in administering preventive interventions.

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.