A Novel Test for the Rapid Rule Out of Heparin-Induced Thrombocytopenia Diagnosis in Intensive Care unit patients

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 1119-1119
Author(s):  
Vassiliki Galea ◽  
Francoise Robert ◽  
Patrick Van Dreden ◽  
Barry J Woodhams ◽  
Grigoris T Gerotziafas ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Unfractionated Heparin ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
False Positive ◽  
Icu Patients ◽  
Predictive Values ◽  
Heparin Induced Thrombocytopenia ◽  
Positive Results

Abstract Abstract 1119 Introduction Diagnosis of heparin-induced thrombocytopenia (HIT) in intensive care unit (ICU) patients represents a major challenge mainly because both the use of unfractionated heparin and the presence of thrombocytopenia are quite common. Despite the existence of several laboratory tests, accurate and prompt HIT diagnostics remains difficult. The ideal combination of an immunological and a functional test is restrictedto specialized laboratories, due to the complexity of the latter. We are in need of an easy-to-perform, widely accessible, rapid and reliably assay. Aim of the study To prospectively evaluate the performance of the latelar-flow immunoassay STic HIT Expert® (Diagnostica Stago, France) for the detection in ICU patients suspected for HIT. Patients-methods Seventy two patients (40 males/32 females) hospitalized in ICU from January to June 2012 were included. Thirty one patients presented with sepsis, 27 underwent extracorporeal circulation (ECC), 21 were hemodialysed and 3 patients were receiving chemotherapy. Sixty one patients were treated with unfractionated heparin and 11 patients received low molecular weight heparin (LMWH). A 4T's score was performed for all patients. All samples were tested in polyspecific ELISA (Zymutest Hyphen Biomed, Neuville-Sur-Oise, France), STic HIT Expert® (Diagnostica Stago, France) and serotonin release assay. In case of a positive polyspecific ELISA, IgG, IgM et IgA isotypes were also performed. Sensitivity, specificity, positive and negative predictive values (PPV an NPV) of STic HIT Expert® were determined against SRA. Results All three tests (polyspecific ELISA, STic HIT Expert®, SRA) were negative in forty patients and had a low HIT suspicion (4T's score: 0–4). In 10 out of 72 patients polyspecific all immunological tests and SRA were positive and HIT suspicion was intermediate or high (4T's score: 4–7). In 9 patients, ELISA tests and STic HIT Expert® were positive but SRA was negative. These patients had a low HIT suspicion (4T's score: 1–4) and underwent ECC (6 out of 9), were hemodialyzed (3 out of 9) or complicated by sepsis (2 out of 9). On the other hand 13 out of 72 patients had ELISA tests positive but STic HIT Expert® and SRA negative. The prevalence of sepsis was high in these patients (8 out of 13), 3 patients underwent ECC and one patient was hemodialysed. STic HIT Expert®, polyspecific and IgG specific ELISA had an excellent sensitivity and negative predictive value at 100%. Moreover STic HIT Expert® was associated with a smaller number of false positive results than the ELISAs. (Table) Conclusion STic HIT Expert® has an excellent performance with a high negative predictive value (100%) and a satisfactory specificity (85%). Less false positive results are detected with STic HIT Expert® than with polyspecific and IgG specific ELISAs. Moreover the test offers a shorter turnaround than ELISA tests and is an easy-to-use single sample test. These characteristics could help avoid HIT over diagnosis in ICU patients. Disclosures: No relevant conflicts of interest to declare.

Presepsin - New Marker of Sepsis Romanian Neonatal Intensive Care Unit Experience

2019 ◽  
Vol 70 (8) ◽  
pp. 3008-3013
Author(s):  
Silvia Maria Stoicescu ◽  
Ramona Mohora ◽  
Monica Luminos ◽  
Madalina Maria Merisescu ◽  
Gheorghita Jugulete ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Neonatal Intensive Care Unit ◽  
Neonatal Sepsis ◽  
Predictive Value ◽  
Neonatal Intensive Care ◽  
Complete Blood Count ◽  
Clinical Manifestations ◽  
Receiver Operating Curve ◽  
Predictive Values

Difficulties in establishing the onset of neonatal sepsis has directed the medical research in recent years to the possibility of identifying early biological markers of diagnosis. Overdiagnosing neonatal sepsis leads to a higher rate and duration in the usage of antibiotics in the Neonatal Intensive Care Unit (NICU), which in term leads to a rise in bacterial resistance, antibiotherapy complications, duration of hospitalization and costs.Concomitant analysis of CRP (C Reactive Protein), procalcitonin, complete blood count, presepsin in newborn babies with suspicion of early or late neonatal sepsis. Presepsin sensibility and specificity in diagnosing neonatal sepsis. The study group consists of newborns admitted to Polizu Neonatology Clinic between 15th February- 15th July 2017, with suspected neonatal sepsis. We analyzed: clinical manifestations and biochemical markers values used for diagnosis of sepsis, namely the value of CRP, presepsin and procalcitonin on the onset day of the disease and later, according to evolution. CRP values may be influenced by clinical pathology. Procalcitonin values were mainly influenced by the presence of jaundice. Presepsin is the biochemical marker with the fastest predictive values of positive infection. Presepsin can be a useful tool for early diagnosis of neonatal sepsis and can guide the antibiotic treatment. Presepsin value is significantly higher in neonatal sepsis compared to healthy newborns (939 vs 368 ng/mL, p [ 0.0001); area under receiver operating curve (AUC) for presepsine was 0.931 (95% confidence interval 0.86-1.0). PSP has a greater sensibility and specificity compared to classical sepsis markers, CRP and PCT respectively (AUC 0.931 vs 0.857 vs 0.819, p [ 0.001). The cut off value for presepsin was established at 538 ng/mLwith a sensibility of 79.5% and a specificity of 87.2 %. The positive predictive value (PPV) is 83.8 % and negative predictive value (NPV) is 83.3%.

scholarly journals Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Comparative Machine Learning Study (Preprint)

2020 ◽  
Author(s):  
Sujeong Hur ◽  
Ji Young Min ◽  
Junsang Yoo ◽  
Kyunga Kim ◽  
Chi Ryang Chung ◽  
...  
Keyword(s):  
Machine Learning ◽  
Intensive Care Unit ◽  
Patient Safety ◽  
Intensive Care ◽  
Predictive Value ◽  
Prediction Models ◽  
Support Vector ◽  
Unplanned Extubation ◽  
Electronic Health Record Data ◽  
Icu Patients

BACKGROUND Patient safety in the intensive care unit (ICU) is one of the most critical issues, and unplanned extubation (UE) is considered as the most adverse event for patient safety. Prevention and early detection of such an event is an essential but difficult component of quality care. OBJECTIVE This study aimed to develop and validate prediction models for UE in ICU patients using machine learning. METHODS This study was conducted an academic tertiary hospital in Seoul. The hospital had approximately 2,000 inpatient beds and 120 intensive care unit (ICU) beds. The number of patients, on daily basis, was approximately 9,000 for the out-patient. The number of annual ICU admission was approximately 10,000. We conducted a retrospective study between January 1, 2010 and December 31, 2018. A total of 6,914 extubation cases were included. We developed an unplanned extubation prediction model using machine learning algorithms, which included random forest (RF), logistic regression (LR), artificial neural network (ANN), and support vector machine (SVM). For evaluating the model’s performance, we used area under the receiver operator characteristic curve (AUROC). Sensitivity, specificity, positive predictive value negative predictive value, and F1-score were also determined for each model. For performance evaluation, we also used calibration curve, the Brier score, and the Hosmer-Lemeshow goodness-of-fit statistic. RESULTS Among the 6,914 extubation cases, 248 underwent UE. In the UE group, there were more males than females, higher use of physical restraints, and fewer surgeries. The incidence of UE was more likely to occur during the night shift compared to the planned extubation group. The rate of reintubation within 24 hours and hospital mortality was higher in the UE group. The UE prediction algorithm was developed, and the AUROC for RF was 0.787, for LR was 0.762, for ANN was 0.762, and for SVM was 0.740. CONCLUSIONS We successfully developed and validated machine learning-based prediction models to predict UE in ICU patients using electronic health record data. The best AUROC was 0.787, which was obtained using RF. CLINICALTRIAL N/A

scholarly journals Use of a Combination Biomarker Algorithm To Identify Medical Intensive Care Unit Patients with Suspected Sepsis at Very Low Likelihood of Bacterial Infection

2015 ◽  
Vol 59 (10) ◽  
pp. 6494-6500 ◽  
Author(s):  
Jennifer H. Han ◽  
Irving Nachamkin ◽  
Susan E. Coffin ◽  
Jeffrey S. Gerber ◽  
Barry Fuchs ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Serum Amyloid ◽  
University Hospital ◽  
Bacterial Sepsis ◽  
Suspected Sepsis ◽  
Icu Patients ◽  
Predictive Values ◽  
Time Points ◽  
Amyloid A

ABSTRACTSepsis remains a diagnostic challenge in the intensive care unit (ICU), and the use of biomarkers may help in differentiating bacterial sepsis from other causes of systemic inflammatory syndrome (SIRS). The goal of this study was to assess test characteristics of a number of biomarkers for identifying ICU patients with a very low likelihood of bacterial sepsis. A prospective cohort study was conducted in a medical ICU of a university hospital. Immunocompetent patients with presumed bacterial sepsis were consecutively enrolled from January 2012 to May 2013. Concentrations of nine biomarkers (α-2 macroglobulin, C-reactive protein [CRP], ferritin, fibrinogen, haptoglobin, procalcitonin [PCT], serum amyloid A, serum amyloid P, and tissue plasminogen activator) were determined at baseline and at 24 h, 48 h, and 72 h after enrollment. Performance characteristics were calculated for various combinations of biomarkers for discrimination of bacterial sepsis from other causes of SIRS. Seventy patients were included during the study period; 31 (44%) had bacterial sepsis, and 39 (56%) had other causes of SIRS. PCT and CRP values were significantly higher at all measured time points in patients with bacterial sepsis. A number of combinations of PCT and CRP, using various cutoff values and measurement time points, demonstrated high negative predictive values (81.1% to 85.7%) and specificities (63.2% to 79.5%) for diagnosing bacterial sepsis. Combinations of PCT and CRP demonstrated a high ability to discriminate bacterial sepsis from other causes of SIRS in medical ICU patients. Future studies should focus on the use of these algorithms to improve antibiotic use in the ICU setting.

scholarly journals Detection of Aspergillus fumigatus in Blood Samples from Critically Ill Patients in Intensive Care Units by Use of the SeptiFast Assay: TABLE 1

2016 ◽  
Vol 54 (7) ◽  
pp. 1918-1921 ◽  
Author(s):  
Joerg Steinmann ◽  
Jan Buer ◽  
Peter-Michael Rath
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Positive Predictive Value ◽  
Aspergillus Fumigatus ◽  
Critically Ill ◽  
Predictive Value ◽  
Icu Patients ◽  
Blood Samples ◽  
Content Type ◽  
Whole Blood Samples

We retrospectively analyzed the performance and relevance of the SeptiFast assay in detectingAspergillus fumigatusDNA in whole blood samples from 38 critically ill intensive care unit (ICU) patients with probable or proven invasive aspergillosis (IA) and 100 ICU patients without IA. The assay exhibited 66% sensitivity, 98% specificity, a 93% positive predictive value, and an 88% negative predictive value.A. fumigatusDNAemia was associated with poor outcome.

scholarly journals Renal dysfunction decreases specificity and overturns cutoff value of serum CC16 while prohibiting 7-day mortality prediction in diagnosing acute respiratory distress syndrome in intensive care unit.

2020 ◽  
Author(s):  
Jinle Lin ◽  
Wuyuan Tao ◽  
Jian Wei ◽  
Wu Jian ◽  
Wenwu Zhang ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Acute Respiratory Distress Syndrome ◽  
Intensive Care ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Renal Dysfunction ◽  
Predictive Value ◽  
Distress Syndrome ◽  
Icu Patients ◽  
Cutoff Value

Abstract Background: A contradictory tendency between occurrence of acute respiratory distress syndrome (ARDS) and serum club cell protein 16 (CC16) level, However, renal dysfunction (RD) separately raised serum CC16 in our current observation. The purpose of this study was to find the limitation caused by renal dysfunction in the diagnostic performance of CC16 on ARDS in intensive care unit (ICU) patients. Method: We measured serum CC16 in 479 ICU patients. Patients were divided into six subgroups: control, acute kidney injury (AKI), chronic kidney dysfunction (CKD), ARDS, ARDS+AKI, and ARDS+CKD. The cutoff value, sensitivity and specificity of serum CC16 were assessed by receiver operating characteristic curves. Result: Serum CC16 increased among the ARDS group when compared to the control group, which helps identify ARDS and predicts the outcome in patients with normal renal function. However, level of serum CC16 was similar among ARDS+AKI, ARDS+CKD, AIK and CKD groups. Consequently, when compare to AKI and CKD, specificity for diagnosing whether ARDS or ARDS with renal failure decreased from 86.62% to 2.82% or 81.70% to 2.12%. Consistently, a cutoff value of 11.57 ng/mL was overturned from previously at 32.77 ng/mL or 33.72 ng/mL. Moreover, its predictive value for mortality is prohibited before 7 day but works after 28 day. Conclusion: Renal dysfunction limits the specificity, cutoff point, and predictive value at 7-day mortality of CC16 in diagnosing ARDS among ICU patients.

Predictive Values of Initial Severity Scores at Intensive Care Unit Admission for Patients With Overnight or Prolonged Stay

2021 ◽  
Author(s):  
Koji Hosokawa ◽  
Nobuaki Shime
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Predictive Value ◽  
Apache Ii ◽  
Icu Patients ◽  
Prolonged Stay ◽  
Saps Ii ◽  
Icu Stay ◽  
Severity Scores

Abstract Background: The predictive value of disease severity scores for intensive care unit (ICU) patients is occasionally inaccurate because ICU patients with mild symptoms are also considered. We, thus, aimed to evaluate the accuracy of severity scores in predicting mortality of patients with complicated conditions admitted for > 24 hours. Methods: Overall, 35,353 adult patients using nationwide ICU data were divided into two groups: (1) overnight ICU stay after elective surgery and alive on discharge within 24 hours and (2) death within 24 hours or prolonged stay. The performance and accuracy of Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation (APACHE) II and III, and Simplified Acute Physiology Score (SAPS) II scores in predicting in-hospital mortality were evaluated. Results: In the overnight stay group, the correlation between SOFA and APACHE III scores or SAPS II was low because many had a SOFA score of 0. In the prolonged stay group, the predictive value of SAPS II and APACHE II and III showed high accuracy but that of SOFA was moderate. Conclusions: When overnight ICU stay patients were not included, the high predictive value for in-hospital mortality of SAPS II and APACHE II and III was evident.

scholarly journals Association of Procalcitonin Value and Bacterial Coinfections in Pediatric Patients With Viral Lower Respiratory Tract Infections Admitted to the Pediatric Intensive Care Unit

2018 ◽  
Vol 23 (6) ◽  
pp. 466-472
Author(s):  
John J. Kotula ◽  
Wayne S. Moore ◽  
Arun Chopra ◽  
Jeffrey J. Cies
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Respiratory Tract ◽  
Negative Predictive Value ◽  
Pediatric Intensive Care Unit ◽  
Predictive Value ◽  
Lower Respiratory Tract ◽  
Pediatric Intensive Care ◽  
Treatment Decisions ◽  
Bacterial Coinfection

OBJECTIVE Our primary objective was to determine the utility of procalcitonin (PCT) in detection of bacterial coinfection in children < 5 years admitted to the pediatric intensive care unit with viral lower respiratory tract infection (LRTI). METHODS Electronic medical record review of children < 5 years admitted to the pediatric intensive care unit with a viral LRTI who also had at least 1 PCT concentration measurement. RESULTS Seventy-five patients were admitted to the intensive care unit and met the inclusion criteria for this investigation. The PCT threshold concentrations of 0.9, 1, 1.4, and 2 ng/mL were found to be statistically significant in determining the presence of a bacterial coinfection. The PCT concentration with the most utility was 1.4 ng/mL with sensitivity, specificity, positive and negative predictive values of 46%, 83%, 68%, and 76%, respectively. For patients with serial PCTs, the second PCT correctly influenced treatment decisions for 11 of 25 patients (44%). CONCLUSIONS A PCT value of 1.4 ng/mL determined the presence of a bacterial coinfection primarily owing to the high specificity and negative predictive value. Our data add evidence to the relatively high negative predictive value of PCT concentrations in identifying patients with bacterial coinfection, specifically in the case of viral LRTI. In addition, our preliminary data indicate serial PCT measurements may help further influence correct treatment decisions. Prospective, controlled studies are warranted to validate an appropriate PCT threshold concentration to help in identifying bacterial coinfection as well as to further explore the role of serial PCT values in determining the absence or presence of a bacterial coinfection.

scholarly journals Evaluation of a Candida Antigen Detection Method (Cand-Tec): Experience from a University Teaching Hospital

1992 ◽  
Vol 3 (4) ◽  
pp. 167-172 ◽  
Author(s):  
Todd J Anderson ◽  
Heather E Bryant ◽  
Deirdre L Church
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Sensitivity And Specificity ◽  
Invasive Candidiasis ◽  
Predictive Value ◽  
High Probability ◽  
University Teaching ◽  
Candidal Infection

The usefulness of a rapid latex agglutination method for the detection of Candida antigen (Cand-Tec; Ramco Laboratories. Texas) was retrospectively assessed in a university teaching hospital over a one year period. Patients were enrolled when the managing physician requested Cand-Tec testing for confirmation of possible invasive candidal infection. The majority of patients were critically ill; 56% were in the intensive care unit, and 30% subsequently died. Analyses were available from 79 patients and 125 samples. Thirty-three patients were diagnosed as having either definite invasive candidiasis or a high probability of infection based upon clinical, microbiological and tissue criteria. The sensitivity and specificity of Candida antigen detection was determined for doubling titres ≥1:4 to ≥1:16. If a titre of ≥1:4 was used as the diagnostic cut-off level for definite candidal infection, overall sensitivity and specificity were 77% and 69%, respectively, while the positive predictive value was 48%, and the negative predictive value 89%. When patients with a high probability of invasive candidal infection were included in analyses for a cut-off titre of ≥1:4, overall sensitivity and specificity were 70% and 69%, respectively, while the positive predictive value was 68%, and the negative predictive value 71%. The usefulness of the Cand-Tec test was not improved further for any subgroup of patients (including those in the intensive care unit), nor by following serial titres in individual patients. In this experience, the Cand-Tec test did not add enough information to include definitively or exclude invasive candidiasis in this high risk general patient population.

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