Serum Lactate/Albumin as a Predictor of In-Hospital Mortality in ICU Pancreatitis Patients: an Analysis of the MIMIC-III Database

Abstract Background: Acute pancreatitis (AP) is a common serious illness, and is characterized by rapid deterioration and a high mortality rate. Several biomarkers can evaluate and guide the treatment of acute pancreatitis, but there is currently no consensus on which markers are the most effective, simple, and economical for treating early-onset AP. In this study, we used the MIMIC III database to conduct a retrospective study on the relationship between early lactate/albumin (LAC/ALB), in-hospital mortality, and complication rates in patients with acute pancreatitis in the ICU.Methods: Basic data and indicators of laboratory tests, hospital deaths, and hospitalization days of acute pancreatitis patients were extracted from the database, after which the relationship between LAC/ALB and hospital mortality, ICU hospitalization days, and organ failure were evaluated using a t-test, a rank-sum test, a chi-square test or Fisher's exact probability method, and a Cox proportional hazard model.Results: 894 patients met the requirements and were selected from the MIMIC III database. They were subsequently grouped according to the lower limit ratio of the LAC/ALB normal value of 0.7. The group with LAC/ALB>0.7 showed higher hospital mortality rates, and the Lac, Inr, nitrogen, blood sugar, AKI incidence, Tbil, Sapsii score, and Sofa scores were all higher than the group with LAC/ALB<0.7. A multivariate Cox regression analysis model was used to explore the relationship between LAC/ALB levels and inpatient mortality. After including different adjustment variables, we determined that LAC/ALB is a risk factor for in-hospital death. The results of the subgroup analysis of LAC/ALB levels and mortality of hospitalized patients indicate that higher levels of LAC/ALB are risk factors for in-hospital deaths in patients with acute pancreatitis.

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COVID-19 in-hospital mortality and mode of death in a dynamic and non-restricted tertiary care model in Germany

10.21203/rs.3.rs-48983/v1 ◽

2020 ◽

Author(s):

Siegbert Rieg ◽

Maja von Cube ◽

Johannes Kalbhenn ◽

Stefan Utzolino ◽

Katharina Pernice ◽

...

Keyword(s):

Mechanical Ventilation ◽

Hospital Mortality ◽

Cox Regression ◽

Medical Center ◽

Tertiary Care ◽

Study Entry ◽

Hospital Death ◽

Care Model ◽

Cox Regression Analysis ◽

Hospitalised Patients

Abstract BackgroundReported mortality of hospitalised COVID-19 patients varies substantially, particularly in critically ill patients. So far COVID-19 in-hospital mortality and modes of death under optimised care conditions have not been systematically studied.MethodsThis retrospective observational monocenter cohort study was performed after implementation of a non-restricted, dynamic tertiary care model at the University Medical Center Freiburg, an experienced ARDS and ECMO referral center. All hospitalised patients with PCR-confirmed SARS-CoV-2 infection were included. The primary endpoint was in-hospital mortality, secondary endpoints included major complications and modes of death. A multistate analysis and a Cox regression analysis for competing risk models were performed. Modes of death were determined by two independent reviewers.ResultsBetween February 25, and May 8, 213 patients were included in the analysis. The median age was 65 years, 129 patients (61%) were male. 70 patients (33%) were admitted to the intensive care unit (ICU), of which 57 patients (81%) received mechanical ventilation and 23 patients (33%) extracorporeal membrane-oxygenation (ECMO) support. According to the multistate model the probability to die within 90 days after COVID-19 onset was 24% in the whole cohort. If the levels of care at time of study entry were accounted for, the probabilities to die were 16% if the patient was initially on a regular ward, 47% if in the ICU and 57% if mechanical ventilation was required at study entry. Age ≥ 65 years and male sex were predictors for in-hospital death. Predominant complications – as judged by two independent reviewers – determining modes of death were multi-organ failure, septic shock and thromboembolic and hemorrhagic complications.ConclusionIn a dynamic care model COVID-19-related in-hospital mortality remained substantial. In the absence of potent antiviral agents, strategies to alleviate or prevent the identified complications should be investigated. In this context, multistate analyses enable comparison of models-of-care and treatment strategies and allow estimation and allocation of health care resources.RegistrationGerman Clinical Trials Register (identifier DRKS00021775), retrospectively registered June 10, 2020.

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In-hospital Mortality and Causes of Death in People Diagnosed With HIV in a General Hospital in Shenyang, China: A Cross-Sectional Study

Frontiers in Public Health ◽

10.3389/fpubh.2021.774614 ◽

2021 ◽

Vol 9 ◽

Author(s):

Cheng Bo Li ◽

Ying Zhou ◽

Yu Wang ◽

Sheng Liu ◽

Wen Wang ◽

...

Keyword(s):

Risk Factors ◽

Hospital Mortality ◽

Medical Care ◽

Protective Factor ◽

Cox Regression ◽

Opportunistic Infections ◽

Antiviral Treatment ◽

Public Health Issue ◽

Hospital Death ◽

Cox Regression Analysis

Background: Acquired immune deficiency syndrome (AIDS), caused by human immunodeficiency virus (HIV) infection, is a serious public health issue. This study investigated the correlated factors and possible changing trend of in-hospital death in patients diagnosed with HIV in the past decade in our hospital.Methods: We retrospectively collected data of firstly hospitalized patients with HIV in the Department of Infectious Disease in the First Affiliated Hospital of China Medical University from January 1, 2010 to December 31, 2019, and compared various factors that correlated with in-hospital death, including age, sex, opportunistic infections, and antiretroviral therapy (ART) status. Cox regression analysis was used to identify the risk factors for death.Results: In total, 711 patients were recruited for this study, and 62 patients died in the hospital. The in-hospital mortality rate was 8.72%. Tuberculosis (TB), malignancies, and thrombocytopenia were associated with mortality. Antiviral treatment before admission was found to be a protective factor. There was a declining trend in in-hospital mortality from 19.2% in 2010 to 6.3% in 2019 (linear-by-linear association test, p < 0.001), partly due to intensified medical care strategy.Conclusions: Till date, AIDS-defining illnesses remain the major cause of hospital admission and in-hospital mortality. TB and malignancies were correlated risk factors for in-hospital mortality. ART before admission was found to be beneficial, and considering the decreasing rate of in-hospital mortality, the implementation of intensified medical care strategy requires further effort.

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Staphylococcus Aureus Bacteriuria as a Predictor of In-Hospital Mortality in Patients with Staphylococcus Aureus Bacteremia. Results of a Retrospective Cohort Study

Journal of Clinical Medicine ◽

10.3390/jcm9020508 ◽

2020 ◽

Vol 9 (2) ◽

pp. 508 ◽

Cited By ~ 1

Author(s):

Tobias Siegfried Kramer ◽

Beate Schlosser ◽

Désirée Gruhl ◽

Michael Behnke ◽

Frank Schwab ◽

...

Keyword(s):

Risk Factors ◽

Staphylococcus Aureus ◽

Cohort Study ◽

Hospital Mortality ◽

Retrospective Cohort Study ◽

Retrospective Cohort ◽

Cox Regression ◽

University Hospital ◽

Hospital Death ◽

Cox Regression Analysis

Staphylococcus aureus bloodstream infection (SA-BSI) is an infection with increasing morbidity and mortality. Concomitant Staphylococcus aureus bacteriuria (SABU) frequently occurs in patients with SA-BSI. It is considered as either a sign of exacerbation of SA-BSI or a primary source in terms of urosepsis. The clinical implications are still under investigation. In this study, we investigated the role of SABU in patients with SA-BSI and its effect on the patients’ mortality. We performed a retrospective cohort study that included all patients in our university hospital (Charité Universitätsmedizin Berlin) between 1 January 2014 and 31 March 2017. We included all patients with positive blood cultures for Staphylococcus aureus who had a urine culture 48 h before or after the first positive blood culture. We identified cases while using the microbiology database and collected additional demographic and clinical parameters, retrospectively, from patient files and charts. We conducted univariate analyses and multivariable Cox regression analysis to evaluate the risk factors for in-hospital mortality. 202 patients met the eligibility criteria. Overall, 55 patients (27.5%) died during their hospital stay. Cox regression showed SABU (OR 2.3), Pitt Bacteremia Score (OR 1.2), as well as moderate to severe liver disease (OR 2.1) to be independent risk factors for in-hospital mortality. Our data indicates that SABU in patients with concurrent SA-BSI is a prognostic marker for in-hospital death. Further studies are needed for evaluating implications for therapeutic optimization.

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Myocardial injury is associated with in-hospital mortality of confirmed or suspected COVID-19 in Wuhan, China: A single center retrospective cohort study

10.1101/2020.03.21.20040121 ◽

2020 ◽

Cited By ~ 13

Author(s):

Fan Zhang ◽

Deyan Yang ◽

Jing Li ◽

Peng Gao ◽

Taibo Chen ◽

...

Keyword(s):

Risk Factors ◽

Hospital Mortality ◽

Cardiac Troponin ◽

Troponin I ◽

Cox Regression ◽

Cardiac Injury ◽

High Sensitivity ◽

Hospital Death ◽

Cox Regression Analysis ◽

D Dimer

AbstractBackgroundSince December 2019, a cluster of coronavirus disease 2019 (COVID-19) occurred in Wuhan, Hubei Province, China and spread rapidly from China to other countries. In-hospital mortality are high in severe cases and cardiac injury characterized by elevated cardiac troponin are common among them. The mechanism of cardiac injury and the relationship between cardiac injury and in-hospital mortality remained unclear. Studies focused on cardiac injury in COVID-19 patients are scarce.ObjectivesTo investigate the association between cardiac injury and in-hospital mortality of patients with confirmed or suspected COVID-19.MethodsDemographic, clinical, treatment, and laboratory data of consecutive confirmed or suspected COVID-19 patients admitted in Wuhan No.1 Hospital from 25th December, 2019 to 15th February, 2020 were extracted from electronic medical records and were retrospectively reviewed and analyzed. Univariate and multivariate Cox regression analysis were used to explore the risk factors associated with in-hospital death.ResultsA total of 110 patients with confirmed (n=80) or suspected (n=30) COVID-19 were screened and 48 patients (female 31.3%, mean age 70.58±13.38 year old) among them with high-sensitivity cardiac troponin I (hs-cTnI) test within 48 hours after admission were included, of whom 17 (17/48, 35.4%) died in hospital while 31 (31/48, 64.6%) were discharged or transferred to other hospital. High-sensitivity cardiac troponin I was elevated in 13 (13/48, 27.1%) patents. Multivariate Cox regression analysis showed pulse oximetry of oxygen saturation (SpO2) on admission (HR 0.704, 95% CI 0.546-0.909, per 1% decrease, p=0.007), elevated hs-cTnI (HR 10.902, 95% 1.279-92.927, p=0.029) and elevated d-dimer (HR 1.103, 95%CI 1.034-1.176, per 1mg/L increase, p=0.003) on admission were independently associated with in-hospital mortality.ConclusionsCardiac injury defined by hs-cTnI elevation and elevated d-dimer on admission were risk factors for in-hospital death, while higher SpO2 could be seen as a protective factor, which could help clinicians to identify patients with adverse outcome at the early stage of COVID-19.

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COVID-19 in-hospital mortality and mode of death in a dynamic and non-restricted tertiary care model in Germany

10.1101/2020.07.22.20160127 ◽

2020 ◽

Author(s):

Siegbert Rieg ◽

Maja von Cube ◽

Johannes Kalbhenn ◽

Stefan Utzolino ◽

Katharina Pernice ◽

...

Keyword(s):

Mechanical Ventilation ◽

Hospital Mortality ◽

Cox Regression ◽

Medical Center ◽

Tertiary Care ◽

Study Entry ◽

Hospital Death ◽

Care Model ◽

Cox Regression Analysis ◽

Hospitalised Patients

Background Reported mortality of hospitalised COVID-19 patients varies substantially, particularly in critically ill patients. So far COVID-19 in-hospital mortality and modes of death under optimised care conditions have not been systematically studied. Methods This retrospective observational monocenter cohort study was performed after implementation of a non-restricted, dynamic tertiary care model at the University Medical Center Freiburg, an experienced ARDS and ECMO referral center. All hospitalised patients with PCR-confirmed SARS-CoV-2 infection were included. The primary endpoint was in-hospital mortality, secondary endpoints included major complications and modes of death. A multistate analysis and a Cox regression analysis for competing risk models were performed. Modes of death were determined by two independent reviewers. Results Between February 25, and May 8, 213 patients were included in the analysis. The median age was 65 years, 129 patients (61%) were male. 70 patients (33%) were admitted to the intensive care unit (ICU), of which 57 patients (81%) received mechanical ventilation and 23 patients (33%) extracorporeal membrane-oxygenation (ECMO) support. According to the multistate model the probability to die within 90 days after COVID-19 onset was 24% in the whole cohort. If the levels of care at time of study entry were accounted for, the probabilities to die were 16% if the patient was initially on a regular ward, 47% if in the ICU and 57% if mechanical ventilation was required at study entry. Age >=65 years and male sex were predictors for in-hospital death. Predominant complications - as judged by two independent reviewers - determining modes of death were multi-organ failure, septic shock and thromboembolic and hemorrhagic complications. Conclusion In a dynamic care model COVID-19-related in-hospital mortality remained substantial. In the absence of potent antiviral agents, strategies to alleviate or prevent the identified complications should be investigated. In this context, multistate analyses enable comparison of models-of-care and treatment strategies and allow estimation and allocation of health care resources.

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Methylprednisolone was Associated with Reduced in-Hospital Mortality in COVID-19 Patients with Low Lymphocyte Counts: a Multicenter Retrospective Propensity Analysis

10.21203/rs.3.rs-639680/v1 ◽

2021 ◽

Author(s):

Huifang Zhang ◽

Congliang Miao ◽

Tao Wang ◽

Yun Xie ◽

Xiaolei Teng ◽

...

Keyword(s):

Hospital Mortality ◽

Lymphocyte Count ◽

Cox Regression ◽

Survival Curve ◽

Hospital Death ◽

Normal Lymphocyte ◽

Cox Regression Analysis ◽

Kaplan Meier ◽

Methylprednisolone Treatment ◽

Novel Coronavirus

Abstract Background: To assess the effect of methylprednisolone on the prognosis of patients with novel coronavirus pneumonia.Methods: Patients with confirmed novel coronavirus pneumonia discharged from Wuhan Third Hospital Guanggu Campus, Shouyi Campus, and Lei Shen Shan Hospital from January 31, 2020, to March 4, 2020, were included. The patients were divided into treatment and control groups according to whether methylprednisolone was used during hospitalization. Propensity score (PS) matching analysis was used to assess in-hospital mortality as the primary outcome and trends in the changes in lymphocytes and the C-reactive protein, creatinine and transaminase levels 7 days after admission (secondary outcomes).Results: A total of 2,062 patients with confirmed novel coronavirus pneumonia were included in this study. Univariate Cox regression analysis suggested that methylprednisolone treatment was associated with increased in-hospital mortality (hazard ratio (HR) 3.70, 95% confidence interval (CI) 2.62-5.23, P<0.01). A total of 624 patients were included after PS matching. The patients were further subdivided into a low lymphocyte count group and a normal lymphocyte count group according to a lymphocyte count cutoff value of 0.9*109/L. Kaplan-Meier survival curve analysis showed that methylprednisolone treatment reduced the risk of in-hospital death in patients with lymphocyte counts less than 0.9×109/L (P=0.022). In contrast, in the normal lymphocyte group, methylprednisolone treatment was not associated with in-hospital mortality (p=0.88).Conclusion: Treatment with methylprednisolone may be associated with reduced in-hospital mortality in coronavirus disease (COVID) patients with low lymphocyte counts.

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Evaluation of independent predictors of in-hospital mortality in patients with severe trauma

Srpski arhiv za celokupno lekarstvo ◽

10.2298/sarh190313057m ◽

2019 ◽

Vol 147 (7-8) ◽

pp. 455-460

Author(s):

Marija Milenkovic ◽

Zaneta Terzioski ◽

Adi Hadzibegovic ◽

Jovana Stanisavljevic ◽

Ksenija Petrovic ◽

...

Keyword(s):

Hospital Mortality ◽

Cox Regression ◽

Arterial Oxygen Saturation ◽

Area Under The Curve ◽

Case Fatality ◽

Scoring Systems ◽

Severe Trauma ◽

Arterial Oxygen ◽

Emergency Center ◽

Cox Regression Analysis

Introduction/Objective. The aim of this study was to determine independent predictors and the best trauma scoring system (REMS, RTS, GSC, SOFA, APPACHE II) of in-hospital mortality in patients with severe trauma at the Department of Emergency, Emergency Center, Clinical Center of Serbia, Belgrade. Methods. Longitudinal study included 208 consecutive patients with severe trauma. In order to determine independent survival contributors, univariate and multivariate Cox regression analyses were performed. The power of above-mentioned scoring systems (measured at admission to the Emergency center) to predict mortality was compared using the area under the curve (AUC). Results. There were 208 patients (159 male, 49 female), with the average age of 47.3 ? 20.7 years. Majority of patients were initially intubated (86.1%) on admission to the emergency department, and 59.6% patients were sedated before intubation. After finishing of diagnostic procedures, 17 patients were additionally intubated, and, at that time, 94.2% patients were on mechanic ventilation. The majority of patients was traumatized in a car crash (33.2%), followed by falls from height (26.4%) and as pedestrians (22.6%). Patients had an average of 24.7 ? 21.2 days spent in intensive care unit. The overall case-fatality ratio was 17/208 (8.2%). In Cox regression analysis only elevated heart rate (HR = 1.03, p = 0.012) and decreased arterial oxygen saturation (SpO2) (HR = 0.91, p = 0.033) singled out as independent contributors to in-hospital mortality of patients with severe trauma. REMS (AUC 0.72 ? 0.64) and SOFA (AUC 0.716 ? 0.067) scores were found fair and similar predictor of in-hospital mortality, while APACHE II (AUC 0.614 ? 0.062) and RTS (0.396 ? 0.068) were poor predictors. Conclusion. Results of this study showed an important role of REMS, which appears to provide balance between the predictive ability and the practical application, and components of REMS in prediction of outcome in patients with severe trauma and that HR and SpO2 are independent predictors of in-hospital mortality.

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Prognostic Significance of Chest Imaging by LUS and CT in COVID-19 Inpatients: The ECOVID Multicenter Study

Respiration ◽

10.1159/000518516 ◽

2021 ◽

pp. 1-10

Author(s):

Claudio Tana ◽

Fabrizio Ricci ◽

Maria Gabriella Coppola ◽

Cesare Mantini ◽

Fulvio Lauretani ◽

...

Keyword(s):

Hospital Mortality ◽

Cox Regression ◽

Pearson Correlation ◽

Prognostic Significance ◽

Chest Ct ◽

Lung Damage ◽

Chest Imaging ◽

Gold Standard Method ◽

Cox Regression Analysis ◽

Total Score Range

Background: Point-of-care lung ultrasound (LUS) score is a semiquantitative score of lung damage severity. High-resolution computed tomography (HRCT) is the gold standard method to evaluate the severity of lung involvement from the novel coronavirus disease (COVID-19). Few studies have investigated the clinical significance of LUS and HRCT scores in patients with COVID-19. Therefore, the aim of this study was to evaluate the prognostic yield of LUS and of HRCT in COVID-19 patients. Methods: We carried out a multicenter, retrospective study aimed at evaluating the prognostic yield of LUS and HRCT by exploring the survival curve of COVID-19 inpatients. LUS and chest CT scores were calculated retrospectively by 2 radiologists with >10 years of experience in chest imaging, and the decisions were reached in consensus. LUS score was calculated on the basis of the presence or not of pleural line abnormalities, B-lines, and lung consolidations. The total score (range 0–36) was obtained from the sum of the highest scores obtained in each region. CT score was calculated for each of the 5 lobes considering the anatomical extension according to the percentage parenchymal involvement. The resulting overall global semiquantitative CT score was the sum of each single lobar score and ranged from 0 (no involvement) to 25 (maximum involvement). Results: One hundred fifty-three COVID-19 inpatients (mean age 65 ± 15 years; 65% M), including 23 (15%) in-hospital deaths for any cause over a mean follow-up of 14 days were included. Mean LUS and CT scores were 19 ± 12 and 10 ± 7, respectively. A strong positive linear correlation between LUS and CT scores (Pearson correlation r = 0.754; R2 = 0.568; p < 0.001) was observed. By ROC curve analysis, the optimal cut-point for mortality prediction was 20 for LUS score and 4.5 for chest CT score. According to Kaplan-Meier survival analysis, in-hospital mortality significantly increased among COVID-19 patients presenting with an LUS score ≥20 (log-rank 0.003; HR 9.87, 95% CI: 2.22–43.83) or a chest CT score ≥4.5 (HR 4.34, 95% CI: 0.97–19.41). At multivariate Cox regression analysis, LUS score was the sole independent predictor of in-hospital mortality yielding an adjusted HR of 7.42 (95% CI: 1.59–34.5). Conclusion: LUS score is useful to stratify the risk in COVID-19 patients, predicting those that are at high risk of mortality.

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Identification and Validation of a Glycolysis Related Metabolic Reprogramming Gene Signature for Predicting Survival in Colon Cancer Patients

10.21203/rs.3.rs-916034/v1 ◽

2021 ◽

Author(s):

Gang Liu ◽

Xiaowang WU ◽

Jian Chen

Keyword(s):

Colon Cancer ◽

Prediction Model ◽

Cox Regression ◽

Malignant Tumors ◽

Gene Signature ◽

Metabolic Reprogramming ◽

Risk Scores ◽

Cox Regression Analysis ◽

Prognosis Model ◽

The Relationship

Abstract Background Colon cancer (CC) is one of the most common gastrointestinal malignant tumors with high mortality rate. Because of malignancy and easily metastasis feather, and limited treatments, the prognosis of CC remains poor. Glycolysis is a metabolic process of glucose in anoxic environments which is an important way to provide energy for tumor. The role of glycolysis in CC largely remains unknown and is necessary to be explored. Method In our study, we analyzed glycolysis related genes expression in CC, patients gene expression and corresponding clinical data were downloaded from GEO dataset, glycolysis related genes sets were collected from Msigdb. Through COX regression analysis, prognosis model based on glycolysis-related genes was established. The efficacy of gene model was tested by Survival analysis, ROC analysis and PCA analysis. Furthermore, the relationship between risk scores and clinical characteristic was researched. Results Our findings identified 13 glycolysis related genes (NUP107, SEC13, ALDH7A1, ALG1, CHPF, FAM162A, FBP2, GALK1, IDH1, TGFA, VLDLR, XYLT2 and OGDHL) consisted prognostic prediction model with relative high accuracy. The relationship between prediction model and clinical feathers were specifically studied, results showed age > 65years, TNM III-IV, T3-4, N1-3, M1 and high-risk score were independent prognostic risk factors with poorer prognosis. Finally, model genes were significantly expressed and EMT were activated in CC patients. Conclusion This study provided a new aspect to advance our understanding in the potential mechanism of glycolysis in CC.

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Relationship Between Creatinine and Body Weight Ratio and Diabetes Mellitus in a Chinese Cohort Study

10.21203/rs.3.rs-360026/v1 ◽

2021 ◽

Author(s):

Xinyu Wang ◽

Zhuangsen Chen ◽

Fan Yang ◽

Xiaohan Ding ◽

Changchun Cao ◽

...

Keyword(s):

Body Weight ◽

Missing Values ◽

Proportional Hazards ◽

Cox Regression ◽

Weight Ratio ◽

Cox Proportional Hazards ◽

Additive Models ◽

Cox Regression Analysis ◽

Non Linear ◽

The Relationship

Abstract Background: Research on the relationship between Creatinine to Body Weight Ratios (Cre/BW ratios) and the prevalence of diabetes is still lacking. The aim of this study was to investigate the potential association between Cre/BW ratios and incident of diabetes in Chinese adults.Methods: This retrospective study was conducted in 199,526 patients from Rich Healthcare Group in China from 2010 to 2016. The participants were divided into quartiles of the Cre/BW ratios. Multivariate multiple imputation and dummy variables were used to handle missing values. Cox proportional-hazards regression was used to investigate the association of Cre/BW and diabetes. Generalized additive models(GAM) were used to identify non-linear relationships.Results: Of all participants,after handling missing values and adjustment for potential confounders, the multivariate Cox regression analysis results showed that Cre/BW ratios was inversely associated with diabetes risk( HR: 0.268; 95% CI:0.229 to 0.314, P < 0.00001).For men, the hazard ratios(HRs) of incident diabetes was 0.255(95%CI: 0.212-0.307);and for women HR= 0.297 (95%CI: 0.218-0.406).Moreover, sensitivity analysis confirmed the stability of the results. Furthermore, GAM revealed a saturation effect on the independent association between Cre/BW and incident of diabetes.Conclusions: This study demonstrated that increased Cre/BW is negatively correlated with incident of diabetes in Chinese for the first time. And we found that the relationship between Cre/BW and incident of diabetes was non-linear.

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