scholarly journals Machine Learning Consensus Clustering Approach for Patients with Lactic Acidosis in Intensive Care Units

2021 ◽  
Vol 11 (11) ◽  
pp. 1132
Author(s):  
Pattharawin Pattharanitima ◽  
Charat Thongprayoon ◽  
Tananchai Petnak ◽  
Narat Srivali ◽  
Guido Gembillo ◽  
...  
Keyword(s):  
Intensive Care ◽  
Lactic Acidosis ◽  
Clustering Analysis ◽  
Laboratory Data ◽  
Severity Index ◽  
Serum Lactate ◽  
Consensus Clustering ◽  
Serum Bicarbonate ◽  
Comorbidity Burden ◽  
Vasopressor Use

Background: Lactic acidosis is a heterogeneous condition with multiple underlying causes and associated outcomes. The use of multi-dimensional patient data to subtype lactic acidosis can personalize patient care. Machine learning consensus clustering may identify lactic acidosis subgroups with unique clinical profiles and outcomes. Methods: We used the Medical Information Mart for Intensive Care III database to abstract electronic medical record data from patients admitted to intensive care units (ICU) in a tertiary care hospital in the United States. We included patients who developed lactic acidosis (defined as serum lactate ≥ 4 mmol/L) within 48 h of ICU admission. We performed consensus clustering analysis based on patient characteristics, comorbidities, vital signs, organ supports, and laboratory data to identify clinically distinct lactic acidosis subgroups. We calculated standardized mean differences to show key subgroup features. We compared outcomes among subgroups. Results: We identified 1919 patients with lactic acidosis. The algorithm revealed three best unique lactic acidosis subgroups based on patient variables. Cluster 1 (n = 554) was characterized by old age, elective admission to cardiac surgery ICU, vasopressor use, mechanical ventilation use, and higher pH and serum bicarbonate. Cluster 2 (n = 815) was characterized by young age, admission to trauma/surgical ICU with higher blood pressure, lower comorbidity burden, lower severity index, and less vasopressor use. Cluster 3 (n = 550) was characterized by admission to medical ICU, history of liver disease and coagulopathy, acute kidney injury, lower blood pressure, higher comorbidity burden, higher severity index, higher serum lactate, and lower pH and serum bicarbonate. Cluster 3 had the worst outcomes, while cluster 1 had the most favorable outcomes in terms of persistent lactic acidosis and mortality. Conclusions: Consensus clustering analysis synthesized the pattern of clinical and laboratory data to reveal clinically distinct lactic acidosis subgroups with different outcomes.

scholarly journals Necrotizing Soft Tissue Infections in Intensive Care

2021 ◽  
pp. 088506662110101
Author(s):  
Alexandru Ogica ◽  
Christoph Burdelski ◽  
Holger Rohde ◽  
Stefan Kluge ◽  
Geraldine de Heer
Keyword(s):  
Septic Shock ◽  
Intensive Care ◽  
Soft Tissue ◽  
Sofa Score ◽  
Laboratory Data ◽  
Serum Lactate ◽  
Soft Tissue Infections ◽  
Necrotizing Soft Tissue Infections ◽  
The Mean ◽  
Organ Dysfunctions

Background: Necrotizing soft tissue infections (NSTIs) are typically characterized by extensive soft tissue destruction with systemic signs of toxicity, ranging from sepsis to septic shock. Our aim was to analyze the clinical characteristics, microbiological results, laboratory data, therapies, and outcome of patients with NSTIs admitted to an intensive care unit (ICU). Methods: A monocentric observational study of patients admitted to the ICU of a university hospital between January 2009 and December 2017. The demographic characteristics, comorbidities, clinical features, microbiology and laboratory results, organ dysfunctions, therapies, and outcome were retrospectively analyzed. Results: There were 59 patients and 70% males. The mean age (± SD) was 55 ± 18; type II (monomicrobial) NSTI was present in 36 patients (61%); the most common isolated pathogen was Streptococcus pyogenes in 28 patients (48%). Septic shock was diagnosed in 41 patients (70%). The most common organ dysfunctions were circulatory and renal in 42 (71%) and 38 patients (64%). The mean value (± SD) of serum lactate at admission to the ICU was 4.22 ± 5.42 mmol/l, the median SOFA score and SAPS II were 7 (IQR 4 - 10) and 46 (IQR 30.5 - 53). ICU mortality rate was 25%. Both SOFA score and serum lactate demonstrated a good prognostic value regarding ICU outcome (OR 1.29, 95%CI 1.07-1.57, P < 0.007 and OR 1.53, 95%CI 1.19-1.98, P < 0.001). A cut-off value for serum lactate of 6.55 mmol/L positively predicted mortality with 67% sensitivity and 97% specificity. Conclusion: NSTIs carry a high risk of septic shock and multiple organ dysfunction syndrome and thus are still associated with high mortality. In our study, the value of serum lactate at admission to the ICU correlated well with mortality. This easy-to-measure parameter could play a role in the decision-making process regarding prognosis and continuation of care.

scholarly journals Clinically Distinct Subtypes of Acute Kidney Injury on Hospital Admission Identified by Machine Learning Consensus Clustering

2021 ◽  
Vol 9 (4) ◽  
pp. 60
Author(s):  
Charat Thongprayoon ◽  
Pradeep Vaitla ◽  
Voravech Nissaisorakarn ◽  
Michael A. Mao ◽  
Jose L. Zabala Genovez ◽  
...  
Keyword(s):  
Machine Learning ◽  
Acute Kidney Injury ◽  
Hospital Admission ◽  
Clustering Analysis ◽  
Kidney Injury ◽  
Consensus Clustering ◽  
Serum Bicarbonate ◽  
Lower Serum ◽  
Serum Chloride ◽  
Cluster 2

Background: We aimed to cluster patients with acute kidney injury at hospital admission into clinically distinct subtypes using an unsupervised machine learning approach and assess the mortality risk among the distinct clusters. Methods: We performed consensus clustering analysis based on demographic information, principal diagnoses, comorbidities, and laboratory data among 4289 hospitalized adult patients with acute kidney injury at admission. The standardized difference of each variable was calculated to identify each cluster’s key features. We assessed the association of each acute kidney injury cluster with hospital and one-year mortality. Results: Consensus clustering analysis identified four distinct clusters. There were 1201 (28%) patients in cluster 1, 1396 (33%) patients in cluster 2, 1191 (28%) patients in cluster 3, and 501 (12%) patients in cluster 4. Cluster 1 patients were the youngest and had the least comorbidities. Cluster 2 and cluster 3 patients were older and had lower baseline kidney function. Cluster 2 patients had lower serum bicarbonate, strong ion difference, and hemoglobin, but higher serum chloride, whereas cluster 3 patients had lower serum chloride but higher serum bicarbonate and strong ion difference. Cluster 4 patients were younger and more likely to be admitted for genitourinary disease and infectious disease but less likely to be admitted for cardiovascular disease. Cluster 4 patients also had more severe acute kidney injury, lower serum sodium, serum chloride, and serum bicarbonate, but higher serum potassium and anion gap. Cluster 2, 3, and 4 patients had significantly higher hospital and one-year mortality than cluster 1 patients (p < 0.001). Conclusion: Our study demonstrated using machine learning consensus clustering analysis to characterize a heterogeneous cohort of patients with acute kidney injury on hospital admission into four clinically distinct clusters with different associated mortality risks.

Intra-aortic balloon pump as a bridge therapy to heart transplant in refractory heart failure

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
G.A.B Boros ◽  
V.S.C Bellini ◽  
D Fatori ◽  
C Bernoche ◽  
M.F Macatrao-Costa ◽  
...  
Keyword(s):  
Heart Failure ◽  
Intensive Care ◽  
Heart Transplant ◽  
Insertion Site ◽  
Laboratory Data ◽  
Central Venous Oxygen Saturation ◽  
Single Center ◽  
Intra Aortic Balloon Pump ◽  
The Impact ◽  
Bridge Therapy

Abstract Background The role of intra-aortic balloon pump (IABP) in advanced heart failure (HF) treatment is still under debate. Some heart transplant (HTx) candidates on the waiting list require mechanical support, and IABP may be the simple and most available device. Purpose Describe the impact of IABP treatment in advanced HF patients who underwent HTx. Methods We retrospectively analysis patients who underwent HTx from a single center intensive care unit (ICU), between 2009 and 2018, to evaluate the use of IABP as bridge therapy. Selection included decompensated chronic HF patients that required intensive care with optimized intravenous drugs before IABP placement. Exclusion criteria were acute myocardial infarction or cardiac surgery 90 days prior to admission, and implant of ventricular assist device before HTx. Results We included 134 HF patients with IABP therapy before HTx. Insertion site was exclusively femoral. Mean time of IABP onset to HTx were 26±21 days, and hospital admission to HTx 65±45 days. The main cardiomyopathy etiology was Chagas Disease (46%) and mean LVEF was 23±6% (TABLE 1). Clinical and laboratory data were compared before and 96 hours after IABP therapy. Mean central venous oxygen saturation (SvO2) increased from 49.7±14.6% to 67.4±11.3% (p&lt;0.001), creatinine decreased from 1.77±0.9 mg/dL to 1.40±0.6 mg/dL (p&lt;0.001), and urine output increased from 1552±886 mL/24h to 2189±1029 mL/24h (p&lt;0.001). These differences were sustained or improved until the day before HTx (FIGURE 1). After 96 hours dobutamine was maintained in 98% of patients, nitroprusside increased from 56% to 67%, milrinone decreased from 26% to 20%, and norepinephrine decreased from 18% to 3%. Significant IABP complications were few (5.2%; n=7: 3 infections, 2 major bleeding, 2 arterial injury). Conclusion In this single center ICU sample, IABP improved hemodynamic status and renal function in refractory HF patients waiting for HTx. IABP can be a reasonable, available and effective bridging therapy. Figure 1 Funding Acknowledgement Type of funding source: None

scholarly journals N6-Methyladenosine RNA modification in cerebrospinal fluid as a novel potential diagnostic biomarker for progressive multiple sclerosis

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Fei Ye ◽  
Tianzhu Wang ◽  
Xiaoxin Wu ◽  
Jie Liang ◽  
Jiaoxing Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Sclerosis ◽  
Clustering Analysis ◽  
Roc Curves ◽  
Progressive Multiple Sclerosis ◽  
Rna Modification ◽  
Diagnostic Model ◽  
Consensus Clustering ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract Background Progressive multiple sclerosis (PMS) is an uncommon and severe subtype of MS that worsens gradually and leads to irreversible disabilities in young adults. Currently, there are no applicable or reliable biomarkers to distinguish PMS from relapsing–remitting multiple sclerosis (RRMS). Previous studies have demonstrated that dysfunction of N6-methyladenosine (m6A) RNA modification is relevant to many neurological disorders. Thus, the aim of this study was to explore the diagnostic biomarkers for PMS based on m6A regulatory genes in the cerebrospinal fluid (CSF). Methods Gene expression matrices were downloaded from the ArrayExpress database. Then, we identified differentially expressed m6A regulatory genes between MS and non-MS patients. MS clusters were identified by consensus clustering analysis. Next, we analyzed the correlation between clusters and clinical characteristics. The random forest (RF) algorithm was applied to select key m6A-related genes. The support vector machine (SVM) was then used to construct a diagnostic gene signature. Receiver operating characteristic (ROC) curves were plotted to evaluate the accuracy of the diagnostic model. In addition, CSF samples from MS and non-MS patients were collected and used for external validation, as evaluated by an m6A RNA Methylation Quantification Kit and by real-time quantitative polymerase chain reaction. Results The 13 central m6A RNA methylation regulators were all upregulated in MS patients when compared with non-MS patients. Consensus clustering analysis identified two clusters, both of which were significantly associated with MS subtypes. Next, we divided 61 MS patients into a training set (n = 41) and a test set (n = 20). The RF algorithm identified eight feature genes, and the SVM method was successfully applied to construct a diagnostic model. ROC curves revealed good performance. Finally, the analysis of 11 CSF samples demonstrated that RRMS samples exhibited significantly higher levels of m6A RNA methylation and higher gene expression levels of m6A-related genes than PMS samples. Conclusions The dynamic modification of m6A RNA methylation is involved in the progression of MS and could potentially represent a novel CSF biomarker for diagnosing MS and distinguishing PMS from RRMS in the early stages of the disease.

The Accuracy of Continuous Glucose Monitoring in the Medical Intensive Care Unit

2021 ◽  
pp. 193229682110275
Author(s):  
Wannita Tingsarat ◽  
Patinut Buranasupkajorn ◽  
Weerapan Khovidhunkit ◽  
Patchaya Boonchaya-anant ◽  
Nitchakarn Laichuthai
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Continuous Glucose Monitoring ◽  
Medical Intensive Care Unit ◽  
Glucose Monitoring ◽  
Relative Difference ◽  
Risk Zone ◽  
Medical Intensive Care ◽  
Vasopressor Use ◽  
Error Grid

Objective: To assess the accuracy of continuous glucose monitoring (CGM) in medical intensive care unit (MICU) patients. Methods: A Medtronic Enlite® sensor accuracy was assessed versus capillary blood glucose (CBG) and plasma glucose (PG) using the mean absolute relative difference (MARD), surveillance error grid (SEG) analysis and modified Bland-Altman plots. Results: Using CBG as a reference, MARD was 6.6%. Overall, 99.7% of the CGM readings were within the “no risk” zone. No significant differences in accuracy were seen within vasopressor subgroups. Using PG as the reference, MARD was 8.8%. The surveillance error grid analysis showed 95.2% of glucose readings were within the “no risk” zone. There were no device-related adverse events. Conclusion: The CGM sensor showed acceptable accuracy in MICU patients, regardless of vasopressor use.

scholarly journals Protein interactions and consensus clustering analysis uncover insights into herpesvirus virion structure and function relationships

PLoS Biology ◽  
2019 ◽  
Vol 17 (6) ◽  
pp. e3000316 ◽  
Author(s):  
Anna Hernández Durán ◽  
Todd M. Greco ◽  
Benjamin Vollmer ◽  
Ileana M. Cristea ◽  
Kay Grünewald ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Clustering Analysis ◽  
Structure And Function ◽  
Consensus Clustering ◽  
Virion Structure ◽  
And Function

COVID-19 situation in Baden-Württemberg, Germany: Preliminary case series study during the first wave

2021 ◽  
Vol 1 (1) ◽  
pp. 6-11
Author(s):  
Dzmitry Katovich ◽  
Claudia Grun ◽  
Hanna Katovich ◽  
Bastian Hauer ◽  
Thomas Iber ◽  
...  
Keyword(s):  
Intensive Care ◽  
Clinical Symptoms ◽  
Fatal Outcome ◽  
Laboratory Data ◽  
Case Series ◽  
Severe Illness ◽  
Case Series Study ◽  
Regional Factors ◽  
Series Study

The present case series study presents the preliminary data of 347 of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) positively tested patients in the Mittelbaden hospital, Baden-Baden Bühl, Germany, during the period from March to June 2020. Among the 347 patients, 55% were males. The mean age-wise was 52.5±20.2 years in the overall cohort and 78.9±11.1 years in fatal outcome cases. A total of 120/347 patients (34.6%) required hospitalization, but only 36/347 (10.37%) cases required intensive care. The overall fatality rate was 6.6% (23/347), of which 12 patients were from the intensive care unit. The most frequent clinical symptoms observed were cough (62.5%), hyperthermia (47.8%), rhinorrhea (25.1%), sore throat (23.1%), dyspnea (22.8%), and headache (19.3%). Laboratory data analysis showed no specific findings, but severe laboratory disturbances could predict critical illness. A higher risk of severe illness or lethal outcome in elderly patients with several comorbidities was the most frequent. The fight against COVID-19 infection in Germany seems to be more successful during the first wave than in other countries. The improvement of the healthcare system against infectious outbreaks depends directly on the analysis of regional factors.

scholarly journals Metformin-Associated Lactic Acidosis Undergoing Renal Replacement Therapy in Intensive Care Units: A Five-Million Population-Based Study in the North-West of Italy

2017 ◽  
Vol 44 (3) ◽  
pp. 198-205 ◽  
Author(s):  
Filippo Mariano ◽  
Marco Pozzato ◽  
Paola Inguaggiato ◽  
Cesare Guarena ◽  
Ernesto Turello ◽  
...  
Keyword(s):  
Intensive Care ◽  
Survival Rate ◽  
Renal Replacement Therapy ◽  
Lactic Acidosis ◽  
Replacement Therapy ◽  
Intensive Care Units ◽  
High Efficiency ◽  
Journal Club ◽  
Large Population ◽  
High Survival

Background: Metformin-associated lactic acidosis (MALA) is a severe complication of drug administration with significant morbidity and mortality. So far no study in large population areas have examined the incidence, clinical profile and outcome of acute kidney injury (AKI)-MALA patients admitted in intensive care units (ICUs) and treated by renal replacement therapy (MALA-RRT). Methods: Retrospective analysis over a 6-year period (2010-2015) in Piedmont and Aosta Valley regions (5,305,940 inhabitants, 141,174 diabetics treated with metformin) of all MALA-RRT cases. Results: One hundred and seventeen cases of AKI-MALA-RRT were observed (12.04/100,000 metformin treated diabetics, 1.45% of all RRT-ICU patients). Survival rate was 78.3%. The average duration of RRT was 4.0 days at mean dialysis effluent of 977 mL/kg/day. At admission most patients were dehydrated, and experienced shock and oliguria. Conclusion: Our data showed that MALA-RRT is a common complication, needing more prevention. Adopted policy of early, extended, continuous and high efficiency dialysis could contribute to an observed high survival rate. Video Journal Club “Cappuccino with Claudio Ronco” at http://www.karger.com/?doi=471917.

scholarly journals Metformin-associated lactic acidosis in an intensive care unit

Critical Care ◽  
2008 ◽  
Vol 12 (6) ◽  
pp. R149 ◽  
Author(s):  
Nicolas Peters ◽  
Nicolas Jay ◽  
Damien Barraud ◽  
Aurélie Cravoisy ◽  
Lionel Nace ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Lactic Acidosis

Diagnostic Validity of Ratio between Differences of Central Venous to Arterial CO2 and Arterial to Central Venous O2 Content in Diagnosis of Anaerobic Metabolism among Septic Patients

2021 ◽  
Vol 8 (1) ◽  
pp. 34-38
Author(s):  
Subroto Kumar Sarker ◽  
Umme Kulsum Choudhury ◽  
Mohammad Mohsin ◽  
Subrata Kumar Mondal ◽  
Muslema Begum
Keyword(s):  
Septic Shock ◽  
Severe Sepsis ◽  
Intensive Care ◽  
Anaerobic Metabolism ◽  
Venous Blood ◽  
Blood Gases ◽  
Serum Lactate ◽  
Central Venous ◽  
College Hospital ◽  
Sepsis And Septic Shock

Background: Detection of anaerobic metabolism is very crucial for the management of the septic patients. Objective: The purpose of the present study was to validate the ratio between differences of central venous to arterial CO2 and arterial to central venous O2 content in diagnosis of anaerobic metabolism among septic patients. Methodology: This prospective observational study was conducted in the Intensive Care Unit of the department of Anaesthesia Analgesia, Palliative and Intensive Care Medicine at Dhaka Medical College Hospital, Dhaka, Bangladesh from January 2016 to December 2016. All patients admitted to ICU with the features of severe sepsis and septic shock according to SSC guidelines with the age of more than or equal to 18 years in both sexes were included in this study. The arterial and central venous blood gases were measure simultaneously. At the same time serum lactate was measured. Result: Among the 69 patients, 31(44.9%) were of severe sepsis and 38(55%) were of septic shock patients. In the severe sepsis and septic shock patients the mean P(v-a)CO2/C(a-v)O2 is 1.39±0.41 and 1.11±0.40 respectively. Serum lactate in case of severe sepsis and septic shock patients is 2.85±1.40 and 3.85±1.04 respectively. The ROC analysis showed an area under curve 0.89 and P(v-a)CO2/C(a-v)O2 ratio cutoff value of 1.21 showed sensitivity 0.84 and specificity 0.94. Conclusion: The P(v-a)CO2/C(a-v)O2  ratio is also a another marker of global anaerobic metabolism and it would be used for diagnosis as well as management of septic patient.  Journal of Current and Advance Medical Research, January 2021;8(1):34-38

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