A simple method for “reference range” estimation from routine laboratory data

1976 ◽  
Vol 9 ◽  
pp. 198-202 ◽  
Author(s):  
Samuel Y. Chu ◽  
P. Cheung ◽  
V.E. Turkington
Keyword(s):  
Reference Range ◽  
Laboratory Data ◽  
Routine Laboratory ◽  
Range Estimation ◽  
Simple Method

scholarly journals Relation between cytokines and routine laboratory data in children with septic shock and purpura

1994 ◽  
Vol 20 (5) ◽  
pp. 371-374 ◽  
Author(s):  
J. A. Hazelzet ◽  
E. van der Voort ◽  
J. Lindemans ◽  
P. G. J. ter Heerdt ◽  
H. J. Neijens
Keyword(s):  
Septic Shock ◽  
Laboratory Data ◽  
Routine Laboratory

A Simple Method for the Characteristic Differentiation of Antibiotics by TLC-Bioautography in Graded Concentration of Ammonium Chloride

1988 ◽  
Vol 51 (10) ◽  
pp. 786-789 ◽  
Author(s):  
FUSAO KONDO
Keyword(s):  
Laboratory Test ◽  
Ammonium Chloride ◽  
Chloride Solution ◽  
Chemical Structure ◽  
Characteristic Change ◽  
Routine Laboratory ◽  
Simple Method ◽  
Tetracycline Antibiotics ◽  
Tlc Bioautography ◽  
Rf Values

A simple classification method for 24 known antibiotics by TLC-bioautographic procedure was developed. The approach used was to change the Rf values in seven TLC systems with an ammonium chloride solution in a graded concentration range (0.5, 1, 2, 3, 5, 10 and 20%). The antibiotics were divided into four groups (A to D) showing the characteristic behavior of Rf values corresponding to similarities in chemical structure: β-lactam, aminoglycoside, macrolide and tetracycline antibiotics. TLC-bioautography helps to estimate the character of antibiotics and the characteristic change of Rf values may be very useful for classifying unknown residual antibiotics in animal samples as a routine laboratory test.

scholarly journals Artificial intelligence assisted electrocardiography for early diagnosis of thyrotoxic periodic paralysis

2021 ◽  
Author(s):  
Chin Lin ◽  
Chin-Sheng Lin ◽  
Ding-Jie Lee ◽  
Chia-Cheng Lee ◽  
Sy-Jou Chen ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Early Diagnosis ◽  
Validation Cohort ◽  
Laboratory Data ◽  
Diagnostic System ◽  
Periodic Paralysis ◽  
Medical Emergency ◽  
Diagnostic Process ◽  
Routine Laboratory ◽  
Thyrotoxic Periodic Paralysis

Abstract CONTEXT Thyrotoxic periodic paralysis (TPP) characterized by acute weakness, hypokalemia and hyperthyroidism is a medical emergency with a great challenge in early diagnosis since most TPP patients do not have overt symptoms. OBJECTIVE To assess artificial intelligence (AI)-assisted electrocardiography (ECG) combined with routine laboratory data in the early diagnosis of TPP. METHODS A deep learning model (DLM) based on ECG12Net, an 82-layer convolutional neural network, was constructed to detect hypokalemia and hyperthyroidism. The development cohort consisted of 39 ECGs from patients with TPP and 502 ECGs of hypokalemic control; the validation cohort consisted of 11 ECGs of TPP and 36 ECGs of non-TPP with weakness. The AI-ECG based TPP diagnostic process was then consecutively evaluated in 22 male patients with TTP-like features. RESULTS In the validation cohort, the DLM-based ECG system detected all cases of hypokalemia in TPP patients with a mean absolute error of 0.26 mEq/L and diagnosed TPP with an area under curve (AUC) of ~80%, surpassing the best standard ECG parameter (AUC=0.7285 for the QR interval). Combining the AI predictions with the estimated glomerular filtration rate (eGFR) and serum chloride (Cl -) boosted the diagnostic accuracy of the algorithm to AUC 0.986. In the prospective study, the integrated AI and routine laboratory diagnostic system had a PPV of 100% and F-measure 87.5%. CONCLUSIONS An AI-ECG system reliably identifies hypokalemia in patients with paralysis and integration with routine blood chemistries provides valuable decision support for the early diagnosis of TPP.

scholarly journals Routine laboratory surveillance of antimicrobial resistance in community-acquired urinary tract infections adequately informs prescribing policy in England

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Vicky Watts ◽  
Benjamin Brown ◽  
Maria Ahmed ◽  
André Charlett ◽  
Carolyn Chew-Graham ◽  
...  
Keyword(s):  
Urinary Tract ◽  
Antimicrobial Resistance ◽  
Urinary Tract Infections ◽  
Laboratory Data ◽  
Routine Data ◽  
Sentinel Surveillance ◽  
Routine Laboratory ◽  
Diagnostic Laboratory ◽  
E Coli ◽  
Tract Infections

Abstract Objectives To assess whether resistance estimates obtained from sentinel surveillance for antimicrobial resistance (AMR) in community-acquired urinary tract infections (UTIs) differ from routinely collected laboratory community UTI data. Methods All patients aged ≥18 years presenting to four sentinel general practices with a suspected UTI, from 13 November 2017 to 12 February 2018, were asked to provide urine specimens for culture and susceptibility. Specimens were processed at the local diagnostic laboratory. Antibiotic susceptibility testing was conducted using automated methods. We calculated the proportion of Escherichia coli isolates that were non-susceptible (according to contemporaneous EUCAST guidelines) to trimethoprim, nitrofurantoin, cefalexin, ciprofloxacin and amoxicillin/clavulanic acid, overall and by age group and sex, and compared this with routine estimates. Results Sentinel practices submitted 740 eligible specimens. The specimen submission rate had increased by 28 specimens per 1000 population per year (95% CI 21–35). Uropathogens were isolated from 23% (169/740) of specimens; 67% were E. coli (113/169). Non-susceptibility of E. coli to trimethoprim was 28.2% (95% CI 20.2–37.7) on sentinel surveillance (33.4%; 95% CI 29.5–37.6 on routine data) and to nitrofurantoin was 0.9% (95% CI 0–5.7) (1.5%; 95% CI 0.7–3.0 on routine data). Conclusions Routine laboratory data resulted in a small overestimation in resistance (although the difference was not statistically significant) and our findings suggest that it provides an adequate estimate of non-susceptibility to key antimicrobials in community-acquired UTIs in England. This study does not support the need for ongoing local sentinel surveillance.

scholarly journals Separate patient serum sodium medians from males and females provide independent information on analytical bias

2017 ◽  
Vol 55 (12) ◽  
Author(s):  
Steen Ingemann Hansen ◽  
Per Hyltoft Petersen ◽  
Flemming Lund ◽  
Callum G. Fraser ◽  
György Sölétormos
Keyword(s):  
Serum Sodium ◽  
Laboratory Data ◽  
Routine Laboratory ◽  
Male And Female ◽  
Female Patients ◽  
Analytical Stability ◽  
Independent Information ◽  
Maximum Bias ◽  
Males And Females ◽  
Over Time

AbstractBackground:During monitoring of monthly medians of results from patients undertaken to assess analytical stability in routine laboratory performance, the medians for serum sodium for male and female patients were found to be significantly related.Methods:Daily, weekly and monthly patient medians of serum sodium for both male and female patients were calculated from results obtained on samples from the population >18 years on three analysers in the hospital laboratory. The half-range of medians was applied as an estimate of the maximum bias. Further, the ratios between the two medians were calculated.Results:The medians of both genders demonstrated dispersions over time, but they were closely connected in like patterns, which were confirmed by the half-range of the ratios of medians for males and females that varied from 0.36% for daily, 0.14% for weekly and 0.036% for monthly ratios over all instruments.Conclusions:The tight relationship between the gender medians for serum sodium is only possible when raw laboratory data are used for calculation. The two patient medians can be used to confirm both and are useful as independent estimates of analytical bias during constant calibration periods. In contrast to the gender combined median, the estimate of analytical bias can be confirmed further by calculation of the ratios of medians for males and females.

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