Physical Restraint Use in Hospitalized Patients: A Study of Routinely Collected Health Records Data.

BACKGROUND: The use of restraints in hospitalized patients is associated with physical and psychological adversity for patients and staff. The minimization of restraint use is a key goal in the hospital setting. Reaching this goal requires an accurate assessment of existing patterns of use across clinical settings. OBJECTIVE: This study reports the rate of physical restraints among patients hospitalized within a multi-entity healthcare network along with stratification by care context, diagnostic, and demographic factors, and examines the sensitivity and specificity of ICD-10 code Z78.1 "physical restraint status" for defining physical restraints relative to electronic health record (EHR) documentation. DESIGN: The EHR was used for a retrospective analysis of all adults hospitalized between 2017 and 2022. PARTICIPANTS: Hospitalized adults. MAIN MEASURES: Patient demographics, structured diagnostic information, care area, length of stay, and in-hospital mortality, Z78.1 coding for physical restraints, restraint documentation in orders and flowsheets. KEY RESULTS: Among 742,607 hospitalizations, 6.3% (n=47,041) involved the use of physical restraint based on coding or EHR documentation. Treatment in the intensive care unit (ICU) included restraint in 39% of encounters whereas treatment outside the ICU included restraint use in 1.3% of encounters. Besides critical illness, demographic factors including increasing age (adjusted odds ratio (aOR)=1.21 [1.19-1.23]), male gender (aOR=1.56, [1.52-1.60]), unknown race (aOR=1.27 [1.19-1.35]), and preferred language other than English (aOR=1.24, [1.18-1.29]) were associated with higher odds of restraint utilization. As compared to EHR orders or documentation of restraint, the ICD-10 code for physical restraint had a sensitivity of 1.5% and a specificity of 99.99%. CONCLUSION: Among adults admitted to acute care hospitals, clinical, demographic, and operational factors were associated with increased odds of restraint, with care in the ICU associated with greatly increased odds of restraint. Research into restraint utilization using coded administrative claims data is likely limited by the sensitivity of physical restraint coding.

Neutron and X-ray Scattering Characterization of Silica Nanoparticle-Stabilized Polymer Hybrid Latex Particles.

A robust route to produce poly(methyl methacrylate) (pMMA) hybrid latex particles (radius ∼250 nm) that are selectively "armored" with silica nanoparticles (radius 12.5 nm) through addition of vinyltriethoxysilane was previously shown ( J. Colloid Interface Sci. 2018, 528, 289-300).Depending on synthesis conditions, the extent of nanoparticle attachment could be varied; however, the mechanism behind this attachment during latex growth remained unclear. The dual population of particles present (silica + polymer) means that particle sizing by dynamic light scattering is ambiguous. Furthermore, the low glass transition temperature (Tg) of polymers such as poly(butyl acrylate) (pBA) typically used in film-forming applications for decorative coatings (i.e., paints) means that the hybrid latex particles are too "soft" for robust analysis through atomic force microscopy (AFM) and scanning electron microscopy (SEM). Here, we show that small- and ultrasmall-angle neutron scattering (SANS and USANS), along with complementary data from small-angle X-ray scattering (SAXS), reveals that these armored hybrid latex particles adopt a raspberry-type configuration, supporting their core-shell structure. The number of nanoparticles present on the surface of the hybrid latex can be adjusted by addition of one of a diverse range of alkyl- or perfluoroalkyl-silanes to alter silica nanoparticle hydrophobicity, and quantified through analysis of scattering data. The approach therefore provides a novel, nonperturbative, and in situ method of quantifying nanoparticle attachment to polymer latex particles.

Comparing survival of older ovarian cancer patients treated with neoadjuvant chemotherapy versus primary cytoreductive surgery: Reducing bias through machine learning.

OBJECTIVE: To develop and evaluate a multidimensional comorbidity index (MCI) that identifies ovarian cancer patients at risk of early mortality more accurately than the Charlson Comorbidity Index (CCI) for use in health services research. METHODS: We utilized SEER-Medicare data to identify patients with stage IIIC and IV ovarian cancer, diagnosed in 2010-2015. We employed partial least squares regression, a supervised machine learning algorithm, to develop the MCI by extracting latent factors that optimally captured the variation in health insurance claims made in the year preceding cancer diagnosis, and 1-year mortality. We assessed the discrimination and calibration of the MCI for 1-year mortality and compared its performance to the commonly-used CCI. Finally, we evaluated the MCI's ability to reduce confounding in the association of neoadjuvant chemotherapy (NACT) and all-cause mortality. RESULTS: We included 4723 patients in the development cohort and 933 in the validation cohort. The MCI demonstrated good discrimination for 1-year mortality (c-index: 0.75, 95% CI: 0.72-0.79), while the CCI had poor discrimination (c-index: 0.59, 95% CI: 0.56-0.63). Calibration plots showed better agreement between predicted and observed 1-year mortality risk for the MCI compared with CCI. When comparing all-cause mortality between NACT with primary cytoreductive surgery, NACT was associated with a higher hazard of death (HR: 1.13, 95% CI: 1.04-1.23) after controlling for tumor characteristics, demographic factors, and the CCI. However, when controlling for the MCI instead of the CCI, there was no longer a significant difference (HR: 1.05, 95% CI: 0.96-1.14). CONCLUSIONS: The MCI outperformed the conventional CCI in predicting 1-year mortality, and reducing confounding due to differences in baseline health status in comparative effectiveness analysis of NACT versus primary surgery.

Implications of childhood adversity for women's perinatal sleep quality and depressive symptoms over time: A serial mediation model.

This study sought to examine the effects of childhood adversity on the longitudinal associations between perinatal sleep quality and depressive symptoms, and to determine the prospective associations between these constructs over time. A cross-lagged autoregressive model was used to examine the longitudinal association between sleep quality and depressive symptoms at four points during the perinatal period: 18 and 32 weeks of pregnancy, and 6 and 12 weeks postpartum. Longitudinal mediation models were used to examine whether sleep quality or depressive symptoms mediated the effects of childhood adversity on these symptoms. Most participants (86%) reported poor sleep quality during pregnancy. Significant cross-lagged effects of depressive symptoms on subsequent sleep quality were observed during pregnancy and postpartum. Depressive symptoms significantly mediated the effects of childhood trauma on sleep quality during pregnancy, but sleep quality did not significantly mediate the effects of childhood trauma on depressive symptoms. While sleep quality and depressive symptoms tend to co-occur, our analyses indicate that perinatal depressive symptoms work as the primary driver of sleep quality over time. Childhood adversity may have long-reaching effects in women as it was associated with more depressive symptoms in the perinatal period, which in turn appeared to undermine sleep quality.

Performance of a Maternal Risk Stratification System for Predicting Low Apgar Scores.

OBJECTIVE: Maternal risk stratification systems are increasingly employed in predicting and preventing obstetric complications. These systems focus primarily on maternal morbidity, and few tools exist to stratify neonatal risk. We sought to determine if a maternal risk stratification score was associated with neonatal morbidity. STUDY DESIGN: Retrospective cohort study of patients with liveborn infants born at ≥24 weeks at four hospitals in one health system between January 1, 2020, and December 31, 2020. The Expanded Obstetric Comorbidity Score (EOCS) is used as the maternal risk score. The primary neonatal outcome was 5-minute Apgar <7. Logistic regression models determined associations between EOCS and neonatal morbidity. Secondary analyses were performed, including stratifying outcomes by gestational age and limiting analysis to "low-risk" term singletons. Model discrimination assessed using the area under the receiver operating characteristic curves (AUC) and calibration via calibration plots. RESULTS: A total of 14,497 maternal-neonatal pairs were included; 236 (1.6%) had 5-minute Apgar <7; EOCS was higher in 5-minute Apgar <7 group (median 41 vs. 11, p < 0.001). AUC for EOCS in predicting Apgar <7 was 0.72 (95% Confidence Interval (CI) 0.68, 0.75), demonstrating relatively good discrimination. Calibration plot revealed that those in the highest EOCS decile had higher risk of neonatal morbidity (7.6 vs. 1.7%, p < 0.001). When stratified by gestational age, discrimination weakened with advancing gestational age: AUC 0.70 for <28 weeks, 0.63 for 28 to 31 weeks, 0.64 for 32 to 36 weeks, and 0.61 for ≥37 weeks. When limited to term low-risk singletons, EOCS had lower discrimination for predicting neonatal morbidity and was not well calibrated. CONCLUSION: A maternal morbidity risk stratification system does not perform well in most patients giving birth, at low risk for neonatal complications. The findings suggest that the association between EOCS and 5-minute Apgar <7 likely reflects a relationship with prematurity. This study cautions against intentional or unintentional extrapolation of maternal morbidity risk for neonatal risk, especially for term deliveries. KEY POINTS: · EOCS had moderate discrimination for Apgar <7.. · Predictive performance declined when limited to low-risk term singletons.. · Relationship between EOCS and Apgar <7 was likely driven by prematurity..

Gender Representation in the ECT Workforce in the United States From 2013 to 2021: A Medicare Physician Data Analysis.

OBJECTIVES: Electroconvulsive therapy (ECT) is an effective treatment for a range of psychiatric disorders. Although much research has examined what patients receive ECT, there is less research describing those physicians who provide ECT services. This study examines the ECT workforce in the United States by analyzing publicly available Medicare billing records. METHODS: Data regarding the providers performing ECT were accessed from the Medicare Physician and Other Supplier Data for the years 2013 through 2021 based on those physicians who billed the ECT procedural code 90870. RESULTS: During the study period, 1402 physicians performed ECT in at least 1 calendar year on a minimum of 11 Medicare beneficiaries, representing 3.9% of the 36,116 psychiatrists who billed Medicare during this period. Female physicians made up 39% of psychiatrists overall who bill Medicare, but 23% of psychiatrists billing for ECT. Fifty percent of billed ECT treatments were performed by 12% of ECT doctors; among these high-volume ECT providers, 16% were female. CONCLUSIONS: Only a small subset of psychiatrists who bill Medicare provide ECT services, and female physicians are under-represented in the ECT workforce and among high-volume ECT providers. Improving workforce equity and with it access to ECT requires further study of psychiatric training and practice environment that may impose barriers on female participation as ECT providers.

Save Your Back: Comparison of the Compressive Force on the Lower Back Based on Differences in the Training Techniques.

INTRODUCTION: Musculoskeletal injury prevention for nurses is aimed at removing the need to manually position patients. In the ED, this is not always possible or practical. The purpose of this study is to compare the calculated estimated compressive force on the lumbar spine between recommended lifting techniques and the SHAPE lifting method during the horizontal transfer of a patient. METHODS: Twenty-one student nurses completed the horizontal transfer of a simulated patient while motion was collected using inertial measurement units. Motion data were analyzed to calculate an estimated compressive force on the lumbar spine while completing the movement based on current recommended lifting methods and while using the SHAPE lifting method. RESULTS: A significant reduction in estimated peak and average compressive force at the lumbar spine was found during both the push and the pull portions (P < .001) of the horizontal transfer. DISCUSSION: While the optimal way to limit musculoskeletal injury among nurses is to eliminate the need for manual handling of a patient, this is not always possible in the ED. It is critical that when emergency nurses must reposition a patient, they perform the movement in the most biomechanically sound method while using a friction reduction. These findings, coupled with the previous biomechanical risk factor reduction related to the SHAPE lifting intervention, gives promise to a safer lifting strategy for emergency nurses moving forward.

Prediction of Kv11.1 potassium channel PAS-domain variants trafficking via machine learning.

Congenital long QT syndrome (LQTS) is characterized by a prolonged QT-interval on an electrocardiogram (ECG). An abnormal prolongation in the QT-interval increases the risk for fatal arrhythmias. Genetic variants in several different cardiac ion channel genes, including KCNH2, are known to cause LQTS. Here, we evaluated whether structure-based molecular dynamics (MD) simulations and machine learning (ML) could improve the identification of missense variants in LQTS-linked genes. To do this, we investigated KCNH2 missense variants in the Kv11.1 channel protein shown to have wild type (WT) like or class II (trafficking-deficient) phenotypes in vitro. We focused on KCNH2 missense variants that disrupt normal Kv11.1 channel protein trafficking, as it is the most common phenotype for LQTS-associated variants. Specifically, we used computational techniques to correlate structural and dynamic changes in the Kv11.1 channel protein PAS domain (PASD) with Kv11.1 channel protein trafficking phenotypes. These simulations unveiled several molecular features, including the numbers of hydrating waters and hydrogen bonding pairs, as well as folding free energy scores, that are predictive of trafficking. We then used statistical and machine learning (ML) (Decision tree (DT), Random forest (RF), and Support vector machine (SVM)) techniques to classify variants using these simulation-derived features. Together with bioinformatics data, such as sequence conservation and folding energies, we were able to predict with reasonable accuracy (≈75%) which KCNH2 variants do not traffic normally. We conclude that structure-based simulations of KCNH2 variants localized to the Kv11.1 channel PASD led to an improvement in classification accuracy. Therefore, this approach should be considered to complement the classification of variant of unknown significance (VUS) in the Kv11.1 channel PASD.

Coding for Physical Restraint Status Among Hospitalized Patients: a 2019 National Inpatient Sample Analysis.

BACKGROUND: The reduction of physical restraint utilization in the hospital setting is a key goal of high-quality care, but little is known about the rate of restraint use in general hospitals in the USA. OBJECTIVE: This study reports the rate of physical restraint coding among acute care hospital discharges in the USA and explores associated demographic and diagnostic factors. DESIGN: The National Inpatient Sample, a de-identified all-payors database of acute care hospital discharges in the USA, was queried for patients aged 18 and older with a diagnosis code for physical restraint status in 2019. PARTICIPANTS: Hospitalized patients aged 18 and older. MAIN MEASURES: Demographics, discharge diagnoses, in-hospital mortality, length of stay, total hospital charges. KEY RESULTS: In total, 220,470 (95% CI: 208,114 to 232,826) hospitalizations, or 0.7% of overall hospitalizations, included a discharge code for physical restraint status. There was a 700-fold difference in coding for restraint utilization based on diagnosis, with 7.4% of patients with encephalitis receiving restraint diagnosis codes compared to < 0.01% of patients with uncomplicated diabetes. In an adjusted model, male sex was associated with an odds ratio of 1.4 (95% CI: 1.4 to 1.5) for restraint utilization coding, and Black race was associated with an odds ratio of 1.3 (95% CI: 1.2 to 1.4) relative to white race. CONCLUSIONS: In the general hospital setting, there is variability in physical restraint coding by sex, race, and clinical diagnosis. More research is needed into the appropriate utilization of restraints in the hospital setting and possible inequities in restraint utilization.

Case-control study of neuropsychiatric symptoms in electronic health records following COVID-19 hospitalization in 2 academic health systems.

Neuropsychiatric symptoms may persist following acute COVID-19 illness, but the extent to which these symptoms are specific to COVID-19 has not been established. We utilized electronic health records across 6 hospitals in Massachusetts to characterize cohorts of individuals discharged following admission for COVID-19 between March 2020 and May 2021, and compared them to individuals hospitalized for other indications during this period. Natural language processing was applied to narrative clinical notes to identify neuropsychiatric symptom domains up to 150 days following hospitalization, in addition to those reflected in diagnostic codes as measured in prior studies. Among 6619 individuals hospitalized for COVID-19 drawn from a total of 42,961 hospital discharges, the most commonly-documented symptom domains between 31 and 90 days after initial positive test were fatigue (13.4%), mood and anxiety symptoms (11.2%), and impaired cognition (8.0%). In regression models adjusted for sociodemographic features and hospital course, none of these were significantly more common among COVID-19 patients; indeed, mood and anxiety symptoms were less frequent (adjusted OR 0.72 95% CI 0.64-0.92). Between 91 and 150 days after positivity, most commonly-detected symptoms were fatigue (10.9%), mood and anxiety symptoms (8.2%), and sleep disruption (6.8%), with impaired cognition in 5.8%. Frequency was again similar among non-COVID-19 post-hospital patients, with mood and anxiety symptoms less common (aOR 0.63, 95% CI 0.52-0.75). Propensity-score matched analyses yielded similar results. Overall, neuropsychiatric symptoms were common up to 150 days after initial hospitalization, but occurred at generally similar rates among individuals hospitalized for other indications during the same period. Post-acute sequelae of COVID-19 may benefit from standard if less-specific treatments developed for rehabilitation after hospitalization.

Changes in self-reported suicidal ideation during treatment with electroconvulsive therapy: A retrospective cohort study.

OBJECTIVE: Suicidal ideation (SI) is common in patients with depressive symptoms, who are the most common recipients of electroconvulsive therapy (ECT). We sought to quantify changes in self-reported SI occurring during treatment with ECT, and to identify factors associated with persistence of SI in patients beginning treatment with SI. METHOD: Retrospective, single-center cohort study of patients receiving ECT and who self-reported symptoms using Quick Inventory of Depressive Symptomatology (QIDS) prior to ECT and after treatment #5 or #10. Changes in QIDS-reported SI over the course of ECT were calculated, and logistic regression models were performed to assess factors associated with reporting SI at the end of treatment. RESULTS: 2554 provided baseline and follow-up SI scores, of whom, 1931 (75.6%) endorsed SI at baseline. There was a reduction in SI with ECT treatment (McNemar's test; df = 1, Χ2 = 803.7; p < 0.001), and in adjusted models 64.0% of individuals with baseline SI reported resolution of SI with ECT treatment, while 3.3% without baseline SI reported SI at the end of treatment. Higher baseline SI severity and outpatient treatment were associated with a higher odds of persistent SI among individuals beginning treatment with SI. CONCLUSION: Electroconvulsive therapy treatment was associated with reductions in self-reported SI. These results support the use of ECT in the treatment of patients with SI, but further research is needed to determine the effects of ECT on suicidal behavior.

Factors associated with early and late response to electroconvulsive therapy.

OBJECTIVE: Electroconvulsive therapy (ECT) is an effective treatment for severe depressive symptoms, yet more research is needed to examine predictors of treatment response, and factors associated with response in patients not initially improving with treatment. This study reports factors associated with time to response (early vs. late) to ECT in a real-world setting. METHODS: This was a retrospective, single-center cohort study of patients endorsing moderate to severe depressive symptoms using the Quick Inventory of Depressive Symptomatology (QIDS; QIDS>10). Response was defined as 50% or greater decrease in QIDS score from baseline. We used logistic regression to predict response at treatment #5 (early response) as well as after treatment #5 (late response) and followed patients through ECT discontinuation or through treatment #20. RESULTS: Of the 1699 patients included in this study, 555 patients (32.7%) responded to ECT treatment at treatment #5 and 397 (23.4%) responded after treatment #5. Among patients who did not respond by treatment #5, those who switched to brief pulse width ECT from ultrabrief pulse ECT had increased odds of response after treatment #5 compared with patients only receiving ultrabrief pulse (aOR = 1.55, 95% CI: 1.16-2.07). Additionally, patients with less improvement in QIDS from baseline to treatment #5 had decreased odds of response after treatment #5 (aOR = 0.97, 95% CI = 0.97-0.98). CONCLUSION: Among depressed patients treated with ECT, response occurred in 56.0% of patients by treatment #20. Patient receiving ultrabrief pulse ECT at baseline and who did not respond by treatment #5 had greater odds of subsequent response if switched to brief pulse ECT than if continued with ultrabrief pulse.

The occurrence of delirium diagnosis among youth hospitalizations in the United States: A Kids' Inpatient Database analysis.

OBJECTIVES: Delirium is an acute neuropsychiatric condition associated with increased morbidity and mortality. There is increasing recognition of delirium as a substantial health burden in younger patients, although few studies have characterized its occurrence. This study analyzes the occurrence of delirium diagnosis, its comorbidities, and cost among youth hospitalized in the United States. METHODS: The Kids' Inpatient Database, a national all-payers sample of pediatric hospitalizations in general hospitals, was examined for the year 2019. Hospitalizations with a discharge diagnosis of delirium among patients aged 1-20 years were included in the analysis. RESULTS: Delirium was diagnosed in 43,138 hospitalizations (95% CI: 41,170-45,106), or 2.3% of studied hospitalizations. Delirium was diagnosed in a broad range of illnesses, with suicide and self-inflicted injury as the most common primary discharge diagnosis among patients with delirium. In-hospital mortality was seven times greater in hospitalizations caring a delirium diagnosis. The diagnosis of delirium was associated with an adjusted increased hospital cost of $8648 per hospitalization, or $373 million in aggregate cost. CONCLUSIONS: Based on a large national claims database, delirium was diagnosed in youth at a lower rate than expected based on prospective studies. The relative absence of delirium diagnosis in claims data may reflect underdiagnosis, a failure to code, and/or a lower rate of delirium in general hospitals compared with other settings. Further research is needed to better characterize the incidence and prevalence of delirium in young people in the hospital setting.

Infant Outcomes in Hypertensive Women: Are there Moderating Effects of Prenatal Care and Race/Ethnicity?

BACKGROUND: Hypertensive disorders of pregnancy is one of the leading causes of adverse infant outcomes. Black women are disproportionately affected by hypertensive disorders of pregnancy, and it associated adverse outcomes. Adequate prenatal care may improve adverse infant outcomes. However, the evidence on adequate prenatal care improving birth outcomes for women with hypertensive disorders of pregnancy especially for Blacks is limited. This study examined the role of adequate prenatal care and race/ethnicity as moderators of hypertensive disorders of pregnancy on infant outcomes. METHODS: The sample was obtained from the 2016-2019 Pregnancy Risk Assessment Monitoring Surveillance dataset from North Carolina. We compared adequate prenatal care among women with hypertensive disorders of pregnancy (n = 610) to women without(n = 2,827), and women with hypertensive disorders of pregnancy with adequate prenatal care to women hypertensive disorders of pregnancy with inadequate prenatal care. RESULTS: The weighted prevalence of hypertensive disorders of pregnancy was 14.1%. Adequate prenatal care was associated with better infant outcomes for low birth weight (AOR = 0.72; 95% CI = 0.58, 0.90) and preterm birth (AOR = 0.62; 95% CI = 0.46, 0.82). Although these effects were not moderated by Black race/ethnicity, Black women independently also had worse outcomes for preterm birth (AOR = 1.59; 95% CI = 1.11, 2.28) and low birth weight (AOR = 1.81; 95% CI = 1.42, 2.29). CONCLUSIONS: Moderation of hypertensive disorders of pregnancy effects on infant outcomes by prenatal care and race/ethnicity was not found. Women with hypertensive disorders of pregnancy who received inadequate prenatal care experienced worse adverse birth outcomes compared to women without hypertensive disorders of pregnancy. Strategies to improve prenatal care, particularly among underserved populations at risk for hypertensive disorders of pregnancy, need to be a public health priority.

The Application of a Standard Risk Threshold for the Stratification of Maternal Morbidity among Population Subgroups.

OBJECTIVE: The aim of this study was to determine if a universally applied risk score threshold for severe maternal morbidity (SMM) resulted in different performance characteristics among subgroups of the population. STUDY DESIGN: This is a retrospective cohort study of deliveries that occurred between July 1, 2016, and June 30, 2020, in a single health system. We examined the performance of a validated comorbidity score to stratify SMM risk in our cohort. We considered the risk score that was associated with the highest decile of predicted risk as a "screen positive" for morbidity. We then used this same threshold to calculate the sensitivity and positive predictive value (PPV) of this "highest risk" designation among subgroups of the overall cohort based on the following characteristics: age, race/ethnicity, parity, gestational age, and planned mode of delivery. RESULTS: In the overall cohort of 53,982 women, the C-statistic was 0.755 (95% confidence interval [CI], 0.741-0.769) and calibration plot demonstrated that the risk score was well calibrated. The model performed less well in the following groups: non-White or Hispanic (C-statistic, 0.734; 95% CI, 0.712-0.755), nulliparas (C-statistic, 0.735; 95% CI, 0.716-0.754), term deliveries (C-statistic, 0.712; 95% CI, 0.694-0.729), and planned vaginal delivery (C-statistic, 0.728; 95% CI, 0.709-0.747). There were differences in the PPVs by gestational age (7.8% term and 29.7% preterm) and by planned mode of delivery (8.7% vaginal and 17.7% cesarean delivery). Sensitivities were lower in women who were <35 years (36.6%), non-White or Hispanic (40.7%), nulliparous (38.9%), and those having a planned vaginal delivery (40.9%) than their counterparts. CONCLUSION: The performance of a risk score for SMM can vary by population subgroups when using standard thresholds derived from the overall cohort. If applied without such considerations, such thresholds may be less likely to identify certain subgroups of the population that may be at increased risk of SMM. KEY POINTS: · Predictive risk models are helpful at condensing complex information into an interpretable output.. · Model performance may vary among different population subgroups.. · Prediction models should be examined for their potential to exacerbate underlying disparities..

Changes in Inpatient Electroconvulsive Therapy Utilization Between 2019 and 2020: A National Inpatient Sample Analysis.

OBJECTIVES: Electroconvulsive therapy (ECT) is an essential procedure for a range of psychiatric conditions. Multiple single-center studies have documented reduction in ECT administration in 2020 because of the coronavirus disease 2019 pandemic, but there have been little nationally representative data from the United States. The aim of this study was to examine the demographics of patients receiving ECT in 2019 and 2020 and to characterize temporal and regional variations in ECT utilization. METHODS: The 2019 and 2020 National Inpatient Sample, an administrative database of inpatient hospitalizations in the United States, was queried for hospitalizations involving the delivery of ECT based on procedural codes. Overall number of ECT procedures was calculated based on the overall number of ECT procedural claims. RESULTS: In the 2019 NIS, 14,230 inpatient hospitalizations (95% confidence interval, 12,936-15,524) involved the use of ECT, with a cumulative 52,450 inpatient ECT procedures administered. In 2020, the number of inpatient hospitalizations with ECT decreased to 12,055 (95% confidence interval, 10,878-13,232), with a 10.0% reduction in overall procedures to 47,180. Whereas January and February ECT hospitalizations were comparable in both years, ECT hospitalizations decreased by more than 25% in March through May 2020 relative to 2019 volume. There was regional variability in the change in ECT utilization between 2019 and 2020. CONCLUSIONS: Electroconvulsive therapy use among general hospital inpatients declined between 2019 and 2020, with regional variability in the magnitude of change. Further study is warranted into the root causes and optimal responses to these changes.

Characteristics of Hospitalized Adults 55 and Older With Clostridioides difficile Infection.

Clostridioides difficile infection in older adults can result in severe infection, difficulty in treating, and complicated disease process, yet few studies have examined the characteristics of hospitalized older adults and recurrent Clostridioides difficile infection. A retrospective cohort study was conducted to explore the characteristics of hospitalized adults 55 years and older with initial Clostridioides difficile infection and recurrences by extracting routinely documented data in the electronic health record. A sample of 1,199 admissions on 871 patients was included, with a recurrence rate of 23.9% ( n = 208). During the first admission, there were 79 deaths (9.1%). Clostridioides difficile infection recurrence was more prevalent in patients between 55 and 64 years old, and if discharged to a skilled nursing facility or with home health services. Chronic diseases significantly more prevalent in recurrent Clostridioides difficile infection included hypertension, heart failure, and chronic kidney disease. On initial admission, no laboratory abnormalities were significantly associated with recurrent Clostridioides difficile infection. This study indicates the need for utilizing routinely captured electronic health record data during acute hospitalizations to aid in targeting care to reduce morbidity, mortality, and recurrence.

Clinical Ethics Consultation During the First COVID-19 Pandemic Surge at an Academic Medical Center: A Mixed Methods Analysis.

While a significant literature has appeared discussing theoretical ethical concerns regarding COVID-19, particularly regarding resource prioritization, as well as a number of personal reflections on providing patient care during the early stages of the pandemic, systematic analysis of the actual ethical issues involving patient care during this time is limited. This single-center retrospective cohort mixed methods study of ethics consultations during the first surge of the COVID 19 pandemic in Massachusetts between March 15, 2020 through June 15, 2020 aim to fill this gap. Results indicate that there was no significant difference in the median number of monthly consultation cases during the first COVID-19 surge compared to the same period the year prior and that the characteristics of the ethics consults during the COVID-19 surge and same period the year prior were also similar. Through inductive analysis, we identified four themes related to ethics consults during the first COVID-19 surge including (1) prognostic difficulty for COVID-19 positive patients, (2) challenges related to visitor restrictions, (3) end of life scenarios, and (4) family members who were also positive for COVID-19. Cases were complex and often aligned with multiple themes. These patient case-related sources of ethical issues were managed against the backdrop of intense systemic ethical issues and a near lockdown of daily life. Healthcare ethics consultants can learn from this experience to enhance training to be ready for future disasters.

Decreased Water Mobility Contributes To Increased α-Synuclein Aggregation.

The solvation shell is essential for the folding and function of proteins, but how it contributes to protein misfolding and aggregation has still to be elucidated. We show that the mobility of solvation shell H2 O molecules influences the aggregation rate of the amyloid protein α-synuclein (αSyn), a protein associated with Parkinson's disease. When the mobility of H2 O within the solvation shell is reduced by the presence of NaCl, αSyn aggregation rate increases. Conversely, in the presence CsI the mobility of the solvation shell is increased and αSyn aggregation is reduced. Changing the solvent from H2 O to D2 O leads to increased aggregation rates, indicating a solvent driven effect. We show the increased aggregation rate is not directly due to a change in the structural conformations of αSyn, it is also influenced by a reduction in both the H2 O mobility and αSyn mobility. We propose that reduced mobility of αSyn contributes to increased aggregation by promoting intermolecular interactions.

Natural language processing of admission notes to predict severe maternal morbidity during the delivery encounter.

BACKGROUND: Severe maternal morbidity and mortality remain public health priorities in the United States, given their high rates relative to other high-income countries and the notable racial and ethnic disparities that exist. In general, accurate risk stratification methods are needed to help patients, providers, hospitals, and health systems plan for and potentially avert adverse outcomes. OBJECTIVE: Our objective was to understand if machine learning methods with natural language processing of history and physical notes could identify a group of patients at high risk of maternal morbidity on admission for delivery without relying on any additional patient information (eg, demographics and diagnosis codes). STUDY DESIGN: This was a retrospective study of people admitted for delivery at 2 hospitals (hospitals A and B) in a single healthcare system between July 1, 2016, and June 30, 2020. The primary outcome was severe maternal morbidity, as defined by the Centers for Disease Control and Prevention; furthermore, we examined nontransfusion severe maternal morbidity. Clinician documents designated as history and physical notes were extracted from the electronic health record for processing and analysis. A bag-of-words approach was used for this natural language processing analysis (ie, each history or physical note was converted into a matrix of counts of individual words (or phrases) that occurred within the document). The least absolute shrinkage and selection operator models were used to generate prediction probabilities for severe maternal morbidity and nontransfusion severe maternal morbidity for each note. Model discrimination was assessed via the area under the receiver operating curve. Discrimination was compared between models using the DeLong test. Calibration plots were generated to assess model calibration. Moreover, the natural language processing models with history and physical note texts were compared with validated obstetrical comorbidity risk scores based on diagnosis codes. RESULTS: There were 13,572 delivery encounters with history and physical notes from hospital A, split between training (Atrain, n=10,250) and testing (Atest, n=3,322) datasets for model derivation and internal validation. There were 23,397 delivery encounters with history and physical notes from hospital B (Bvalid) used for external validation. For the outcome of severe maternal morbidity, the natural language processing model had an area under the receiver operating curve of 0.67 (95% confidence interval, 0.63-0.72) and 0.72 (95% confidence interval, 0.70-0.74) in the Atest and Bvalid datasets, respectively. For the outcome of nontransfusion severe maternal morbidity, the area under the receiver operating curve was 0.72 (95% confidence interval, 0.65-0.80) and 0.76 (95% confidence interval, 0.73-0.79) in the Atest and Bvalid datasets, respectively. The calibration plots demonstrated the bag-of-words model's ability to distinguish a group of individuals at a substantially higher risk of severe maternal morbidity and nontransfusion severe maternal morbidity, notably those in the top deciles of predicted risk. Areas under the receiver operating curve in the natural language processing-based models were similar to those generated using a validated, retrospectively derived, diagnosis code-based comorbidity score. CONCLUSION: In this practical application of machine learning, we demonstrated the capabilities of natural language processing for the prediction of severe maternal morbidity based on provider documentation inherently generated at the time of admission. This work should serve as a catalyst for providers, hospitals, and electronic health record systems to explore ways that artificial intelligence can be incorporated into clinical practice and evaluated rigorously for their ability to improve health.