Long-term outcome of retroperitoneoscopic partial versus total adrenalectomy in patients with Cushing's syndrome

BACKGROUND

We analyze the long-term outcome of surgery for Cushing's syndrome (CS) and the influence of the extent of surgical resection on the duration of postoperative cortisone substitution.

METHODS

One-hundred forty-one patients (129 female, 12 males; mean age: 45.7 ± 12.8 years) operated between January 2000 to June 2020 were included in the analysis. Patients suffered from manifest (124) or subclinical (17) CS due to benign unilateral adrenal neoplasia. All tumors were removed by the posterior retroperitoneoscopic approach. 105 patients had total (TA) and 36 partial (PA) adrenalectomies. All patients were discharged with ongoing corticosteroid supplementation therapy.

RESULTS

Follow-up data could be obtained for 83 patients. Twenty-four (1 male, 23 females; mean age 42.3 years) underwent PA and 59 TA (6 males, 53 females; mean age 44.6 years). Mean follow-up time was 107 ± 68 months (range: 6-243 months). The median duration of postoperative corticosteroid therapy was 9.5 months after PA and 11 months after TA (p = 0.1). Significantly, more patients after total adrenalectomy required corticosteroid therapy for more than 24 months (25% vs. 4%; p = 0.03). Recurrent ipsilateral disease occurred in one case after partial adrenalectomy and was treated by completion adrenalectomy. A case of contralateral recurrence associated with subclinical Cushing's syndrome was observed after total adrenalectomy.

CONCLUSIONS

The risk of local recurrence after partial adrenalectomy in CS is low. Cortical-sparing surgery may shorten corticosteroid supplementation therapy after surgery.

Glucose pattern in children with classical congenital adrenal hyperplasia: evidence from continuous glucose monitoring

BACKGROUND

While the risk for hypoglycemia during acute illness is well described in children with classical congenital adrenal hyperplasia (CAH), there is little evidence for the prevalence of asymptomatic hypoglycemia and the daily glucose patterns in CAH. Herein, we explored the daytime glucose profile of children with classical CAH.

METHODS

We conducted an observational study in 11 children (6 female; age 3.1 years [1.4, 5.1]; body mass index 17.3 kg/m2 [15.6, 17.9]) with a genetic diagnosis of classical CAH receiving hydrocortisone and fludrocortisone replacement therapy. Participants underwent 2 14-day continuous glucose monitoring (CGM) sessions and an inpatient 24 h series cortisol and adrenocorticotropic hormone (ACTH) measures. Data were analyzed for 3 daytime lags (7 Am-4 Pm, 4 Pm-10pm, 10 Pm-7 Am) corresponding to the hydrocortisone dosing period with cortisol and ACTH measured before the hydrocortisone dose.

RESULTS

Eleven participants completed at least 1 CGM session, and 7 out of 11 underwent both the CGM session and the cortisol/ACTH serial measures. In the whole cohort, the percentage of time of sensor glucose values <70 mg/dL was higher during the 10 Pm-7 Am and the 7 Am-4 Pm time slots than in the late afternoon period (17% [7, 54] and 15% [6.8, 24] vs 2% [1.1, 16.7] during the periods 7 Am-4 Pm and 4 Pm-10 Pm, respectively [P = .006 and P = .003]). Nighttime hypoglycemia was mostly spent below the 65 mg/dL (10.9% [4.1, 34]). The glycemic pattern paralleled the nadir of daily cortisol at 7 Am (10.3±4.4 μg/dL). A greater percentage of time in hypoglycemia was associated with lower cortisol concentration at 7 Am and 10 Pm (P < .001 and P = .005).

CONCLUSIONS

Continuous glucose monitoring demonstrated a disrupted daily glucose pattern in children with CAH, paralleled by a lower cortisol concentration.

CLINICALTRIALS.GOV REGISTRATION

NCT04322435.

Identifying patient-related predictors of permanent growth hormone deficiency

Objective

Isolated childhood growth hormone deficiency (GHD) can persist into adulthood, and re-testing at the transition period is needed to determine whether continued growth hormone therapy is indicated. Here, our objective was to identify predictors of permanent GHD.

Design

Retrospective single-centre study of patients with childhood-onset GHD who were re-tested after adult height attainment.

Methods

Auxological, clinical, laboratory, and MRI data throughout follow-up were collected.

Results

We included 101 patients. At GH treatment initiation, age was 8.1 ± 0.4 years, height -2.25 ± 0.8, and BMI -0.27 ± 0.1 SDS. The 29 (28.7%) patients with persistent GHD had lower height SDS (-2.57 ± 0.1 vs. -2.11 ± 0.1, p<0.001) and mean GH peaks (8.4 ± 1.0 vs.13.2 ± 0.5 mIU/L, p<0.001) at GHD diagnosis; at adult height, they had lower IGF1 (232 ± 19.9 vs. 331 ± 9.1 ng/mL, p<0.001) and higher BMI SDS (-0.15 ± 0.27 vs. -0.73 ± 0.13, p<0.005). By multivariate analysis, the best predictive model included height and BMI SDS, both GH peaks, and MRI findings at diagnosis. Patients with height at diagnosis <-3 SDS had a 7.7 (95% IC 1.4-43.1, p=0.02) fold higher risk of persistent GHD after adjustment on BMI SDS. An abnormal pituitary region by MRI was the strongest single predictor (7.2 times, 95% CI 2.7-19.8) and after multivariate analysis adjustment for GH peaks and height SDS at diagnosis, the risk increased to 10.6 (1.8 - 61.3) times.

Conclusions

Height <-3 SDS at GHD diagnosis and pituitary MRI abnormalities should lead to a high index of suspicion for persistent GHD.

Assessment of Puberty and Hypothalamic-Pituitary-Gonadal Axis Function After Childhood Brain Tumor Treatment

CONTEXT

Endocrine complications are common in pediatric brain tumor patients.

OBJECTIVE

To describe hypothalamic-pituitary-gonadal axis (HPGA) function in patients treated in childhood for a primary brain tumor more than 5 years earlier, in order to identify risk factors for HPGA impairment.

METHODS

We retrospectively included 204 patients diagnosed with a primary brain tumor before 18 years of age and monitored at the pediatric endocrinology unit of the Necker Enfants-Malades University Hospital (Paris, France) between January 2010 and December 2015. Patients with pituitary adenoma or untreated glioma were excluded.

RESULTS

Among patients with suprasellar glioma not treated by radiotherapy, the prevalence of advanced puberty was 65% overall and 70% when the diagnosis occurred before 5 years of age. Medulloblastoma chemotherapy caused gonadal toxicity in 70% of all patients and in 87.5% of those younger than 5 years at diagnosis. In the group with craniopharyngioma, 70% of patients had hypogonadotropic hypogonadism, which was consistently accompanied by growth hormone deficiency.

CONCLUSION

Tumor type, location, and treatment were the risk main factors for HPGA impairment. Awareness that onset can be delayed is essential to guide information of parents and patients, patient monitoring, and timely hormone replacement therapy.

GH and Childhood-onset Craniopharyngioma: When to Initiate GH Replacement Therapy?

CONTEXT

Craniopharyngioma is a benign brain tumor with frequent local recurrence or progression after treatment. GH replacement therapy (GHRT) is prescribed in children with GH deficiency resulting from childhood-onset craniopharyngioma.

OBJECTIVE

To evaluate whether a shorter delay of GHRT initiation after childhood-onset craniopharyngioma completion therapy increased the risk of a new event (progression or recurrence).

METHODS

Retrospective, observational, monocenter study. We compared a cohort of 71 childhood-onset patients with craniopharyngiomas treated with recombinant human GH (rhGH). Twenty-seven patients were treated with rhGH at least 12 months after craniopharyngioma treatment (>12-month group) and 44 patients before 12 months (<12-month group), among which 29 patients were treated between 6 and 12 months (6-12 month group). The main outcome was the risk of tumor new event (progression of residual tumor or tumor recurrence after complete resection) after primary treatment in the >12-month group and in the <12 month or in the 6- to 12-month group patients.

RESULTS

In the >12-month group, the 2- and 5-year event-free survivals were respectively 81.5% (95% CI, 61.1-91.9) and 69.4% (95% CI, 47.9-83.4) compared with 72.2% (95% CI, 56.3-83.1) and 69.8% (95% CI, 53.8-81.2) in the <12-month group. The 2- and 5-year event-free survivals were the same in the 6- to 12-month group (72.4%; 95% CI, 52.4-85.1). By log-rank test, the event-free survival was not different between groups (P = .98 and P = .91).The median time for event was not statistically different.In univariate and multivariate analysis, the risk of craniopharyngioma new event was not associated with the GHRT time delay after craniopharyngioma treatment.

CONCLUSIONS

No association was found between GHRT time delay after childhood-onset craniopharyngioma treatment and an increased risk of recurrence or tumor progression, suggesting GH replacement therapy can be initiated 6 months after last treatment for craniopharyngiomas.

Late-onset enteric virus infection associated with hepatitis (EVAH) in transplanted SCID patients

BACKGROUND

Allogenic hematopoietic stem cell transplantation (HSCT) and gene therapy (GT) are potentially curative treatments for severe combined immunodeficiency (SCID). Late-onset posttreatment manifestations (such as persistent hepatitis) are not uncommon.

OBJECTIVE

We sought to characterize the prevalence and pathophysiology of persistent hepatitis in transplanted SCID patients (SCIDH+) and to evaluate risk factors and treatments.

METHODS

We used various techniques (including pathology assessments, metagenomics, single-cell transcriptomics, and cytometry by time of flight) to perform an in-depth study of different tissues from patients in the SCIDH+ group and corresponding asymptomatic similarly transplanted SCID patients without hepatitis (SCIDH-).

RESULTS

Eleven patients developed persistent hepatitis (median of 6 years after HSCT or GT). This condition was associated with the chronic detection of enteric viruses (human Aichi virus, norovirus, and sapovirus) in liver and/or stools, which were not found in stools from the SCIDH- group (n = 12). Multiomics analysis identified an expansion of effector memory CD8+ T cells with high type I and II interferon signatures. Hepatitis was associated with absence of myeloablation during conditioning, split chimerism, and defective B-cell function, representing 25% of the 44 patients with SCID having these characteristics. Partially myeloablative retransplantation or GT of patients with this condition (which we have named as "enteric virus infection associated with hepatitis") led to the reconstitution of T- and B-cell immunity and remission of hepatitis in 5 patients, concomitantly with viral clearance.

CONCLUSIONS

Enteric virus infection associated with hepatitis is related to chronic enteric viral infection and immune dysregulation and is an important risk for transplanted SCID patients with defective B-cell function.

POS0464 DIFFERENTIAL MOLECULAR PROFILES IN THE SYNOVIAL TISSUE AND SYNOVIAL FLUID OF PATIENTS WITH RHEUMATOID ARTHRITIS AND PSORIATIC ARTHRITIS

Background

The differential diagnosis of Rheumatoid Arthritis (RA) and Psoriatic arthritis (PsA) is often difficult due to the similarity of symptoms and the unavailability of reliable clinical biomarkers. Molecular alterations have been suggested to contribute to the pathophysiological processes in the knee joint, and it is known that chronic inflammation induces significant changes in the synovial tissue (ST) and synovial fluid (SF) lipidome and proteome.

Objectives

We aimed to evaluate whether specific characteristics in the molecular profiles from ST and SF could support the differential diagnosis of these diseases.

Methods

ST frozen samples of patients affected by RA (n=6), PsA (n=12) and control donors (n=10) were compared using Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) for spatially resolved lipid analysis. To this end, tissue sections were measured on a RapifleX MALDI-TOF/TOF instrument. Next, a targeted approach based on multiple reaction monitoring (MRM-MS) was performed to further validate the lipidomic alterations reported by MALDI-MSI between RA and PsA tissues. In this case, lipids extracted from SF (control donors (n=4), RA (n=21) and PsA (n=27)) were analyzed in a QTRAP 4000 mass spectrometer for the targeted analysis of 84 lipid species. Finally, a quantitative proteomic analysis was carried out on FFPE ST from RA (n=13), PsA (n=13) and controls (n=8) by nLC-MS/MS analysis using a TimsTOF Pro system (Bruker). Statistical analyses were performed using GraphPad Prism, Metaboanalyst and Perseus software.

Results

Lipid profiles in ST from PsA and RA were unequivocally distinguished by MALDI-MSI followed by PCA-DA, and were also different comparing with control tissues. Interestingly, several lipid species, including sphingomyelins, phosphatidylcholines (PC) and phosphatidylethanolamines (PE), presented the greatest separation power to classify RA and PsA tissue samples. ANOVA analysis found 35 lipid species significantly different among the study groups, most of them significantly increased in RA and PsA compared to controls. Particularly, 11 lipids showed higher levels in PsA tissues compared with RA, including several PC and PE. The spatial distribution of these PE species was associated with areas of the sublining layer with increased vascularity and inflammatory cell infiltrates, according to MALDI-MSI images. On the other hand, RA and PsA patients were also correctly classified based on the SF levels of all quantified lipid species according to PCA and clustering analysis. Finally, the proteomic analysis quantified around 2,500 distinct proteins in the ST, including several related with lipid metabolism. Near 300 proteins showed altered abundance in the pathological tissues compared to healthy controls (FDR 0.01%, Figure 1A), being the small subset increased in controls mainly extracellular matrix proteins. The comparison between RA and PsA ST led to the identification of a panel of 36 proteins discriminating the two tissues with high statistical significance (p-value <0.01). In this comparison, all proteins except two appeared increased in RA (Figure 1B). A discriminant analysis shows the usefulness of this protein panel to differentiate the two diseases (Figure 1C).

Figure 1.

Results from the proteomic analysis carried out on synovial tissues. A) Heatmap showing the differential protein profiles between synovial tissues (PsA and RA) and healthy controls (CTL), at FDR 0.01. B) Characteristic protein panel discriminating PsA and RA tissues (p-value < 0.01). C) Discriminant analysis performed using this protein panel.

Conclusion

Our study shows distinct molecular profiles between RA and PsA synovial tissue and synovial fluid, and reports potential clinically useful lipid and protein markers for the differential diagnosis of these diseases.

Disclosure of Interests

None declared.

High Prevalence of Early Endocrine Disorders After Childhood Brain Tumors in a Large Cohort

CONTEXT

Endocrine complications are common in pediatric brain tumor patients.

OBJECTIVE

We aimed to describe the endocrine follow-up of patients with primary brain tumors.

METHODS

This is a noninterventional observational study based on data collection from medical records of 221 patients followed at a Pediatric Endocrinology Department.

RESULTS

Median age at diagnosis was 6.7 years (range, 0-15.9), median follow-up 6.7 years (0.3-26.6), 48.9% female. Main tumor types were medulloblastoma (37.6%), craniopharyngioma (29.0%), and glioma (20.4%). By anatomic location, 48% were suprasellar (SS) and 52% non-suprasellar (NSS). Growth hormone deficiency (GHD) prevalence was similar in both groups (SS: 83.0%, NSS: 76.5%; P = 0.338), appearing at median 1.8 years (-0.8 to 12.4) after diagnosis; postradiotherapy GHD appeared median 1.6 years after radiotherapy (0.2-10.7). Hypothyroidism was more prevalent in SS (76.4%), than NSS (33.9%) (P < 0.001), as well as ACTH deficiency (SS: 69.8%, NSS: 6.1%; P < 0.001). Early puberty was similar in SS (16%) and NSS (12.2%). Hypogonadotropic hypogonadism was predominant in SS (63.1%) vs NSS (1.3%), P < 0.001, and postchemotherapy gonadal toxicity in NSS (29.6%) vs SS (2.8%), P < 0.001. Adult height was lower for NSS compared to target height (-1.0 SD, P < 0.0001) and to SS patients (P < 0.0001). Thyroid nodules were found in 13/45 patients (28.8%), including 4 cancers (4.8-11.5 years after radiotherapy). Last follow-up visit BMI was higher in both groups (P = 0.0001), and obesity incidence was higher for SS (46.2%) than NSS (17.4%).

CONCLUSION

We found a high incidence of early-onset endocrine disorders. An endocrine consultation and nutritional evaluation should be mandatory for all patients with a brain tumor, especially when the tumor is suprasellar or after hypothalamus/pituitary irradiation.

Diabetes Mellitus in Prader-Willi Syndrome: Natural History during the Transition from Childhood to Adulthood in a Cohort of 39 Patients

Type 2 diabetes mellitus (T2DM) affects 20% of patients with Prader-Willi syndrome (PWS), with many cases diagnosed during the transition period. Our aim was to describe the natural history of T2DM in patients with PWS before the age of 25 years and to develop screening and preventive strategies. Thirty-nine patients followed in the French PWS Reference Center were included (median age 25.6 years [23.7; 31.7]). Twenty-one had been treated with growth hormone (GH), fifteen had not, and three had an unknown status. The median age at T2DM diagnosis was 16.8 years (11–24) and the median BMI was 39 kg/m² [34.6; 45], with 34/35 patients living with obesity. The patients displayed frequent psychiatric (48.3% hospitalization,) and metabolic (56.4% hypertriglyceridemia,) comorbidities and a parental history of T2DM (35.7%) or overweight (53.6%) compared to the PWS general population. There was no difference in BMI and metabolic complications between the GH-treated and non-GH-treated groups at T2DM diagnosis. Patients with PWS who develop early T2DM have severe obesity, a high frequency of psychiatric and metabolic disorders, and a family history of T2DM and overweight. These results underline the need for early identification of patients at risk, prevention of obesity, and repeated blood glucose monitoring during the transition period.

Transcatheter aortic valve replacement in severe aortic stenosis and cardiac amyloidosis: a systematic review and meta-analysis

Background

Aortic stenosis (AS) and cardiac amyloidosis (CA) are typical degenerative diseases of the elderly. According to recent studies, up to 16% of patients referred to transcatheter aortic valve replacement (TAVR) have a concomitant diagnosis of CA. Until recently, TAVR in patients with CA and AS has been considered futile, following the results of small observational studies. However, few studies recently suggested a beneficial impact of TAVR in patients with AS and CA as compared with medical therapy alone.

Purpose

To clarify the efficacy and safety profile of TAVR in CA-AS patients.

Methods

We performed a systematic review and meta-analysis of studies evaluating the risk of mortality after TAVR in CA-AS patients as compared with medical therapy. Moreover, we performed a systematic review and descriptive meta-analysis of studies reporting outcomes and complication rates of TAVR in CA-AS patients as compared with patients with AS alone.

Results

We identified 4 observational studies reporting data on mortality in CA-AS patients treated with either TAVR or medical therapy. Mortality was significantly lower in patients undergoing TAVR (OR 0.23, 95% CI 0.07–0.73, I2=0%, NNT=2.6) as compared with medical therapy. A sensitivity analysis with hazard ratio as effect estimate showed consistent results. Then, we identified 4 observational studies reporting data on mortality, re-hospitalizations and periprocedural complications of TAVR in CA-AS patients as compared with patients with AS alone. We found higher rates of mortality, cardiovascular hospitalization and need for permanent pacemaker implantation in CA-AS patients as compared to lone AS patients undergoing TAVR. Conversely, no differences were found in terms of stroke, acute kidney injury and vascular complications.

Conclusions

Our analysis rejects the idea of futility of TAVR in CA-AS patients showing a clear survival benefit of CA-AS patients undergoing TAVR as compared with medical therapy. Moreover, these patients may undergo TAVR with an acceptable procedural risk, that is substantially comparable to lone AS patients, except for a higher incidence of permanent pacemaker implantation.

Funding Acknowledgement

Type of funding sources: None.

Paradoxical low severity of COVID-19 in Prader-Willi syndrome: data from a French survey on 647 patients

BACKGROUND

Patients with Prader-Willi syndrome (PWS) often have comorbidities, especially obesity, that may constitute a risk factor for severe forms of COVID-19. We aimed to assess prevalence and medical course of SARS-CoV-2 infection in children and adults with PWS. From November 2020 to January 2021, we performed a detailed medical survey on 342 adults and 305 children with PWS followed in the French reference center.

RESULTS

We obtained responses from 288 adults (84%) and 239 children (78%). From March 2020 to January 2021, 38 adults (13.2%) and 13 children (5.4%) with PWS had SARS-CoV-2 infection. Mean age of adults was 34.1 ± 11.9 years and mean body mass index was 40.6 ± 12.7 kg/m2; 82% had obesity and 37% had diabetes. Only 3 children (23%) had obesity and none had diabetes. Similar to the general population, the most frequent symptoms of COVID-19 were asthenia, fever, cough, headache and shortness of breath. All patients had a favorable outcome.

CONCLUSION

PWS itself is not a risk factor for severe COVID-19 in children and adults. On the contrary, evolution of SARS-CoV-2 infection in adults with PWS seems more favorable than expected, given their comorbidities.

Transition of young adults with endocrine and metabolic diseases: the 'TRANSEND' cohort

OBJECTIVE

The transition from paediatric to adult medicine involves risks of poor patient outcomes and of significant losses of patients to follow up. The research aimed to analyse the implementation in an initial cohort of patients of a new programme of transition to adult care based on a case management approach.

DESIGN

A longitudinal study of the case management approach to transition, initiated in a university hospital in France in September 2016.

METHODS

Patients with the endocrine or metabolic disease diagnosed during childhood and transferred to adult care were included. The transition programme includes three steps based on case management: liaising with paediatric services, personalising care pathways, and liaising with structures outside the hospital (general practitioners, agencies in the educational and social sector).

RESULTS

The cohort included 500 patients, with malignant brain tumour (n = 56 (11%)), obesity (n = 55 (11%)), type 1 diabetes (n = 54 (11%)), or other disease (n = 335 (67%)). Their median age at transfer was 19, and the sex ratio was 0.5. At median 21 months of follow-up, 439 (88%) had a regular follow-up in or outside the hospital, 47 (9%) had irregular follow-up (absence at the last appointment or no appointment scheduled within the time recommended), 4 had stopped care on doctor's advice, 4 had died, 3 had moved, and 3 had refused care. The programme involved 9615 case management actions; 7% of patients required more than 50 actions. Patients requiring most support were usually those affected by a rare genetic form of obesity.

CONCLUSIONS

Case managers successfully addressed the complex needs of patients. Over time, the cohort will provide unprecedented long-term outcome results for patients with various conditions who experienced this form of transition.

Enhancing AI-guided STEMI detection algorithms by incorporating higher quality fiduciary EKG elements

Background

As EKG interpretation paradigms to a physician-free milieu, accumulating massive quantities of distilled pre-processed data becomes a must for machine learning techniques. In our pursuit of reducing ischemic times in STEMI management, we have improved our Artificial Intelligence (AI)-guided diagnostic tool by following a three-step approach: 1) Increase accuracy by adding larger clusters of data. 2) Increase the breadth of EKG classifications to provide more precise feedback and further refine the inputs which ultimately reflects in better and more accurate outputs. 3) Improving the algorithms' ability to discern between cardiovascular entities reflected in the EKG records.

Purpose

To bolster our algorithm's accuracy and reliability for electrocardiographic STEMI recognition.

Methods

Dataset: A total of 7,286 12-lead EKG records of 10-seconds length with a sampling frequency of 500 Hz obtained from Latin America Telemedicine Infarct Network from April 2014 to December 2019. This included the following balanced classes: angiographically confirmed STEMI, branch blocks, non-specific ST-T abnormalities, normal, and abnormal (200+ CPT codes, excluding the ones included in other classes). Labels of each record were manually checked by cardiologists to ensure precision (Ground truth). Pre-processing: First and last 250 samples were discarded to avoid a standardization pulse. Order 5 digital low pass filters with a 35 Hz cut-off was applied. For each record, the mean was subtracted to each individual lead. Classification: Determined classes were “STEMI” and “Not-STEMI” (A combination of randomly sampled normal, branch blocks, non-specific ST-T abnormalities and abnormal records – 25% of each subclass). Training & Testing: A 1-D Convolutional Neural Network was trained and tested with a dataset proportion of 90/10, respectively. The last dense layer outputs a probability for each record of being STEMI or Not-STEMI. Additional testing was performed with a subset of the original complete dataset of unconfirmed STEMI. Performance indicators (accuracy, sensitivity, and specificity) were calculated for each model and results were compared with our previous findings from past experiments.

Results

Complete STEMI data: Accuracy: 95.9% Sensitivity: 95.7% Specificity: 96.5%; Confirmed STEMI: Accuracy: 98.1% Sensitivity: 98.1% Specificity: 98.1%; Prior Data obtained in our previous experiments are shown below for comparison.

Conclusion(s)

After the addition of clustered pre-processed data, all performance indicators for STEMI detection increased considerably between both Confirmed STEMI datasets. On the other hand, the Complete STEMI dataset kept a strong and steady set of performance metrics when compared with past results. These findings not only validate the consistency and reliability of our algorithm but also connotes the importance of creating a pristine dataset for this and any other AI-derived medical tools.

Funding Acknowledgement

Type of funding source: None

Waddling beyond door to balloon times and impinging true ischemic times with artificial intelligence-guided single lead EKG for STEMI detection

Background

The present process of STEMI detection is cumbersome as it utilizes outdated equipment and requires a trained technician and an expert cardiologist. We have developed a patient-administered, Artificial Intelligence (AI) guided, Single Lead EKG for early STEMI detection.

Purpose

To answer the question “Is early STEMI detection possible with a Single Lead EKG?”

Methods

We experimented with an AI-guided algorithm for a single-lead EKG for STEMI detection with the following step-wise developments: 1) An AI algorithm that predictably interprets STEMI using a 12-lead EKG; 2) An AI algorithm for STEMI detection using a single-lead EKG; 3) A methodology for identifying the best single lead to detect STEMI; 4) Advanced AI algorithms for STEMI localization with a single-lead EKG. The AI methodology was as follows: Sample: The mammoth Latin American Telemedicine Infarct Network telemedicine database that provides an umbrella of AMI management to 100 million patients in Brazil, Colombia, Mexico, Chile, and Argentina was queried for cardiologist annotated EKG. A total of 8,511 EKG and 90,592 classified heartbeats were selected for the experiments. Preprocessing: segmentation of each ECG into individual heartbeats. Training & Testing: 90% and 10%, respectively, of the total dataset. Classification: 1-D Convolutional Neural Network; classes were construed for each heartbeat. Performance indicators were calculated per lead.

Results

The algorithm was able to provide an accuracy of 91.9%. Lead V2 yielded the best results among individual leads for STEMI detection.

Conclusions

Early experiments provide a framework for augmenting STEMI detection with the use of AI-guided, single lead techniques. Such approaches seem rational as we target the reduction of true STEMI ischemic times.

Funding Acknowledgement

Type of funding source: None

Maximum artificial intelligence and complete reconstruct of population-based AMI care

Background

After creating a behemoth hub and spoke AMI network that encompasses more than 100 million patients in 5 countries, we have begun to incorporate Artificial Intelligence (AI) algorithms into our telemedicine strategy with the goal of creating comprehensive, very early AMI diagnosis and physician-free triage. In doing so, we have replaced door-to-balloon times (d2b) with symptom-to-balloon times (s2b) as an immutable objective.

Purpose

To incorporate AI attributes for very early AMI detection, triage, and management.

Methods

We expanded our effective telemedicine strategy (100 million population; 877,178 telemedicine encounters; 55% overall mortality reduction; $291 million cost savings) with a logistic reset to impact s2b. To do this, we incorporated our Single Lead 1.0 (lead I) and Single Lead 2.0 (lead V2) technology for self-administered AMI detection with our physician-free STEMI diagnosis and triage AI algorithms. Single Lead algorithms and physician-free protocols were generated by utilizing Machine Learning from our mammoth annotated EKG repository.

Results

In addition to three logistic markers of efficiency Time-to-Telemedicine Diagnosis (TTD), Door-In-Door-Out (DIDO) and Transfer Times (TT); we are monitoring s2b. A gradual release of the algorithms and single lead is occurring at the telemedicine spokes. Detailed results will be available at the time of presentation.

Conclusions

Impacting s2b, the Achilles Heel of Primary PCI, may be achieved with the use of patient-administered AMI detection tools. Incorporation of these technologies into AI algorithms will add to telemedicine efficiencies for population-based AMI care.

Funding Acknowledgement

Type of funding source: None

Moving in sync – concordance betweena artificial intelligence and cardiologist on detecting normal electrocardiograms

Background

Merging modern technologies with classic diagnostic tests often results in a sense of insecurity within the medical community, particularly so with potentially life-saving studies such as the electrocardiogram (EKG). In order to provide a greater sense of trust between Artificial Intelligence (AI) and cardiologists, we provide an AI-driven algorithm capable of accurately and reliably characterize an EKG as normal within a highly complex, cardiologist-reviewed EKG database and report the degree of concordance between this machine vs physician scenario.

Purpose

To provide a dependable and accurate AI algorithm that conducts EKG interpretation in a cardiologist-tier manner.

Methods

The International Telemedical System (ITMS) developed and tested an EKG assessing AI algorithm and incorporated it into the workflow of their Telemedicine Integrated Platform, a digital EKG reading program where cardiologists continuously report their findings remotely in real-time. During the month of April 2,019; 35 ITMS cardiologists reported a grand total of 61,441 EKG records, later submitting them to the AI algorithm implemented through the “One Click Report” process. Through this simple 2-step approach, the algorithm provides a suggestion of “Normal” or “Abnormal” to the cardiologist based on the patterns of the fiducial points included in said EKG reports. Confirmation of these suggestions by the cardiologists ensued.

Results

Overall, cardiologists confirmed 23,213 out of 25,013 AI outputs for “Normal” EKGs, demonstrating a concordance of 92.8% for Normal diagnosis.

Conclusion

Through this methodology, we provide an AI technology that can be reliably applied and trusted in EKG digital platforms to identify and suitably label a normal EKG. Further testing will accrue into a multi label algorithm compatible with abnormal cardiovascular entities, potentially precluding the role of the cardiologist for triaging, particularly in the prehospital setting. We anticipate that this approach will become a promising methodology in modern cardiology practice.

Funding Acknowledgement

Type of funding source: None

Innovative techniques to construct powerful artificial intelligence algorithms for st-elevation myocardial infarction

Background

With the sudden advent of Artificial Intelligence (AI), incorporation of these technologies into key aspects of our working environment has become an ever so delicate task, especially so when dealing with time-sensitive and potentially lethal scenarios such as ST-Elevation Myocardial Infarction (STEMI) management. By further expanding into our successful experiences with AI-guided algorithms for STEMI detection, we implemented an innovative ensemble method into our methodology as we seek to improve the algorithm's predictive capabilities.

Purpose

Through the ensemble method, we combined two ML techniques to boost our previous experiments' accuracy and reliability.

Methods

Database: EKG records obtained from Latin America Telemedicine Infarct Network (Mexico, Colombia, Argentina, and Brazil) from April 2014 to December 2019. Dataset: Two separate datasets were used to train and test two sets of AI algorithms. The first comprised of 11,567 records and the second 7,286 records, each composed of 12-lead EKG records of 10-second length with sampling frequency of 500 Hz, including the following balanced classes: unconfirmed & angiographically confirmed STEMI (first model); angiographically confirmed STEMI only (second model); and, for both models, we included branch blocks, non-specific ST-T abnormalities, normal, and abnormal (200+ CPT codes, excluding the ones included in other classes). Label per record was manually checked by cardiologists to ensure precision (Ground truth). Pre-processing: First and last 250 samples were discarded to avoid a standardization pulse. An order 5 digital low pass filter with a 35 Hz cut-off was applied. For each record, the mean was subtracted to each individual lead. Classification: The determined classes were STEMI and Not-STEMI (A combination of randomly sampled normal, branch blocks, non-specific ST-T abnormalities and abnormal records – 25% of each subclass). Training & Testing: The last dense layer outputs a probability for each record of being STEMI or Not-STEMI. These probabilities were calculated for each model (Model 1 trained with Complete STEMI dataset and Model 2 trained with confirmed STEMI only dataset) and aggregated using the mean aggregation to generate the final label for each record. A 1-D Convolutional Neural Network was trained and tested with a dataset proportion of 90%/10%; respectively. Results are reported for both testing datasets (Complete and confirmed STEMI only records).

Results

Complete STEMI Dataset: Accuracy: 96.5% Sensitivity: 96.2% Specificity: 96.9% – Confirmed STEMI only Dataset: Accuracy: 98.5% Sensitivity: 98.3% Specificity: 98.6%'

Conclusion(s)

While Model 1 and Model 2 achieved similar performances with promising results on their own, applying a combination of both through the ensemble model exhibits a clear improvement in performance when applied to both datasets. This provides a blueprint for advanced automated STEMI detection through wearable devices.

Funding Acknowledgement

Type of funding source: None

Artificial intelligence methodology: multi-label classification of abnormal EKG records

Background

Our previous experience with Artificial Intelligence (AI)-conducted EKG characterization displayed outstanding results in fast and reliable identification of Normal EKGs within the International Telemedical System (ITMS)'s massive record repository. By expanding the array of recognizable cardiovascular entities, we upgraded our methodology to accurately discriminate an anomaly amongst a highly complex database of EKG records.

Purpose

To present a feasible AI-guided filter that can accurately discriminate and classify Normal and Abnormal EKG records within a multilabeled cardiologist-annotated EKG database.

Methods

ITMS developed and tested the “One Click”' process, a “Normal/Abnormal” EKG assessing AI algorithm, by incorporating it into their digital EKG reading platform where cardiologists continuously report their findings remotely in real time. To ameliorate the diagnostic range of the algorithm, a separate dataset of 121,641 12-lead EKG records was consolidated from the ITMS database from October 2011 to January 2019. Only de-identified data was used. Preprocessing: The first 2s of each short lead and 9s of the long lead were considered. Limb leads I, II and III; and precordial leads V1, V2, V3, and V5 were used. The mean was removed from each lead. AI models/Classification: Two models were created and tested independently based on the method of EKG acquisition (69,852 records transtelephonic [TTP]; 52,259 mobile transmission [MOB]). Each record is categorized into six disjoint classes based on the most common types of cardiac disorders (Low/null co-occurrence pathologies in these datasets were grouped into analogous groups). Training/Testing: Distribution of both sets per transmission type was performed through a greedy algorithm, which identified multiple diagnoses per EKG record and labeled it separately to the corresponding group, ensuring sufficient samples per class. Detailed class distribution is shown below. An inception convolutional neural network was implemented; “Normal” or “Abnormal” labels were assigned to each EKG record independently and were compared to cardiologists' reports; performance indicators were calculated for each model and group.

Results

MOB model accrued an average accuracy of 86.7%; sensitivity of 90.5%; and specificity of 83.9%. TTP model yielded an average accuracy of 77.2%; sensitivity of 91.1%; and specificity of 69.4% (Lower values were attributed to the “Ventricular Complexes” group, which challenged the algorithm by having a smaller ratio of abnormal exams). Detailed results of each training set are shown below.

Conclusion

Providing an effective and reliable multilabel-capable EKG triaging tool remains a challenging but attainable goal. Continuous systematic enhancement of our AI-driven methodology has led us to satisfactory, yet imperfect results which compel us to further study and improve our efforts to provide a trustworthy cardiologist-friendly triage device.

Funding Acknowledgement

Type of funding source: None

Change in renal function post-nephrectomy for renal cell carcinoma in patients with and without hypertension and/or diabetes

BACKGROUND

The standard of care for surgically resectable disease renal cell carcinoma (RCC) is a nephrectomy. Post-nephrectomy, these patients are at risk for the development of new onset chronic kidney disease or the progression of pre-existing chronic kidney disease. We aimed to report the changes in renal function in patients who had a nephrectomy for RCC.

METHODS

This retrospective, descriptive, cross-sectional study identified 137 patients who had a nephrectomy for RCC from 1 January 2009 to 31 December 2017. The pre-nephrectomy and post-nephrectomy estimated glomerular filtration rate (eGFR) and the histological subtype of RCC on histopathological analysis of the resected specimen were recorded from the National Health Laboratory Services online results platform. All analyses were conducted using SPSS (Version 25) and the significance level was set at p < 0.05.

RESULTS

After a mean follow-up period of 26.5 ± 22 months (median = 19 months), the patients' eGFR dropped by a mean of 4.82 ± 8.67 ml/min/1.73 m2 (95% CI 3.23-6.41) post-nephrectomy. The mean eGFR fall in patients' who had hypertension and/or diabetes (n = 63) was significantly larger compared to patients who had neither of these comorbidities (n = 54; p < .001; mean = 7.30 ± 8.40 ml/min/1.73 m2 (95% CI 5.19-9.42) and 1.93 ± 8.14 ml/min/1.73 m2 (95% CI 0.30-4.15) respectively.

CONCLUSIONS

The decline in renal function in patients with hypertension and/or diabetes mellitus is more pronounced than in patients with neither of these comorbidities. In these high-risk patients, measures must be taken to prevent the development and limit the progression of chronic kidney disease.

Hypophosphatemic rickets: A rare complication of congenital melanocytic nevus syndrome

We report the case of a child who presented with a giant melanocytic nevus with numerous satellite nevi at birth and developed hypophosphatemic rickets due to excessive secretion of the FGF23 hormone. A NRAS c.182A>G (Q61R) mutation was identified in the lesional skin. The functional outcome was favorable with medical treatment.

High Diagnostic Yield of Targeted Next-Generation Sequencing in a Cohort of Patients With Congenital Hypothyroidism Due to Dyshormonogenesis

OBJECTIVE

To elucidate the molecular cause in a well-characterized cohort of patients with Congenital Hypothyroidism (CH) and Dyshormonogenesis (DH) by using targeted next-generation sequencing (TNGS).

STUDY DESIGN

We studied 19 well-characterized patients diagnosed with CH and DH by targeted NGS including genes involved in thyroid hormone production. The pathogenicity of novel mutations was assessed based on in silico prediction tool results, functional studies when possible, variant location in important protein domains, and a review of the recent literature.

RESULTS

TNGS with variant prioritization and detailed assessment identified likely disease-causing mutations in 10 patients (53%). Monogenic defects most often involved TG, followed by DUOXA2, DUOX2, and NIS and were usually homozygous or compound heterozygous. Our review shows the importance of the detailed phenotypic description of patients and accurate analysis of variants to provide a molecular diagnosis.

CONCLUSIONS

In a clinically well-characterized cohort, TNGS had a diagnostic yield of 53%, in accordance with previous studies using a similar strategy. TG mutations were the most common genetic defect. TNGS identified gene mutations causing DH, thereby providing a rapid and cost-effective genetic diagnosis in patients with CH due to DH.

Sleep-disordered breathing in children with pycnodysostosis

Upper airway obstruction is a common feature in pycnodysostosis and may cause obstructive sleep apnea (OSA). The aim of our study was to analyze sleep-disordered breathing and respiratory management in children with pycnodysostosis. A retrospective review of the clinical charts and sleep studies of 10 consecutive children (three girls and seven boys) with pycnodysostosis seen over a time period of 10 years was performed. Six patients had severe OSA and/or nocturnal hypoventilation and were started on continuous positive airway pressure (CPAP) as a first treatment at a median age of 3.4 ± 2.6 years, because of the lack of indication of any surgical treatment. Three patients could be weaned after several years from CPAP after spontaneous improvement (two patients) or multiple upper airway surgeries (one patient). Three patients had upper airway surgery prior to their first sleep study with two patients still needing CPAP during their follow-up. Only one patient never developed OSA. Patients with pycnodysostosis are at a high risk of severe OSA, underlying the importance of a systematic screening for sleep-disordered breathing. Multidisciplinary care is mandatory because of the multilevel airway obstruction. CPAP is very effective and well accepted for treating OSA.

Causes of death in Prader-Willi syndrome: lessons from 11 years' experience of a national reference center

Background

In the last 20 years, substantial improvements have been made in the diagnosis, treatment and management of patients with Prader-Willi syndrome (PWS). Few data on causes of death are available since those improvements were made. Our study assessed the causes of death among French patients with PWS over the first 11 years of experience of the nationwide French Reference Center for PWS (FRC-PWS).

Methods

Our study relied on two sources of mortality information at national level between 2004 and 2014: The French Epidemiological Centre for the Medical Causes of Death (CépiDc) Registry and the FRC-PWS database. Causes of death were classified into seven categories: respiratory, cardiovascular, gastrointestinal, severe infection, sudden death, other causes, and unknown. Descriptive statistics were calculated separately for children (< 18 years-old) and adults (≥18 years-old).

Results

One hundred and four deaths were identified in France from 2004 to 2014. The median age at death was 30 years, ranging from less than 1 month to 58 years. Seventeen deaths occurred in patients under 18 years, with 70% of them in children under 2 years. Respiratory causes accounted for more than 50% of the deaths in patients with PWS in both children and adults. Both cause and age of death did not significantly differ according to gender or genetic subtype.

Conclusions

Patients with PWS die prematurely due to a respiratory cause in most cases at all ages. In those adult patients with data on obesity, 98% were reported to be obese.

Effect of topiramate on eating behaviours in Prader-Willi syndrome: TOPRADER double-blind randomised placebo-controlled study

Prader-Willi Syndrome (PWS) is a rare genetic syndrome leading to severe behavioural disorders and mild cognitive impairment. The objective of this double-blind randomised placebo-controlled trial was to study the efficacy and tolerance of topiramate on behavioural disorders in patients with PWS. Participants (aged 12-45 years) had genetically confirmed PWS and severe irritability/impulsivity, eating disorders and/or obesity, and skin picking. Thirty-two participants received a placebo (PBO), and 30 participants received topiramate (TOP) (50-200 mg/day) for 8 weeks. The primary outcome was the rate of responders using the Clinical Global Impression-Improvement (CGI-I) scale. The secondary outcome measures included the Aberrant Behaviour Checklist, the Dykens Hyperphagia Questionnaire (DHK), the Self-Injurious Behaviour Scale (SIBS) and the body mass index (BMI). We found no significant difference in the primary outcome (the CGI-I): 9 (30%) patients were very much or much improved in the TOP group compared to 7 (22.6%) patients in the PBO group. However, the DHK behaviour and severity scores improved significantly more over time in patients treated with topiramate versus those receiving a placebo, with a significant dose-effect relationship. DHK scores were also significantly associated with genetic subtypes and hospitalisation status. The effects of topiramate on eating behaviours remained significant after adjusting for genetic subtype and hospitalisation. Topiramate had therefore a significant effect on eating disorders, with a dose-effect relationship. Given the burden of eating disorders in PWS, we believe that topiramate may become the first psychotropic option within the global care of obesity in individuals with PWS.

P6422Physician vs machine: an innovative ST-elevation myocardial infarction pathway through artificial intelligence

Background

The diagnosis of ST-Elevation Myocardial Infarction (STEMI) has traditionally relied on a cardiologist's interpretation of an Electrocardiogram (EKG). This cumbersome process is costly, inefficient and out of date. Artificial Intelligence (AI) -guided algorithms can provide point-of-care, accurate STEMI diagnosis that will facilitate STEMI management.

Purpose

To demonstrate the feasibility of an automated AI-guided EKG analysis for STEMI diagnosis.

Methods

An observational, retrospective, case-control study. Sample: 8,511 EKG cardiologist-annotated records, including 4,255 STEMI cases. Records excluded patient and medical information. The sample was derived from the private International Telemedical Systems (ITMS) database. LUMENGT-AI Algorithm was employed. Preprocessing: detection of QRS complexes by wavelet system, segmentation of each EKG into individual heartbeats (90,592 total beats) with fixed window of 0.4s to the left and 0.9s to the right of main QRS; Classification: A 1-D convolutional neural network was implemented, “STEMI” and “Not-STEMI” classes were considered for each heartbeat, individual probabilities were aggregated to generate the final label for each record. Training & Testing: 90% and 10% of the sample were used, respectively. Experiments: Intel PC i7 8750H processor at 2.21GHz, 16GB RAM, Windows 10 OS with NVidia GTX 1070 GPU, 8GB RAM.

Results

The model achieved an accuracy of 96.5%, with a sensitivity of 96.3%, and a specificity of 96.8%.

Conclusion(s)

1) AI-guided interpretation of the EKG can reliably diagnose STEMI; 2) AI algorithms can be incorporated into ambulance systems for pre-hospital diagnosis, single page activation, emergency department bypass, facilitating more efficient STEMI pathways.

P1524Women are from venus and face barriers for AMI treatment

Background

The Latin American Telemedicine Infarct Network (LATIN), a program for managing population-based AMI care, has utilized an innovative hub-spoke strategy and remote guidance to expand medical access in remote parts of Brazil, Colombia, Mexico, and Argentina. Based on the Global Lumen Organization for Women (GLOW) project, that has previously demonstrated gender inequalities and worse outcomes for women who undergo Primary PCI, our research explored the management of female patients in our network.

Purpose

To demonstrate gender disparities in a telemedicine-guided, population based AMI program.

Methods

Meta-analysis of >750,000 patients within LATIN. Telemedicine was employed as a screening tool to accurately diagnose AMI. According to the duration of chest pain and transfer time, AMI patients were triaged into guidelines-based pathways of thrombolysis, pharmaco-invasive management or Primary PCI. Resource allocation was identical for men and women.

Results

Data from 784,395 screened patients reveals broad gender disparities. The critical results yielded that female patients have a lower prevalence of STEMI diagnosis and treatment regardless of the technique – PCI, pharmaco-invasive or CABG (p<0.01). These findings assume more significance given the fact that more women than men, were screened through the Telemedicine pathway.

Conclusions

LATIN gender data signals the urgency to demand better AMI care for women.

P3352Telemedicine transcends national boundaries in quest of creating a behemoth ami program

Background

The Latin America Telemedicine Infarct Network (LATIN) has exploited the remarkable competence of telemedicine for remote guidance. In doing so, LATIN created a mammoth population-based AMI network that employed experts located several hundred miles away to guide the reperfusion strategies for almost 800,000 screened patients. In this pioneering project, telemedicine was initially utilized to guide AMI management within national confines. We speculated whether LATIN telemedicine navigation could outstrip countrywide borders.

Purpose

To maximally harness the vast possibilities of telemedicine for improving AMI care.

Methods

During its pilot phase, LATIN began as a hub and spoke, AMI system in Colombia where 20 spokes (small community health centers and rural clinics) were configured with 3 hubs that could perform Primary PCI. These sites were linked through web-based connectivity. Expert cardiologists, located 50–250 miles away in Bogota, Colombia, used sophisticated telemedicine platforms for urgent EKG diagnosis and teleconsultation of the entire AMI process. Based upon the duration of chest pain and travel time to the hub, these experts guided patients through guideline-based strategies of thrombolysis, pharmaco invasive management or primary PCI. Efficiency of the telemedicine process was measured with the new metric of time to telemedicine diagnosis (TTD). Cloud computing, GPS navigation, and numerous business intelligent tools were gradually incorporated into LATIN telemedicine. As systems became more scalable, the program was expanded to Brazil, where LATIN flourished. Over the last 18 months, LATIN telemedicine capabilities have been pressed across national boundaries. Presently, all 82 LATIN centers in Mexico are guided by experts located in Bogota, Colombia and the 7 Argentina centers channeled through Santiago, Chile.

Results

784,947 patients were screened for AMI at 350 LATIN centers (Brazil 143, Colombia 118, Mexico 82, Argentina 7). Navigation pathways are depicted in the attached figure. TTD remains extremely low in all four countries, and comparable efficiency and tele-accuracy have been achieved. With expanded geographic reach, 8,448 (1.08%) patients were diagnosed with STEMI and 3,911 (46.3%) urgently reperfused, including 3,049 (78%) with Primary PCI. Time to TTD ranged between 2.8 to 5.8 minutes, with a mean of 3.5 min. Tele-accuracy was 98.5%, D2B 51 min, and in-hospital mortality 5.2%. Various other comparative metrics for the 4 countries are being gathered and will be available at the time of presentation.

Conclusions

LATIN demonstrates the robust ability of telemedicine to transcend national boundaries to guide AMI management. This strategy can be adopted in under-developed countries in Asia and Africa to provide an umbrella of AMI care for the millions of disadvantaged patients.

P6417Increasing the accuracy of a machine learning algorithm for STEMI diagnosis by incorporating demographic variables

Background

Our previous work demonstrated the diagnostic value of Artificial Intelligence (AI) -driven algorithms for ST-Elevation Myocardial Infarction (STEMI). In the present research, we explore the importance of demographic data inclusion, in order to achieve a more accurate diagnosis.

Purpose

To demonstrate that incorporation of demographic variables into the sample records will augment the accuracy of AI-based protocols for STEMI diagnosis.

Methods

An observational, retrospective, case-control study. Demographic data (age and gender) male/female ratio 1.3, ages 98–18 years was added to the sample records. Sample: 8,511 EKG records, previously diagnosed as normal, abnormal (over 200 conditions) or STEMI. Records excluded other patient and medical information. The sample was derived from the private International Telemedical Systems (ITMS) database. LUMENGT-AI Algorithm was employed. Preprocessing: detection of QRS complexes by wavelet system, segmentation of each EKG into individual heartbeats (90,592 total beats) with fixed window of 0.4s to the left and 0.9s to the right of main QRS; Classification: A 1-D convolutional neural network was implemented, “STEMI” and “Not-STEMI” classes were considered for each heartbeat, individual probabilities were aggregated to generate the final label for each record. Training & Testing: 90% and 10% of the sample was used, respectively. Experiments: Intel PC i7 8750H processor at 2.21GHz, 16GB RAM, Windows 10 OS with Nvidia GTX 1070GPU, 8GB RAM.

Results

The model yielded an accuracy of 97.1%, a sensitivity of 96.8%, and a specificity of 97.5%.

Conclusions

The ability of AI-guided algorithms to diagnose STEMI is increased by expanding the morphological variables with demographic data. This approach may be applied to improve the EKG diagnosis of other cardiovascular entities and improve clinical management.

P6418The continued proficiency of artificial intelligence for interpreting EKG: single lead EKG for STEMI culprit lesion localization

Background

Traditionally, the 12-lead electrocardiogram (EKG) has been used for diagnosing ST-Elevation Myocardial Infarction (STEMI) and for identifying the culprit lesion. We have previously demonstrated the impact of combining a Single Lead approach with Artificial Intelligence (AI) to replace tasks previously dominated by the 12 lead EKG. This research explores the role of the single lead EKG in identifying a culprit lesion.

Purpose

To test the use of a single lead approach to accurately locate the culprit vessel.

Methods

An observational, retrospective, case-control study. Sample: 2,542 exclusively STEMI diagnosis EKG records that included post discharge feedback from healthcare centers, confirming diagnosis and culprit vessel (Left Main Coronary Artery [LMCA]; Left Anterior Descending [LAD]; Right Coronary Artery [RCA]; Left Circumflex Artery [LCX]; Saphenous Vein Graft [SVG]). Records excluded other patient and medical information. The sample was derived from the private International Telemedical Systems (ITMS) database. LUMENGT-AI Algorithm was employed. Preprocessing:detection of QRS complexes using a wavelet system, segmentation of each EKG into individual heartbeats (27,125 total beats) with fixed window of 0.4s to the left and 0.9s to the right of main QRS; Classification: A 1-D convolutional neural network was implemented; “LCMA”, “LAD”, “CX”, “RCA”, “SVG”, and “No Information” classes were considered for each heartbeat per lead; individual probabilities were aggregated to generate the final label for each record. Training & Testing: 90% and 10% of the sample was used, respectively. Experiments: Intel PC i7 8750H processor at 2.21GHz, 16GB RAM, Windows 10 OS with NVidia GTX 1070 GPU, 8GB RAM.

Results

Accuracy: 77.4% Lead III; Sensitivity: LMCA (Lead aVL 25%); LAD (Lead aVF 87.8%); RCA (Leads V1, V3 92.9%); LCX (Lead aVL 21.7%).

Conclusions

Our results yielded the dominance of a specific single lead to each culprit vessels, aVF for LAD and V1 and V3 for RCA. We continue testing with different algorithms to search for reliable results for the LMCA and LCX. Nonetheless, conjugating a Single Lead EKG with an AI-augmented algorithm enables faster and easier management for patients that present with STEMI affecting the LAD and RCA territories.

P2426Validating the diagnostic value of a machine learning algorithm for STEMI detection

Background

We have previously reported the use of Artificial Intelligence (AI) guided EKG analysis for detection of ST-Elevation Myocardial Infarction (STEMI). To demonstrate the diagnostic value of our algorithm, we compared AI predictions with reports that were confirmed as STEMI.

Purpose

To demonstrate the absolute proficiency of AI for detecting STEMI in a standard12-lead EKG.

Methods

An observational, retrospective, case-control study. Sample: 5,087 EKG records, including 2,543 confirmed STEMI cases obtained via feedback from health centers following appropriate patient management (thrombolysis, primary Percutaneous Coronary Intervention (PCI), pharmacoinvasive therapy or coronary artery bypass surgery). Records excluded patient and medical information. The sample was derived from the International Telemedical Systems (ITMS) database. LUMENGT-AI Algorithm was employed. Preprocessing: detection of QRS complexes by wavelet system, segmentation of each EKG into individual heartbeats (53,667 total beats) with fixed window of 0.4s to the left and 0.9s to the right of main QRS; Classification: A 1-D convolutional neural network was implemented, “STEMI” and “Not-STEMI” classes were considered for each heartbeat, individual probabilities were aggregated to generate the final label for each record. Training & Testing: 90% and 10% of the sample were used, respectively. Experiments: Intel PC i7 8750H processor at 2.21GHz, 16GB RAM, Windows 10 OS with NVIDIA GTX 1070 GPU, 8GB RAM.

Results

The model yielded an accuracy of 97.2%, a sensitivity of 95.8%, and a specificity of 98.5%.

Conclusion(s)

Our AI-based algorithm can reliably diagnose STEMI and will preclude the role of a cardiologist for screening and diagnosis, especially in the pre-hospital setting.

P575Merging technologies to provide Mexico an innovative nationwide AMI management network

Background

“Cόdigo Infarto”, the vast patient-centric, app-based, educational crusade of the Mexican Society of Interventional Cardiology (SOCIME) has been combined with the Latin America Telemedicine Infarct Network (LATIN) to create a comprehensive, national AMI program for Mexico.

Purpose

To demonstrate the benefits of amalgamating educational initiatives of national cardiology societies with a global telemedicine program for improving AMI management.

Methods

“Cόdigo Infarto” App connects patients to a network of several hundred cardiologists and 250 Primary PCI-capable labs. LATIN provides the partnership with its robust telemedicine platform, a hub-spoke strategy that supports patient's access to appropriate medical management. Remotely located experts, in Colombia, provide urgent EKG diagnosis via tele-consultation to the entire LATIN Mexico network. They activate ambulance dispatch and implement guideline-based protocols.

Results

Numerous “Cόdigo Infarto” sites have incorporated LATIN to provide a simple and accelerated management of AMI patients. Currently, the partnership (7 hubs, 78 spokes) has screened 19,886 patients. A total of 359 STEMI cases (1.8%) have been diagnosed; 118 patients (33%) were urgently reperfused, Primary PCI was performed in 74% of the latter cases. D2B time was 41 min. Reasons for the lack of treatment include delayed presentation, lack of ICU beds and insurance denials. Currently, these constraints are being methodically probed. Updated results will be available at time of presentation.

Conclusions

The synergy of the AMI initiative for Mexico provides a template for similar initiatives in developing countries.

Laparoscopic sleeve gastrectomy for morbid obesity: role of intraluminal and intraperitoneal postoperative drainage

BACKGROUND AND AIMS

Bleeding and staple line leak are the most common postoperative complications of LSG. To prevent and/or to promptly identify such complications, conventional peri-operative protocols imply post-operative gastric decompression (NGT) and staple line drain (IAD). Our aim was to evaluate the role of naso-gastric tube (NGT) and intra-abdominal drain (IAD) in preventing and/or facilitating identification and treatment of post-operative complications after sleeve gastrectomy.

PATIENTS AND METHODS

A retrospective observational study on two consecutive series has been undertaken to evaluate the real utility of routine placement of NGT and IAD at the end of a LSG to prevent (primary end-point), promptly identify (secondary end-point) and manage (tertiary end-point) bleeding and staple line leakage. Collected outcome data of all consecutive cases, which underwent primary LSG at our Department, were analyzed. The first 100 consecutive patients (group A) received the standard perioperative protocol and the other consecutive 100 (group B) received a fast track protocol (no NGT neither IAD).

RESULTS

The two groups were not different in their outcome. Two bleeding occurred in Group A and were conservatively treated. One abscess developed in group B soon after surgery. It was diagnosed by an abdominal CT performed because patients presented fever, leucocitosis and tachycardia. It was successfully treated by percutaneous ultrasound-guided drainage. One fistula occurred in group B after discharge on 30th post-operative day. Fistula was suspected based on fever and tachycardia in absence of any abdominal discomfort and was confirmed by an abdominal CT. The patient was successfully treated in 40 days by endoscopic positioning of a gastric tube-prosthesis and percutaneous ultrasound-guided drainage of abdominal collection. A third patient in group B experienced bleeding suspected due to hemoglobin drop and confirmed by abdominal CT. He also was conservatively treated.

CONCLUSIONS

In conclusion, placement of drains does not facilitate detection of leak, abscess, or bleeding after primary LSG.

Improved General and Height-Specific Quality of Life in Children With Short Stature After 1 Year on Growth Hormone

OBJECTIVE

Short stature in children and adolescents may lead to social and emotional stress, with negative effects on quality of life (QoL). GH treatment may improve QoL through height normalization. Our objective here was to evaluate general and height-specific QoL after 1 year of GH treatment.

DESIGN

Prospective, single-center, observational cohort study.

METHODS

Children ≥ 4 years of age starting GH at our center from 2012 to 2015 to treat short stature were studied. Patients with serious diseases, syndromic short stature, or developmental delay were excluded. At treatment initiation and 1 year later, patients and their parents completed the general PedsQL 4.0 and height-specific Quality of Life in Short Stature Youth (QoLiSSY) questionnaires. Correlations between self-report and parent-report scores and between height gain and QoL improvements were assessed based on Pearson correlation coefficients.

RESULTS

Seventy-four children (42 boys, 32 girls), median age (± SD), 10.2 ± 3.0 years (range, 4.1 to 16.6 years), were included. The self-report PedsQL indicated significant improvements in emotional (P = 0.02) and social (P = 0.03) QoL. As assessed by the QoLiSSY, children reported improvement of social QoL (+0.2 SD; P = 0.04), and parents reported improvement of children's physical (+0.1 SD; P < 0.0001), emotional (+0.3 SD; P < 0.0001), and social (+0.3 SD; P < 0.0001) QoL. Height SD score (SDS) gains showed moderate positive correlations with QoLISSY self-report score gains (R = 0.53, R2 = 0.28; P < 0.001) and QoLISSY parent-report gains (R = 0.60, R2 = 0.41; P < 0.00001).

CONCLUSIONS

After 1 year of GH treatment, children had significant gains in emotional and social QoL, as assessed by a general self-report questionnaire and height-specific parent-report questionnaire.

Seroepidemiological Studies of Arboviruses in Africa

The literature on sero-epidemiological studies of flaviviral infections in the African continent is quite scarce. Much of the viral epidemiology studies have been focussing on diseases such as HIV/AIDS because of their sheer magnitude and impact on the lives of people in the various affected countries. Increasingly disease outbreaks caused by arboviruses such as the recent cases of chikungunya virus, dengue virus and yellow fever virus have prompted renewed interest in studying these viruses. International agencies from the US, several EU nations and China are starting to build collaborations to build capacity in many African countries together with established institutions to conduct these studies. The Tofo Advanced Study Week (TASW) was established to bring the best scientists from the world to the tiny seaside town of Praia do Tofo to rub shoulders with African virologists and discuss cutting-edge science and listen to the work of researchers in the field. In 2015 the 1st TASW focussed on Ebola virus. The collections of abstracts from participants at the 2nd TASW which focused on Dengue and Zika virus as well as presentations on other arboviruses are collated in this chapter.

Impact of transitional care on endocrine and anthropometric parameters in Prader-Willi syndrome

CONTEXT

The transition of patients with Prader-Willi syndrome (PWS) to adult life for medical care is challenging because of multiple comorbidities, including hormone deficiencies, obesity and cognitive and behavioral disabilities.

OBJECTIVE

To assess endocrine management, and metabolic and anthropometric parameters of PWS adults who received (n = 31) or not (n = 64) transitional care, defined as specialized pediatric care followed by a structured care pathway to a multidisciplinary adult team.

PATIENTS AND STUDY DESIGN

Hormonal and metabolic parameters were retrospectively recorded in 95 adults with PWS (mean ± s.d. age 24.7 ± 8.2 years, BMI: 39.8 ± 12.1 kg/m²) referred to our Reference Center and compared according to transition.

RESULTS

Among the entire cohort, 35.8% received growth hormone (GH) during childhood and 16.8% had a GH stimulation test after completion of growth. In adulthood, 14.7% were treated with GH, 56.8% received sex-hormone therapy, whereas 91.1% were hypogonadic and 37.9% had undergone valid screening of the corticotropic axis. The main reason for suboptimal endocrine management was marked behavioral disorders. Patients receiving transitional care were more likely to have had a GH stimulation test and hormonal substitutions in childhood. They also had a lower BMI, percentage of fat mass, improved metabolic parameters and fewer antidepressant treatments. Transitional care remained significantly associated with these parameters in multivariate analysis when adjusted on GH treatment.

CONCLUSION

A coordinated care pathway with specialized pediatric care and transition to a multidisciplinary adult team accustomed to managing complex disability including psychiatric troubles are associated with a better health status in adults with PWS.

Kaolin modulates ABA and IAA dynamics and physiology of grapevine under Mediterranean summer stress

The foliar exogenous application of kaolin, a radiation-reflecting inert mineral, has proven to be an effective short-term climate change mitigation strategy for Mediterranean vineyards. In this work, we address the hypothesis that kaolin could improve both the hormonal dynamics and physiological responses of grapevines growing in Douro Region, northern Portugal. For this purpose, the leaf water potential, gas exchange and chlorophyll a fluorescence parameters were monitored, as well as the abscisic acid (ABA) and indole-3-acetic acid (IAA) quantification and immunolocalization were assessed. The study revealed a slight decrease in ABA and an increase in IAA in the kaolin treatment, which in turn were associated with the improvement of physiological performance. A month after spraying, kaolin improves the water potential respectively, 30% and 17% in the predawn and midday periods. Besides, plants treated with kaolin showed higher values of stomatal conductance, net CO₂ assimilation rate and intrinsic water use efficiency. Kaolin also ameliorates the effective PSII efficiency (67%), as well as the maximum quantum efficiency of photosystem II and the photosynthetic electron transport rate (>73%). These results were consistent with the higher photochemical quenching and the lower non-photochemical quenching observed in treated leaves and with the better performance obtained by the JIP test parameters. Physiological and hormonal analysis confirmed that kaolin effectively enhance grapevine summer stress tolerance.

Efficacy and Safety of Continuous Subcutaneous Infusion of Recombinant Human Gonadotropins for Congenital Micropenis during Early Infancy

BACKGROUND

Early postnatal administration of gonadotropins to infants with congenital hypogonadotropic hypogonadism (CHH) can mimic minipuberty, thereby increasing penile growth. We assessed the effects of gonadotropin infusion on stretched penile length (SPL) and hormone levels in infants with congenital micropenis.

METHODS

Single-center study including 6 males with micropenis in case of isolated CHH (n = 4), panhypopituitarism (n = 1), and partial androgen insensitivity syndrome (PAIS; n = 1). Patients were evaluated at baseline, monthly and at the end of the study through a clinical examination (SPL, testicular position and size), serum hormone assays (testosterone, luteinizing hormone, follicle-stimulating hormone, inhibin B, anti-Müllerian hormone [AMH]), and ultrasound of penis/testes.

RESULTS

In CHH, significant increases occurred in serum testosterone (from undetectable level to 3.5 ± 4.06 ng/mL [12.15 ± 14.09 nmol/L]), SPL (from 13.8 ± 4.5 to 42.6 ± 5 mm; p < 0.0001), inhibin B (from 94.8 ± 74.9 to 469.4 ± 282.5 pg/mL, p = 0.04), and AMH (from 49.6 ± 30.6 to 142 ± 76.5 ng/mL, p = 0.03). Micropenis was corrected in all patients, except one. On treatment, in the patient with PAIS, SPL was increased from 13 to 38 mm.

CONCLUSIONS

Early gonadotropin infusion is a safe, well-tolerated and effective treatment. The effect in PAIS has not been reported previously. Long-term follow-up is needed to assess the impact, if any, on future fertility and reproduction.
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