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Key pointsO_ST_ABSQuestionC_ST_ABSHow do nomograms and machine-learning algorithms of severity risk prediction and triage of COVID-19 patients at hospital admission perform? FindingsThis model was prospectively validated on six test datasets comprising of 426 patients and yielded AUCs ranging from 0.816 to 0.976, accuracies ranging from 70.8% to 93.8%, sensitivities ranging from 83.7% to 100%, and specificities ranging from 41.0% to 95.7%. The cut-off probability values for low, medium, and high-risk groups were 0.072 and 0.244. MeaningThe findings of this study suggest that our models performs well for the diagnosis and prediction of progression to severe or critical illness of COVID-19 patients and could be used for triage of COVID-19 patients at hospital admission. IMPORTANCEThe outbreak of the coronavirus disease 2019 (COVID-19) has globally strained medical resources and caused significant mortality for severely and critically ill patients. However, the availability of validated nomograms and the machine-learning model to predict severity risk and triage of affected patients is limited. OBJECTIVETo develop and validate nomograms and machine-learning models for severity risk assessment and triage for COVID-19 patients at hospital admission. DESIGN, SETTING, AND PARTICIPANTSA retrospective cohort of 299 consecutively hospitalized COVID-19 patients at The Central Hospital of Wuhan, China, from December 23, 2019, to February 13, 2020, was used to train and validate the models. Six cohorts with 426 patients from eight centers in China, Italy, and Belgium, from February 20, 2020, to March 21, 2020, were used to prospectively validate the models. MAIN OUTCOME AND MEASURESThe main outcome was the onset of severe or critical illness during hospitalization. Model performances were quantified using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. RESULTSOf the 299 hospitalized COVID-19 patients in the retrospective cohort, the median age was 50 years ((interquartile range, 35.5-63.0; range, 20-94 years) and 137 (45.8%) were men. Of the 426 hospitalized COVID-19 patients in the prospective cohorts, the median age was 62.0 years ((interquartile range, 50.0-72.0; range, 19-94 years) and 236 (55.4%) were men. The model was prospectively validated on six cohorts yielding AUCs ranging from 0.816 to 0.976, with accuracies ranging from 70.8% to 93.8%, sensitivities ranging from 83.7% to 100%, and specificities ranging from 41.0% to 95.7%. The cut-off values of the low, medium, and high-risk probabilities were 0.072 and 0.244. The developed online calculators can be found at https://covid19risk.ai/. CONCLUSION AND RELEVANCEThe machine learning models, nomograms, and online calculators might be useful for the prediction of onset of severe and critical illness among COVID-19 patients and triage at hospital admission. Further prospective research and clinical feedback are necessary to evaluate the clinical usefulness of this model and to determine whether these models can help optimize medical resources and reduce mortality rates compared with current clinical practices.
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ABATRACTO_ST_ABSIMPORTANCEC_ST_ABSIn the epidemic, surgeons cannot distinguish infectious acute abdomen patients suspected COVID-19 quickly and effectively. OBJECTIVETo develop and validate a predication model, presented as nomogram and scale, to distinguish infectious acute abdomen patients suspected coronavirus disease 2019 (COVID-19). DESIGNDiagnostic model based on retrospective case series. SETTINGTwo hospitals in Wuhan and Beijing, China. PTRTICIPANTS584 patients admitted to hospital with laboratory confirmed SARS-CoV-2 from 2 Jan 2020 to15 Feb 2020 and 238 infectious acute abdomen patients receiving emergency operation from 28 Feb 2019 to 3 Apr 2020. METHODSLASSO regression and multivariable logistic regression analysis were conducted to develop the prediction model in training cohort. The performance of the nomogram was evaluated by calibration curves, receiver operating characteristic (ROC) curves, decision curve analysis (DCA) and clinical impact curves in training and validation cohort. A simplified screening scale and managing algorithm was generated according to the nomogram. RESULTSSix potential COVID-19 prediction variables were selected and the variable abdominal pain was excluded for overmuch weight. The five potential predictors, including fever, chest computed tomography (CT), leukocytes (white blood cells, WBC), C-reactive protein (CRP) and procalcitonin (PCT), were all independent predictors in multivariable logistic regression analysis (p [≤]0.001) and the nomogram, named COVID-19 Infectious Acute Abdomen Distinguishment (CIAAD) nomogram, was generated. The CIAAD nomogram showed good discrimination and calibration (C-index of 0.981 (95% CI, 0.963 to 0.999) and AUC of 0.970 (95% CI, 0.961 to 0.982)), which was validated in the validation cohort (C-index of 0.966 (95% CI, 0.960 to 0.972) and AUC of 0.966 (95% CI, 0.957 to 0.975)). Decision curve analysis revealed that the CIAAD nomogram was clinically useful. The nomogram was further simplified into the CIAAD scale. CONCLUSIONSWe established an easy and effective screening model and scale for surgeons in emergency department to distinguish COVID-19 patients from infectious acute abdomen patients. The algorithm based on CIAAD scale will help surgeons manage infectious acute abdomen patients suspected COVID-19 more efficiently.
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BackgroundThe outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) results in a cluster of coronavirus disease 2019 (COVID-19). We reported the clinical characteristics of COVID-19 patients with acute respiratory distress syndrome (ARDS), and further investigated the treatment and progression of ARDS in COVID-19. MethodsThis study enrolled 109 patients with COVID-19 admitted to the Central Hospital of Wuhan, a designated hospital in Wuhan, China, from January 2 to February 1, 2020. Patients were followed up to February 12, 2020. The clinical data were collected from the electronic medical records. The differences in the treatment and progression with the time and the severity of ARDS were determined. FindingsAmong 109 patients, mean age was 55 years, and 59 patients were male. With a median 15 days (range, 4 to 30 days) follow-up period, 31 patients (28.4%) died, while 78 (71.6%) survived and discharged. Of all patients, 53 (48.6%) developed ARDS. Compared to non-ARDS patients, ARDS patients were elder (mean age, 61 years vs. 49 years), and more likely to have the coexistent conditions, including diabetes (20.8% vs. 1.8%), cerebrovascular disease (11.3% vs. 0%), and chronic kidney disease (15.1% vs. 3.6%). Compared to mild ARDS patients, those with moderate and severe ARDS had higher mortality rates. No significant effect of antivirus, glucocorticoid, or immunoglobulin treatment on survival was observed in patients with ARDS. InterpretationThe mortality rate increased with the severity of ARDS in COVID-19, and the effects of current therapies on the survival for these patients were not satisfactory, which needs more attention from clinicians. FundingHealth and Family Planning Commission of Wuhan Municipality.
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Objective To investigate the efficacy of intravenous antioxidants therapy in treating moderately severe acute pancreatitis (MSAP) and severe acute pancreatitis (SAP).Methods Pubmed,Embase,Cochrane library and CNKI databases for all randomized control trials published before March 18st,2016 manually was searched by computer.Data on AP associated mortality and length of stay (LOS) were collected.The quality of the trials included was assessed by the Cochrane systematic review method.Results Fifteen trials with data of 620 patients were eligible for final inclusion.Among the 15 trials,detailed randomization for grouping was clearly described in 5 studies and obvious bias was observed in 1 study.Three studies had obvious biases considering whether outcome assessment was blinded,outcome data was incomplete and outcome report was selective.No other apparent bias was found.Statistical analysis showed that compared with control group,intravenous antioxidants administration did not significantly reduce mortality (12.1 vs 9.7,RD=-0.02,95％ CI-0.08～-0.03,P=0.44;RR=0.83.95％ CI0.51～ 1.34,P=0.44),but could shorten LOS (MD=-2.02;95％ CI-4.00～-0.05;P=0.04).Conclusions Intravenous antioxidants could greatly shorten LOS of patients with MSAP and SAP.
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OBJECTIVE:To investigate the effectiveness and economics of 10 mg/d rosuvastatin and 20 mg/d atorvastatin in the treatment of hyperlipidemia (HLP). METHODS:The information of 180 HLP patients selected from Tianmen Municipal First People's Hospital during Mar. 2015-Feb. 2016 were divided into group A and B according to medication regimen,with 90 cases in each group. Group A was given Atorvastatin calcium tablet 20 mg,qd;group B was given Rosuvastatin calcium tablet 10 mg,qd. Treatment course of 2 groups lasted for 8 weeks. Blood lipid indexes before and after treatment,lipid-lowering efficacy,the rate of qualified blood lipid and the occurrence of ADR after treatment were compared between 2 groups. Cost-effectiveness analysis was adopted for economic evaluation. RESULTS:Before treatment,there was no statistical significance in the levels of blood lipid in-dexes between 2 groups (P>0.05). After treatment,TC and LDL-C levels of 2 groups were significantly lower than before treat-ment,and those of group B were significantly lower than those of group A,with statistical significance(P0.05). The costs of group A and B were 488.32,436.24 yuan,and cost-effectiveness ratios were 5.63,4.46;incremental cost-effectiveness ratio was -4.69. The plan of group B had cost-effective-ness advantage. The results of cost-effectiveness analysis were supported by sensitivity analysis. CONCLUSIONS:In the view of short-term efficacy,10 mg/d rosuvastatin plan is better than 20 mg/d atorvastatin plan in lowering lipid and has cost-effectiveness advantage,and both have similar safety.
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Objective To investigate the effect of rapid repeated cold air inhalation stimulation on cold-sensitive chan-nel transient receptor potential ankyrin 1(TRPA1) associated inflammatory cytokines in living lungs .Methods A total of 20 male Wistar rats were randomly and evenly divided into 4 groups:cold air inhalation group , warm air inhalation group , TRPA1 channel agonist inhalation group and normal group , respectively . Tracheal intubation was carried out after anesthesia in rats of cold air inhalation group , and the tubes were linked to the air temperature controlled device with the temperature controlled at ( 2 ±1 )℃.The rats of warm air inhalation group were treated in the same way as cold air inhalation group except for the temperature at (36 ±1)℃.The rats of both groups were treated for 3 times, 1 hour each time.There were 12 hour intervals between treatments .The rats of TRPA1 channel agonist inhalation group were treated with atomizing inhalation of 60 mmol/L acrolein at room temperature (24 ±2)℃for 3 times, 1 hour each time.There were 12 hour intervals between two treatments .The rats were sacrificed after the last treatment .The tracheas and left lung tissues of all rats were taken and total RNA was extracted .The mRNA expressions of TRPA1, interleukin 1 beta ( IL-1β), interleukin 5(IL-5),and neutrophil chemoattractant chemokine (CXCL-1/KC)in the rat lungs were detected by real-time quantitative PCR .Results TRPA1 was expressed in rat lung tissues .In the short term cold air inhalation group , the expressions of IL-1β,IL-5 and CXCL-1/KC mRNA in the rat lungs were higher than those of the warm air inhalation or the normal groups .Similar results were also found in the specific TRPA 1 channel positive agonist ( acrolein ) inhalation group . Conclusion In living animals, the TRPA1 channels of the lungs can be activated by short-term cold air(<17℃),which results in the increasing expression of some inflammatory cytokines in lungs .
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OBJECTIVE:To establish a HPLC method for the quantitative determination of Geniposide in Zhibo mixture.METHODS:The separation of sample was performed on Shim-pack VP-ODS C18 column(150mm?4.6mm,5?m)at a temperature of 25℃.The mobile phase consisted of acetonitrile-water(12∶88)at a flow rate of 1mL?min-1.The detection wavelength was set at 238nm.RESULTS:The linear range of Geniposide was 25～100mg?L-1(r=0.999 7).The average recovery was 99.89%(RSD=0.80%,n=9).CONCLUSION:The method was proved to be sensitive,specific,reproducible and suitable for quality control of Zhibo mixture.
