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Use of antenatal corticosteroids among infants with gestational age at 24 to 31 weeks in 57 neonatal intensive care units of China: a cross-sectional study

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Chinese Medical Journal 2023年第7期136卷 822-829页

作者： Jing Zhao Zongtai Feng Yun Dai Wanxian Zhang Siyuan Jiang Yanchen Wang Xinyue Gu Jianhua Sun Yun Cao Shoo KLee Xiuying Tian Zuming Yang on behalf of the Chinese Neonatal Network(CHNN) Division of Neonatology Tianjin Central Hospital of Obstetrics and GynecologyTianjin 300052China Tianjin Key Laboratory of Human Development and Reproductive Regulation Tianjin 300052China Nankai University Maternity Hospital Tianjin 300052China Division of Neonatology The Affiliated Suzhou Hospital of Nanjing Medical UniversitySuzhouJiangsu 215002China Division of Neonatology Children’s Hospital of Fudan UniversityShanghai 201102China NHC Key Laboratory of Neonatal Diseases Fudan UniversityChildren’s Hospital of Fudan UniversityShanghai 201102China Department of Neonatology Shanghai Children’s Medical CenterSchool of MedicineShanghai Jiao Tong UniversityShanghai 200127China Maternal-Infants care Research Centre Mount Sinai HospitalTorontoON M5G 1X5Canada University of Toronto TorontoON M5T 3M7Canada 不详

Background:Antenatal corticosteroids(ACS)can significantly improve the outcomes of preterm *** study aimed to describe the ACS use rates among preterm infants admitted to Chinese neonatal intensive care units(NICU)and to explore perinatal factors associated with ACS use,using the largest contemporary cohort of very preterm infants in ***:This cross-sectional study enrolled all infants born at 24^(+0)to 31^(+6)weeks and admitted to 57 NICUs of the Chinese Neonatal Network from January 1st,2019 to December 30th,*** ACS administration was defined as at least one dose of dexamethasone and betamethasone given before *** logistic regressions were applied to determine the association between perinatal factors and ACS ***:A total of 7828 infants were enrolled,among which 6103(78.0%)infants received *** use rates increased with increasing gestational age(GA),from 177/259(68.3%)at 24 to 25 weeks’gestation to 3120/3960(78.8%)at 30 to 31 weeks’*** infants exposed to ACS,2999 of 6103(49.1%)infants received a single complete course,and 33.4%(2039/6103)infants received a partial *** use rates varied from 30.2%to 100%among different *** regression showed that increasing GA,born in hospital(inborn),increasing maternal age,maternal hypertension and premature rupture of membranes were associated with higher likelihood to receive ***:The use rate of ACS remained low for infants at 24 to 31 weeks’gestation admitted to Chinese NICUs,with fewer infants receiving a complete *** use rates varied significantly among different *** are urgently needed to propose improvement measures and thus improve the usage of ACS.

关键词： Infant,newborn Antenatal corticosteroids Adrenal cortex hormones Betamethasone Dexamethasone Gestational age Maternal age Very preterm infant intensive care unit,neonatal China

Variations in length of stay among survived very preterm infants admitted to Chinese neonatal intensive care units

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World Journal of Pediatrics 2022年第2期18卷 126-134页

作者： Min Zhang Yan-Chen Wang Jin-Xing Feng Ai-Zhen Yu Jing-Wei Huang Si-Yuan Jiang Xin-Yue Gu Jian-Hua Sun Yun Cao Wen-Hao Zhou Shoo KLee Li-Li Wang Rong Yin Division of Neonatology The First Affiliated Hospital of Anhui Medical UniversityNo.218Jixi RoadShushan DistrictHefei 230022China NHC Key Laboratory of Neonatal Diseases Fudan UniversityChildren's Hospital of Fudan UniversityShanghai 201102China Division of Neonatology Shenzhen Children's HospitalShenzhen 518038China Division of Neonatology.Children's Hospital of Fudan University 399 Wanyuan RoadMinhang DistrictShanghai 201102China Division of Neonatology Shanghai Children's Medical CenterShanghai Jiao Tong University School of MedicineShanghai 200127China Maternal-Infants care Research Centre and Department of Pediatrics Mount Sinai HospitalTorontoON M5G 1X5.Canada Professor Emeritus University of Toronto.TorontoON M5T 3M7Canada

Background This study aimed to describe length of stay(LOS)to discharge and site variations among very preterm infants(VPIs)admitted to 57 Chinese neonatal intensive care units(NICUs)and to investigate factors associated with LOS for *** This retrospective multicenter cohort study enrolled all infantscare practices requiring further investigation and quality improvement.

关键词： Length of stay to discharge home Neonatal intensive care Preterm Risk factors

Lessons for intensive care units in COVID-19 pandemic-moving towards sustainability

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Discussion of Clinical Cases 2020年第3期7卷 1-6页

作者： Prashant Nasa Ruchi Nasa Aanchal Singh Critical care Medicine NMC Speciality HospitalDubaiUnited Arab Emirates Department of Pathology Medeor HospitalDubaiUnited Arab Emirates

The Coronavirus disease-2019(COVID-19)pandemic has inundated critical care services *** intensive care units(ICUs)and critical care providers have been forefront of this pandemic,evolving continuously from experiences and emerging *** this review,we discuss the key lessons from the ongoing wave of COVID-19 pandemic and preparations for a future surge or second *** model of sustainable critical care services should be based on 1)infrastructure development,2)preparation and training of manpower,3)implementing standard of care and infection control,4)sustained supply-chain and finally,and 5)surge planning.

关键词： COVID-19 Learnings from SARS-CoV-2 pandemic Preparation for second wave Preparation of ICU for COVID-19 Surge planning ICU preparedness for an outbreak

Prediction of massive transfusion in trauma patients in the surgical intensive care units (THAI-SICU study)

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Chinese Journal of Traumatology 2019年第4期22卷 219-222页

作者： Osaree Akaraborworn Onuma Chaiwat Sunisa Chatmongkolchart Chanatthee Kitsiripant Kaweesak Chittawatanarat Sunthiti Morakul Thammasak Thawitsri Petch Wacharasintg Sujaree Poopipatpab Waraporn Chau-In Chaiyapruk Kusumaphanyo Division of Trauma and Critical care Department of Surgery Faculty of Medicine Prince of Songkla University Hat Yai Songkhla Thailand Department of Anesthesiology Faculty of Medicine Srinakharinwirot University Nakhon Nayok Thailand Department of Anesthesiology. Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand Department of Anesthesiology Faculty of Medicine Prince of Songkla University Hat Yai Songkhla Thailand Department of Surgery Faculty of Medicine Chiang Mai University Chiang Mai Thailand Department of Anesthesiology Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok Thailand Department of Anesthesiology Faculty of Medicine King Chulalongkorn Memorial Hospital Bangkok Chulalongkorn University Thailand Department of Anesthesiology Phramongkutklao Hospital Bangkok Thailand Department of Anesthesiology Navamindradhiraj University Bangkok Thailand Department of Anesthesiology Khon Kaen University Khon Kaen Thailand

Purpose: After damage control surgery, trauma patients are transferred to intensive care units to restore the physiology. During this period, massive transfusion might be required for ongoing bleeding and coagulopathy. This research aimed to identify predictors of massive blood transfusion in the surgical intensive care units (SICUs). Methods: This is an analysis of the THAI-SICU study which was a prospective cohort that was done in the 9-university-based SICUs in Thailand. The study included only patients admitted due to trauma mechanisms. Massive transfusion was defined as received >10 units of packed red blood cells on the first day of admission. Patient characteristics and physiologic data were analyzed to identify the potential factors. A multivariable regression was then performed to identify the significant model. Results: Three hundred and seventy patients were enrolled. Sixteen patients (5%) received massive transfusion in the SICUs. The factors that significantly predicted massive transfusion were an initial sequential organ failure assessment (SOFA)>9 (risk difference (RD) 0.13, 95% confidence interval (CI): 0.03—0.22, p = 0.01);intra-operative blood loss > 4900 mL (RD 0.33, 95% CI: 0.04—0.62, p = 0.02) and intra-operative blood transfusion > 10 units (RD 0.45, 95% Cl: 0.06 to 0.84, p = 0.02). The probability to have massive transfusion was 0.976 in patients who had these 3 factors. Conclusion: Massive blood transfusion in the SICUs occurred in 5%. An initial SOFA >9, intra-operative blood loss >4900 mL, and intra-operative blood transfusion >10 units were the significant factors to predict massive transfusion in the SICUs.

关键词： Massive transfusion Massive bleeding Surgical intensive care Multiple trauma

National preparedness survey of pediatric intensive care units with simulation centers during the coronavirus pandemic

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World Journal of Critical care Medicine 2020年第5期9卷 74-87页

作者： Kamal Abulebda Rami A Ahmed Marc A Auerbach Anna M Bona Lauren E Falvo Patrick G Hughes Isabel T Gross Elisa J Sarmiento Paul R Barach Department of Pediatrics Division of Critical CareIndiana University School of MedicineRiley Hospital for Children at Indiana University HealthIndianapolisIN 46202United States Department of Emergency Medicine School of MedicineIndiana UniversityIndianapolisIN 46202United States Department of Pediatrics Division of Pediatrics Emergency MedicineYale University School of MedicineNew HavenCT 06504United States Department of Integrated Medical Science Florida Atlantic UniversityBoca RatonFL 33431United States Department of Emergency Medicine Yale University School of MedicineNew HavenCT 06504United States Department of Pediatrics Wayne State University School of MedicineDetroitMI 48202Jefferson College of Population HealthPhiladelphiaPA19107United States

The coronavirus disease pandemic caught many pediatric hospitals unpreparedand has forced pediatric healthcare systems to scramble as they examine and planfor the optimal allocation of medical resources for the highest priority *** is limited data describing pediatric intensive care unit (PICU) preparednessand their health worker *** describe the current coronavirus disease 2019 (COVID-19) preparedness effortsamong a set of PICUs within a simulation-based network *** A cross-sectional multi-center national survey of PICU medical director(s) fromchildren’s hospitals across the United States. The questionnaire was developedand reviewed by physicians with expertise in pediatric critical care, disasterreadiness, human factors, and survey development. Thirty-five children’shospitals were identified for recruitment through a long-established nationalresearch network. The questions focused on six themes: (1) PICU and medicaldirector demographics;(2) Pediatric patient flow during the pandemic;(3)Changes to the staffing models related to the pandemic;(4) Use of personalprotective equipment (PPE);(5) Changes in clinical practice and innovations;and(6) Current modalities of training including *** report on survey responses from 22 of 35 PICUs (63%). The majority of PICUswere located within children’s hospitals (87%). All PICUs cared for pediatricpatients with COVID-19 at the time of the survey. The majority of PICUs (83.4%)witnessed decreases in non-COVID-19 patients, 43% had COVID-19 dedicatedunits, and 74.6% pivoted to accept adult COVID-19 patients. All PICUsimplemented changes to their staffing models with the most common changesbeing changes in COVID-19 patient room assignment in 50% of surveyed PICUsand introducing remote patient monitoring in 36% of the PICU units. Ninety-fivepercent of PICUs conducted training for donning and doffing of enhanced *** 6 months into the pandemic, one-third of PICUs across the U

关键词： COVID-19 Pediatric intensive care unit Simulation Practice innovations Training Preparedness

Effects of strengthening prospective nursing practice on sleep quality,anxiety,and depression of awake patients in intensive care unit

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World Journal of Psychiatry 2024年第5期14卷 735-741页

作者： Fei Lin Lei Liu Department of intensive care Unit Dushu Lake Hospital Affiliated to Soochow UniversitySuzhou 215000Jiangsu ProvinceChina

BACKGROUND The intensive care unit(ICU)is a specialized hospital *** patients in the ICU frequently encounter adverse psychological states,such as anxiety and fear,often accompanied by poor sleep *** situation has garnered significant attention within the medical *** To investigate the impact of prospective nursing intervention strategies on the sleep quality and negative emotional state of conscious ICU *** One hundred and twenty ICU awake patients admitted to our hospital were selected and randomly divided into control(n=60)and observation(n=60)*** in the control group were cared for using the conventional nursing model,while patients in the observation group were cared for using the prospective nursing *** improvement was assessed using the International Standardized Sleep Efficiency Formula and Pittsburgh Sleep Quality Index(PSQI).The PSQI,Generalized Anxiety Disorder 7-item(GAD-7)scale,Self-Depression Scale(SDS),and satisfaction before and after treatment were used to assess the negative emotional states of patients under the two care *** Patient satisfaction in the observation group was significantly higher than in the control *** GAD-7 and SDS scores in the observation group were significantly lower than those in the control group,and the total effective rate of sleep improvement in the observation group was significantly higher than in the control *** treatment,the PSQI scores of the two groups significantly decreased(P<0.05).The decrease in the observation group was more significan than that in the control group,and the difference between the two groups was statistically *** Prospective nursing interventions can improve sleep quality and psychological levels and significantly affect conscious patients in the ICU,which is worthy of clinical application.

关键词： Prospective nursing intensive care unit Sobriety Mental health sleep quality Anxiety and depression

intensive care unit-acquired weakness: Recent insights

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Journal of intensive Medicine 2024年第1期4卷 73-80页

作者： Juan Chen Man Huang Department of General intensive care Unit The Second Affiliated Hospital of Zhejiang University School of MedicineHangzhou 310009ZhejiangChina

intensive care unit-acquired weakness(ICU-AW)is a common complication in critically ill patients and is associated with a variety of adverse *** include the need for prolonged mechanical ventilation and ICU stay;higher ICU,in-hospital,and 1-year mortality;and increased in-hospital ***-AW is associated with multiple risk factors including age,underlying disease,severity of illness,organ failure,sepsis,immobilization,receipt of mechanical ventilation,and other factors related to critical *** pathological mechanism of ICUAW remains unclear and may be considerably *** review aimed to evaluate recent insights into ICU-AW from several aspects including risk factors,pathophysiology,diagnosis,and treatment strategies;this provides new perspectives for future research.

关键词： intensive care unit-acquired weakness Muscle weakness Muscle atrophy Risk factor Mechanism Treatment

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

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World Journal of Clinical Cases 2024年第7期12卷 1235-1242页

作者： Ling Wang Deng-Yan Long intensive care Unit People's Hospital of Qiandongnan Miao and Dong Autonomous PrefectureKaili 556000Guizhou ProvinceChina

BACKGROUND intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse ***,there is a lack of effective preventive *** To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and *** Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU *** data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were *** relationships between these variables and ICU-AW were *** iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic *** Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW ***,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical *** most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechani

关键词： intensive care unit-acquired weakness Risk factors Machine learning Prevention Strategies

Optimizing artificial intelligence in sepsis management: Opportunities in the present and looking closely to the future

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Journal of intensive Medicine 2024年第1期4卷 34-45页

作者： Darragh O’Reilly Jennifer McGrath Ignacio Martin-Loeches Department of intensive care Medicine Multidisciplinary Intensive Care Research Organization(MICRO)St James’HospitalDublinIreland Department of Respiratory intensive care Hospital ClinicUniversitat de BarcelonaIDIBAPSCIBERESBarcelonaSpain

Sepsis remains a major challenge internationally for healthcare *** incidence is rising due to poor public awareness and delays in its recognition and subsequent *** sepsis,mortality increases with every hour left *** intelligence(AI)is transforming worldwide healthcare delivery at *** review has outlined how AI can augment strategies to address this global disease *** and machine learning(ML)algorithms can analyze vast quantities of increasingly complex clinical datasets from electronic medical records to assist clinicians in diagnosing and treating sepsis earlier than traditional *** review highlights how these models can predict the risk of sepsis and organ failure even before it *** gives providers additional time to plan and execute treatment plans,thereby avoiding increasing complications associated with delayed diagnosis of *** potential for cost savings with AI implementation is also discussed,including improving workflow efficiencies,reducing administrative costs,and improving healthcare *** these advantages,clinicians have been slow to adopt AI into clinical *** of the limitations posed by AI solutions include the lack of diverse data sets for model building so that they are widely applicable for routine clinical ***,the subsequent algorithms are often based on complex mathematics leading to clinician hesitancy to embrace such ***,we highlight the need for robust political and regulatory frameworks in this area to achieve the trust and approval of clinicians and patients to implement this transformational technology。

关键词： Artificial intelligence Data science Machine learning intensive care unit(ICU) Critical care Sepsis