Background: In Mozambique, and other low-income countries (LICs), there is little information on the burden of child maltreatment (CM). Emergency care services (ECS) play an important role in recognizing, treating, and intervening in situations of CM. We aim to identify knowledge, attitudes, and practices regarding CM among health care providers in ECS at Mavalane General Hospital in Maputo, Mozambique. Methods: This exploratory cross-sectional study evaluates the knowledge, attitudes, and practices of health care providers to diagnose and treat cases of CM. A 25min, pilot-tested verbal interview questionnaire was administered to 49 physicians and nurses working in ECS at Mavalane General Hospital. Interviews were completed between October-November 2010. Data were managed and analyzed in SPSS 14.0 and descriptive statistics were generated. Results: Of 49 health care providers, 83.6% reporting receiving no, or very little CM education or training. Only 61.2% had knowledge of physical abuse as a main form of child maltreatment and 38.8% were able to identify corresponding symptoms of physical abuse. Sexual abuse as a main form of CM was mentioned by 26.5 and 2% cited its symptoms. While 87.7% of health care providers strongly agreed or agreed that they hold an important role in preventing CM, 51.1% also strongly disagreed or disagreed that they feel confident diagnosing and treating CM cases. In regards to follow-up, 14.3% strongly disagreed or disagreed that they know where to refer victims for further follow-up and an additional 14.3% did not know whether they agreed or disagreed. Conclusion: This study revealed knowledge gaps in emergency health care provider knowledge of the main forms of CM and their symptoms. The fact that a majority of health care providers in our sample did not receive information specific to CM in their medical education and training could explain this gap, as well as their unawareness of where to refer victims. Given that health care providers believe they play an important role in identifying and treating CM, future research should focus on raising physician awareness of CM and developing education and training materials grounded in cultural contexts to build response capacity in Mozambique and other LICs.

Background There is a dearth of information and guidance for healthcare providers on how to manage a patient's return to driving following a mild traumatic brain injury (mTBI). Methods Using the 2020 DocStyles survey, 958 healthcare providers were surveyed about their diagnosis and management practices related to driving after an mTBI. Results Approximately half (52.0%) of respondents reported routinely (more than 75% of the time) talking with patients with mTBI about how to safely return to driving after their injury. When asked about how many days they recommend their patients with mTBI wait before returning to driving after their injury: 1.0% recommended 1 day or less; 11.7% recommended 2-3 days; 24.5% recommended 4-7 days and 45.9% recommended more than 7 days. Many respondents did not consistently screen patients with mTBI for risk factors that may affect their driving ability or provide them with written instructions on how to safely return to driving (59.7% and 62.6%, respectively). Approximately 16.8% of respondents reported they do not usually make a recommendation regarding how long patients should wait after their injury to return to driving. Conclusions Many healthcare providers in this study reported that they do not consistently screen nor educate patients with mTBI about driving after their injury. In order to develop interventions, future studies are needed to assess factors that influence healthcare providers behaviours on this topic.

Objective. Prompt identification and recognization of myocardial ischemia/infarction (MI) is the most important goal in the management of acute coronary syndrome. The 12-lead electrocardiogram (ECG) is widely used as the initial screening tool for patients with chest pain but its diagnostic accuracy remains limited. There is early evidence that machine learning (ML) algorithms applied to ECG waveforms can improve performance. Most studies are designed to classify MI from healthy controls and thus are limited due to the lack of consideration of ECG abnormalities from other cardiac conditions, leading to false positives. Moreover, clinical information beyond ECG has not yet been well leveraged in existing ML models. Approach. The present study considered downstream clinical implementation scenarios in the initial model design by dichotomizing study recordings from a public large-scale ECG dataset into a MI class and a non-MI class with the inclusion of MI-confounding conditions. Two experiments were conducted to systematically investigate the impact of two important factors entrained in the modeling process, including the duration of ECG, and the value of multimodal information for model training. A novel multimodal deep learning architecture was proposed to learn joint features from both ECG and patient demographics. Main results. The multimodal model achieved better performance than the ECG-only model, with a mean area under the receiver operating characteristic curve of 92.1% and a mean accuracy of 87.4%, which is on par with existing studies despite the increased task difficulty due to the new class definition. By investigation of model explainability, it revealed the contribution of patient information in model performance and clinical concordance of the model’s attention with existing clinical insights. Significance. The findings in this study help guide the development of ML solutions for prompt MI detection and move the models one step closer to real-world clinical applications.

Penetrating traumatic brain injury (pTBI) affects civilian and military populations resulting in significant morbidity, mortality, and healthcare costs. No up-to-date and evidence-based guidelines exist to assist modern medical and surgical management of these complex injuries. A preliminary literature search revealed a need for updated guidelines, supported by the Brain Trauma Foundation. Methodologists experienced in TBI guidelines were recruited to support project development alongside two cochairs and a diverse steering committee. An expert multi-disciplinary workgroup was established and vetted to inform key clinical questions, to perform an evidence review and the development of recommendations relevant to pTBI. The methodological approach for the project was finalized. The development of up-to-date evidence- and consensus-based clinical care guidelines and algorithms for pTBI will provide critical guidance to care providers in the pre-hospital and emergent, medical, and surgical settings.

Background: Intracerebral hemorrhage (ICH) is a potentially devastating condition with elevated early mortality rates, poor functional outcomes, and high costs of care. Standard of care involves intensive supportive therapy to prevent secondary injury. To date, there is no randomized control study demonstrating benefit of early evacuation of supratentorial ICH. Methods: The Early Minimally Invasive Removal of Intracerebral Hemorrhage (ENRICH) Trial was designed to evaluate the minimally invasive trans-sulcal parafascicular surgery (MIPS) approach, a technique for safe access to deep brain structures and ICH removal using the BrainPath® and Myriad® devices (NICO Corporation, Indianapolis, IN). ENRICH is a multi-centered, two-arm, randomized, adaptive comparative-effectiveness study, where patients are block randomized by ICH location and Glasgow Coma Score (GCS) to early ICH evacuation using MIPS plus standard guideline-based management vs. standard management alone to determine if MIPS results in improved outcomes defined by the utility-weighted modified Rankin score (UWmRS) at 180 days as the primary endpoint. Secondary endpoints include clinical and economic outcomes of MIPS using cost per quality-adjusted life years (QALYs). The inclusion and exclusion criteria aim to capture a broad group of patients with high risk of significant morbidity and mortality to determine optimal treatment strategy. Discussion: ENRICH will result in improved understanding of the benefit of MIPS for both lobar and deep ICH affecting the basal ganglia. The ongoing study will lead to Level-I evidence to guide clinicians treatment options in the management of acute treatment of ICH. Trial registration: This study is registered with clinicaltrials.gov (Identifier: NCT02880878).

Objective: We sought to determine whether administration of Intravenous Thrombolysis (IVT) to patients with Acute Ischemic Stroke (AIS) within 60 min from hospital arrival is associated with lower 2-year mortality. Methods: This retrospective study was conducted among patients receiving IVT in hospitals participating in the Georgia Coverdell Acute Stroke Registry (GCASR) from January 1, 2008 through June 30, 2018. Two-year mortality data was obtained by linking the 2008–2018 Georgia Discharge Data System data and the 2008–2020 Georgia death records. We analyzed the study population in two groups based on the time from hospital arrival to initiation of IVT expressed as Door to Needle time (DTN) in a dichotomized (DTN ≤ 60 vs. > 60 min) fashion. Results: The median age of patients was 68 years, 49.4% were females, and the median NIHSS was 9. DTN ≤60 min was associated with lower 30-day [odds ratio (OR), 0.62; 95% CI, 0.52–0.73; P < 0.0001], 1-year (OR, 0.71; 95% CI, 0.61–0.83; P < 0.0001) and 2-year (OR, 0.76; 95% CI, 0.65–0.88; P = 0.001) mortality as well as lower rates of sICH at 36 h (OR, 0.57; 95% CI, 0.43–0.75; P = 0.0001), higher rates of ambulation at discharge (OR, 1.38; 95% CI, 1.25–1.53; P < 0.0001) and discharge to home (OR, 1.36; 95% CI, 1.23–1.52; P < 0.0001). Conclusion: Faster DTN in patients with AIS was associated with lower 2-year mortality across all age, gender and race subgroups. These findings reinforce the need for intensifying quality improvement measures to reduce DTN in AIS patients.

Severe traumatic brain injury (TBI) activates a robust systemic response that involves inflammatory and other factors, including estradiol (E2), associated with increased deaths. Tumor necrosis factor-alpha (TNFα) is a significant mediator of systemic shock, and it is an extra-gonadal transcription factor for E2 production. The study objectives were to test the hypotheses: (1) a positive feedback relationship exists between acute serum TNFα and E2; and (2) acute concentrations of E2 and TNFα are prognostic indicators of death after severe TBI. This prospective cohort study included N = 157 adults with severe TBI. Serum samples were collected for the first five days post-injury. The TNFα and E2 levels were averaged into two time epochs: first 72 h (T1) and second 72 h post-injury (T2). A cross-lag panel analysis conducted between T1 and T2 TNFα and E2 levels showed significant cross-lag effects: T1 TNFα and T1 E2 were related to T2 E2 and T2 TNFα, respectively. Cox proportional hazards multi variable regression models determined that increases in T1 E2 (hazard ratio [HR] = 1.79, 95% confidence interval [CI]: 1.15, 2.81), but not T2 E2 (HR = 0.91, 95% CI: 0.56, 1.47), were associated with increased risk of death. Increased T2 TNFα (HR = 2.47, 95% CI: 1.35, 4.53), and T1 TNFα (HR = 1.47, 95% CI: 0.99, 2.19), to a lesser degree, were associated with increased risk of death. Relationships of death with T2 TNFα and T1 E2 were mediated partially by cardiovascular, hepatic, and renal dysfunction. Both E2 and TNFα are systemic, reciprocally related biomarkers that may be indicative of systemic compromise and increased risk of death after severe TBI.

Mild traumatic brain injury (mTBI) remains a diagnostic challenge and therefore strategies for objective assessment of neurological function are key to limiting long-term sequelae. Current assessment methods are not optimal in austere environments such as athletic fields; therefore, we developed an immersive tool, the Display Enhanced Testing for Cognitive Impairment and mTBI (DETECT) platform, for rapid objective neuropsychological (NP) testing. The objectives of this study were to assess the ability of DETECT to accurately identify neurocognitive deficits associated with concussion and evaluate the relationship between neurocognitive measures and subconcussive head impacts. DETECT was used over a single season of two high school and two college football teams. Study participants were instrumented with Riddell Head Impact Telemetry (HIT) sensors and a subset tested with DETECT immediately after confirmed impacts for different combinations of linear and rotational acceleration. A total of 123 athletes were enrolled and completed baseline testing. Twenty-one players were pulled from play for suspected concussion and tested with DETECT. DETECT was 86.7% sensitive (95% confidence interval [CI]: 59.5%, 98.3%) and 66.7% specific (95% CI: 22.3%, 95.7%) in correctly identifying athletes with concussions (15 of 21). Weak but significant correlations were found between complex choice response time (processing speed and divided attention) and both linear (Spearman rank correlation coefficient 0.262, p = 0.02) and rotational (Spearman coefficient 0.254, p = 0.03) acceleration on a subset of 76 players (113 DETECT tests) with no concussion symptoms. This study demonstrates that DETECT confers moderate to high sensitivity in identifying acute cognitive impairment and suggests that football impacts that do not result in concussion may negatively affect cognitive performance immediately following an impact. Specificity, however, was not optimal and points to the need for additional studies across multiple neurological domains. Given the need for more objective concussion screening in triage situations, DETECT may provide a solution for mTBI assessment.

Objectives: Determine the frequency of and the predictive factors for abnormal ocular fundus findings among emergency department (ED) headache patients. Methods: Cross-sectional study of prospectively enrolled adult patients presenting to our ED with a chief complaint of headache. Ocular fundus photographs were obtained using a nonmydriatic fundus camera that does not require pupillary dilation. Demographic and neuroimaging information was collected. Photographs were reviewed independently by 2 neuroophthalmologists for findings relevant to acute care. The results were analyzed using univariate statistics and logistic regression modeling. Results: We included 497 patients (median age: 40 years, 73% women), among whom 42 (8.5%, 95% confidence interval: 6%–11%) had ocular fundus abnormalities. Of these 42 patients, 12 had disc edema, 9 had optic nerve pallor, 6 had grade III/IV hypertensive retinopathy, and 15 had isolated retinal hemorrhages. Body mass index ≥35 kg/m2 (odds ratio [OR]: 2.3, p = 0.02), younger age (OR: 0.7 per 10-year increase, p = 0.02), and higher mean arterial blood pressure (OR: 1.3 per 10-mm Hg increase, p = 0.003) were predictive of abnormal retinal photography. Patients with an abnormal fundus had a higher percentage of hospital admission (21% vs 10%, p = 0.04). Among the 34 patients with abnormal ocular fundi who had brain imaging, 14 (41%) had normal imaging. Conclusions: Ocular fundus abnormalities were found in 8.5% of patients with headache presenting to our ED. Predictors of abnormal funduscopic findings included higher body mass index, younger age, and higher blood pressure. Our study confirms the importance of funduscopic examination in patients with headache, particularly in the ED, and reaffirms the utility of nonmydriatic fundus photography in this setting.

Heart failure (HF) exacerbations, characterized by pulmonary congestion and breathless-ness, require frequent hospitalizations, often resulting in poor outcomes. Current methods for tracking lung fluid and respiratory distress are unable to produce continuous, holistic measures of cardiopulmonary health. We present a multimodal sensing system that captures bioimpedance spectroscopy (BIS), multi-channel lung sounds from four contact microphones, multi-frequency impedance pneumography (IP), temperature, and kinematics to track changes in cardiopulmonary status. We first validated the system on healthy subjects (n = 10) and then conducted a feasibility study on patients (n = 14) with HF in clinical settings. Three measurements were taken throughout the course of hospitalization, and parameters relevant to lung fluid status—the ratio of the resistances at 5 kHz to those at 150 kHz (K)—and respiratory timings (e.g., respiratory rate) were extracted. We found a statistically significant increase in K (p < 0.05) from admission to discharge and observed respiratory timings in physiologically plausible ranges. The IP-derived respiratory signals and lung sounds were sensitive enough to detect abnormal respiratory patterns (Cheyne–Stokes) and inspiratory crackles from patient recordings, respectively. We demonstrated that the proposed system is suita-ble for detecting changes in pulmonary fluid status and capturing high-quality respiratory signals and lung sounds in a clinical setting.