Al-Harmi Jehad Abdullah, Alsannan Baydaa, Alhadhoud Fatemah, Akbar Zahraa, Alazmi Eman, AlMuzayen Khaled, Hussain Eelaf, Aldarweesh Mariam, Pecorino Basilio, Laganà Antonio Simone, D'Amato Antonio, Agrifoglio Vittorio, Etrusco Andrea
Department of Obstetrics and Gynecology, College of Medicine, Kuwait University, Safat, 13110, Kuwait.
Department of Obstetrics and Gynecology, Kuwait Ministry of Health, Maternity Hospital, Kuwait City, Kuwait.
Open Med (Wars). 2024 Oct 28;19(1):20241062. doi: 10.1515/med-2024-1062. eCollection 2024.
The COVID-19 pandemic had adverse health outcomes on individuals and communities. In this cross-sectional study we evaluated the admission rates in a tertiary-level hospital during the first wave of the pandemic (March 22, 2020 to August 31, 2020).
We compared the indications for admission during the first wave of the pandemic to a control period prior to the lockdown (November 9, 2019 to March 22, 2020).
Most hospital admissions during the curfew period were obstetric emergencies (46.88%), which were significantly higher than the control group (38.19%) ≤ 0.0001. Among the obstetric emergencies, cases in active labor (65.63%) were dominant. Significant rises in car deliveries (2.46%, ≤ 0.0001) and admissions during the second stage of labor (6.43%, ≤ 0.001) were noted. There was also an increased rate of admissions for early pregnancy complications, induction of labor, elective obstetric cases, and medical obstetric cases.
This study demonstrates that lockdown precautions implemented had a significant impact on the rate of admissions to Maternity Hospital. The data obtained may be a used to aid in designing robust policies for future pandemics to avoid adverse health outcomes.
新冠疫情对个人和社区产生了不良健康影响。在这项横断面研究中,我们评估了疫情第一波期间(2020年3月22日至2020年8月31日)一家三级医院的收治率。
我们将疫情第一波期间的入院指征与封锁前的对照期(2019年11月9日至2020年3月22日)进行了比较。
宵禁期间,大多数医院收治的是产科急症(46.88%),显著高于对照组(38.19%),P≤0.0001。在产科急症中,活跃期分娩的病例占主导(65.63%)。剖宫产率(2.46%,P≤0.0001)和第二产程入院率(6.43%,P≤0.001)显著上升。早孕并发症、引产、择期产科病例和内科产科病例的入院率也有所增加。
本研究表明,实施的封锁预防措施对妇产医院的收治率有显著影响。所获得的数据可用于帮助制定应对未来疫情的有力政策,以避免不良健康后果。