Effects of high-gravity acceleration forces and anti-gravity maneuver on the cardiac function of fighter pilots.

The fighter pilots exposed to high gravitational (G) acceleration must perform anti-G maneuvers similar to the Valsalva maneuver. However, the effects of high-G acceleration and anti-G maneuvers on cardiac function have rarely been studied. This study aimed to investigate the effects of high-G forces on cardiac function of fighter pilots. Fighter pilots who underwent regular health check-ups and echocardiography were included (n = 29; 100% men, 41 ± 10 years old; mean flight time, 1821 ± 1186 h). Trainees who had not experienced any flights were included in the control group (n = 16; 100% men, 36 ± 17 years old). Echocardiographic data included left ventricular chamber size, systolic and diastolic functions, right ventricular systolic pressure (RVSP), inferior vena cava (IVC) collapsibility, and tricuspid annular plane systolic excursion (TAPSE). No significant differences in left ventricular ejection fraction, RVSP, or IVC collapsibility were observed between two groups. In the multivariate linear regression analysis with total flight time as an independent continuous variable for fighter pilots, TAPSE was positively correlated with total flight time. The experience of fighter pilots who were exposed to high-G acceleration forces and anti-G maneuvers did not cause cardiac structural changes, but the exposure might be associated with right heart function changes.

Impact of height difference between coronary ostium and location of intracoronary pressure sensor on fractional flow reserve measurements.

BACKGROUND: During fractional flow reserve (FFR) measurements, distal coronary pressure (Pd) can be influenced by hydrostatic pressure changes resulting from the height difference (HD) between the coronary ostium and the location of the distal pressure sensor. AIMS: We investigated the effect of aortocoronary HD on the FFR measurements in each coronary artery. METHODS: In this retrospective cohort study, we analyzed 257 patients who underwent FFR measurements and coronary computed tomography (CCTA) within a year. Using CCTA, we measured HD as the vertical distance between the coronary ostium and a matched point of the distal coronary pressure sensor identified on coronary angiography. RESULTS: The location of the Pd sensor was higher than the coronary ostium in the left anterior descending artery (LAD) (-4.64 ± 1.15 cm) and lower than the coronary ostium in the left circumflex artery (LCX) (2.54 ± 1.05 cm) and right coronary artery (RCA) (2.03 ± 1.28 cm). The corrected FFR values by HD were higher in the LAD (0.78 ± 0.09 to 0.82 ± 0.09, P<0.01) and lower in the LCX and RCA than the original FFR values (0.87 ± 0.07 to 0.85 ± 0.08, P<0.01; 0.87 ± 0.10 to 0.86 ± 0.10, P<0.01, respectively). Using an FFR cut-off value of 0.8, the concordance rates between the FFR and corrected FFR values were 77.8%, 95.2%, and 100% in the LAD, LCX, and RCA, respectively. CONCLUSION: HD between the coronary ostium and the distal coronary pressure sensor may affect FFR measurements and FFR-guided treatment decisions for coronary artery disease.

Artificial intelligence versus physicians on interpretation of printed ECG images: Diagnostic performance of ST-elevation myocardial infarction on electrocardiography.

BACKGROUND: Smartphone-based ECG analyzer using camera input can be useful as everyone have it. The purpose of this study was to evaluate whether such a system can outperform clinicians in detecting ST-elevation myocardial infarction (STEMI) regardless of image acquisition conditions. METHODS: We retrospectively enrolled suspected STEMI patients in an emergency department from January to October 2021. A multifaceted cardiovascular assessment system (Quantitative ECG, QCG™) using ECG images to produce a quantitative score (QCG score, ranging from 0 to 100) was compared to human experts of 7 emergency physicians and 3 cardiologists. Voting scores (number of participants answering "yes" for STEMI) were calculated for comparison. The system's robustness was evaluated using an equivalence test where we prove its performance metric (area under the curve of the receiver operating characteristic curve, AUC-ROC) changes within a predetermined equivalence range (-0.01 to 0.01) in 6 different environments (A combination of three different smartphones and two image sources including computer screen and paper). RESULTS: 187 patients (96 STEMI, 51.3%) were analyzed. AUC-ROC of QCG score was 0.919 (0.880-0.957). AUC-ROCs of voting scores, 0.856 (0.799-0.913) for all clinicians, 0.843 (0.786-0.900) for emergency physicians, 0.817 (0.756-0.877) for cardiologists, and 0.848 (0.790-0.905) for high-performance group were significantly lower compared to that of QCG score. The change in AUC-ROC by image acquisition condition was negligible with a narrow confidence interval within -0.01 to 0.01 confirming the equivalence. CONCLUSIONS: Image-based AI system can outperform clinicians in STEMI diagnosis and its performance was robust to change in image acquisition conditions.

Electrocardiographic biomarker based on machine learning for detecting overt hyperthyroidism.

Aims: Although overt hyperthyroidism adversely affects a patient's prognosis, thyroid function tests (TFTs) are not routinely conducted. Furthermore, vague symptoms of hyperthyroidism often lead to hyperthyroidism being overlooked. An electrocardiogram (ECG) is a commonly used screening test, and the association between thyroid function and ECG is well known. However, it is difficult for clinicians to detect hyperthyroidism through subtle ECG changes. For early detection of hyperthyroidism, we aimed to develop and validate an electrocardiographic biomarker based on a deep learning model (DLM) for detecting hyperthyroidism. Methods and results: This multicentre retrospective cohort study included patients who underwent ECG and TFTs within 24 h. For model development and internal validation, we obtained 174 331 ECGs from 113 194 patients. We extracted 48 648 ECGs from 33 478 patients from another hospital for external validation. Using 500 Hz raw ECG, we developed a DLM with 12-lead, 6-lead (limb leads, precordial leads), and single-lead (lead I) ECGs to detect overt hyperthyroidism. We calculated the model's performance on the internal and external validation sets using the area under the receiver operating characteristic curve (AUC). The AUC of the DLM using a 12-lead ECG was 0.926 (0.913-0.94) for internal validation and 0.883(0.855-0.911) for external validation. The AUC of DLMs using six and a single-lead were in the range of 0.889-0.906 for internal validation and 0.847-0.882 for external validation. Conclusion: We developed a DLM using ECG for non-invasive screening of overt hyperthyroidism. We expect this model to contribute to the early diagnosis of diseases and improve patient prognosis.

Visit-to-visit systolic blood pressure variability in patients with ST-elevation myocardial infarction predicts long-term cardiovascular outcomes.

Elevated visit-to-visit blood pressure variability (BPV), independent of mean BP, has been associated with cardiovascular events. However, its impact after ST-elevation myocardial infarction (STEMI) has not been established. This study aimed to investigate the prognostic impact of BPV on patients after STEMI. We analyzed the data and clinical outcomes of STEMI survivors who underwent successful primary coronary intervention from 2003 to 2009. BP was measured at discharge and at 1, 3, 6, 12, 24, and 36 months, and we calculated BPV as the intra-individual standard deviations (SDs) of systolic BP (SBP) across these measurements. We classified the patients as high and low-BPV group, and evaluated the outcomes: occurrence of major adverse cardiovascular events (MACEs), death, recurrent myocardial infarction, and target vessel revascularization within 60 months. We enrolled 343 patients, and mean follow-up duration was 68 ± 34 months (median: 76 months). Mean and median SBP SDs were 13.2 and 12.3 mmHg, and patients were divided into one of the two groups based on the median (high-BPV group = SD ≥ 12.3 mmHg; low-BPV group = SD < 12.3 mmHg). The MACE-free survival in the high-BPV group was significantly worse than that in low-BPV group (log-rank p = 0.035). For the high-BPV group, the risk of a MACE significantly increased by 57% (95% confidence interval: 1.03-2.39; p = 0.038). Visit-to-visit systolic BPV was associated with increased rates of adverse clinical outcomes in patients after STEMI. Careful assessment of BP and attempts to reduce BPV might be also important in STEMI survivors.

Thrombocytopenia in Systemic Lupus Erythematosus: Clinical Manifestations, Treatment, and Prognosis in 230 Patients.

The aim of the study was to examine the clinical characteristics and prognosis according to severity of thrombocytopenia and response to treatment for thrombocytopenia in patients with systemic lupus erythematosus (SLE).We retrospectively evaluated 230 SLE patients with thrombocytopenia, and reviewed their clinical data and laboratory findings. Thrombocytopenia was defined as platelet counts under 100,000/mm, and patients were divided into 3 thrombocytopenia groups according to severity: mild (platelet counts >50,000/mm), moderate (>20,000/mm, ≤50,000/mm), and severe (≤20,000/mm). Clinical characteristics, treatments, and prognoses were compared among the groups. Furthermore, complete remission of thrombocytopenia was defined as platelet counts >100,000/mm after treatment.There was no significant difference in clinical or laboratory findings among the groups according to severity of thrombocytopenia. However, hemorrhagic complications were more frequent in severe thrombocytopenia (P < 0.001) and mortality was also higher (P = 0.001). Complete remission was achieved in 85.2% of patients. The clinical characteristics and modality of treatment did not differ between the patients with and without complete remission. Mortality in patients with complete remission (1.5%) was significantly lower than in those without complete remission (29.4%, P < 0.001). Survival was significantly higher in patients with complete remission from thrombocytopenia (odds ratio = 0.049, 95% confidence interval: 0.013-0.191, P < 0.001).The severity of thrombocytopenia in SLE patients can be a useful independent prognostic factor to predict survival. Moreover, complete remission of thrombocytopenia after treatment is an important prognostic factor. The severity of thrombocytopenia and response to treatment should be closely monitored to predict prognosis in SLE patients.