Ratios of calcium to citrate administration in blood transfusion for traumatic hemorrhage: A retrospective cohort study.

BACKGROUND: Massive transfusion with citrated blood products causes hypocalcemia, which is associated with mortality. Recognition of this problem has led to increased calcium administration; however, the optimal dosing is still unknown. STUDY DESIGN AND METHODS: This retrospective, single-center study included level 1 trauma patients in 2019 and 2020 who underwent an operation within 12 h of arrival and received a transfusion. Preoperative and intraoperative administrations were totaled to calculate the ratio of administered calcium to the number of blood transfusions for each patient. The citrate content of each blood component was estimated to calculate a second ratio, the ratio of administered calcium to administered citrate. Receiver Operating Characteristic (ROC) curves were performed on both ratios to determine the optimal cutoff values for predicting severe hypocalcemia (ionized calcium <0.9 mmol/L) and hypercalcemia (>1.35 mmol/L) at the end of the intraoperative period. RESULTS: A total of 506 trauma activations were included, receiving a mean of 17.4 citrated blood products and 16.3 mmol of calcium (equivalent to 2400 mg of calcium chloride). No ratio was statistically significant in differentiating severely hypocalcemic patients from the rest. A calcium to blood ratio of 0.903 mmol of administered calcium per citrated blood product differentiated hypercalcemic patients from the rest. DISCUSSION: Quantifying received calcium and citrated blood products was insufficient to predict severe hypocalcemia, suggesting other contributions to hypocalcemia. We demonstrated an upper-limit ratio for calcium administration in traumatic hemorrhage; however, further studies are required to determine what calcium dosing regimen results in the best outcomes.

A mosaic of whole-body representations in human motor cortex.

Understanding how the body is represented in motor cortex is key to understanding how the brain controls movement. The precentral gyrus (PCG) has long been thought to contain largely distinct regions for the arm, leg and face (represented by the "motor homunculus"). However, mounting evidence has begun to reveal a more intermixed, interrelated and broadly tuned motor map. Here, we revisit the motor homunculus using microelectrode array recordings from 20 arrays that broadly sample PCG across 8 individuals, creating a comprehensive map of human motor cortex at single neuron resolution. We found whole-body representations throughout all sampled points of PCG, contradicting traditional leg/arm/face boundaries. We also found two speech-preferential areas with a broadly tuned, orofacial-dominant area in between them, previously unaccounted for by the homunculus. Throughout PCG, movement representations of the four limbs were interlinked, with homologous movements of different limbs (e.g., toe curl and hand close) having correlated representations. Our findings indicate that, while the classic homunculus aligns with each area's preferred body region at a coarse level, at a finer scale, PCG may be better described as a mosaic of functional zones, each with its own whole-body representation.

Association of Daily Physical Activity With Motivation in Prefrail and Frail Older Adults Living in Retirement Communities.

Older adults living in retirement communities are an understudied population, and the association between their motivation and daily physical activity is unknown. We recruited participants (n = 173) living in a retirement community who completed the Behavioral Regulation in Exercise Questionnaire-2 and wore an activPAL accelerometer to evaluate this relationship. Participants had a median age of 81 years and demonstrated low levels of daily activity with an average step count of 3,637 (±1,965) steps per day and 52 (±25) min of daily stepping time. External motivation was negatively associated with the square root of daily step count (ß = -4.57; p < .001) and square root of daily stepping time (ß = -0.49; p < .001). Older adults living in retirement communities demonstrated low levels of daily activity, with a negative association between external motivation and daily activity. Strategies are needed to make an active lifestyle supportive and enticing for older adults in these communities.

Automated Extraction of Patient-Centered Outcomes After Breast Cancer Treatment: An Open-Source Large Language Model-Based Toolkit.

PURPOSE: Patient-centered outcomes (PCOs) are pivotal in cancer treatment, as they directly reflect patients' quality of life. Although multiple studies suggest that factors affecting breast cancer-related morbidity and survival are influenced by treatment side effects and adherence to long-term treatment, such data are generally only available on a smaller scale or from a single center. The primary challenge with collecting these data is that the outcomes are captured as free text in clinical narratives written by clinicians. MATERIALS AND METHODS: Given the complexity of PCO documentation in these narratives, computerized methods are necessary to unlock the wealth of information buried in unstructured text notes that often document PCOs. Inspired by the success of large language models (LLMs), we examined the adaptability of three LLMs, GPT-2, BioGPT, and PMC-LLaMA, on PCO tasks across three institutions, Mayo Clinic, Emory University Hospital, and Stanford University. We developed an open-source framework for fine-tuning LLM that can directly extract the five different categories of PCO from the clinic notes. RESULTS: We found that these LLMs without fine-tuning (zero-shot) struggle with challenging PCO extraction tasks, displaying almost random performance, even with some task-specific examples (few-shot learning). The performance of our fine-tuned, task-specific models is notably superior compared with their non-fine-tuned LLM models. Moreover, the fine-tuned GPT-2 model has demonstrated a significantly better performance than the other two larger LLMs. CONCLUSION: Our discovery indicates that although LLMs serve as effective general-purpose models for tasks across various domains, they require fine-tuning when applied to the clinician domain. Our proposed approach has the potential to lead more efficient, adaptable models for PCO information extraction, reducing reliance on extensive computational resources while still delivering superior performance for specific tasks.

SGLT-2 inhibitors in heart failure and chronic kidney disease: A review for internists.

Despite current therapies, heart failure and chronic kidney disease continue to be major causes of morbidity and mortality. Sodium-glucose cotransporter 2 (SGLT-2) inhibitors have recently become standard-of-care therapy for these conditions. This review summarizes important randomized controlled trials of SGLT-2 inhibitors and guidelines for using these agents in patients with heart failure and chronic kidney disease in both clinic and hospital settings.

Privacy preservation for federated learning in health care.

Artificial intelligence (AI) shows potential to improve health care by leveraging data to build models that can inform clinical workflows. However, access to large quantities of diverse data is needed to develop robust generalizable models. Data sharing across institutions is not always feasible due to legal, security, and privacy concerns. Federated learning (FL) allows for multi-institutional training of AI models, obviating data sharing, albeit with different security and privacy concerns. Specifically, insights exchanged during FL can leak information about institutional data. In addition, FL can introduce issues when there is limited trust among the entities performing the compute. With the growing adoption of FL in health care, it is imperative to elucidate the potential risks. We thus summarize privacy-preserving FL literature in this work with special regard to health care. We draw attention to threats and review mitigation approaches. We anticipate this review to become a health-care researcher's guide to security and privacy in FL.

The association between neighborhood disadvantage and frailty: A retrospective case series.

Background: Frailty predicts poorer outcomes in surgical patients. Recent studies have found socioeconomic status to be an important characteristic for surgical outcomes. We evaluated the association of Area Deprivation Index (ADI) and Social Vulnerability Index (SVI), two geospatial atlases that provide a multidimensional evaluation of neighborhood deprivation, with frailty in a surgery population. Design & methods: A retrospective study of patients undergoing routine frailty screening was conducted 12/2020-8/2022. Frailty was measured using Fried's Frailty Phenotype (FFP) and the five-item Modified Frailty Index (mFI-5). ADI and SVI quartiles were determined using patient residence. Logistic regression models were used to evaluated associations of FFP (frail only vs not frail) and mFI-5 (≥2 vs 0-1) with ADI and SVI (α = 0.05). Results: Of 372 screened patients, 41% (154) were women, median age was 68% (63-74), and 46% (170) identified as non-White. Across ADI and SVI quartiles, higher number of comorbidities, decreasing median income, and frailty were associated with increasing deprivation (p < 0.01). When controlling for age, sex, comorbidities, and BMI category, frailty by FFP was associated with the most deprived two quartiles of ADI (OR 2.61, CI: [1.35-5.03], p < 0.01) and the most deprived quartile of SVI (OR 2.33, [1.10-4.95], p < 0.05). These trends were also seen with mFI-5 scores ≥2 (ADI: OR 1.64, [1.02-2.63], p < 0.05; SVI: OR 1.71, [1.01-2.91], p < 0.05). Conclusions: Surgical patients living in socioeconomically deprived neighborhoods are more likely to be frail. Interventions may include screening of disadvantaged populations and resource allocation to vulnerable neighborhoods.

Implementing a Frailty-Specific Postoperative Order Set to Improve Postoperative Outcomes in Frail Adults After Elective Thoracic Surgery.

BACKGROUND: Frailty is independently associated with adverse patient outcomes after surgery. The current standards of postoperative care rarely consider frailty status. LOCAL PROBLEM: There was no standardized protocol to optimize specialized postoperative care for frail patients at an academic medical center. METHODS: A quasi-experimental pre-/postimplementation study design, using the Reach, Effectiveness, Adoption, Implementation, Maintenance implementation framework, was utilized. INTERVENTIONS: A frailty-specific postoperative order set (FPOS) was developed, including tailored nursing care, activity levels, and nutritional goals. RESULTS: There were significant improvements in nurse's self-reported familiarity with frailty ( P = .003) and FPOS awareness ( P < .001). The number of orders for delirium prevention, elimination, nutrition, sleep promotion, and sensory support increased ( P < .001). CONCLUSIONS: Implementing an FPOS showed improvements in nurse frailty knowledge, awareness, and order set utilization.

Abdominal CT metrics in 17,646 patients reveal associations between myopenia, myosteatosis, and medical phenotypes: a phenome-wide association study.

BACKGROUND: Deep learning facilitates large-scale automated imaging evaluation of body composition. However, associations of body composition biomarkers with medical phenotypes have been underexplored. Phenome-wide association study (PheWAS) techniques search for medical phenotypes associated with biomarkers. A PheWAS integrating large-scale analysis of imaging biomarkers and electronic health record (EHR) data could discover previously unreported associations and validate expected associations. Here we use PheWAS methodology to determine the association of abdominal CT-based skeletal muscle metrics with medical phenotypes in a large North American cohort. METHODS: An automated deep learning pipeline was used to measure skeletal muscle index (SMI; biomarker of myopenia) and skeletal muscle density (SMD; biomarker of myosteatosis) from abdominal CT scans of adults between 2012 and 2018. A PheWAS was performed with logistic regression using patient sex and age as covariates to assess for associations between CT-derived muscle metrics and 611 common EHR-derived medical phenotypes. PheWAS P values were considered significant at a Bonferroni corrected threshold (α = 0.05/1222). FINDINGS: 17,646 adults (mean age, 56 years ± 19 [SD]; 57.5% women) were included. CT-derived SMI was significantly associated with 268 medical phenotypes; SMD with 340 medical phenotypes. Previously unreported associations with the highest magnitude of significance included higher SMI with decreased cardiac dysrhythmias (OR [95% CI], 0.59 [0.55-0.64]; P < 0.0001), decreased epilepsy (OR, 0.59 [0.50-0.70]; P < 0.0001), and increased elevated prostate-specific antigen (OR, 1.84 [1.47-2.31]; P < 0.0001), and higher SMD with decreased decubitus ulcers (OR, 0.36 [0.31-0.42]; P < 0.0001), sleep disorders (OR, 0.39 [0.32-0.47]; P < 0.0001), and osteomyelitis (OR, 0.43 [0.36-0.52]; P < 0.0001). INTERPRETATION: PheWAS methodology reveals previously unreported associations between CT-derived biomarkers of myopenia and myosteatosis and EHR medical phenotypes. The high-throughput PheWAS technique applied on a population scale can generate research hypotheses related to myopenia and myosteatosis and can be adapted to research possible associations of other imaging biomarkers with hundreds of EHR medical phenotypes. FUNDING: National Institutes of Health, Stanford AIMI-HAI pilot grant, Stanford Precision Health and Integrated Diagnostics, Stanford Cardiovascular Institute, Stanford Center for Digital Health, and Stanford Knight-Hennessy Scholars.

Exploration of a Potential DOOR Endpoint for Hospital-acquired Bacterial Pneumonia and Ventilator-associated Bacterial Pneumonia Using Six Registrational Trials for Antibacterial Drugs.

BACKGROUND: Desirability of outcome ranking (DOOR) is an innovative approach to clinical trial design and analysis that uses an ordinal ranking system to incorporate the overall risks and benefits of a therapeutic intervention into a single measurement. Here we derived and evaluated a disease-specific DOOR endpoint for registrational trials for hospital-acquired bacterial pneumonia and ventilator-associated bacterial pneumonia (HABP/VABP). METHODS: Through comprehensive examination of data from nearly 4000 participants enrolled in six registrational trials for HABP/VABP submitted to the Food and Drug Administration (FDA) between 2005 and 2022, we derived and applied a HABP/VABP specific endpoint. We estimated the probability that a participant assigned to the study treatment arm would have a more favorable overall DOOR or component outcome than a participant assigned to comparator. RESULTS: DOOR distributions between treatment arms were similar in all trials. DOOR probability estimates ranged from 48.3% to 52.9% and were not statistically different. There were no significant differences between treatment arms in the component analyses. Although infectious complications and serious adverse events occurred more frequently in ventilated participants compared to non-ventilated participants, the types of events were similar. CONCLUSIONS: Through a data-driven approach, we constructed and applied a potential DOOR endpoint for HABP/VABP trials. The inclusion of syndrome-specific events may help to better delineate and evaluate participant experiences and outcomes in future HABP/VABP trials and could help inform data collection and trial design.

Confronting Health Misinformation Surrounding COVID-19 Vaccines in the State of Florida.

COVID-19 vaccination is estimated to have averted more than 2.4 million deaths globally. In the United States (U.S.) alone, more than 120,000 deaths and 700,000 hospitalizations are reportedly estimated to have been prevented during the first six months of the vaccine campaign. Despite the overwhelming evidence regarding the safety and efficacy of vaccination, COVID-19 vaccine hesitancy continues to pose a significant threat to public health. Notably, an unexpected source of vaccine misinformation has been the Surgeon General of the State of Florida, Dr. Joseph Ladapo. While both a tenured faculty member of the University of Florida, College of Medicine and the Surgeon General of Florida, Dr. Ladapo has delivered official Florida Department of Health statements regarding COVID-19 vaccines that run contrary to those of the U.S. Centers for Disease Control and Prevention (CDC). While tenure is designed to protect those with contrarian views, we believe that the University has an ethical obligation to condemn misleading statements that put public health at risk. Herein, we explore the challenges of managing misinformation disseminated by someone who is simultaneously a tenured professor at a public, state-supported university, and a politically appointed public health official.

Regulatory Considerations in the Approval of Rezafungin (Rezzayo) for the Treatment of Candidemia and Invasive Candidiasis in Adults.

On 22 March 2023, the FDA approved rezafungin (Rezzayo) for the treatment of candidemia and invasive candidiasis in adults with limited or no alternative treatment options. Rezafungin is an echinocandin that supports weekly dosing, enabling outpatient parenteral treatment that potentially avoids the need for a central venous catheter. Approval of rezafungin was based on a single adequate and well-controlled phase 3 study designed with a day 30 all-cause mortality primary end point and 20% noninferiority margin, which demonstrated that rezafungin is noninferior to the comparator echinocandin. Nonclinical studies of rezafungin in nonhuman primates identified a neurotoxicity safety signal; however, rezafungin's safety profile in the completed clinical studies was similar to other Food and Drug Administration-approved echinocandins. Here we describe the rationale for this approval and important considerations during the review process for a flexible development program intended to expedite the availability of antimicrobial therapies to treat serious infections in patients with limited treatment options. Clinical Trials Registration . NCT02734862 and NCT03667690.

Comprehensive geriatric assessment predicts listing for kidney transplant in patients with end-stage renal disease: a retrospective cohort study.

BACKGROUND: Comprehensive geriatric assessment (CGA) involves a formal broad approach to assess frailty and creating a plan for management. However, the impact of CGA and its components on listing for kidney transplant in older adults has not been investigated. METHODS: We performed a single-center retrospective study of patients with end-stage renal disease who underwent CGA during kidney transplant candidacy evaluation between 2017 and 2021. All patients ≥ 65 years old and those under 65 with any team member concern for frailty were referred for CGA, which included measurements of healthcare utilization, comorbidities, social support, short physical performance battery, Montreal Cognitive Assessment (MoCA), and Physical Frailty Phenotype (FPP), and estimate of surgical risk by the geriatrician. RESULTS: Two hundred and thirty patients underwent baseline CGA evaluation; 58.7% (135) had high CGA ("Excellent" or "Good" rating for transplant candidacy) and 41.3% (95) had low CGA ratings ("Borderline," "Fair," or "Poor"). High CGA rating (OR 8.46; p < 0.05), greater number of CGA visits (OR 4.93; p = 0.05), younger age (OR 0.88; p < 0.05), higher MoCA scores (OR 1.17; p < 0.05), and high physical activity (OR 4.41; p < 0.05) were all associated with listing on transplant waitlist. CONCLUSIONS: The CGA is a useful, comprehensive tool to help select older adults for kidney transplantation. Further study is needed to better understand the predictive value of CGA in predicting post-operative outcomes.

Barriers and facilitators to smartwatch-based prehabilitation participation among frail surgery patients: a qualitative study.

BACKGROUND: For older, frail adults, exercise before surgery through prehabilitation (prehab) may hasten return recovery and reduce postoperative complications. We developed a smartwatch-based prehab program (BeFitMe) for older adults that encourages and tracks at-home exercise. The objective of this study was to assess patient perceptions about facilitators and barriers to prehab generally and to using a smartwatch prehab program among older adult thoracic surgery patients to optimize future program implementation. METHODS: We recruited patients, aged ≥50 years who had or were having surgery and were screened for frailty (Fried's Frailty Phenotype) at a thoracic surgery clinic at a single academic institution. Semi-structured interviews were conducted by telephone after obtaining informed consent. Participants were given a description of the BeFitMe program. The interview questions were informed by The Five "Rights" of Clinical Decision-Making framework (Information, Person, Time, Channel, and Format) and sought to identify the factors perceived to influence smartwatch prehab program participation. Interview transcripts were transcribed and independently coded to identify themes in for each of the Five "Rights" domains. RESULTS: A total of 29 interviews were conducted. Participants were 52% men (n = 15), 48% Black (n = 14), and 59% pre-frail (n = 11) or frail (n = 6) with a mean age of 68 ± 9 years. Eleven total themes emerged. Facilitator themes included the importance of providers (right person) clearly explaining the significance of prehab (right information) during the preoperative visit (right time); providing written instructions and exercise prescriptions; and providing a preprogrammed and set-up (right format) Apple Watch (right channel). Barrier themes included pre-existing conditions and disinterest in exercise and/or technology. Participants provided suggestions to overcome the technology barrier, which included individualized training and support on usage and responsibilities. CONCLUSIONS: This study reports the perceived facilitators and barriers to a smartwatch-based prehab program for pre-frail and frail thoracic surgery patients. The future BeFitMe implementation protocol must ensure surgical providers emphasize the beneficial impact of participating in prehab before surgery and provide a written prehab prescription; must include a thorough guide on smartwatch use along with the preprogrammed device to be successful. The findings are relevant to other smartwatch-based interventions for older adults.

Factors Predicting 90-Day Readmissions for US Older Adult Burn Patients From the 2016-2018 Nationwide Readmissions Database.

Older adults with burn injuries have a high risk of readmission after the initial burn admission. Frailty is associated with poor outcomes from the initial burn injury, however, it remains unknown if frailty impacts readmission in older adults after the initial index burn admission. Our study aims to examine patient, frailty, burn, surgical, and hospital factors that contribute to 90-day readmissions in older adults with an acute burn. Patients ≥ 50 years of age with an acute burn diagnosis in the Nationwide Readmissions Database (2016-2018) were included. Patients who died during index admissions were excluded from the readmission analysis. Patient, burn, hospital stay, and hospital characteristics were analyzed. Using variables significant from univariate logistic regression analysis, we performed a multivariable logistic regression analysis to identify factors associated with 90-day readmissions. A total of 41,500 weighted index burn admissions were included. The 90-day readmission rate was 25.6% (10,641/41,500). Almost all the readmissions were unplanned (96.5%). The most common primary readmission diagnoses based on Clinical Classifications Software Refined were burn injury and septicemia. Multivariable logistic regression analysis demonstrated an increased hospital frailty risk and lower-body-only burns were associated with an increased risk of readmission. Notably, surgical treatment of the burn injury during the index admission was associated with a decreased risk of readmission. This highlights the importance and challenges of surgical decision-making for older adults with high comorbidity burden. Future studies are needed to develop decision guides to help clinicians identify patients who would benefit from surgical treatment versus more conservative strategies in older adult patients with burns.

Towards trustworthy seizure onset detection using workflow notes.

A major barrier to deploying healthcare AI is trustworthiness. One form of trustworthiness is a model's robustness across subgroups: while models may exhibit expert-level performance on aggregate metrics, they often rely on non-causal features, leading to errors in hidden subgroups. To take a step closer towards trustworthy seizure onset detection from EEG, we propose to leverage annotations that are produced by healthcare personnel in routine clinical workflows-which we refer to as workflow notes-that include multiple event descriptions beyond seizures. Using workflow notes, we first show that by scaling training data to 68,920 EEG hours, seizure onset detection performance significantly improves by 12.3 AUROC (Area Under the Receiver Operating Characteristic) points compared to relying on smaller training sets with gold-standard labels. Second, we reveal that our binary seizure onset detection model underperforms on clinically relevant subgroups (e.g., up to a margin of 6.5 AUROC points between pediatrics and adults), while having significantly higher FPRs (False Positive Rates) on EEG clips showing non-epileptiform abnormalities (+19 FPR points). To improve model robustness to hidden subgroups, we train a multilabel model that classifies 26 attributes other than seizures (e.g., spikes and movement artifacts) and significantly improve overall performance (+5.9 AUROC points) while greatly improving performance among subgroups (up to +8.3 AUROC points) and decreasing false positives on non-epileptiform abnormalities (by 8 FPR points). Finally, we find that our multilabel model improves clinical utility (false positives per 24 EEG hours) by a factor of 2×.

Moving Beyond Mortality: Development and Application of a Desirability of Outcome Ranking (DOOR) Endpoint for Hospital-Acquired Bacterial Pneumonia and Ventilator-Associated Bacterial Pneumonia.

BACKGROUND: Hospital-acquired and ventilator-associated bacterial pneumonia (HABP/VABP) are frequently caused by multidrug-resistant organisms. Patient-centered endpoints in clinical trials are needed to develop new antibiotics for HABP/VABP. Desirability of outcome ranking (DOOR) is a paradigm for the design, analysis, and interpretation of clinical trials based on a patient-centered, benefit-risk evaluation. METHODS: A multidisciplinary committee created an infectious diseases DOOR endpoint customized for HABP/VABP, incorporating infectious complications, serious adverse events, and mortality. We applied this to 2 previously completed, large randomized controlled trials for HABP/VABP. ZEPHyR compared vancomycin to linezolid and VITAL compared linezolid to tedizolid. For each trial, we evaluated the DOOR distribution and probability, including DOOR component and partial credit analyses. We also applied DOOR in subgroup analyses. RESULTS: In both trials, the HABP/VABP DOOR demonstrated similar overall clinical outcomes between treatment groups. In ZEPHyR, the probability that a participant treated with linezolid would have a more desirable outcome than a participant treated with vancomycin was 50.2% (95% confidence interval [CI], 45.1%--55.3%). In VITAL, the probability that a participant treated with tedizolid would have a more desirable outcome than a participant treated with linezolid was 48.7% (95% CI, 44.8%-52.6%). The DOOR component analysis revealed that participants treated with tedizolid had a less desirable outcome than those treated with linezolid when considering clinical response alone. However, participants with decreased renal function had improved overall outcomes with tedizolid. CONCLUSIONS: The HABP/VABP DOOR provided more granular information about clinical outcomes than is typically presented in clinical trials. HABP/VABP trials would benefit from prospectively using DOOR.

Trends and In-Hospital Mortality for Perioperative Myocardial Infarction After the Introduction of a Diagnostic Code for Type 2 Myocardial Infarction in the United States Between 2016 and 2018.

BACKGROUND: The frequency of perioperative myocardial infarction has been declining; however, previous studies have only described type 1 myocardial infarctions. Here, we evaluate the overall frequency of myocardial infarction with the addition of an International Classification of Diseases 10th revision (ICD-10-CM) code for type 2 myocardial infarction and the independent association with in-hospital mortality. METHODS: A longitudinal cohort study spanning the introduction of the ICD-10-CM diagnostic code for type 2 myocardial infarction using the National Inpatient Sample (NIS) from 2016 to 2018. Hospital discharges that included a primary surgical procedure code for intrathoracic, intraabdominal, or suprainguinal vascular surgery were included. Type 1 and type 2 myocardial infarctions were identified using ICD-10-CM codes. We used segmented logistic regression to estimate change in frequency of myocardial infarctions and multivariable logistic regression to determine the association with in-hospital mortality. RESULTS: A total of 360,264 unweighted discharges were included, representing 1,801,239 weighted discharges, with median age 59 and 56% female. The overall incidence of myocardial infarction was 0.76% (13,605/1,801,239). Before the introduction of type 2 myocardial infarction code, there was a small baseline decrease in the monthly frequency of perioperative myocardial infarctions (odds ratio [OR], 0.992; 95% confidence interval [CI], 0.984-1.000; P = .042), but no change in the trend after the introduction of the diagnostic code (OR, 0.998; 95% CI, 0.991-1.005; P = .50). In 2018, where there was an entire year where type 2 myocardial infarction was officially a diagnosis, the distribution of myocardial infarction type 1 was 8.8% (405/4580) ST elevation myocardial infarction (STEMI), 45.6% (2090/4580) non-ST elevation myocardial infarction (NSTEMI), and 45.5% (2085/4580) type 2 myocardial infarction. STEMI and NSTEMI were associated with increased in-hospital mortality (OR, 8.96; 95% CI, 6.20-12.96; P < .001 and OR, 1.59; 95% CI, 1.34-1.89; P < .001). A diagnosis of type 2 myocardial infarction was not associated with increased odds of in-hospital mortality (OR, 1.11; 95% CI, 0.81-1.53; P = .50) when accounting for surgical procedure, medical comorbidities, patient demographics, and hospital characteristics. CONCLUSIONS: The frequency of perioperative myocardial infarctions did not increase after the introduction of a new diagnostic code for type 2 myocardial infarctions. A diagnosis of type 2 myocardial infarction was not associated with increased in-patient mortality; however, few patients received invasive management that may have confirmed the diagnosis. Further research is needed to identify what type of intervention, if any, may improve outcomes in this patient population.

Quantitative metrics of the LV trabeculated layer by cardiac CT and cardiac MRI in patients with suspected noncompaction cardiomyopathy.

OBJECTIVES: To compare cardiac computed tomography (CCT) and cardiac magnetic resonance (CMR) for the quantitative assessment of the left ventricular (LV) trabeculated layer in patients with suspected noncompaction cardiomyopathy (NCCM). MATERIALS AND METHODS: Subjects with LV excessive trabeculation who underwent both CMR and CCT imaging as part of the prospective international multicenter NONCOMPACT clinical study were included. For each subject, short-axis CCT and CMR slices were matched. Four quantitative metrics were estimated: 1D noncompacted-to-compacted ratio (NCC), trabecular-to-myocardial area ratio (TMA), trabecular-to-endocardial cavity area ratio (TCA), and trabecular-to-myocardial volume ratio (TMV). In 20 subjects, end-diastolic and mid-diastolic CCT images were compared for the quantification of the trabeculated layer. Relationships between the metrics were investigated using linear regression models and Bland-Altman analyses. RESULTS: Forty-eight subjects (49.9 ± 12.8 years; 28 female) were included in this study. NCC was moderately correlated (r = 0.62), TMA and TMV were strongly correlated (r = 0.78 and 0.78), and TCA had excellent correlation (r = 0.92) between CMR and CCT, with an underestimation bias from CCT of 0.3 units, and 5.1, 4.8, and 5.4 percent-points for the 4 metrics, respectively. TMA, TCA, and TMV had excellent correlations (r = 0.93, 0.96, 0.94) and low biases (- 3.8, 0.8, - 3.8 percent-points) between the end-diastolic and mid-diastolic CCT images. CONCLUSIONS: TMA, TCA, and TMV metrics of the LV trabeculated layer in patients with suspected NCCM demonstrated high concordance between CCT and CMR images. TMA and TCA were highly reproducible and demonstrated minimal differences between mid-diastolic and end-diastolic CCT images. CLINICAL RELEVANCE STATEMENT: The results indicate similarity of CCT to CMR for quantifying the LV trabeculated layer, and the small differences in quantification between end-diastole and mid-diastole demonstrate the potential for quantifying the LV trabeculated layer from clinically performed coronary CT angiograms. KEY POINTS: • Data on cardiac CT for quantifying the left ventricular trabeculated layer are limited. • Cardiac CT yielded highly reproducible metrics of the left ventricular trabeculated layer that correlated well with metrics defined by cardiac MR. • Cardiac CT appears to be equivalent to cardiac MR for the quantification of the left ventricular trabeculated layer.