Search results for: Renad Kalantan

Authors: Mohammed S. Bhader, Abdullah A. Ghaddaf, Anas Alamoudi, Amal Abualola, Renad Kalantan, Noura Alkhulaifi, Ibrahim Halawani, Mohammed Alhindi

Abstract:

Background: Noninvasive neurally adjusted ventilatory assist (NAVA) is a relatively new mode of noninvasive ventilation with promising clinical and patient-ventilator outcomes for preterm infants. The aim of this systematic review was to compare NAVA to nasal continuous or positive airway pressure (NCPAP) or intermittent positive airway pressure (NIPP) for preterm infants. Methods: We searched the online databases Medline, Embase, and CENTRAL. We included randomized controlled trials (RCTs) that compared NAVA to NCPAP or NIPP for preterm infants < 37 weeks gestational age. We sought to evaluate the following outcomes: noninvasive intubation failure rate, desaturation rate, the fraction of inspired oxygen (FiO2), and length of stay in the neonatal intensive care unit (NICU). We used the mean difference (MD) to represent continuous outcomes, while the odds ratio (OR) was used to represent dichotomous outcomes. Results: A total of 11 RCTs that enrolled 429 preterm infants were deemed eligible. NAVA showed similar clinical outcomes to NCPAP or NIPP with respect to noninvasive intubation failure (RR for NAVA versus NCPAP: 0.82, 95% confidence interval (CI): 0.49 to 1.37), desaturation rate (RR for NAVA versus NCPAP: 0.69, 95%CI: 0.36 to 1.29; RR for NAVA versus NIPP: 0.58, 95%CI: 0.08 to 4.25), FiO2 (MD for NAVA versus NCPAP: –0.01, 95%CI: –0.04 to 0.02; MD for NAVA versus NIPP: –7.16, 95%CI: –22.63 to 8.31), and length of stay in the NICU (MD for NAVA versus NCPAP: 1.34, 95%CI: –4.17 to 6.85). Conclusion: NAVA showed similar clinical and ventilator-related outcomes compared to the usual care noninvasive respiratory support measures NCPAP or NIPP for preterm infants.

Keywords: preterm infants, noninvasive neurally adjusted ventilatory assist, NIV-NAVA, non-invasive ventilation, nasal continuous or positive airway pressure, NCPAP, intermittent positive airway pressure ventilation, NIPP, respiratory distress syndrome, RDS

Procedia PDF Downloads 110

Authors: Dania Baaboud, Renad Al-zahrani, Mahnoor Khan, Riya Afroz

Abstract:

Flo is a smart period-tracking tool that uses artificial intelligence (AI) to offer individualized reproductive health predictions and insights. Flo makes very accurate predictions about menstrual cycles, ovulation, and fertility windows by evaluating user inputs, including cycle duration, symptoms, and patterns. Its machine learning algorithms are constantly evolving, providing personalized health recommendations, instructional materials, and early identification of possible health abnormalities such as reproductive problems and hormone imbalances. Flo, which was introduced in 2015 and upgraded with AI in 2017, is a revolutionary use of technology in healthcare that empowers people to make knowledgeable decisions regarding their well-being. Despite its advantages, our study included drawbacks, such as limited access to premium services and a small sample size. While highlighting unique characteristics, a comparative comparison with similar applications such as Clue and Glow confirmed Flo's outstanding AI integration for individualized healthcare. All things considered, Flo is a prime example of how AI can be used to tackle intricate biological processes, giving consumers the ability to efficiently control their reproductive health and opening the door for improvements in individualized medical technology.

Keywords: Flo, period-tracking app, period symptoms, women’s health, machinery

Procedia PDF Downloads 6