2.Acute respiratory distress syndrome: focusing on secondary injury.
Pan PAN ; Long-Xiang SU ; Da-Wei LIU ; Xiao-Ting WANG
Chinese Medical Journal 2021;134(17):2017-2024
Acute respiratory distress syndrome (ARDS) is one of the most common severe diseases seen in the clinical setting. With the continuous exploration of ARDS in recent decades, the understanding of ARDS has improved. ARDS is not a simple lung disease but a clinical syndrome with various etiologies and pathophysiological changes. However, in the intensive care unit, ARDS often occurs a few days after primary lung injury or after a few days of treatment for other severe extrapulmonary diseases. Under such conditions, ARDS often progresses rapidly to severe ARDS and is difficult to treat. The occurrence and development of ARDS in these circumstances are thus not related to primary lung injury; the real cause of ARDS may be the "second hit" caused by inappropriate treatment. In view of the limited effective treatments for ARDS, the strategic focus has shifted to identifying potential or high-risk ARDS patients during the early stages of the disease and implementing treatment strategies aimed at reducing ARDS and related organ failure. Future research should focus on the prevention of ARDS.
Humans
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Intensive Care Units
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Respiratory Distress Syndrome/etiology*
;
Treatment Outcome
3.Progression in the application of machine learning in acute respiratory distress syndrome.
Weijun ZHANG ; Jianxiao CHEN ; Yuan GAO
Chinese Critical Care Medicine 2023;35(6):662-664
Acute respiratory distress syndrome (ARDS) is a clinical syndrome defined by acute onset of hypoxemia and bilateral pulmonary opacities not fully explained by cardiac failure or volume overload. At present, there is no specific drug treatment for ARDS, and the mortality rate is high. The reason may be that ARDS has rapid onset, rapid progression, complex etiology, and great heterogeneity of clinical manifestations and treatment. Compared with traditional data analysis, machine learning algorithms can automatically analyze and obtain rules from complex data and interpret them to assist clinical decision making. This review aims to provide a brief overview of the machine learning progression in ARDS clinical phenotype, onset prediction, prognosis stratification, and interpretable machine learning in recent years, in order to provide reference for clinical.
Humans
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Hypoxia/complications*
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Respiratory Distress Syndrome/etiology*
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Prognosis
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Machine Learning
4.Report of a case with Potter's syndrome.
Chinese Journal of Pediatrics 2004;42(7):556-556
7.Analysis of risk factors for acute lung injury/acute respiratory distress syndrome after esophagectomy.
Jia Xuan XU ; Hong Zhi WANG ; Jun DONG ; Xiao Jie CHEN ; Yong YANG ; Ren Xiong CHEN ; Guo Dong WANG
Journal of Peking University(Health Sciences) 2018;50(6):1057-1062
OBJECTIVE:
To explore the incidence and risk factors for the acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) after resection of esophageal carcinoma.
METHODS:
We retrospectively analyzed 422 consecutive patients admitted to the Department of Critical Care Medicine with esophageal carcinoma undergoing esophagectomy from January 2010 to December 2016 in Peking University Cancer Hospital. ALI/ARDS were diagnosed, the patients were divided into ALI/ARDS group and control group without ALI/ARDS, the differences of clinical features were contrasted between the two groups, and the multivariate Logistic regression modeling was used to identify the independent risk factors for ALI/ARDS.
RESULTS:
In the study, 41 ALI/ARDS cases were diagnosed, making up 9.7% (41/422) of all the enrolled patients undergoing esophagectomy. Comparisons of the ALI/ARDS group and the control group indicated significant statistical differences in the average length of their hospital stay [(18.9±9.7) d vs. (14.8±3.6) d, P=0.011], the proportion of the patients who needed mechanical ventilation support [51.2% (21/41) vs. 9.4% (36/381), P<0.001] and in-hospital mortality [31.7% (13/41) vs. 5.0% (19/381), P<0.001]. Univariate analysis showed significant differences between the patients with ALI/ARDS and without ALI/ARDS in smoking history (P=0.064), preoperative forced expiratory volume in one second/forced vital capacity (FEV1/FVC) (P=0.020), diffusing capacity of the lung for carbon monoxide (DLCO) (P=0.011), body weight index (BMI) (P=0.044), American Society of Anesthesiologists (ASA) physical status classification (P=0.049) and one lung ventilation duration (P=0.008), while multivariate Logistic regression analysis indicated that preoperative FEV1/FVC (OR=1.053, P=0.016, 95%CI 1.010-1.098), ASA physical status classification (OR=2.392, P=0.033, 95%CI 1.073-5.335) and one lung ventilation duration (OR=0.994, P=0.028, 95%CI 0.989-0.999) were the independent risk factors for ALI/ARDS after esophagectomy.
CONCLUSION
ALI/ARDS was a serious complication in patients undergoing esophagectomy associated with increment in length of hospital stay and in-hospital mortality. Multivariate Logistic regression analysis indicated that preoperative FEV1/FVC, ASA classification and one lung ventilation duration were the independent risk factors for ALI/ARDS after esophagectomy. Carefully assessing the patient before operation, shortening one lung ventilation duration were the key points in preventing ALI/ARDS after esophagectomy.
Acute Lung Injury/etiology*
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Esophagectomy/adverse effects*
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Humans
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Respiration, Artificial
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Respiratory Distress Syndrome/etiology*
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Retrospective Studies
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Risk Factors
8.Comparison between tow methods of acute physiology and chronic health evaluation III and acute lung injury scale to evaluate the severity and prognosis of severe acute respiratory syndrome.
Guo-qiang ZHANG ; Cheng-dong GU ; Yu-qing ZHU ; Li-ye WANG ; Peng LIU
Chinese Journal of Epidemiology 2004;25(9):802-804
OBJECTIVETo evaluate the acute physiology and chronic health evaluation III (APACHE III) and acute lung injury (ALI) scale in the severity and prognosis of severe acute respiratory syndrome (SARS).
METHODSThe clinical data of 38 SARS patients, including survivors (24 cases) and no survivors (14 cases) were collected and evaluated with APACHE III and ALI scoring systems. The correlation of scores and prognosis was evaluated.
RESULTSThe scores of APACHE III in the non survivors were higher remarkably than those in the survivor group (P < 0.001). The scores of APACHE III had positive correlation with the overall fatality rate. When the scores of APACHE III was higher than 60, the mortality increased obviously (chi(2) = 3.886, P < 0.05). Elderly patients with SARS who were over 60 years old had a high mortality (chi(2) = 8.660, P < 0.05). The scores of ALI in the non survivors had not statistical significance than those in the survivor group (P = 0.127).
CONCLUSIONSThe score of APACHE III in the SARS are correlated with the patient's condition and prognosis. Elderly patients with SARS have a high mortality.
APACHE ; Adult ; Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; Prognosis ; Respiratory Distress Syndrome, Adult ; etiology ; physiopathology ; Severe Acute Respiratory Syndrome ; physiopathology
9.Pathogenicity and treatment of acute respiratory distress syndrome after thoracotomy.
Xiao-feng CHEN ; Jia-an DING ; Wen GAO ; Lei JIANG ; Guang-ya SUN ; Zheng-he HU
Chinese Journal of Surgery 2003;41(12):906-908
OBJECTIVETo investigate the causes of acute respiratory distress (ARDS) after thoracotomy and to find out the measures to prevent ARDS.
METHODSThe characteristics of incidence, pathogenicity and treatment of ARDS after thoracotomy in 31 patients were analysed.
RESULTSThe patients who had chronic obstructive pulmonary disease, long history of smoking, hypertension were prone to ARDS. Injury to lung in operation, shock and pulmonary infection probably caused ARDS. Clearing away respiratory tract secretion, preserving of a clear airway, controlling pulmonary infection, alleviating pneumonedema by diuresis, early executing tracheotomy or mechanic assistant ventilation by tracheointubation were keys to rescuing patients successfully.
CONCLUSIONSIt is suggested that multi factors were related to ARDS after thoracotomy. Shock, injury to lung in operation, pulmonary infection, are important factors that lead to post-operative ARDS after thoracotomy. Early treatment can reduce mortality of ARDS.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Respiratory Distress Syndrome, Adult ; etiology ; prevention & control ; therapy ; Thoracotomy ; adverse effects
10.Perinatal conditions of preterm infants with different severities of respiratory distress syndrome.
Fa-Lin XU ; Fang-Li ZHUANG ; Qiong-Dan BAI ; Jia-Jia DUAN
Chinese Journal of Contemporary Pediatrics 2011;13(10):780-782
OBJECTIVETo understand the risk factors for respiratory distress syndrome (RDS) by comparing the perinatal conditions of preterm infants with different severities of RDS.
METHODSA total of 667 preterm infants with RDS were classified into 4 groups according to the chest X-ray severity: grade I (217 cases), grade II (225 cases), grade III (126 cases) and grade IV (99 cases). The perinatal conditions of the preterm infants were reviewed retrospectively.
RESULTSThere were no significant differences in the gender, the percentage of twins, the percentage of the younger one in twins, maternal age, the percentage of using antenatal corticosteroids, the percentage of premature rupture of membranes, the percentage of placental abruption, the delivery mode and the fertilization mode in preterm infants with different severities of RDS. With the increasing severity of RDS, the birth weight and the gestational age decreased, and the percentage of the infants with Apgar score ≤7 or maternal pregnancy-induced hypertension increased (P<0.05).
CONCLUSIONSThe severity of RDS is related to gestational age, birth weight and perinatal asphyxia in preterm infants.
Birth Weight ; Female ; Gestational Age ; Humans ; Infant, Newborn ; Infant, Premature ; Male ; Prognosis ; Respiratory Distress Syndrome, Newborn ; classification ; etiology