Accuracy of spontaneous breathing trial using ET-CPAP in predicting successful extubation of neonates

Objective: Extubation failure is common in mechanically ventilated neonates. Finding objective criteria for predicting successful extubation may help to reduce the incidence of failure and the length of mechanical ventilation (MV). We conducted this study to determine the accuracy of the spontaneous breathing trial (SBT) and lung function measurements in predicting successful extubation in neonates.Methodology: This cross-sectional validation study was conducted at a tertiary care neonatal intensive care unit (NICU) over 12 months from December 2019 to December 2020. Neonates intubated for \u3e24 hours and considered ready for extubation were enrolled in the study. Neonates who met defined eligibility criteria underwent a three minutes SBT using endotracheal continuous positive airway pressure (ET-CPAP) before extubation. The primary clinical team was blinded to the results, and all neonates were extubated after SBT. Extubation was considered successful if patients remained extubated for 48 hours.Results: Among the 107 infants, 77.5% (n=83) of infants passed the SBT. Of these, 78 were successfully extubated, giving the positive predictive value of 93.97%. The overall extubation success rate was 90% (n=96). The sensitivity and specificity of SBT were 81.2% and 54.5%, respectively. VE (ET-CPAP) and VE-ventilator at a cutoff of ≥238 ml and ≥143.7 ml have an area under the curve (AUC) of 0.77 and 0.75 respectively to predict successful extubation (p-value 0.003, 0.008 respectively).Conclusion: SBT predicts extubation success with pronounced accuracy. Therefore, we propose SBT as a valuable and crucial step that guides clinicians\u27 decision-making regarding extubation preparedness or impending failure in neonates

Factors leading to meconium aspiration syndrome in term- and post-term neonates

Background: Meconium aspiration syndrome (MAS) is considered a major cause of respiratory morbidity. It is a common issue encountered in the delivery room and newborn nursery. There is a need to identify the factors that lead to MAS to develop strategies to screen such patients at an early stage to decrease the mortality and morbidity. The objective of this study was to determine the factors leading to MAS in neonates delivered at ≥37 weeks of gestational age. Methods: A cross-sectional study was conducted through non-probability consecutive sampling technique at Liaquat University Hospital, Hyderabad from August 2016 to February 2017. All neonates at ≥37 weeks of gestation with meconium-stained amniotic fluid (MSAF) detected during delivery were included in this study after obtaining informed consent from their parents. The demographic and factors related to MAS were recorded through predesigned proforma and analyzed using SPSS version 22. Mean and standard deviation were determined for quantitative variables whereas frequency and percentages were calculated for qualitative variables. Results: Overall 136 neonates were included in the study. The mean gestational age was 38 ± 1.43 weeks. The major factors for MAS were detected as fetal distress (67.0%, n = 91), non-reassuring fetal heart rate (54.0%, n = 73), cesarean birth (48.0%, n = 65), intrauterine growth restriction (IUGR; 17.0%, n = 23), and post maturity (12.0%, n = 16). Conclusion: We conclude that the major factors for MAS are fetal distress, non-reassuring FHR tracing, cesarean birth, IUGR, and post maturity. Screening of such patients at an early stage may minimize morbidity and mortality related to MAS

Design and Co-Simulation of Depth Estimation Using Simulink HDL Coder and Modelsim

In this paper a novel VHDL design procedure of depth estimation algorithm using HDL (Hardware Description Language) Coder is presented. A framework is developed that takes depth estimation algorithm described in MATLAB as input and generates VHDL code, which dramatically decreases the time required to implement an application on FPGAs (Field Programmable Gate Arrays). In the first phase, design is carriedout in MATLAB. Using HDL Coder, MATLAB floating- point design is converted to an efficient fixed-point design and generated VHDL Code and test-bench from fixed point MATLAB code. Further, the generated VHDL code of design is verified with co-simulation using Mentor Graphic ModelSim10.3d software. Simulation results are presented which indicate that VHDL simulations match with the MATLAB simulations and confirm the efficiency of presented methodology

Comparative Analysis of Feature Extraction Methods for Cotton Leaf Diseases Detection

Cotton leaf diseases must be accurately detected and classified to reduce plant diseases and output losses. Feature extraction strategies for automated cotton leaf disease diagnosis are compared in this study. The research uses HOG, SIFT, SURF, GLCM, and Gabor wavelets filter feature extractor to extract features. We gathered and preprocessed 2400 cotton leaf images of healthy and diseases, Angular Leaf Spot, Bacterial Blight, Cotton curl leaf disease (CLCuD), as well as Alternaria Disease. K-means clustering separates leaf areas and improves feature extraction in image segmentation. Discriminative features are extracted using the mentioned methods, and Support Vector Machine (SVM) classifier is employed for disease identification. The comparative analysis based on Accuracy, Precision, and Sensitivity reveals the Gabor Wavelet Filter Feature Extractor as the top performer, achieving 92% accuracy on the test dataset containing bacterial blight, curl virus, alternaria, and healthy leaves. While HOG, SIFT, SURF, and GLCM methods also perform well, they are outperformed by the Gabor Wavelet method. This study shows Gabor wavelet-based features can accurately identify and classify cotton leaf illnesses, helping farmers fight plant diseases. The results underscore the need of choosing proper feature extraction methods for autonomous plant disease diagnostic systems

The Pattern of Musculoskeletal Cancers in Pakistan

OBJECTIVE: The study aimed to assess the pattern of musculoskeletal cancers in the Pakistani population who visited NIMRA hospital situated at Jamshoro. METHODOLOGY: It was an observational retrospective study conducted at the Nuclear Institute of Medicine and Radiotherapy (NIMRA) and LUMHS, Jamshoro, from August 2019 to December 2020. A total of 626 patients were selected for this study. The data regarding patients were sourced from NIMRA, LUMHS Jamshoro. All the patients of both genders and ages diagnosed at NIMRA with any cancer were included in the study. Patients who did not return for follow-up after their metastatic and laboratory tests were excluded from the study. A Chi-square test was conducted to assess the association between diagnosed cancers versus gender and age groups. The confidence interval was set at 95%, and the probability value ≤0.05 was statistically significant. RESULTS: A total of 626 patients were selected for this study. Of them, 362 (57.8%) were males and 264 (42.2%) were females, with a mean age of 34.67 years and a standard deviation of 18.998. The most prevalent cancer is soft-tissue sarcoma (STS) 129 (20.6%), followed by chondrosarcoma 119 (19%), and osteosarcoma 91 (14.5%). Forty percent of the cancers were diagnosed as stage II, followed by stage III (22%), stage IV (22%) and stage-I (16%), respectively. A significant association between diagnosed cancers were found with gender (p=0.001) and age group (p=<0.001). CONCLUSION: Soft-tissue sarcoma, chondrosarcoma, and osteosarcoma are the most common musculoskeletal cancers in the Pakistani population

Ventilator associated pneumonia in neonatal intensive care unit: Occurrence and risk factors

Objectives: To examine the occurrence of pneumonia linked with a ventilator in the neonatal intensive care unit and to determine the related risk factors.Purpose of study: To better identify the associated morbidity and mortality, pathophysiology, and recommended measures to avoid this disease, paediatric VAP diagnosis methods must become more standardized and exact.Study design: A cross-sectional studyPlace and Duration: This study was conducted at Aga Khan University hospital from May 2021 to May 2022Methodology: This study includes a total of 70 participants admitted in neonatal intensive care unit. All the patients were put under the ventilator for more than 2 days. At the time of admission, the X-ray of the chest was performed, and it was also performed every day. When certain organisms were present on the tracheal aspirate, ventilator-associated pneumonia (VAP) was diagnosed. After 2 days of ventilation, microbial analysis and gram staining were done for tracheal aspirates. They were later examined to determine the occurrence of nosocomial pneumonia and what are the risk factors linked with it. A Chi-square test and t-test were conducted to examine all the data. A confidence level of 0.05 was set.Results: Pneumonia associated with the ventilator occurred in 31.4% of the participants where a large number had developed it between 4-14 days after intubation. There were certain risk factors that were determined in our research. They include the use of H2 blockers, invasive lines, low PaO2/FiO2, and re-intubation. There were two things (use of steroids and enteral feeding through nasogastric) that were not linked with the occurrence of this pneumonia. The patients who were in the group of ventilator-associated pneumonia were having a longer time period of stay and mechanical ventilation.Practical implication: In newborn and paediatric intensive care units, VAP continues to be a significant and unresolved problem. The results of this study will highlight the numerous elements that significantly contribute to ventilator-associated pneumonia.Conclusion: The occurrence of pneumonia associated with ventilators is high. Those patients who were having above mentioned risk factors should require pay special attention towards prevention

An Improved Framework for Sindh School Monitoring System Android App

Sindh government has presented a system for observing schools called the Sindh School Monitoring System (SSMS) Framework. One of the part of the system is SSMS app, which is based on Android. SSMS app is widely used in the Sindh province in order to monitor the school with major focus on attendance. The SSMS app has increased the system performance in terms of attendance, however several flaw are present in its current framework. This paper identifies the key issues in the current framework such as identification and verification of Monitoring assistant (MA), school search options and SMC, teacher performance evaluation, reporting, curriculum, student performance evaluation and census, school building details, SNE, school amenities, GR register, NADRA verification, rights of MAs and online reporting options in the app. The changes are proposed in the existing framework, for the said key issues, which could improve the overall system performance. In order to validate the key findings and proposed changes in the existing framework a questionnaire has been prepared and evaluated from the SSMS app users. All the app users validated the proposed changes in the framework

Enhancing SCTP Performance through the Selection of Appropriate Retransmission Policies

The Stream Control Transmission Protocol (SCTP) is a reliable transport protocol that provides message oriented communication services between applications. One of the critical functions of SCTP is to ensure reliable delivery of data by detecting the lost or missing packets due to transmission errors. Once the errors are detected the SCTP uses retransmission policies for immediate retransmission of data along the same or alternate path. However, the performance of SCTP retransmission policies can significantly impact its efficiency and reliability in different network conditions. In this paper, we analyzed three retransmission policies of SCTP that are (1) CWND, (2) SSTHRESHOLD and (3) LOSSRATE, and evaluated their performance in terms of network bandwidth, propagation delay and packet loss. We conducted simulations using the NS-2 network simulator and evaluated the performance of each policy under different network conditions and in each simulation the impact on throughput is analyzed. From the simulation results, the retransmission policy that uses loss rate parameter (LOSSRATE) for the transmission of data outperforms the retransmission policy that uses parameters such as congestion window (CWND) and the slow start threshold (SSTHRESHOLD). The analysis on the obtained results provides valuable insights into the tradeoffs between different SCTP retransmission policies and can help network administrators and application developers optimize SCTP performance in different network environments

Frequency of early morbidities in low birth weight neonates at the Aga khan university hospital, Karachi

Background: Globally, approximately 14.6% children are born with low birth weight (LBW) annually. In Pakistan, this figure however reaches approximately 16%. Low birth weight infants are vulnerable to develop early morbidities like hypothermia, hypoglycemia, respiratory distress syndrome and hypocalcemia. There is a scarcity of statistics which creates a gap in development of strategies for improving quality of care in developing countries. The aim of our study was to determine the frequency of early morbidities such as respiratory distress syndrome (RDS), hypoglycemia, hypothermia and hypocalcemia in low birth weight neonates. Methodology: prospective descriptive study was conducted via non-probability sampling technique from 1st April 2016 to 30th September 2016 at The Aga Khan University Hospital, Karachi. All low birth weight infants, i.e., those with birth weight \u3c 2500 grams were included in this study and observed for early morbidities, including hypothermia, hypoglycemia, hypocalcemia and respiratory distress syndrome. Descriptive analysis was done using SPSS version 22 (IBM Corp., Armonk, NY), mean and standard deviation were determined for quantitative variables, whereas frequency and percentages were calculated for qualitative variables. Result: A total of 2082 neonates were born during the study period, of which 271 (13%) were born with low birth weight. One hundred and eighty-five (68.1%) of these LBW neonates were preterm babies while 86 (31.9%) were born at term. Among LBW neonates 137 (51.0%) were males and 134 (49.0%) females. In the study population, hypoglycemia was seen in 17.3%, hypocalcemia in 13.6%, respiratory distress syndrome in 11%, and hypothermia in 2.5%. Conclusion: our study highlighted major early morbidities of LBW neonates, and their association with birth weight, gestational age and gender. Significant association of birth weight was found with hypothermia and hypocalcemia, whereas hypocalcemia and RDS were significantly associated with gestational age. However, none of the early morbidities had significant association with gender. Keeping in perspective the early morbidities in this population we propose that priority be given to providing adequate attention to low birth weight neonates