Burcu Bayramoglu

In mass casualty incidents, the demand for healthcare services far exceeds existing capacity, underscoring the importance of triage. This study supports drone-based triage by developing and validating algorithms for non-contact vital sign measurement from drone footage. Heart rate was measured by extracting average frame colour values from RGB videos and applying signal processing. Respiratory rate was obtained by analyzing temperature changes in the nasal region. Body temperature was analyzed based on the maximum temperature values in the forehead region’ thermal images. For oxygen saturation measurement, a deep learning model trained with features extracted from thermal images. Thirty-seven participants (mean age: 29.7 ± 8.45 years; 64.9% male) were simultaneously recorded using a drone-mounted camera and monitored with a standard bedside reference monitor, with seven recordings obtained outdoors and 30 indoors. The videos were analyzed by creating 15-second segments for respiratory rate and 13-second segments for the other parameters, with 1-second shifts. The accuracy rates of the oxygen saturation, body temperature, heart rate, and respiratory rate measurement algorithms were 98.65%, 98.59%, 97.70%, and 85.22%, respectively, for indoor recordings, and 99.60%, 98.48%, 96.85%, and 82.83% for outdoor recordings. The mean differences between the image processing–based and reference measurements for indoor recordings were 1.26% for oxygen saturation, 0.19 °C for body temperature, -0.37 breaths/min for respiratory rate, and −0.31 beats/min for heart rate; for outdoor recordings, the corresponding mean differences were 0.34%, 0.27 °C, −0.52 breaths/min, and −0.38 beats/min, respectively. The vital sign measurement algorithms demonstrated strong performance and can be successfully integrated into drone-based triage and other remote monitoring systems.

Background: Cardiopulmonary resuscitation (CPR) is a highly effort-intensive intervention and, in cases of cardiac arrest, the ability to predict a return of spontaneous circulation (ROSC) is of great importance for the efficient use of resources. This real-time assessment approach offers a practical advantage by increasing the applicability of prognostic models during acute resuscitation in an emergency department. Method: In this study, the data of patients who underwent CPR in the emergency department of a tertiary care hospital between 1 June 2019 and 1 June 2024 and underwent cardiopulmonary resuscitation were retrospectively analyzed. The patients’ demographics, comorbidities, CPR characteristics, and laboratory findings were evaluated using logistic regression and ROC curve analysis to identify the predictors of ROSC. Result: Our study revealed that cases with shockable rhythms and a shorter CPR duration were more likely to achieve ROSC. Elevated levels of albumin, creatine kinase, glucose, hemoglobin, and white blood cells were significantly associated with ROSC, while higher levels of creatinine, base excess, and eosinophils were more common in non-survivors. Atrial fibrillation and neurodegenerative disease were associated with lower ROSC rates. Conclusions: Although the criteria for the termination of cardiac arrest resuscitation are not definitive, certain patient characteristics and laboratory findings may guide the prediction of ROSC or the identification of cases requiring prolonged CPR. The integration of these real-time predictors into clinical algorithms may support decision making in crowded emergency departments.

Heart failure is one of the common reasons for presentations to emergency departments. Heart failure, which has an increasing prevalence and high mortality rate, significantly affects the health system. Therefore, it is important to predict mortality in emergency department. This study investigated the performance of the Emergency Heart Failure Mortality Risk Grade (EHMRG) score. In this study, we retrospectively examined the data of patients who presented to our emergency department with heart failure symptoms and were diagnosed with decompensated heart failure. The ability of the EHMRG score to determine hospitalization/discharge status and predict 7- and 30-day mortality was investigated. The study included 469 patients with a mean age of 73.09 ± 11.82 years. Patients admitted to the hospital and those who died within 7 or 30 days had higher EHMRG scores compared to those who were discharged and those who survived beyond these timeframes (P < .05). The score had a sensitivity of 69.48% and a specificity of 53.91% for making hospitalization/discharge decisions; a sensitivity and specificity of 50% and 88.96%, respectively, for the prediction of 7-day mortality; and a sensitivity and specificity of 60.98% and 74.53%, respectively, for the prediction of 30-day mortality. The EHMRG score is a useful tool for assessing disease severity, making hospital admission decisions, and predicting 7- and 30-day mortality. However, it is not a discriminatory scoring system for determining whether admitted patients require ward or intensive care. The EHMRG score can be utilized without any reservations in countries where metolazone is not available.

Background and Objectives: Early repolarization (ER), previously considered benign for many years, is now recognized as a substantial risk factor for malignant arrhythmia, coronary artery disease, and mortality. The ER pattern, previously regarded as a benign electrocardiographic characteristic, has lately been demonstrated to have a strong association with malignant arrhythmias, coronary artery disease, and elevated death rates. This study seeks to illustrate the prognostic significance of QT interval (QTc) prolongation on electrocardiograms for acute coronary syndrome and death in emergency cases. Prolongation of QTc duration on electrocardiography in emergency room cases may serve as a possible predictor for acute coronary syndrome and mortality. Materials and Methods: A retrospective study was conducted on 924 patients diagnosed with ER in the emergency department from 2020 to 2023. The QTc durations, serum glucose levels, troponin I levels, and additional auxiliary data of the patients were assessed. The alteration in the aVR derivation, often overlooked and deemed insignificant, was compared with clinical severity in ER cases. Results: The average age of the 924 patients in the study was 48.43 (9.65) years, with 30.7% being female. In the non-cardiac group, the mean age was 51.67 (7.98) years, with 738 females (31.9%). The QTc interval in the patient group was 409.54 (33.46) ms, while in the control group it was 411.57 (27.91) ms (p < 0.001). The one-year death rate was 49 (5.3%) for the ER group and nine (0.9%) for the follow-up group. The most common comorbid condition in both groups was tobacco and/or tobacco product intake. Univariate and multivariate regression analyses conducted for both ER types and mortality indicated that QTc prolongation may serve as a predictive factor (p < 0.001). The sensitivity and specificity of prolonged QTc in predicting acute coronary syndrome and mortality were determined to be 76% at the lowest and 98% at the highest levels in ER cases (p < 0.001). The Kaplan–Meier survival analysis for ER types revealed 321 days for the horizontal type and 363 days for the ascending type. Conclusions: Prolonged QTc duration in early repolarization cases may serve as an independent predictor of acute coronary syndrome and mortality.

Reverse transcription-polymerase chain reaction (RT-PCR) is the reference standard for COVID-19 diagnosis, but the need for rapid, reproducible, and cost-effective diagnostic tools remains. This study investigated the diagnostic performance of a novel artificial intelligence−based multispectrum analysis (MSA, AP23) technique that detects the biomolecular fingerprint of severe acute respiratory syndrome coronavirus 2. A prospective, double-blinded observational design was used, involving 3614 volunteers. The artificial intelligence was trained with 2448 samples, validated with 816, and tested against RT-PCR using a blinded set of 350 samples. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated. During validation, MSA achieved 88.4% sensitivity, 88.76% specificity, 86.77% positive predictive value, and 90.18% negative predictive value. In the blinded comparison phase, these values were 81.73%, 81.99%, 75.16%, and 87.81%, respectively, with an area under the receiver operating characteristic curve of 0.89. These findings suggest that MSA offers reliable diagnostic performance and may be a promising alternative to RT-PCR in COVID-19 diagnosis. The study was registered on ClinicalTrials.gov (NCT04860895).

Changes Occurring in Health Services Provided to Syrian Refugees Between 2017-2023 and the Current Situation after the Kahramanmaraş Earthquake - Global Emergency And Critical Care

Background/Aim. Tactical Combat Casualty Care (TCCC) protocols are trauma protocols used on the battlefield aimed at preventing death in the first hours of injury. In T?rkiye, a regulation requires security and safety personnel to undergo TCCC training. This training is provided to non-medical military personnel by specialized military and civilian healthcare professionals at various hospitals. The TCCC protocols include standardized interventions through protocols such as Massive hemorrhage, Airway, Respiration, Circulation, Hypothermia/Head injury (MARCH) protocol and Military Acute Concussion Evaluation (MACE) protocol to ensure consistency in trauma care. The aim of the study was to evaluate the effects of TCCC on MPs who received the training. Methods. The study included MPs who received TCCC training at Istanbul?s Sancaktepe Hospital between March 7 and May 13, 2022, and between October 3 and December 2, 2022. Volunteers who consented to participate were asked survey questions to evaluate their knowledge before and after the training on various medical conditions to assess changes in knowledge and skills. Their opinions about the training were solicited both before and after the training. In addition to the survey questions, participants were asked to provide their views and suggestions about the training through open-ended questions. Results. The study included 49 volunteers aged between 23 and 35. There was a statistically significant increase in knowledge and skill levels regarding medical conditions before and after the training (p < 0.001). Participants concluded that the training was beneficial and that the knowledge and skills acquired could be applied in the field. Conclusion. Providing TCCC training will help MPs perform life-saving interventions under fire, thereby reducing fatalities and disabilities. Additionally, TCCC training will increase health literacy awareness among civilians, enabling trained personnel to not only save lives on the battle-field but also provide first aid in civilian emergencies.