Objectives: To find out the factors influencing discharge process turnaround time (TAT) and to accurately predict the discharge process TAT. Methods: The discharge process of cardiology department inpatients in a tertiary care hospital was mapped over a month. The likely factors influencing discharge TAT were tested for significance by ANOVA. Multiple linear regression (MLR) was used to predict the TAT. The sample was divided into testing and training sets for regression. A model was generated using the training set and compared with the testing set for accuracy. Results: After a process map was plotted, the significant factors influencing the TAT were identified to be the treating doctor, and pending evaluations on the day of discharge. The MLR model was developed with Python libraries based on the two factors identified. The model predicted the discharge TAT with a 69% R2 value and 32.4 minutes (standard error) on the testing set and a 77.3% R2 value and 26.7 minutes (standard error) on the overall sample. Conclusions This study was an initiation to find out factors influencing discharge TAT and how those factors can be used to predict discharge in the hospital of interest. The study was validated and predicted the TAT with 77% accuracy after the significant factors that affect the discharge process were identified.

Objective: This study was conducted to investigate the relationship of semen parameters in samples used for intracytoplasmic sperm injection (ICSI) with fertilization and pregnancy rates in infertile couples. Methods: In this prospective study of Infertile couples with male factor infertility that had undergone ICSI, fractions of the same semen samples obtained for microinjection (to ensure the best predictability) were evaluated to determine the semen parameters and sperm DNA fragmentation index (DFI) on the day of oocyte recovery. Results: In total, 120 couples completed the study and were subdivided into fertilized (n=87) and non-fertilized couples (n=33). The fertilized couples were further classified into pregnant (n=48) and non-pregnant (n=39) couples. Compared to non-fertilized and non-pregnant couples, fertilized and pregnant couples showed statistically significantly higher sperm viability and percentage of normal sperm morphology, as well as significantly lower sperm DFI values. A receiver operating characteristic curve analysis of data from the 120 ICSI cycles showed that sperm viability, normal sperm morphology percentages, and sperm DFI were significant prognostic indicators of fertilization at cutoff values of 40%, 7%, and 46%, respectively. A sperm DFI of 46% showed sensitivity and specificity of 95% and 90%, respectively, for predicting fertilization, and no clinical pregnancies occurred in couples with a sperm DFI above 46%. Conclusion Semen parameters from the ICSI day sample, especially sperm viability, normal morphology, and DFI, had an impact on fertilization and pregnancy outcomes in ICSI cycles.

Objective: The present study aimed to detect the behavioral problems pre- and post-cochlear implantation in comparison to normal hearing group to be able to manage these problems to get more benefit from using cochlear implants. Methods: A case-control study included 53 children was done. They were divided into 2 groups, the control group included 28 healthy volunteers with normal hearing and the case group included 25 children with severe to profound hearing loss, fitted for cochlear implantation. The Arabic Child Behavior Checklist (CBCL) was used to detect different behavioral problems in both groups. Case group children were followed up and reassessed again by CBCL 3 months later after cochlear implantation. Results: There were highly significant differences regarding total scores of internalizing and externalizing domains of empirically based CBCL between the control group and the case group after cochlear implants (p=0.001). There were non-significant differences in children within case group (pre- and post-cochlear implantation) regarding emotional and behavioral problems on both empirically based and Diagnostic and Statistical Manual of Mental Disorders-based CBCL. Conclusion For better results, it is necessary to include a specialist of psychosomatic medicine in the cochlear rehabilitation teamwork.