scholarly journals Understanding critically ill sepsis patients with normal serum lactate levels: results from U.S. and European ICU cohorts

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Christopher M. Sauer ◽  
Josep Gómez ◽  
Manuel Ruiz Botella ◽  
David R. Ziehr ◽  
William M. Oldham ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Critically Ill ◽  
Serum Lactate ◽  
High Serum ◽  
Normal Serum ◽  
Partial Least Square ◽  
Least Square ◽  
Data Set ◽  
Severity Scores ◽  
Lactate Levels

AbstractWhile serum lactate level is a predictor of poor clinical outcomes among critically ill patients with sepsis, many have normal serum lactate. A better understanding of this discordance may help differentiate sepsis phenotypes and offer clues to sepsis pathophysiology. Three intensive care unit datasets were utilized. Adult sepsis patients in the highest quartile of illness severity scores were identified. Logistic regression, random forests, and partial least square models were built for each data set. Features differentiating patients with normal/high serum lactate on day 1 were reported. To exclude that differences between the groups were due to potential confounding by pre-resuscitation hyperlactatemia, the analyses were repeated for day 2. Of 4861 patients included, 47% had normal lactate levels. Patients with normal serum lactate levels had lower 28-day mortality rates than those with high lactate levels (17% versus 40%) despite comparable physiologic phenotypes. While performance varied between datasets, logistic regression consistently performed best (area under the receiver operator curve 87–99%). The variables most strongly associated with normal serum lactate were serum bicarbonate, chloride, and pulmonary disease, while serum sodium, AST and liver disease were associated with high serum lactate. Future studies should confirm these findings and establish the underlying pathophysiological mechanisms, thus disentangling association and causation.

scholarly journals Assessment of pSOFA-L score in predicting the clinical outcome of critically ill children

2020 ◽  
Vol 7 (4) ◽  
pp. 925
Author(s):  
Shrishail Kumbar ◽  
Chandrashekhara .
Keyword(s):  
Mortality Rate ◽  
Clinical Outcome ◽  
Critically Ill ◽  
Analytical Study ◽  
Serum Lactate ◽  
High Serum ◽  
Critically Ill Children ◽  
Prediction Of Mortality ◽  
Failure Assessment ◽  
Lactate Levels

Background: Recently Pediatric Sequential Organ Failure Assessment (pSOFA) score was adapted and validated in critically ill children to predict the clinical outcome. This study was aimed to evaluate the lactate level association with the outcome and thereby formulating pSOFA-L score to predict the clinical outcome better in critically ill children.Methods: This hospital based prospective, observational, analytical study was conducted in the Department of Paediatrics, A. J Hospital, Mangalore, Karnataka. Requirement of oxygen, inotrope support and other parameters were studied and compared the score with clinical outcome. A total of 75 cases were studied.Results: In this study total of 51 children had high serum lactate levels (68%). Out of 28 expired children 23 children had higher serum lactate levels that accounts for about 82.14% which is statistically significant (p<0.001). ROC curve of pSOFA-L score in predicting the mortality yielded AUC: 0.92 and cut off value: 10.5 which is statistically significant (p<0.001). In the present study mortality rate was 26.09% in children whose pSOFA-L score was less than 9 and mortality rate of 38.89% and 50.00% in children whose pSOFA-L score was 9 to 11 and more than 11 respectively.Conclusions: In this study increase in pSOFA-L score is associated with high mortality and poor outcome. The findings of the present study validate and emphasize that, pSOFA-L score helps in accurate prediction of mortality of critically ill children.

From managing customers to joint venturing with customers: co-creating service value in the digital age

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Christine Falkenreck ◽  
Ralf Wagner
Keyword(s):  
Perceived Risk ◽  
Structural Equation ◽  
Business Models ◽  
Joint Venture ◽  
Digital Age ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
Data Set ◽  
Content Type

Purpose Until today, scholars claim that the phenomenon of “co-creation” of value in an “interacted” economy and in the context of positive actor-to-actor relationships has not been adequately explored. This study aims to first to identify and separate the accessible values of internet of things (IoT)-based business models for business-to-business (B2B) and business-to-government (B2G) customer groups. It quantifies the drivers to successfully implement disruptive business models. Design/methodology/approach Data were gathered from 292 customers in Western Europe. The conceptual framework was tested using partial least square structural equation modeling. Findings Managing disruptions in the digital age is closely related to the fact that the existing trust in buyer-seller relationships is not enough to accept IoT projects. A company’s digitalization capabilities, satisfaction with the existing relationship and trust in the IoT credibility of the manufacturer drives the perceived value of IoT-based business models in B2B settings. Contrastingly, in B2G settings, money is less important. Research limitations/implications Research refers to one business field, the data set is of European origin only. Findings indicate that the drivers to engage in IoT-related projects differ significantly between the customer groups and therefore require different marketing management strategies. Saving time today is more important to B2G buyers than saving money. Practical implications The disparate nature of B2B and B2G buyers indicates that market segmentation and targeted marketing must be considered before joint-venturing in IoT business models. To joint venture supply chain partners co-creating value in the context of IoT-related business models, relationship management should be focused with buyers on the same footing, as active players and co-developers of a personalized experience in digital service projects. Originality/value Diverging from established studies focusing on the relationship within a network of actors, this study defines disruptive business models and identifies its drivers in B2B and B2G relationships. This study proposes joint venturing with B2B and B2G customers to overcome the perceived risk of these IoT-related business models. Including customers in platforms and networks may lead to the co-creation of value in joint IoT projects.

scholarly journals Association Between Serum Osmolality and Acute Kidney Injury in Critically Ill Patients: A Retrospective Cohort Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Jie Yang ◽  
Yisong Cheng ◽  
Ruoran Wang ◽  
Bo Wang
Keyword(s):  
Acute Kidney Injury ◽  
Logistic Regression ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Retrospective Cohort ◽  
Kidney Injury ◽  
High Serum ◽  
Serum Osmolality ◽  
Multivariate Logistic Regression ◽  
Low Serum

Purposes: Acute kidney injury (AKI) is a common complication in critically ill patients and is usually associated with poor outcomes. Serum osmolality has been validated in predicting critically ill patient mortality. However, data about the association between serum osmolality and AKI is still lacking in ICU. Therefore, the purpose of the present study was to investigate the association between early serum osmolality and the development of AKI in critically ill patients.Methods: The present study was a retrospective cohort analysis based on the medical information mart for intensive care III (MIMIC-III) database. 20,160 patients were involved in this study and divided into six subgroups according to causes for ICU admission. The primary outcome was the incidence of AKI after ICU admission. The association between early serum osmolality and AKI was explored using univariate and multivariate logistic regression analyses.Results: The normal range of serum osmolality was 285–300 mmol/L. High serum osmolality was defined as serum osmolality &gt;300 mmol/L and low serum osmolality was defined as serum osmolality &lt;285 mmol/L. Multivariate logistic regression indicated that high serum osmolality was independently associated with increased development of AKI with OR = 1.198 (95% CL = 1.199–1.479, P &lt; 0.001) and low serum osmolality was also independently associated with increased development of AKI with OR = 1.332 (95% CL = 1.199–1.479, P &lt; 0.001), compared with normal serum osmolality, respectively.Conclusions: In critically ill patients, early high serum osmolality and low serum osmolality were both independently associated with an increased risk of development of AKI.

scholarly journals Entrepreneurial self-efficacy and entrepreneurial intention: The mediating role of the need for independence

2021 ◽  
Vol 17 (4) ◽  
pp. 91-119
Author(s):  
Victor Osadolor ◽  
◽  
Kalu Emmanuel Agbaeze ◽  
Ejikeme Emmanuel Isichei ◽  
Samuel Taiwo Olabosinde ◽  
...  
Keyword(s):  
Self Efficacy ◽  
Structural Equation ◽  
Entrepreneurial Intention ◽  
Partial Least Square ◽  
Least Square ◽  
Data Set ◽  
Behavioral Reasoning Theory ◽  
The Relationship ◽  
Behavioral Reasoning

PURPOSE: The paper focuses on assessing the direct effect of entrepreneurial self-efficacy and entrepreneurial intention and the indirect effect of the need for independence on the relationship between the constructs. Despite increased efforts towards steering the interest of young graduates towards entrepreneurial venture, the response rate has been rather unimpressive and discouraging, thus demanding the need to account for what factors could drive intention towards venture ownership among graduates in Nigeria. METHODOLOGY: A quantitative approach was adopted and a data set from 235 graduates was used for the study. The data was analyzed using the partial least square structural equation model (PLS-SEM). FINDINGS: It was found that self-efficacy does not significantly affect intention. It was also found that the need for independence affects entrepreneurial intention. The study found that the need for independence fully mediates the relationship between entrepreneurial self-efficacy and entrepreneurial intention. PRACTICAL IMPLICATIONS: This paper provides new insight into the behavioral reasoning theory, through its application in explaining the cognitive role of the need for independence in decision-making, using samples from a developing economy. ORIGINALITY AND VALUE: The study advances a new perspective on the underlining factors that account for an entrepreneur’s intent to start a business venture, most especially among young graduates in Nigeria, through the lens of the behavioral reasoning theory. We further support the application of the theory in entrepreneurship literature, given the paucity of studies that have adopted the theory despite its relevance.

Factors that trigger bullying amongst subcontractors toward intention to quit in the construction projects

2019 ◽  
Vol 10 (1) ◽  
pp. 140-152
Author(s):  
Alireza Jalali ◽  
Nur Izzati Hidzir ◽  
Mastura Jaafar ◽  
Norziani Dahalan
Keyword(s):  
Construction Projects ◽  
Workplace Bullying ◽  
Construction Project ◽  
Partial Least Square ◽  
Least Square ◽  
Intention To Quit ◽  
Equation Modeling ◽  
Key Factors ◽  
Data Set ◽  
Content Type

Purpose The purpose of this paper is to examine the relationships between three key factors that cause workplace bullying among subcontractor managers toward intention to quit the undertaken project within the context of Malaysia. Design/methodology/approach This study utilized the simple sampling method to select its study sample, while the questionnaire survey approach was implemented amidst 500 G6 and G7 contractor managers across Peninsular Malaysia. A total of 210 completed questionnaires were returned. Partial least square-structural equation modeling was administered to analyze the data via SmartPls 3.0 software. Findings This study discovered three significant factors (main contractor leadership, construction culture, work organization and job design) that displayed positive effect on workplace bullying among subcontractor managers toward intention to quit. The study outcomes can serve as a direction for policy makers to reduce bullying within the construction project environment. Practical implications This study serves as an instruction for main contractors to reinvent their style of management in overcoming bullying in construction projects. This paper guides that collaborative relationship among various parties in construction projects, including the representatives of main contractors and subcontractor managers, may assist in addressing the hostile environment of construction project, in order to create a constructive relationship between them that leads to overall project success. Originality/value Recognition of the three key factors that lead to workplace bullying among subcontractor managers in the construction industry, which are bound to enhance intention to quit based on the data set with strong statistical results, has made the research original.

scholarly journals High-Normal Serum Magnesium and Hypermagnesemia Are Associated With Increased 30-Day In-Hospital Mortality: A Retrospective Cohort Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Liao Tan ◽  
Qian Xu ◽  
Chan Li ◽  
Jie Liu ◽  
Ruizheng Shi
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Hospital Mortality ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Cox Regression ◽  
Serum Magnesium ◽  
Normal Serum ◽  
Magnesium Level ◽  
Serum Magnesium Level

Background: Magnesium, the fourth most abundant mineral nutrient in our body, plays a critical role in regulating ion channels and energy generation, intracardiac conduction, and myocardial contraction. In this study, we assessed the association of admission serum magnesium level with all-cause in-hospital mortality in critically ill patients with acute myocardial infarction (AMI).Methods: Clinical data were extracted from the eICU Collaborative Research Database (eICU-CRD). Only the data for the first intensive care unit (ICU) admission of each patient were used, and baseline data were extracted within 24 h after ICU admission. Logistic regression, Cox regression, and subgroup analyses were conducted to determine the relationship between admission serum magnesium level and 30-day in-hospital mortality in ICU patients with AMI.Results: A total of 9,005 eligible patients were included. In the logistic regression analysis, serum magnesium at 2.2 to ≤2.4 and &gt;2.4 mg/dl levels were both significant predictors of all-cause in-hospital mortality in AMI patients. Moreover, serum magnesium of 2.2 to ≤2.4 mg/dl showed higher risk of in-hospital mortality than magnesium of &gt;2.4 mg/dl (adjusted odds ratio, 1.63 vs. 1.39). The Cox regression analysis yielded similar results (adjusted hazard ratio, 1.36 vs. 1.25).Conclusions: High-normal serum magnesium and hypermagnesemia may be useful and easier predictors for 30-day in-hospital mortality in critically ill patients with AMI.

Corn microbial diversity and its relationship to yield

2020 ◽  
Vol 66 (8) ◽  
pp. 457-473
Author(s):  
Shimaila Ali ◽  
Soledad Saldias ◽  
Nimalka Weerasuriya ◽  
Kristen Delaney ◽  
Saveetha Kandasamy ◽  
...  
Keyword(s):  
Restriction Fragment ◽  
Binary Data ◽  
Bacterial Population ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Reference Database ◽  
Corn Yield ◽  
Data Set ◽  
Highly Correlated

This study aimed to identify possible relationships between corn (Zea mays L.) productivity and its endosphere microbial community. Any insights would be used to develop testable hypotheses at the farm level. Sap was collected from 14 fields in 2014 and 10 fields in 2017, with a yield range of 10.1 to 21.7 tonnes per hectare (t/ha). The microbial sap communities were analyzed using terminal restriction fragment length polymorphism (TRFLP) and identified using an internal pure culture reference database and BLAST. This technique is rapid and inexpensive and is suitable for use at the grower level. Diversity, richness, and normalized abundances of each bacterial population in corn sap samples were evaluated to link the microbiome of a specific field to its yield. A negative trend was observed (r = –0.60), with higher-yielding fields having lower terminal restriction fragment (TRF) richness. A partial least square regression analysis of TRF intensity and binary data from 2014 identified 10 TRFs (bacterial genera) that positively, or negatively, correlated with corn yields, when either absent or present at certain levels or ratios. Using these observations, a model was developed that accommodated criteria for each of the 10 microbes and assigned a score for each field out of 10. Data collected in 2014 showed that sites with higher model scores were highly correlated with larger yields (r = 0.83). This correlation was also seen when the 2017 data set was used (r = 0.87). We were able to conclude that a positive significant effect was seen with the model score and yield (adjusted R2 = 0.67, F[1,22] = 46.7, p < 0.001) when combining 2014 and 2017 data. The results of this study are being expanded to identify the key microbes in the corn sap community that potentially impact corn yield, regardless of corn variety, geographic factors, or edaphic factors.

Serum Lactate Level as a Predictor for Blood Transfusion in Postpartum Hemorrhage

2021 ◽  
Author(s):  
Surbhi Agrawal ◽  
Maria Smith ◽  
Robert Berg ◽  
Iffath A. Hoskins
Keyword(s):  
Blood Transfusion ◽  
Postpartum Hemorrhage ◽  
Lactate Level ◽  
Serum Lactate ◽  
Normal Serum ◽  
Red Blood Cell Transfusion ◽  
Blood Transfusions ◽  
Serum Lactate Level ◽  
Obstetric Hemorrhage ◽  
Lactate Levels

Objective Postpartum hemorrhage (PPH) is the leading cause of maternal morbidity and mortality. At present, there are no reliable clinical or laboratory indicators to identify which patients might require blood transfusions during a PPH. Serum lactate has long been used as an early biomarker of tissue hypoperfusion in trauma settings. The aim of this study is to understand serum lactate's role in the management of obstetric hemorrhage. Study Design A retrospective chart review was performed of women who delivered between 2016 and 2019 at our institution and experienced a PPH. The patients were divided into two groups: those with a normal serum lactate level, defined as ≤2 mmol/L, and those with an abnormal serum lactate level, defined as >2 mmol/L. Need for packed red blood cell transfusion, as part of the resuscitation, was assessed for both groups. Results During the study period, 938 women experienced PPH. Of these, 108 (11.5%) had a normal serum lactate, ≤2 mmol/L, and 830 (88.5%) had an abnormal lactate, >2 mmol/L. Women with elevated lactate levels were more likely to receive a blood transfusion versus those with a normal lactate level (57.0 vs. 46.3%, p = 0.035, respectively). Additionally, the average number of blood transfusions administered was significantly higher in the abnormal lactate group versus in the normal lactate group (1.34 vs. 0.97, respectively, p = 0.004). In a multivariable linear regression model, increasing serum lactate levels were found to be predictive of requiring more than 1 unit of blood (p < 0.001). Conclusion Women with elevated serum lactate levels were more likely to require blood transfusions during a PPH versus those with a normal serum lactate level. Thus, serum lactate levels are useful as an early indicator of requirement for blood transfusion in the management of obstetric hemorrhage. Key Points

Diagnostic Plasma-Derived Proteomic Biomarkers of Aggressive Diffuse Large B-Cell Lymphoma: Preliminary Data Based On the 075 French GEOLAMS Multicentric and Prospective Trial.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 2933-2933
Author(s):  
Delphine Maucort-Boulch ◽  
Marie Arlotto ◽  
Delphine Rossille ◽  
Céline Pangault ◽  
Pascal Roy ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Stem Cell ◽  
B Cell ◽  
B Cell Lymphoma ◽  
Partial Least Square ◽  
The Body ◽  
Least Square ◽  
Clinical Proteomics ◽  
High Dose ◽  
Large B Cell

Abstract Abstract 2933 Poster Board II-909 The challenge of clinical proteomic is to link protein expression profile variations to specific disease phenotypes and identify relevant biomarkers in order to develop straightforward diagnostic or prognosis tools. Blood, a tissue that interfaces with virtually every part of the body, is considered to be a deep source of native and secreted diagnostic analytes. Despite this great potential, the first decade of the proteomics era met with little success, not only because of the vast and complex nature of the proteome but also due to proteins dynamic range and complex degradation pathways, and to the heterogeneity of plasma protein profiles in the human population. Altogether, progress in clinical proteomics will reside in the elaboration of standardized preanalytic procedures, cross-comparisons between samples and independent validation. In aggressive diffuse large B-cell lymphomas (DLBCL), diagnostic and prognostic biomarkers are mandatory to optimize treatment, and include patients in future trials. The aim of the present study was first to identify diagnostic blood biomarkers of DLBCL based on the 075 French GOELAMS ongoing trial -which involved adults younger than 60 suffering from an aggressive form of DLBCL- that randomized patients between CHOP-14 Rituximab or intensive chemotherapy plus Rituximab including autologous stem-cell support. This protocol was built after our group demonstrated the high efficiency of high-dose chemotherapy and autologous stem-cell transplantation as frontline therapy in this disease compared to conventional CHOP (New Engl J Med, 2004). In this study, 200 patients were compared to 100 controls matched for sex and age. Well-defined pre-analytic steps were applied and plasma was collected, at the time of diagnosis, on the specific anti-proteasic P100v1.1 tube from Becton Dickinson. All samples were centralized and aliquoted in a unique platform prior to analytic steps. The whole series of 300 samples was randomly assigned on chips to be analyzed with SELDI-TOF/MS using three different chemistry protocols (CM10, Q10 & IMAC30) and two beam intensities (2000 and 4000, respectively). There was a longer delay in the process of patient's samples before plasma isolation compared to controls; this time had to be considered since it could participate to the protein degradation process and lead to proteomic modifications. Statistical analyses were implemented with the R package software [R development core team. R: A Language for Environmental and Statistical Computing. Vienna: R Foundation, 2008.]. Univariate analyses comparison resulted in 185 peaks differential of the case-control status (t-test, FDR=5%). Multivariate analyses were then performed according to chemistry and beam intensity using stepforward logistic regression. This resulted in 78 peaks related to DLBCL diagnosis. In order to reduce dimension, partial least square regression [A. L. Boulesteix and K. Strimmer (2005). Predicting Transcription Factor Activities from Combined Analysis of Microarray and ChIP Data: A Partial Least Squares Approach] was applied, resulting in two components corresponding to a weighted sum of the 78 peaks. These two components were introduced as covariates in logistic regression so that the 78 peaks could be ranked according to their global coefficient, allowing then top peaks to be studied. Sparse partial least square was also considered as another approach to reduce dimension and select peaks among the 78 identified. These two approaches were compared and proteins studied in greater detail. Altogether, this study allowed to identify promising candidate cancer biomarkers that are currently being validated through the analysis of additional plasma issued from other types of lymphoma (follicular, mantle cell and low burden DLBCL) and non-cancerous septic patients. Highly specific peak combinations will be considered before peptide characterization in order to end up with a diagnostic set of proteins useful for the diagnosis and management of aggressive DLBCLs. Disclosures: No relevant conflicts of interest to declare.

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