The Production, Assessment, and Utility of 3D-Printed Video Laryngoscopes in Eastern India: A Low-Cost Alternative to Conventional Video Laryngoscopes.

Introduction Recognizing the limitations of traditional direct laryngoscopes, particularly in difficult airway situations, video laryngoscopy has emerged as a potentially safer and more effective alternative. This study evaluated the utility of two 3D-printed video laryngoscopes: a standard geometry video laryngoscope (SGVL), resembling the traditional Macintosh blade, and a hyper-angulated video laryngoscope (HAVL) with a more curved design. Their performance was compared to a standard Macintosh direct laryngoscope across various intubation parameters. By leveraging the cost-effectiveness of 3D printing with polylactic acid, the study aimed to assess the potential of this technology to improve airway management across diverse clinical settings and varying levels of physician expertise. Methods This prospective randomized crossover study compared the effectiveness of 3D-printed video laryngoscopes (VL) and a standard direct laryngoscope in intubation. After obtaining IRB approval, physicians from various specialties across multiple centers participated. Participants received training on SGVL, HAVL, and DL intubation using an instructional video and hands-on practice. The training was standardized for all participants. The primary outcome measures were time to successful intubation, number of attempts, and time to visualize vocal cords. Participants were randomized to use all three laryngoscopes on a manikin, with a maximum of two attempts per scope. A 30-minute break separated each laryngoscope evaluation. Successful intubation was defined as the single insertion of each laryngoscope and bougie, followed by endotracheal tube placement and confirmation of lung inflation. Results Ninety-eight doctors, mostly from the EM team (73.5%) and ICU team (23.4%). Teams consist of consultants, residents, and medical officers of the concerned departments. Forty-eight of the participants (49%) were novice operators (<25 intubations). Successful first-attempt intubation in those with <1 year of experience with intubation (n=33) was highest for SGVL (97%) compared to DL (82%) and HAVL (67%). Participants who learned intubation through self-directed learning exhibited a higher acceptance of VL and achieved 100% success on their first attempt. Among those who followed modules or workshops, 97% had successful first-attempt intubation with VL. The average time taken to visualize the vocal cords was lower in SGVL compared to DL (5.6 vs. 7.5 seconds) (p<0.001). The HAVL also had a lower average time compared to the DL (7.1 vs. 7.5 secs) (p<0.001). However, the time taken to intubate using DL (24.2 ±8.7 sec) was similar to SGVL (28.1 ±13 sec). Lastly, the intubation time using HAVL was the longest (49.6 ±35.5 sec). The time to intubate with DL and SGVL had Spearman's rho of 0.64 (p<0.001), and DL and HAVL had 0.59 (p<0.001). Conclusions The ease of use and its cost-effective nature make 3D-printed VLs beneficial in situations where traditional VLs may not be available, especially in simulation and training.

Ventricular Septal Rupture and Artificial Intelligence (AI)-Assisted Healthcare.

This case report highlights the use of point-of-care ultrasound (POCUS) for the diagnosis of ventricular septal rupture (VSR), a severe consequence of acute myocardial infarction (AMI). VSR has a broad spectrum of signs and inconspicuous symptoms, making the diagnosis difficult. POCUS offers non-invasive, real-time cardiac imaging and has an advantage over other methods due to its ability to identify VSR early. Here we present a 63-year-old female with a history of type 2 diabetes, hypothyroidism, hyperlipidemia, and a family history of cardiovascular disease, who came to the ED with chest pain for three days, palpitations, and dyspnea at rest. On examination, the patient was hypotensive, tachycardic, and had crackles with a harsh holosystolic murmur. An EKG and elevated troponin levels suggested acute on chronic anterior-lateral wall ST-elevation myocardial infarction (STEMI). Resuscitation efforts were initiated, followed by a lung ultrasound that revealed good lung sliding and multiple B lines without pleural thickening, indicating pulmonary edema. Echocardiography revealed ischemic heart disease with moderate left ventricle (LV) systolic dysfunction and a 14 mm apical ventricular septal rupture (hypokinetic thinning of the anterior wall, septum, apex, and anterolateral wall with a left ventricular ejection fraction (LVEF) of 39%). The presence of flow on color Doppler across the interventricular septum, showing left-to-right shunting, led to a definitive diagnosis of acute-on-chronic myocardial infarction (MI) with ventricular septal rupture. The case report also emphasizes how modern AI applications like ChatGPT (OpenAI, San Francisco, California, United States), aid in language and research, saving time and redefining the healthcare and research industry. As a result, we are confident that AI-assisted healthcare will be the next global breakthrough.