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.

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..

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.

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.

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.

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.

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.

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.

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.

Efficacy of App-Based Cognitive Behavioral Therapy for Body Dysmorphic Disorder with Coach Support: Initial Randomized Controlled Clinical Trial.

INTRODUCTION: Body dysmorphic disorder (BDD) is severe, chronic, and undertreated. Apps could substantially improve treatment access. OBJECTIVE: We provide an initial test of the usability and efficacy of coach-supported app-based cognitive behavioral therapy (CBT) for BDD. The Perspectives app covers core treatment components: psychoeducation, cognitive restructuring, exposure with response prevention, mindfulness, attention retraining, and relapse prevention. METHODS: A randomized waitlist-controlled trial was conducted. Adults (N = 80) with primary BDD were assigned to 12 weeks of Perspectives or waitlist. Coaches promoted engagement and answered questions via in-app messaging and phone calls. BDD severity was measured at baseline, mid-treatment, and end of treatment by blinded independent evaluators (Yale-Brown Obsessive Compulsive Scale Modified for BDD; BDD-YBOCS). Secondary outcomes included BDD-related insight, depression, quality of life, and functioning. RESULTS: App uptake and satisfaction were high. In intent-to-treat analyses, Perspectives app-based CBT was associated with significantly lower BDD-YBOCS severity at end of treatment (M [SD]: 16.8 [7.5]) compared to the waitlist (26.7 [6.2]; p < 0.001, d = 1.44). App-based CBT was associated with greater improvements across all secondary measures, with medium to large effects. CONCLUSIONS: Perspectives, supported by a bachelor's-level coach, is an efficacious, scalable treatment for adults with BDD.

Real-world evidence of age-independent electroconvulsive therapy efficacy: A retrospective cohort study.

OBJECTIVES: Electroconvulsive therapy (ECT) is an effective treatment for depressive disorders and approved for use in adolescents and adults, but it is unclear whether efficacy or cognitive side effect burden differs with age or if effectiveness in usual clinical practice matches that in prospective studies. We examined the effects of ECT on depression and cognition in a large clinical cohort. METHODS: A retrospective cohort study of patients ages 16 and older receiving ECT between 2011 and 2020 and who were evaluated with the Quick Inventory of Depressive Symptomatology (QIDS), the Behavior and Symptom Identification Scale-24 (BASIS-24), and the Montreal Cognitive Assessment (MoCA) at baseline and after treatment #10. RESULTS: Among 1698 patients, ECT was associated with a decrease in depression symptoms (QIDS reduction from 17.1 ± 4.9 to 10.1 ± 5.2) and improvement in self-reported mental health (BASIS-24 scores improved from 1.92 ± 0.55 to 1.17 ± 0.60). There was a reduction in MoCA scores from 25.8 ± 3.1 to 25.4 ± 3.1. In multivariate models, age was not associated with a differential QIDS or BASIS-24 response, but older age was associated with a lesser reduction in MoCA. CONCLUSION: Among 1698 patients aged 16 and older, ECT was associated with improvement in depression and overall self-reported mental health, with a slight decrease in cognition. Age was not associated with changes in efficacy, but older age was associated with a lesser cognitive change as measured by the MoCA. These results provide normative data of real-world effectiveness of ECT, and add further support to its utility in patients with severe psychiatric illness.

The Duration in Treatment With Electroconvulsive Therapy Among Patients Screening Positive or Negative for Borderline Personality Disorder Traits: A Retrospective Cohort Study.

OBJECTIVE: While emerging evidence suggests that electroconvulsive therapy (ECT) is an effective treatment for depressive symptoms in patients with co-occurring borderline personality disorder (BPD) traits, it is unclear whether the presence of BPD traits modulates the tolerability of ECT. This study estimates the association between BPD traits and retention in acute course ECT treatment. METHODS: This study used a retrospective cohort of patients receiving ECT between 2015 and 2020 and who were assessed using the McLean Screening Instrument for BPD, the Quick Inventory of Depressive Symptomatology Self-Report 16-item scale, and the Montreal Cognitive Assessment before initiating treatment. RESULTS: One thousand five hundred eight patients received ECT during the study period, of whom 277 (18.4%) screened positive for BPD traits. Borderline personality disorder traits were associated with a higher odds of remaining in ECT for at least 10 treatments (adjusted odds ratio, 1.502; 95% confidence interval, 1.11-2.02; P = 0.007). Among individual symptom domains, only endorsing chronically feeling empty was associated with duration in ECT treatment. CONCLUSIONS: Among patients receiving ECT, screening positive for BPD traits was associated with a higher odds of receiving at least 10 ECT treatments. These results support the overall tolerability of ECT in patients with BPD traits.

Experience with a Revised Hospital Policy on Not Offering Cardiopulmonary Resuscitation.

Critical care society guidelines recommend that ethics committees mediate intractable conflict over potentially inappropriate treatment, including Do Not Resuscitate (DNR) status. There are, however, limited data on cases and circumstances in which ethics consultants recommend not offering cardiopulmonary resuscitation (CPR) despite patient or surrogate requests and whether physicians follow these recommendations. This was a retrospective cohort of all adult patients at a large academic medical center for whom an ethics consult was requested for disagreement over DNR status. Patient demographic predictors of ethics consult outcomes were analyzed. In 42 of the 116 cases (36.2%), the patient or surrogate agreed to the clinician recommended DNR order following ethics consultation. In 72 of 74 (97.3%) of the remaining cases, ethics consultants recommended not offering CPR. Physicians went on to write a DNR order without patient/surrogate consent in 57 (79.2%) of those cases. There were no significant differences in age, race/ethnicity, country of origin, or functional status between patients where a DNR order was and was not placed without consent. Physicians were more likely to place a DNR order for patients believed to be imminently dying (p = 0.007). The median time from DNR order to death was 4 days with a 90-day mortality of 88.2%. In this single-center cohort study, there was no evidence that patient demographic factors affected ethics consultants' recommendation to withhold CPR despite patient/surrogate requests. Physicians were most likely to place a DNR order without consent for imminently dying patients.

Rate of continuing acute course treatment using right unilateral ultrabrief pulse electroconvulsive therapy at a large academic medical center.

Right unilateral ultrabrief pulse (RUL-UBP) ECT has emerged as a promising technique for minimizing cognitive side effects of ECT while retaining clinical efficacy, but it is unknown how often patients will require alternative treatment parameters and at what point in the treatment course this occurs. To better define this problem, this study analyzes continuation in RUL-UBP ECT in a retrospective cohort of patients beginning acute course treatment. A single-center retrospective chart review was conducted of adult patients receiving a first lifetime course of ECT from 2010 to 2017 starting with RUL-UBP treatment parameters. 1793 patients met study criteria. Patients received a mean of 10.0 ± 3.2 ECT treatments, of which a mean of 8.4 ± 3.4 were RUL-UBP treatments; proportion using RUL-UBP through 12 treatments was 57.8%. In total, 65.6% of patients were treated with RUL-UPB ECT exclusively. Mean dose increased from 7.6 × seizure threshold at the second RUL-UBP treatment to 14.3 × seizure threshold at the twelfth RUL-UBP treatment. Rates of continuation in RUL-UBP ECT did not differ based on age or on primary diagnosis of major depression vs. bipolar disorder. Among patients beginning acute-course treatment using RUL-UPB ECT, two thirds were treated with these parameters exclusively. Among patients who received twelve RUL-UBP treatments, mean final dose was 14.3 × seizure threshold. Further studies regarding optimal dosing of RUL-UBP ECT are indicated.

Total Charge Required to Induce a Seizure in a Retrospective Cohort of Patients Undergoing Dose Titration of Right Unilateral Ultrabrief Pulse Electroconvulsive Therapy.

OBJECTIVES: The use of ultrabrief pulse (UBP) stimuli and individual seizure threshold determination have been proposed as ways of minimizing the cognitive side effects of electroconvulsive therapy (ECT), but large samples of patients receiving UBP ECT are lacking. This study reports a retrospective cohort of patients receiving an index course of right unilateral UBP ECT and characterizes the amount of charge required to induce a seizure. METHODS: A single-center retrospective chart review was conducted of adult patients receiving a first lifetime course of ECT using an UBP titration from 2005 to 2017. RESULTS: There were 2328 patients that received a dose titration during the study period, with a mean dose of 21.82 ± 21.61 mC applied to induce a seizure. During the early part of the study period, a mean dose of 18.73 ± 8.99 mC was used, with 28% of patients seizing at a dose of less than 19.2 mC. In the later period, the initial step of dose titration was standardized at 19.2 mC, yielding a mean initial dose to induce a seizure of 22.72 ± 24.00 mC. CONCLUSIONS: Mean seizure thresholds may be lower than reported in previous studies, and a significant proportion of patients may have a seizure threshold lower than the first step of many existing dose titration protocols.

Duration of Treatment in Electroconvulsive Therapy Among Patients Beginning With Acute Course Right Unilateral Brief Pulse Stimuli.

OBJECTIVES: Right unilateral brief pulse (RUL-BP) electroconvulsive therapy (ECT) has been adopted as a technique for reducing the cognitive side effects of ECT relative to sine wave or bilateral treatments, but it is unknown how often patients are transitioned to alternative electrode placements. This study analyzes time in first lifetime acute course RUL-BP ECT. METHODS: A single-center retrospective chart review was conducted of adult patients receiving a first lifetime course of ECT from 2000 to 2017 beginning with individualized seizure threshold determination using RUL-BP treatment parameters. RESULTS: A total of 1383 patients met study criteria and received a mean number of 9.4 ± 3.1 treatments, of which 7.6 ± 3.3 were using RUL-BP stimuli. Only 37.5% of patients were transitioned from RUL to bilateral treatments. Younger patients and those diagnosed with bipolar disorder were more likely to transition from RUL-BP to bilateral treatments, but the overall number of treatments did not differ based on age or primary diagnosis. CONCLUSIONS: Among patients who begin treatment with RUL-BP ECT, more than 60% use exclusively those parameters throughout their acute course.

Characterizing DSM-5 and ICD-11 personality disorder features in psychiatric inpatients at scale using electronic health records.

BACKGROUND: Investigation of personality traits and pathology in large, generalizable clinical cohorts has been hindered by inconsistent assessment and failure to consider a range of personality disorders (PDs) simultaneously. METHODS: We applied natural language processing (NLP) of electronic health record notes to characterize a psychiatric inpatient cohort. A set of terms reflecting personality trait domains were derived, expanded, and then refined based on expert consensus. Latent Dirichlet allocation was used to score notes to estimate the extent to which any given note reflected PD topics. Regression models were used to examine the relationship of these estimates with sociodemographic features and length of stay. RESULTS: Among 3623 patients with 4702 admissions, being male, non-white, having a low burden of medical comorbidity, being admitted through the emergency department, and having public insurance were independently associated with greater levels of disinhibition, detachment, and psychoticism. Being female, white, and having private insurance were independently associated with greater levels of negative affectivity. The presence of disinhibition, psychoticism, and negative affectivity were each significantly associated with a longer stay, while detachment was associated with a shorter stay. CONCLUSIONS: Personality features can be systematically and scalably measured using NLP in the inpatient setting, and some of these features associate with length of stay. Developing treatment strategies for patients scoring high in certain personality dimensions may facilitate more efficient, targeted interventions, and may help reduce the impact of personality features on mental health service utilization.

Modified Anesthesia Protocol for Electroconvulsive Therapy Permits Reduction in Aerosol-Generating Bag-Mask Ventilation during the COVID-19 Pandemic.

INTRODUCTION: Electroconvulsive therapy (ECT) is a critical procedure in psychiatric treatment, but as typically delivered involves the use of bag-mask ventilation (BMV), which during the COVID-19 pandemic exposes patients and treatment staff to potentially infectious aerosols. OBJECTIVE: To demonstrate the utility of a modified anesthesia protocol for ECT utilizing preoxygenation by facemask and withholding the use of BMV for only those patients who desaturate during the apneic period. METHODS: This chart review study analyzes patients who were treated with ECT using both the traditional and modified anesthesia protocols. RESULTS: A total of 106 patients were analyzed, of whom 51 (48.1%) required BMV using the new protocol. Of clinical factors, only patient BMI was significantly associated with the requirement for BMV. Mean seizure duration reduced from 52.0 ± 22.4 to 46.6 ± 17.1 s, but seizure duration was adequate in all cases. No acute physical, respiratory, or psychiatric complications occurred during treatment. CONCLUSIONS: A modified anesthesia protocol reduces the use of BMV by more than 50%, while retaining adequate seizure duration.