Suppression of Fibrinolysis and Hypercoagulability, Severity of Hypoxemia, and Mortality in COVID-19 Patients: A Retrospective Cohort Study.

BACKGROUND: COVID-19 causes hypercoagulability, but the association between coagulopathy and hypoxemia in critically ill patients has not been thoroughly explored. This study hypothesized that severity of coagulopathy would be associated with acute respiratory distress syndrome severity, major thrombotic events, and mortality in patients requiring intensive care unit-level care. METHODS: Viscoelastic testing by rotational thromboelastometry and coagulation factor biomarker analyses were performed in this prospective observational cohort study of critically ill COVID-19 patients from April 2020 to October 2020. Statistical analyses were performed to identify significant coagulopathic biomarkers such as fibrinolysis-inhibiting plasminogen activator inhibitor 1 and their associations with clinical outcomes such as mortality, extracorporeal membrane oxygenation requirement, occurrence of major thrombotic events, and severity of hypoxemia (arterial partial pressure of oxygen/fraction of inspired oxygen categorized into mild, moderate, and severe per the Berlin criteria). RESULTS: In total, 53 of 55 (96%) of the cohort required mechanical ventilation and 9 of 55 (16%) required extracorporeal membrane oxygenation. Extracorporeal membrane oxygenation-naïve patients demonstrated lysis indices at 30 min indicative of fibrinolytic suppression on rotational thromboelastometry. Survivors demonstrated fewer procoagulate acute phase reactants, such as microparticle-bound tissue factor levels (odds ratio, 0.14 [0.02, 0.99]; P = 0.049). Those who did not experience significant bleeding events had smaller changes in ADAMTS13 levels compared to those who did (odds ratio, 0.05 [0, 0.7]; P = 0.026). Elevations in plasminogen activator inhibitor 1 (odds ratio, 1.95 [1.21, 3.14]; P = 0.006), d-dimer (odds ratio, 3.52 [0.99, 12.48]; P = 0.05), and factor VIII (no clot, 1.15 ± 0.28 vs. clot, 1.42 ± 0.31; P = 0.003) were also demonstrated in extracorporeal membrane oxygenation-naïve patients who experienced major thrombotic events. Plasminogen activator inhibitor 1 levels were significantly elevated during periods of severe compared to mild and moderate acute respiratory distress syndrome (severe, 44.2 ± 14.9 ng/ml vs. mild, 31.8 ± 14.7 ng/ml and moderate, 33.1 ± 15.9 ng/ml; P = 0.029 and 0.039, respectively). CONCLUSIONS: Increased inflammatory and procoagulant markers such as plasminogen activator inhibitor 1, microparticle-bound tissue factor, and von Willebrand factor levels are associated with severe hypoxemia and major thrombotic events, implicating fibrinolytic suppression in the microcirculatory system and subsequent micro- and macrovascular thrombosis in severe COVID-19.

Rationale and design of the Prone Position and Respiratory Outcomes in Non-intubated COVID-19 PatiEnts: The "PRONE" Study.

While benefits of prone position in mechanically-ventilated patients have been well-described, a randomized-control trial to determine the effects of prone positioning in awake, spontaneously-breathing patients with an acute pneumonia has not been previously conducted. Prone Position and Respiratory Outcomes in Non-Intubated COVID-19 PatiEnts: the "PRONE" Study (PRONE) was conducted in non-intubated hospitalized patients with coronavirus disease 2019 (COVID-19) pneumonia as defined by respiratory rate ≥ 20/min or an oxyhemoglobin saturation (SpO2) ≤ 93% without supplemental oxygen [1]. The PRONE trial was designed to investigate the effects of prone positioning on need for escalation in respiratory support, as defined by need for transition to a higher acuity level of care, increased fraction of inspired oxygen (FiO2), or the initiation of invasive mechanical ventilation. Secondary objectives were to assess the duration of effect of prone positioning on respiratory parameters such as respiratory rate and SpO2, as well as other outcomes such as time to discharge or transition in level of care.

Impact of diagnosis code grouping method on clinical prediction model performance: A multi-site retrospective observational study.

OBJECTIVE: The primary purpose of this work is to systematically assess the performance trade-offs on clinical prediction tasks of four diagnosis code groupings: AHRQ-Elixhauser, Single-level CCS, truncated ICD-9-CM codes, and raw ICD-9-CM codes. MATERIALS AND METHODS: We used two distinct datasets from different geographic regions and patient populations and train models for three prediction tasks: 1-year mortality following an ICU stay, 30-day mortality following surgery, and 30-day complication following surgery. We run multiple commonly-used binary classification models including penalized logistic regression, random forest, and gradient boosted trees. Model performance is evaluated using the Area Under the Receiver Operating Characteristic (AUROC) and the Area Under the Precision-Recall Curve (AUCPR). RESULTS: Single-level CCS, truncated codes, and raw codes significantly outperformed AHRQ-Elixhauser ICD grouping when predicting 30-day postoperative complication and one-year mortality after ICU admission. The performance across groupings was more similar in the 30-day postoperative mortality prediction task. DISCUSSION: Single-level CCS groupings represent aggregations of raw codes into meaningful clinical concepts and consistently balance interoperability between ICD-9-CM and ICD-10-CM while maintaining strong model performance as measured by AUROC and AUCPR. Key limitations include experimentation across two datasets and three prediction tasks, which although were well labeled and sufficiently prevalent, do not encompass all modeling tasks and outcomes. CONCLUSION: Single-level CCS groupings may serve as a good baseline for future models that incorporate diagnosis codes as features in clinical prediction tasks. Code and a compute environment summary are provided along with the analyses to enable reproducibility and to support future research.

Wide range of perioperative drugs and doses used in inguinal hernia repairs for premature infants.

OBJECTIVE: Characterize the types and doses of commonly administered perioperative drugs in inguinal hernia (IH) repair for premature infants. STUDY DESIGN: Single-center, retrospective cohort study. RESULTS: In total, 112 premature infants underwent IH repair between 2010 and 2015. Twenty-one drugs were used during IH repair, with each infant receiving a median seven drugs. Acetaminophen (88%), bupivacaine (84%), cisatracurium (74%), sevoflurane (72%), and propofol (71%) were the most commonly used agents. Thirty-two infants underwent additional procedures with IH repair. Additional procedures were not associated with a higher number of perioperative drugs, however infants with additional procedures were exposed to higher cumulative doses of cisatracurium (p < 0.001) and fentanyl (p = 0.002). CONCLUSION: There is wide variability in the drugs and doses used for a common surgical procedure in this population, even within a single center. Future research should focus on the safety and efficacy of the most commonly used perioperative drugs described in this study.

Machine learning for early detection of sepsis: an internal and temporal validation study.

OBJECTIVE: Determine if deep learning detects sepsis earlier and more accurately than other models. To evaluate model performance using implementation-oriented metrics that simulate clinical practice. MATERIALS AND METHODS: We trained internally and temporally validated a deep learning model (multi-output Gaussian process and recurrent neural network [MGP-RNN]) to detect sepsis using encounters from adult hospitalized patients at a large tertiary academic center. Sepsis was defined as the presence of 2 or more systemic inflammatory response syndrome (SIRS) criteria, a blood culture order, and at least one element of end-organ failure. The training dataset included demographics, comorbidities, vital signs, medication administrations, and labs from October 1, 2014 to December 1, 2015, while the temporal validation dataset was from March 1, 2018 to August 31, 2018. Comparisons were made to 3 machine learning methods, random forest (RF), Cox regression (CR), and penalized logistic regression (PLR), and 3 clinical scores used to detect sepsis, SIRS, quick Sequential Organ Failure Assessment (qSOFA), and National Early Warning Score (NEWS). Traditional discrimination statistics such as the C-statistic as well as metrics aligned with operational implementation were assessed. RESULTS: The training set and internal validation included 42 979 encounters, while the temporal validation set included 39 786 encounters. The C-statistic for predicting sepsis within 4 h of onset was 0.88 for the MGP-RNN compared to 0.836 for RF, 0.849 for CR, 0.822 for PLR, 0.756 for SIRS, 0.619 for NEWS, and 0.481 for qSOFA. MGP-RNN detected sepsis a median of 5 h in advance. Temporal validation assessment continued to show the MGP-RNN outperform all 7 clinical risk score and machine learning comparisons. CONCLUSIONS: We developed and validated a novel deep learning model to detect sepsis. Using our data elements and feature set, our modeling approach outperformed other machine learning methods and clinical scores.

Real-World Integration of a Sepsis Deep Learning Technology Into Routine Clinical Care: Implementation Study.

BACKGROUND: Successful integrations of machine learning into routine clinical care are exceedingly rare, and barriers to its adoption are poorly characterized in the literature. OBJECTIVE: This study aims to report a quality improvement effort to integrate a deep learning sepsis detection and management platform, Sepsis Watch, into routine clinical care. METHODS: In 2016, a multidisciplinary team consisting of statisticians, data scientists, data engineers, and clinicians was assembled by the leadership of an academic health system to radically improve the detection and treatment of sepsis. This report of the quality improvement effort follows the learning health system framework to describe the problem assessment, design, development, implementation, and evaluation plan of Sepsis Watch. RESULTS: Sepsis Watch was successfully integrated into routine clinical care and reshaped how local machine learning projects are executed. Frontline clinical staff were highly engaged in the design and development of the workflow, machine learning model, and application. Novel machine learning methods were developed to detect sepsis early, and implementation of the model required robust infrastructure. Significant investment was required to align stakeholders, develop trusting relationships, define roles and responsibilities, and to train frontline staff, leading to the establishment of 3 partnerships with internal and external research groups to evaluate Sepsis Watch. CONCLUSIONS: Machine learning models are commonly developed to enhance clinical decision making, but successful integrations of machine learning into routine clinical care are rare. Although there is no playbook for integrating deep learning into clinical care, learnings from the Sepsis Watch integration can inform efforts to develop machine learning technologies at other health care delivery systems.

Pulmonary Valve Endocarditis: The Potential Utility of Multimodal Imaging Prior to Surgery.

BACKGROUND: The presence of echocardiographic (echo) evidence is a major criterion for the diagnosis of infective endocarditis (IE) by modified Duke criteria. Pulmonary valve (PV) IE, however, can be challenging to identify by echo. We sought to evaluate the added utility of multimodal imaging in PV IE. METHODS: This is a single-center case series. We retrospectively analyzed demographic, laboratory, imaging, clinical, and surgical data from patients diagnosed with PV IE from 2008 to 2018. RESULTS: A total of 23 patients were identified with definite PV IE by Duke criteria (83% male and ages 2 months to 70 years). Twenty-two patients had congenital heart disease, with 21 involving the right ventricular outflow tract (including three with transcatheter PV implant). Overall, 20 (87%) of 23 had positive blood cultures. A total of 17 (74%) of 23 patients demonstrated echo evidence of PV IE. In three cases, echo was negative (did not show vegetations) but showed new PV obstruction. In four cases with negative transthoracic echocardiogram and transesophageal echocardiogram, evidence of PV IE was subsequently seen by positron emission tomography/computed tomography (n = 2) or cardiac magnetic resonance imaging (n = 2). Pulmonary valve IE was confirmed at surgery by evaluation of pathologic samples in 20 cases. CONCLUSIONS: Multimodal imaging improves the ability to preoperatively identify endocardial involvement in PV IE in cases where echo is negative. Consideration should be given to revise Duke criteria to include new obstruction and endocardial involvement by multimodal imaging for PV IE.

Racial and Socioeconomic Factors Associated with the Use of Complementary and Alternative Modalities for Pain in Cancer Outpatients: An Integrative Review.

OBJECTIVES: Racial and ethnic disparities in pain management are widely documented in the United States. The 2016 Centers for Disease Control and Prevention (CDC) guidelines for opioid prescribing have generated new imperatives for using complementary and alternative medicine approaches (CAM) to manage chronic pain, including cancer pain. This review's purpose was to explore the prevalence of CAM use for cancer-related pain among racial and ethnic minorities and to organize these findings according to the CAM modalities proposed by the National Center for Complementary and Integrative Health (NCCIH). DESIGN: An integrative review of the literature published between 2007 and 2017. DATA SOURCES: PubMed and SCOPUS databases (2007-2017). REVIEW/ANALYSIS METHODS: Articles were included if they engaged in explicit analysis of racial or ethnic differences in CAM use for cancer pain in the outpatient setting, yielding 13 articles for final analysis. RESULTS AND CONCLUSIONS: Overall, CAM use for any modality ranged from 51% to 83%. Mind-body therapies were reported most, and energy therapies the least. Differences in CAM use were most often attributable to socioeconomic status (SES), with those of higher SES associated with greater use of practitioner-assisted CAM therapies and those of lower SES with greater use of free therapies. This difference has implications for achieving adequate and consistent pain relief among subgroups of patients with cancer. This review also identifies a literature gap regarding racial/ethnic disparities in access to CAM for cancer pain, and a need for validated measures to assess CAM use.

Assessing Quality of Surgical Real-World Data from an Automated Electronic Health Record Pipeline.

BACKGROUND: Significant analysis errors can be caused by nonvalidated data quality of electronic health records data. To determine surgical data fitness, a framework of foundational and study-specific data analyses was adapted and assessed using conformance, completeness, and plausibility analyses. STUDY DESIGN: Electronic health records-derived data from a cohort of 241,695 patients undergoing 412,182 procedures from October 1, 2014 to August 31, 2018 at 3 hospital sites was evaluated. Data quality analyses tested CPT codes, medication administrations, vital signs, provider notes, labs, orders, diagnosis codes, medication lists, and encounters. RESULTS: Foundational checks showed that all encounters had procedures within the inclusion period, all admission dates occurred before discharge dates, and race was missing for 1% of patients. All procedures had associated CPT codes, 69% had recorded blood pressure, pulse, temperature, respiration rate, and oxygen saturation. After curation, all medication matched RxNorm medication naming standards, 84% of procedures had current outpatient medication lists, and 15% of procedures had missing procedure notes. Study-specific checks temporally validated CPT codes, intraoperative medication doses were in conventional units, and of the 13,500 patients who received blood pressure medication intraoperatively, 93% had a systolic blood pressure >140 mmHg. All procedure notes were completed within less than 30 days of the procedure and 93% of patients after total knee arthroplasty had postoperative physical therapy notes. All patients with postoperative troponin-T lab values ≥0.10 ng/mL had more than 1 ECG with relevant diagnoses. Postoperative opioid prescription decreased by 8.8% and nonopioid use increased by 8.8%. CONCLUSIONS: High levels of conformance, completeness, and clinical plausability demonstrate higher quality of real-world data fitness and low levels demonstrate less-fit-for-use data.

Predictors of psychological distress and sleep quality in former family caregivers of people with dementia.

Objectives: The stress-related psychological symptoms experienced by informal family caregivers do not always improve or resolve after the death of the care recipient. The purpose of this study was to explore the independent associations of sociodemographic variables, personality and coping, environmental variables, and caregiver guilt with the sleep quality and psychological distress of former family caregivers of individuals with dementia following care recipient's death.Method: A cross-sectional, correlational study was conducted with a sample of 171 former family caregivers of people with dementia. Participants completed an online survey comprised of six instruments and demographic items. Caregiver personal variables (e.g. personality and coping), environmental variables, guilt, psychological distress (depressive and anxiety symptoms), and sleep quality were evaluated using psychometrically validated measures.Results: In bivariate analysis, post-caregiving guilt was significantly associated with depressive and anxiety symptoms (p < 0.01). After controlling for covariates, dysfunctional coping and neuroticism explained 32% of the variance in depressive symptoms (R2 = .52, ΔR2 = .32, F(5, 165) = 36.24, p < .001) and 24% of the variance in anxiety symptoms (R2 = .41, ΔR2 = .24, F(5, 165) = 22.65, p < .001), while dysfunctional coping, pre-loss depression, and extraversion accounted for 16% of the variance in sleep quality (R2 = .30, ΔR2 = .16, F(6, 164) = 11.44, p < .001).Conclusion: This study demonstrates the critical role of personal variables, including personality traits, coping strategies, and pre-loss depression, in explaining psychological distress and sleep quality in this sample of former dementia caregivers.

Associations Among End-of-Life Discussions, Health-Care Utilization, and Costs in Persons With Advanced Cancer: A Systematic Review.

BACKGROUND: Aggressive end-of-life (EOL) care is associated with lower quality of life and greater regret about treatment decisions. Higher EOL costs are also associated with lower quality EOL care. Advance care planning and goals-of-care conversations ("EOL discussions") may influence EOL health-care utilization and costs among persons with cancer. OBJECTIVE: To describe associations among EOL discussions, health-care utilization and place of death, and costs in persons with advanced cancer and explore variation in study measures. METHODS: A systematic review was conducted using PubMed, Embase, and CINAHL. Twenty quantitative studies published between January 2012 and January 2019 were included. RESULTS: End-of-life discussions are associated with lower health-care costs in the last 30 days of life (median US$1048 vs US$23482; P < .001); lower likelihood of acute care at EOL (odds ratio [(OR] ranging 0.43-0.69); lower likelihood of intensive care at EOL (ORs ranging 0.26-0.68); lower odds of chemotherapy near death (ORs 0.41, 0.57); lower odds of emergency department use and shorter length of hospital stay; greater use of hospice (ORs ranging 1.79 to 6.88); and greater likelihood of death outside the hospital. Earlier EOL discussions (30+ days before death) are more strongly associated with less aggressive care outcomes than conversations occurring near death. CONCLUSIONS: End-of-life discussions are associated with less aggressive, less costly EOL care. Clinicians should initiate these discussions with patients having cancer earlier to better align care with preferences.

The relationship between impaired control, impulsivity, and alcohol self-administration in nondependent drinkers.

Impaired control over drinking is a significant marker of alcohol use disorder (AUD), and a potential target of intervention (Heather, Tebbutt, Mattick, & Zamir, 1993; Leeman, Toll, Taylor, & Volpicelli, 2009). Impaired control may be related to, but conceptually distinct from, impulsivity (Leeman, Patock-Peckham, & Potenza, 2012; Leeman, Ralevski, et al., 2014). However, the relationship between impaired control, impulsivity, and alcohol consumption, particularly in nondependent drinkers is less clear. This study aimed to characterize these relationships using a free-access intravenous alcohol self-administration (IV-ASA) paradigm in nondependent drinkers (N = 48). Results showed individuals with higher self-reported impaired control achieved higher blood alcohol concentrations (BAC) during the IV-ASA session and reported greater hedonic subjective responses to alcohol. Higher impaired control was also associated with greater positive urgency and reward sensitivity. Moderated-mediation analysis showed that the relationship between positive urgency and peak BAC was mediated by impaired control, and partially moderated by subjective alcohol response. These findings highlight the critical role of impaired control over drinking on alcohol consumption and subjective responses in nondependent drinkers. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Utilizing Internet-based recruitment and data collection to access different age groups of former family caregivers.

As Internet accessibility grows among adults in the United States, researchers' utilization of Internet-based surveys and recruitment strategies has increased, but there is a paucity of knowledge about their use in different age groups of former dementia caregivers. The purpose of this secondary analysis is to describe 1) the use of Internet-based recruitment in obtaining a sample inclusive of young and middle aged (age 18-64), young-old (age 65-74), and older-old (age 75 and older) former dementia caregivers and 2) the feasibility of collecting data using an online survey in young and middle aged, young-old, and older-old former dementia caregivers. Utilizing convenience sampling, a four-step recruitment strategy encompassing a combination of Internet-based and non-Internet-based recruitment strategies was employed. Participants (N = 171) completed an online survey. Older-old, young-old, and young and middle-aged participants comprised 9%, 30%, and 61% of the sample respectively. All age cohorts provided minimal missing data using an online survey, but older-old participants required 15 additional minutes to complete the survey than young-old participants. Both cohorts of older adults were directed to the survey less frequently through online referral sources than young and middle-aged participants, and no older-old participants were referred via Facebook. All three age cohorts consisted of mostly white women. Internet-based surveys and recruitment were feasible among the age groups but may present challenges for the older-old and minorities. Further research on Internet-based data collection and recruitment is indicated in minority and older-old caregivers, focusing on trust, educational and financial disparities, and technological proficiency as potential barriers.

Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): A retrospective, single-site study.

BACKGROUND: Pythia is an automated, clinically curated surgical data pipeline and repository housing all surgical patient electronic health record (EHR) data from a large, quaternary, multisite health institute for data science initiatives. In an effort to better identify high-risk surgical patients from complex data, a machine learning project trained on Pythia was built to predict postoperative complication risk. METHODS AND FINDINGS: A curated data repository of surgical outcomes was created using automated SQL and R code that extracted and processed patient clinical and surgical data across 37 million clinical encounters from the EHRs. A total of 194 clinical features including patient demographics (e.g., age, sex, race), smoking status, medications, comorbidities, procedure information, and proxies for surgical complexity were constructed and aggregated. A cohort of 66,370 patients that had undergone 99,755 invasive procedural encounters between January 1, 2014, and January 31, 2017, was studied further for the purpose of predicting postoperative complications. The average complication and 30-day postoperative mortality rates of this cohort were 16.0% and 0.51%, respectively. Least absolute shrinkage and selection operator (lasso) penalized logistic regression, random forest models, and extreme gradient boosted decision trees were trained on this surgical cohort with cross-validation on 14 specific postoperative outcome groupings. Resulting models had area under the receiver operator characteristic curve (AUC) values ranging between 0.747 and 0.924, calculated on an out-of-sample test set from the last 5 months of data. Lasso penalized regression was identified as a high-performing model, providing clinically interpretable actionable insights. Highest and lowest performing lasso models predicted postoperative shock and genitourinary outcomes with AUCs of 0.924 (95% CI: 0.901, 0.946) and 0.780 (95% CI: 0.752, 0.810), respectively. A calculator requiring input of 9 data fields was created to produce a risk assessment for the 14 groupings of postoperative outcomes. A high-risk threshold (15% risk of any complication) was determined to identify high-risk surgical patients. The model sensitivity was 76%, with a specificity of 76%. Compared to heuristics that identify high-risk patients developed by clinical experts and the ACS NSQIP calculator, this tool performed superiorly, providing an improved approach for clinicians to estimate postoperative risk for patients. Limitations of this study include the missingness of data that were removed for analysis. CONCLUSIONS: Extracting and curating a large, local institution's EHR data for machine learning purposes resulted in models with strong predictive performance. These models can be used in clinical settings as decision support tools for identification of high-risk patients as well as patient evaluation and care management. Further work is necessary to evaluate the impact of the Pythia risk calculator within the clinical workflow on postoperative outcomes and to optimize this data flow for future machine learning efforts.

When Caregiving Ends: The Experiences of Former Family Caregivers of People With Dementia.

PURPOSE OF THE STUDY: Numerous adverse physiological and psychological effects of family caregiving are documented in the literature. However, there is little knowledge about family caregivers after caregiving ends. The purpose of this study is to examine the health of former family caregivers and describe their experiences following the death of a care recipient with dementia. METHODS: Eight former family caregivers were recruited using convenience sampling. Each caregiver participated in one semi-structured interview ranging from 45 minutes to 3 hours in length. The interviews were audio recorded and transcribed for qualitative content analysis. RESULTS: Three overarching themes emerged from the data: (a) sleep disturbances, (b) changes in health status, and (c) learning to live again. Despite relief from caregiving duties, sleep disturbances in former family caregivers persisted for as long as 10 years post-caregiving. Caregivers reported changes in health such as acute health crises, ongoing illness, or a cascade of nonacute illnesses. Caregivers illustrated post-caregiving as a process of learning to live again, characterized by initial uncertainty about how to proceed in life and a reluctance to relinquish caregiving after years of identifying with the caregiver role. IMPLICATIONS: The results of this study suggest that there may be long-term effects of caregiving on health that persist well beyond the first year post-caregiving. Former caregivers would benefit from further research on the physical and psychological health of former caregivers after the first year of post-caregiving, the role of triggering events during post-caregiving, and interventions to meet the needs of former caregivers.

An exploration of caregiver choice through the lens of Sartrean existentialism.

There are innumerable social and ethical factors which affect one's decision to become an informal caregiver for someone with chronic illness. The existential philosophy of Jean-Paul Sartre provides unique insight into human motivation and choice. The purpose of this paper was to examine the social and ethical influences on the individual's decision to become a caregiver through the lens of Sartrean existentialism and discuss how this unique philosophy can advance nursing knowledge. The factors affecting one's choice to become a caregiver were considered using the Sartrean existential concepts of The Other, human freedom, choice, bad faith, shame and authenticity. When explored through the perspective of Sartrean existentialism, the choice to become a caregiver is strongly influenced by fear of judgement from The Other and the resulting sense of social obligation and shame. However, the interaction with The Other often results in the loss of authenticity through the pursuit of bad faith. To avert bad faith, potential caregivers must act authentically by exercising their freedom to choose and by choosing an action for its own sake and not for some extraneous purpose. The results of this philosophical inquiry contribute to nursing knowledge by providing a unique, alternative perspective by which nurses may understand the choices of potential caregivers and support them in making authentic decisions. This perspective may provide a foundation for theory development and promote further nursing knowledge which will improve caregiver health and well-being.

Clinical outcomes in very low birth weight infants with major congenital heart defects.

BACKGROUND: The combination of major congenital heart disease (CHD) and prematurity is associated with poor prognosis, but previous studies have not fully characterized morbidity and mortality in this population. We conducted a retrospective cohort study of very low birth weight (VLBW) infants with major CHD to describe outcomes, including mortality, over time. METHODS: We included all infants <1500 g birth weight with major CHD discharged from Pediatrix Medical Group neonatal intensive care units from 1997 to 2012. We report incidences of major CHD in VLBW infants and compare mortality and morbidity by infant birth weight, type of major CHD, and time period. RESULTS: Of 105,539 VLBW infants, 299 (0.3%) were diagnosed with 15 different major CHDs. Coarctation of the aorta (n=67, 22%), atrioventricular septal defect (n=58, 19%), and tetralogy of Fallot (n=53, 18%) were the most common major CHDs identified. Overall mortality was 163/299 (55%). Mortality was ≥70% for 10 lesions and <30% for isolated aortic valve stenosis (6/30, 20%). Mortality in infants with major CHD did not significantly change over time: 76/133 (57%) in 1997-2005, 49/95 (52%) in 2006-2009, and 38/71 (54%) in 2010-2012 (p=0.70). The majority of infants suffered ≥1 comorbidity or died (218/299, 73%). CONCLUSION: Major CHD is associated with high morbidity and mortality. While mortality varies by lesion, overall survival and incidence of major morbidity have not improved over time.

Frequency of anomalies and hospital outcomes in infants with gastroschisis and omphalocele.

BACKGROUND: Gastroschisis and omphalocele are the most common anterior abdominal wall defects affecting infants. There are few large cohort studies describing the frequency of associated anomalies in infants with these 2 conditions. We describe associated anomalies and outcomes in infants with these defects using a large, multi-center clinical database. METHODS: We identified all infants with gastroschisis or omphalocele from a prospectively collected database of infants discharged from 348 neonatal intensive care units in North America from 1997 to 2012. Maternal and patient demographic data, associated anomalies, and outcome data were compared between infants with gastroschisis and omphalocele. RESULTS: A total of 4687 infants with gastroschisis and 1448 infants with omphalocele were identified. Infants with omphalocele were more likely to be diagnosed with at least 1 other anomaly compared with infants with gastroschisis (35% vs. 8%, p<0.001). Infants with omphalocele were more likely to develop pulmonary hypertension compared with those with gastroschisis (odds ratio [OR] 7.78; 95% confidence interval 5.81, 10.41) and had higher overall mortality (OR 6.81 [5.33, 8.71]). CONCLUSION: Infants with omphalocele were more likely to have other anomalies, be diagnosed with pulmonary hypertension, and have higher mortality than infants with gastroschisis.

Vaccine counseling: a content analysis of patient-physician discussions regarding human papilloma virus vaccine.

OBJECTIVES: (1) Describe content and character of patient-physician human papilloma virus (HPV) vaccine discussions; (2) explore the relationship between selected characteristics and vaccine uptake. METHODS: Content analyses were conducted on 184 transcripts of audio-taped patient encounters with 11-26 year old female patients that occurred from August 2008 to March 2009 and contained mention of the HPV vaccine. Directed qualitative content analysis sought to identify key themes with a focus on elements related to communication. Quantitative content analysis included determination of associations between selected factors (e.g., physician specialty, communication variables, patient age) and vaccination rates. RESULTS: Communication themes identified though qualitative content analysis demonstrated potential opportunities for improvement in vaccine communication were identified. Quantitative content analysis showed twenty-eight percent of eligible patients received HPV vaccine and on average these patients were younger (17.0 vs. 19.6 years). The youngest and oldest patients were vaccinated less frequently. CONCLUSIONS: Targeting age groups with lower vaccination rates may increase overall vaccine uptake. Additional quantitative analyses of patient-physician discussions about vaccine may generate further recommendations regarding optimal communication strategies for HPV vaccine counseling.