Reporting diagnostic performance results using standard performance measures, such as: sensitivity, specificity, and predictive values, have been a standard practice for decades. Issues with reporting using only numerical values include: 1) often only a subset of performance measures are reported, thus results could be misinterpreted and misused, 2) difficult to visualize the complex relationships of the reported performance measures. To overcome these shortcomings, a graphical presentation has been developed to further improve the test results reporting.The 2-dimentional performance graph uses line segment, area, ratio of line segments, ratio of areas, and sum of areas to represent most of the commonly used performance measures in this single graph.Advantages of the new graphic presentation are: 1) large number of performance measures can be presented and visualized simultaneously in a single graph, 2) allow the complex relationships of all performance measures to be understood more easily, 3) reduce the need to memorize some of the complex formulas for computing the performance measures, and 4) a great teaching tool in explaining the relationships of the commonly used performance measures.

Background The 12‑lead ECG plays an important role in triaging patients with symptomatic coronary artery disease, making automated ECG interpretation statements of “Acute MI” or “Acute Ischemia” crucial, especially during prehospital transport when access to physician interpretation of the ECG is limited. However, it remains unknown how automated interpretation statements correspond to adjudicated clinical outcomes during hospitalization. We sought to evaluate the diagnostic performance of prehospital automated interpretation statements to four well-defined clinical outcomes of interest: confirmed ST- segment elevation myocardial infarction (STEMI); presence of actionable coronary culprit lesions, myocardial necrosis, or any acute coronary syndrome (ACS). Methods An observational cohort study that enrolled consecutive patients with non-traumatic chest pain transported via ambulance. Prehospital ECGs were obtained with the Philips MRX monitor from the medical command center and re-processed using manufacturer-specific diagnostic algorithms to denote the likelihood of >>>Acute MI<<< or >>>Acute Ischemia<<<. Two independent reviewers retrospectively adjudicated the study outcomes and disagreements were resolved by a third reviewer. Results Our study included 2400 patients (age 59 ± 16, 47% females, 41% Black), with 190 (8%) patients with documented automated diagnostic statements of acute MI or acute ischemia. The sensitivity/specificity of the automated algorithm for detecting confirmed STEMI (n = 143, 6%); presence of actionable coronary culprit lesions (n = 258, 11%), myocardial necrosis (n = 291, 12%), or any ACS (n = 378, 16%) were 62.9%/95.6%; 37.2%/95.6%; 38.5%/96.4%; and 30.7%/96.3%, respectively. Conclusion Although being very specific, automated interpretation statements of acute MI/acute ischemia on prehospital ECGs are not satisfactorily sensitive to exclude symptomatic coronary disease. Patients without these automated interpretation statements should be considered further for significant underlying coronary disease based on the clinical context. Trial registration ClinicalTrials.gov # NCT04237688

Real-time ST-segment monitoring for ischemia detection was introduced for clinical use in the 80s. To overcome the earlier systems' limitation on the number of leads monitored, systems that support continuous 12-lead ECG acquisition were developed. Derived 12-lead ECGs from 5-wire and 6-wire lead sets were also developed when direct 12-lead acquisition was not practical. Several innovative graphical solutions were developed to manage the large amount of date from continuous 12-lead ST monitoring, including ST Map for better visual tracking of ST measurements, STEMI Map for more accurate tracking of STEMI criteria, and ST Topology for more efficient ST trending review. To further improve the accuracy of acute ischemia/infraction detection, two advanced 12-lead based lead derivation methods are being developed. The vesselspecific leads (VSLs) method measures ST elevation from three optimal leads, calculated from the 12-lead ECG, for detecting ST-segment deviation during coronary occlusion. The computed electrocardiographic imaging (CEI) method presents a bulls-eye polar plot of the heart surface potentials based on inverse calculation from the body-surface potential mapping derived from the 12-lead ECG. Early results show that these methods could be a useful clinical decision support tool for improving the accuracy of ECG-based triage of chest-pain patients.

Implantable pacemakers are widely used for managing patients with certain cardiac rhythm abnormalities to reduce mortality and morbidity while improving quality of life. However, for ECG devices that have to analyze the surface ECG signals, it has always been a major challenge to maintain a high level of performance. Several recent advances in pacemaker development have created even further challenges for the ECG devices. Earlier developments such as ventricular pacing, atrial pacing, dual-chamber pacing, unipolar vs. bipolar pacing are well understood. However, more recent advances such as: biventricular pacing, multipoint pacing, leadless pacemakers, device-specific algorithms for reducing frequency of right ventricle pacing and managing pacing output to improve battery life are much more complex and thus are more difficult to evaluate whether the ECG devices can still function effectively. To ensure continuous safe and effective monitoring, the basic requirements are: a) mandatory manufacture disclosure of device information required for monitoring algorithm design, b) development of up-to-date paced algorithm performance evaluation procedures, and c) a suitable paced database for algorithm development and testing. This would require the cooperation of pacemaker and ECG device manufactures, and regulatory agencies.

Numerous diagnostic tests are routinely performed clinically to: 1) screen for disease, 2) establish or rule out a diagnosis, and 3) track and monitor disease progression and effectiveness of treatment. Thus, interpretation of diagnostic test results is critical in supporting clinical decisions for the most effective patient management. The basic performance statistics required in the test results interpretation, including sensitivity (Se), specificity (Sp), overall accuracy (ACC), pretest likelihood (prevalence), and posttest likelihood including positive predictive value (PPV) and negative predictive value (NPV) are reviewed. The definitions and formulas of these performance measures and their relationships are summarized. Unlike Se and Sp, which are independent of the prevalence of the condition being tested, the other three performance measures PPV, NPV, and ACC depend on the disease prevalence. It is very important to understand the impact of disease prevalence when using these performance measures in reporting and interpreting the test results. The problem (also known as "accuracy paradox") of using the single performance measure ACC to characterize the test performance is described and explained. Despite its simplicity and frequent use in the published literatures for performance reporting, it is shown that the overall accuracy is not a reliable performance measure and its use should be avoided. The most important relationship of PPV as a function of the pretest likelihood and the accuracy of the test method (specified by Se and Sp) is clearly described and explained. With a clear understanding of the relationship between the pretest likelihood and PPV, discussion of several topics are presented to show how these basic statistical concepts can be applied in a variety of situations for effective decision support and patient management.

Electrocardiographic monitoring, which allows for continuous non-invasive detection and documentation of cardiac arrhythmia, is one of the most frequently used monitoring procedures for managing in-hospital patients. The most often cited issue of using these systems is the large number of alarms generated by these systems. These alarms include both false alarms and repetitive non-actionable true alarms. This paper provides an overview of potential solutions for managing these alarms.Device based solutions for false alarm reduction include a) providing more specific information in assisting users to identify the root cause of the false alarms, and b) continuing the development of more robust ECG and multi-parameter based algorithms.Frequent repetitive non-actionable alarms can be reduced and managed by developing a more robust alarm generation structure. An overview of the key features/components of a robust alarm generation structure is provided with an example to show how such a system could be used to manage and reduce the repetitive non-actionable alarms.Despite continuous development of the computerized ECG/arrhythmia monitoring systems over the last several decades, numerous opportunities still exist to further improve the usability of these systems. In addition to continuous algorithm enhancement ( both ECG and multi-parameter based), other potential areas for enhancement include: better user support tools for trouble-shooting and work around, and better and more flexible alarm generation structures.

The aeration tanks at two Ohio wastewater treatment plants (Mill Creek and Upper Mill Creek) were investigated to improve phosphorus (P) removal. Although these plants were operated in modes conducive to biological P removal (BPR) and had high P removal efficiencies, they still had difficulty in consistently meeting their P discharge targets. Pilot-Scale Batch Reactors (PSBR’s) were installed and fed mixed liquor from the head end of the aeration tanks to investigate the influence of anaerobic/anoxic and aerobic zones on BPR. The PSBR’s were useful in investigating the influence of anaerobic/anoxic and aerobic zones on BPR. The results were used to recommend process modifications to improve BPR. BACKGROUND AND PURPOSE Historically, phosphorus removal technology has relied on chemical precipitation by the addition of iron or aluminum salts. However, in recent years more emphasis has been placed on biological phosphorus removal (BPR) followed by chemical precipitation only if necessary to meet discharge limits (Carrera et al. 2001). BPR from wastewater can be achieved in two ways: stoichiometric coupling to microbial growth or enhanced storage in the biomass as polyphosphate (poly-P). The latter was formerly called “luxury uptake” and is the key mechanism in enhanced biological phosphorus removal (EBPR) (Carucci et al. 1999; Jeon et al. 2001a, b; Mino et al. 1998; Seviour et al. 2003). EBPR has been proved to be the most economical and sustainable method for phosphorus removal (Keller et al. 2002; Pijuan et al. 2004). The EBPR process is primarily characterized by circulation of activated sludge through anaerobic and aerobic phases, coupled with the introduction of influent wastewater into the anaerobic phase. By this anaerobic/aerobic configuration, microorganisms that accumulate poly-P and thus have high phosphorus content, are selected and grow to dominance in the process. High phosphate removal efficiency can be achieved by withdrawing the excess sludge with high phosphorus content (Mino et al. 1998). The Pilot Scale Batch Reactors (PSBR’s) used in this study were modified based on the widely used Sequencing Batch Reactor (SBR) process. The SBR process includes a provision for recycled biomass, as well as allowance for feed time, react time, settling time, and effluent withdrawal time. The PSBR’s employed here were fed mixed liquor, had very short fill and withdrawal times, and did not provide for settling. SBR is widely used in nitrogen and phosphorus removal research (Randall et al. 1997; Baetens et al. 1999; Nielsen et al. 1999; Dassanayake and Irvine 2001; Hood and Randall 2001; Jeon et al. 2001a, b; Zeng et al. 2003; Chen et al. 2004). For instance, Oa and Choi (1997) studied phosphorus removal from nightsoil using an SBR. They found that phosphorus could be removed 36% in the cellular form, 42% by chemical precipitation, and 5% by adsorption. Biological phosphorus removal could be increased by increasing the anaerobic period. The nitrogen removal potential of poly-P accumulalting organisms (PAOs) under anoxic conditions was evaluated using a laboratory scale SBR fed with synthetic wastewater and operated in a sequence of anaerobic, anoxic and aerobic periods (Artan et al. 1998). The phosphate uptake rate under anoxic conditions was lower than that under aerobic conditions. However, in the presence of an external substrate such as glucose or acetate, the fate of phosphate was dependent on the substrate type. Phosphate release occurred in the presence of nitrate as long as acetate was present, and glucose did not cause any phosphate release. Hood and Randall (2001) conducted anaerobic/aerobic batch experiments with a variety of volatile fatty acids (VFAs) and amino acids on two sequencing batch reactor populations displaying enhanced biological phosphorus removal. Jeon et al. (2001b) evaluated the effect of pH on phosphorus removal by repeating operation of a sequencing batch reactor supplied with acetate as a sole carbon source. The purpose of this study was to explore improvements in biological phosphorus removal at two full-scale treatment plants. Pilot scale batch reactors were used to investigate the influence of anaerobic/anoxic and aerobic zones on BPR efficiency. PILOT-SCALE BATCH REACTOR (PSBR) The PSBR’s employed in this study were fed mixed liquor from the head end of the aeration tank and the reaction period was equal to the nominal retention time of the plant aeration tank. After each reaction period, the reactor discharged its entire volume and was refilled with mixed liquor. Because the reactor was fed mixed liquor from the head of the aeration tank, it mimicked the operation of a plug flow aeration tank with spatial sequences occurring in the aeration tank, mimicked by temporal sequences in the PSBR. An advantage of the PSBR is that the dissolved oxygen conditions (e.g. anaerobic/anoxic, vs aerobic conditions) can be easily manipulated and the short term effects of these conditions can be readily measured The PSBR’s consisted of columns nominally 3 meters high and 0.30 meters in diameter (Figure 1). The column height 1 Corresponding Author, 12716 Ginger Wood Lane, Clarksburg, MD 20871, U.S.A. Phone: (301)247-1767 Email: johnwang1974@gmail.com 2 Department of Civil and Environmental Engineering, PO Box 210071, University of Cincinnati, Cincinnati, OH 45221-0071, U.S.A. Use of Pilot-Scale Batch Reactors to Explore Improvements in Biological Phosphorus Removal at Full-Scale Treatment Plants Page 3 Environmental Engineer: Applied Research & Practice, Volume 11 http://www.aaees.org could be varied by adding or removing column segments. The column cross sectional area was 0.067 m2 and the volume was 0.181 m3 for a water height of 2.7 meter. The diffuser used in the bottom was a fine pore ceramic disc diffuser and was the same as that used in the full-scale aeration tanks. Although several sampling ports along the column length, only the port, located at one meter from the column bottom, was used in this study to draw samples at various time intervals. A DO probe was placed into the column from the open top and measured the DO level at about 50 cm depth. A pump with a maximum capacity of 22.7 liters/min was used to pump the mixed liquor from the head end of the full-scale aeration tanks into the column. An air compressor was used to supply air at a maximum flow of 56.6 liters/min (120 cubic feet/hour) under 3.0 m water head. A Kings flow meter was used to control the airflow into the column. Based on the column volume, an air flow of approximately 5.7 liters/min (12 cubic feet/hour) was required to achieve the current full-scale aeration level, and thus the air flow meter was chosen to have a maximum capacity of 9.4 liters/min (20 cubic feet/hour) under standard conditions. Temperature and pressure corrections were done using the chart provided with the flow meter to convert the airflow to the standard temperature and pressure. The whole system was placed on a steel cart with four wheels installed underneath to make it movable (Figure 2). MILL CREEK PLANT STUDY The Metropolitan Sewer District of Greater Cincinnati (MSD) provides wastewater removal and treatment for over 800,000 customers throughout Cincinnati and Hamilton County. The area served includes 33 municipalities and unincorporated areas covering more than 400 square miles. Over 200,000 separate sewer connections tie into the 3,000+ miles of sanitary and combined sewers. Overview of the Mill Creek Plant The Mill Creek Wastewater Treatment Plant (WWTP) is the largest of seven major WWTPs operated by Cincinnati MSD. The influent wastewater is composed of 30% industrial wastewater and 70% municipal sewage. The plant was designed with a capacity of 120 million gallon per day (MGD) (454,249 m3/day) and a peak flow of 300 MGD (1,135,624 m3/day). The wastewater treatment process consists of primary sedimentation, activated sludge treatment, secondary settling and chlorination. There are six equally sized aeration tanks designed as plug flow reactors, and each tank has three passes. Each pass is 110 m long, 10.5 m wide and 5.5 m deep, with a volume of 18,896 m3 (5 million gallons). Hydraulic retention time (HRT) in each aeration tank at design flow is 6 FIGURE 1 Schematic of the Pilot-Scale Batch Reactor MLSS from the oxidation ditch influence Pump Aeration Column Sampling Ports

In the paper, we present a fully automated real-time multi-lead ST-segment monitoring algorithm. For a representative normal beat in each ST measurement interval, the ECG leads with low signal quality are excluded and the remaining leads are used in a multi-lead waveform-length transformation to form a length signal for Q-onset (Q) and J-point (J) determination. From Q, the isoelectric point is determined and used with the J to measure the ST-segment at J or J plus an offset for all available leads. A development set of 158 records and a test set of 60 records with cardiologists' beat-by-beat Q and J annotations were used to develop and evaluate the Q and J detection. The ESC ST-T Database and a 60-patient annotated 12-lead PTCA dataset were used to evaluate the algorithm's ST performance. Detailed statistical results are given in the paper. The test results demonstrate that the described ST-segment monitoring algorithm is effective and reliable.

Several arrhythmia performance measures as specified in the current AAMI recommended practice document do not adequately reflect actual clinical experience in real-time patient monitoring. Additional reporting requirements that are more clinical relevant are thus needed: 1) Due to the large number of QRS complexes that need to be analyzed, even an algorithm with high specificity will generate a large number of false positives, which is not directly reflected by the reported false positive rate. A new recommendation is to report the actual number of false positives. 2) Due to the low PVC prevalence in most monitored patients, the high positive predictive values (PPV) reported using databases with high PVC prevalence are not clinically relevant. A proposed recommendation is to report PPVs at much lower PVC rates. 3) Arrhythmia performance measures as specified in the recommended practice do not include performance bounds. A new proposal is to use the bootstrap method with sample replacement to generate the mean values and 95% confident intervals for all the reported arrhythmia performance measures. Conclusions: Additional performance measures are proposed to further improve the clinical relevance of the reported results. These measures should be considered for inclusion as part of the standard reporting.

To conduct the micro-environment study of flocs in an enhanced biological phosphorus removal (EBPR) process, a phosphate ion-selective microelectrode was developed. The cobalt-based microelectrodes have tip diameters of 5-20μm and respond to all the three forms of phosphate ions, namely, H(2)PO(4)(-), HPO(4)(2-), and PO(4)(3-). The calibration curve at pH 7.5 had a slope of 31.5mV per decade change of concentration and a R(2) value of 0.99. Other characteristics of this microelectrode, such as response time, interferences from pH, ion strength, DO and other anions were also evaluated.