Keltouma Oumbarek

Preeclampsia is a leading cause of maternal mortality worldwide. The aim of this study was to identify factors associated with maternal death due to severe preeclampsia (SPE) in Souss Massa, region of southern Morocco. A multicentric retrospective cross-sectional study was conducted in three referral hospitals from March 2020 to March 2024, based on the medical records of pregnant women with blood pressure ≥ 160/120 mmHg and proteinuria ≥ 3+. Univariate and multivariate logistic regression analyses were performed with a 95% confidence interval and a 5% significance level. A total of 295 records were initially collected. After incomplete records were excluded, 237 patients were eligible. The case fatality rate was 13.2%. The multivariate analysis revealed six variables as potential factors associated with maternal death: absence of fetal heartbeat (aOR = 55.74 [10.89–285.17]) and fetal bradycardia (aOR = 26.85 [2.12–338.78]), altered consciousness (aOR = 10.31 [2.15–49.33]), maternal age <25 years (aOR = 12.97 [1.80–93.51]) and ≥35 years (aOR = 6.01 [1.07–33.60]), rural residence (aOR = 7.72 [1.80–93.51]), severe anaemia (aOR = 13.72 [1.67–112.65]), and preexisting diabetes mellitus (aOR = 6.05 [1.01–36.30]). This study highlights the high-risk profiles of maternal death due to SPE in a Moroccan region with significant prevalence and lethality. Managing modifiable risk factors and addressing disparities in access to skilled maternal care could mitigate the adverse outcomes of preeclampsia. Future research should adopt a prospective, longitudinal design, focusing on sociocultural context specific to the region.

Sleep in intensive care unit (ICU) patients is frequently disrupted, which may adversely affect their overall health and recovery. Despite the implementation of various strategies to promote sleep, accurately assessing its quality remains complex. This pilot study aimed to evaluate both the quality and quantity of sleep in ICU patients using actigraphy (ACT) and the Richards–Campbell Sleep Questionnaire (RCSQ) and to compare the diagnostic performance of these two tools. We conducted a prospective observational study including 228 ICU patients. Sleep was assessed using both RCSQ and ACT. Receiver Operating Characteristic (ROC) curve analysis was used to evaluate the discriminative ability of each tool (Area Under the Curve [AUC], sensitivity, specificity), with optimal cut-off points determined using Youden’s Index. The Mann–Whitney U test was used to compare sleep parameters between patients classified as having good or poor sleep based on ACT measurements. The mean RCSQ score was 38.16 ± 17.09, indicating poor perceived sleep quality. Sleep onset latency (based on RCSQ) was 35.71 ± 21.44 min, with a mean of 40.32 ± 20.03 awakenings. According to ACT, sleep latency was 39.23 ± 22.09 min, and total sleep duration was 198.15 ± 128.42 min (approximately 3 h and 18 min), which is significantly below recommended levels. The average number of awakenings recorded was 24.85. In terms of diagnostic performance, the RCSQ demonstrated excellent discriminative ability (AUC = 1.00 for the total score), while ACT showed more variable results: total sleep duration had a good AUC of 0.91, while sleep latency showed a lower performance with an AUC of 0.50. The RCSQ proved to be more reliable than ACT in assessing sleep quality in ICU patients, providing consistent results across multiple parameters, including sleep depth, latency, and number of awakenings. Conversely, ACT yielded less consistent findings, particularly regarding sleep latency and nighttime interruptions. Further studies are warranted to refine objective tools for evaluating sleep in critically ill patients.

Introduction: Sleep in intensive care unit (ICU) patients is frequently disrupted, which may adversely affect their overall health and recovery. despite the implementation of various strategies to promote sleep, accurately assessing its quality remains complex. This pilot study aimed to evaluate both the quality and quantity of sleep in ICU patients using actigraphy (ACT) and the Richards-Campbell Sleep Questionnaire (RCSQ), and to compare the diagnostic performance of these two tools. Methods: We conducted a prospective observational study including 228 ICU patients. Sleep was assessed using both the RCSQ and ACT. Receiver Operating Characteristic (ROC) curve analysis was used to evaluate the discriminative ability of each tool (Area Under the Curve [AUC], sensitivity, specificity), with optimal cut-off points determined using Youden's Index. The Mann-Whitney U test was used to compare sleep parameters between patients classified as having good or poor sleep based on ACT measurements. Results: The mean RCSQ score was 38.16 ± 17.09, indicating poor perceived sleep quality. Sleep onset latency (based on RCSQ) was 35.71 ± 21.44 minutes, with a mean of 40.32 ± 20.03 awakenings. According to ACT, sleep latency was 39.23 ± 22.09 minutes, and total sleep duration was 198.15 ± 128.42 minutes (approximately 3 hours and 18 minutes), which is significantly below recommended levels. The average number of awakenings recorded 24.85. In terms of diagnostic performance, the RCSQ demonstrated excellent discriminative ability (AUC = 1.00 for the total score), while ACT showed more variable results: Total sleep duration had a good AUC of 0.91, while sleep latency showed a lower performance with an AUC of 0.50. Conclusion: The RCSQ proved to be more reliable than ACT in assessing sleep quality in ICU patients, providing consistent results across multiple parameters, including sleep depth, latency, and number of awakenings. Conversely, ACT yielded less consistent findings, particularly regarding sleep latency and nighttime interruptions. Further studies are warranted to refine objective tools for evaluating sleep in critically ill patients.

Introduction: For patients in intensive care units, the Richards–Campbell Sleep Questionnaire (RCSQ) seems to be a useful tool for assessing sleep quality. However, its application in the Moroccan medical context could be limited due to the lack of a dialectal Arabic version for Morocco. This study’s objective was to translate and validate the RCSQ into Arabic for Moroccan speakers. Patients and methods: For this investigation, a cross-sectional design was adopted. The RCSQ was translated and validated into Arabic for Morocco in accordance with the recommendations. For every scale, psychometric properties were computed. The Cronbach’s α coefficient was utilized to evaluate the internal consistency of multi-item measures. Results: The study involved 224 patients, whose mean age was 47 ± 18.3 years. The RCSQ’s internal consistency, or Cronbach’s alpha, was computed, and all dimensions showed good reliability over the 0.92 (0.894–0.983) level. The items demonstrated good reliability and validity, with correlation values larger than 0.4, according to the data. Conclusion: The RCSQ translated into Arabic for Morocco appears to have good psychometric qualities, making it useful for assessing the quality of sleep of patients in intensive care units within Moroccan healthcare settings.

Introduction: Sleep disturbances are a common and often underestimated complication during intensive care unit (ICU) stays. These disturbances can significantly impact patients’ recovery and overall well-being. This study aimed to assess the sleep quality of ICU patients and investigate the environmental and clinical factors that affect sleep quality during their ICU stay. Methods: We conducted a six-month cross-sectional study involving patients who had stayed in the ICU for at least three nights and were oriented to time and place upon discharge. Sleep quality was assessed using the Arabic version of the Freedman Sleep Questionnaire. Both environmental factors (e.g., noise, light, and nursing interventions) and clinical variables (illness severity and pain) were examined. The differences across three time periods were analyzed using the Wilcoxon test and Spearman’s correlation. Multiple regression analysis identified the factors influencing sleep quality. Statistical analyses were performed using JAMOVI software (version 2.3.28). Results: The study enrolled 328 patients, with an average age of 49.74 ± 17.89 years. Of the participants, 75.3% were adults. The primary reasons for admission were circulatory distress (45.73%) and metabolic disorders (24.09%). Sleep quality was significantly lower in the ICU compared to patients’ sleep at home (Z = −14.870, p < 0.001). The EVA and APACHE II scores had a statistically significant effect on sleep quality (p < 0.001 and p = 0.015, respectively). In contrast, the Charlson and Quick SOFA scores did not show significant effects (p = 0.128 and p = 0.894). Environmental factors, including noise (p = 0.008), light (p = 0.009), and nursing interventions (p = 0.009), significantly impacted sleep quality. Conclusions: Patients in the ICU generally reported poor sleep quality. Our findings suggest that improving pain management, minimizing environmental noise, and reducing staff-related disturbances could significantly enhance sleep quality for patients in the intensive care unit (ICU).

Introduction: Sleep disturbances are a commonly underestimated complication of intensive care unit (ICU) stays. This study aimed to assess sleep quality among ICU patients and to analyze the environmental and clinical factors influencing sleep quality during their stay in the ICU. Methods: We conducted a six-month cross-sectional study involving patients who stayed in the ICU for ≥ 3 nights and were oriented to time and place upon discharge. Sleep quality was assessed using the Arabic version of the Freedman sleep questionnaire, examining both environmental and non-environmental factors, such as illness severity and pain. Differences across three periods were analyzed using the Wilcoxon test and Spearman correlation, while multiple regression analyses identified factors influencing sleep quality. Statistical analyses were performed using JAMOVI software (version 2.3.28). Results: 328 patients were recruited. The average age was 49.74 ± 17.89 years. 75.3% of the participants were adults. The primary admission reasons were circulatory distress 45.73%, followed by metabolic disorders 24.09%. Self-reported sleep quality score at home and the ICU strongly indicated a difference in sleep quality between the two environments (Z = -14.870, p < 0.001), with significantly lower ranks for sleep quality in the ICU. The EVA and APACHE II scores showed a statistically significant effect on sleep quality (p < 0.001 and p= 0.015), while the Charlson and Quick Sofa scores are not significant (p = 0.128 and p=0.894). Several environmental factors showed a statistically significant impact on sleep quality such noise (p = 0.008), light (p = 0.009), and nursing intervention (p=0.009) significantly influence sleep quality. Conclusion: Patients generally reported a poor perception of nighttime sleep quality. Enhancing the pain management and minimizing both environmental noise and staff-related disturbances could significantly improve their sleep quality.