A Low Cost Device for Monitoring the Urine Output of Critical Care Patients

In critical care units most of the patients’ physiological parameters are sensed by commercial monitoring devices. These devices can also supervise whether the values of the parameters lie within a pre-established range set by the clinician. The automation of the sensing and supervision tasks has discharged the healthcare staff of a considerable workload and avoids human errors, which are common in repetitive and monotonous tasks. Urine output is very likely the most relevant physiological parameter that has yet to be sensed or supervised automatically. This paper presents a low cost patent-pending device capable of sensing and supervising urine output. The device uses reed switches activated by a magnetic float in order to measure the amount of urine collected in two containers which are arranged in cascade. When either of the containers fills, it is emptied automatically using a siphon mechanism and urine begins to collect again. An electronic unit sends the state of the reed switches via Bluetooth to a PC that calculates the urine output from this information and supervises the achievement of therapeutic goals

An automatic critical care urine meter

Nowadays patients admitted to critical care units have most of their physiological parameters measured automatically by sophisticated commercial monitoring devices. More often than not, these devices supervise whether the values of the parameters they measure lie within a pre-established range, and issue warning of deviations from this range by triggering alarms. The automation of measuring and supervising tasks not only discharges the healthcare staff of a considerable workload but also avoids human errors in these repetitive and monotonous tasks. Arguably, the most relevant physiological parameter that is still measured and supervised manually by critical care unit staff is urine output (UO). In this paper we present a patent-pending device that provides continuous and accurate measurements of patient’s UO. The device uses capacitive sensors to take continuous measurements of the height of the column of liquid accumulated in two chambers that make up a plastic container. The first chamber, where the urine inputs, has a small volume. Once it has been filled it overflows into a second bigger chamber. The first chamber provides accurate UO measures of patients whose UO has to be closely supervised, while the second one avoids the need for frequent interventions by the nursing staff to empty the containe

An automatic critical care urine meter

Nowadays patients admitted to critical care units have most of their physiological parameters measured automatically by sophisticated commercial monitoring devices. More often than not, these devices supervise whether the values of the parameters they measure lie within a pre-established range, and issue warning of deviations from this range by triggering alarms. The automation of measuring and supervising tasks not only discharges the healthcare staff of a considerable workload but also avoids human errors in these repetitive and monotonous tasks. Arguably, the most relevant physiological parameter that is still measured and supervised manually by critical care unit staff is urine output (UO). In this paper we present a patent-pending device that provides continuous and accurate measurements of patient’s UO. The device uses capacitive sensors to take continuous measurements of the height of the column of liquid accumulated in two chambers that make up a plastic container. The first chamber, where the urine inputs, has a small volume. Once it has been filled it overflows into a second bigger chamber. The first chamber provides accurate UO measures of patients whose UO has to be closely supervised, while the second one avoids the need for frequent interventions by the nursing staff to empty the containe

Development of a prototype sensor-integrated urine bag for real-time measuring.

The urine output is a rapid bedside test for kidney function, and reduced output is the common biomarker for an acute kidney injury (AKI). The consensus definition of the symptom is used urine output <0.5 ml/kg/hour for ≥6 hours to define AKI. If a patient is suspected to have this problem, the urine output monitoring needs to be done hourly, and this task consumes a lot of time, and easily affected by human errors. Moreover, available evidences in literatures indicate that more frequent patient monitoring could impact clinical decision making and patient’s outcome. However, it is not possible for nurses to dedicate their precious time manually up to minute manually measurements. To date, there is no reliable device has been used in the clinical routine. From the literatures, only a few automated devices were found with the ability to automatically monitor urine outputs, and could reduce nurse workload and at the same time enhance work performance, but these still have some limitations to measure human urine. In this thesis presents the development and testing for such a device. The research was aimed at building a prototype that could be measured a small amount of urine output, and transit information via wireless to a Cloud database with inexpensive and less complex components. The concept is to provide a real-time measurement and generates data records in Cloud database without requiring any intervention by the nurse. The initial experiment was done measure small amount of liquid using a dropvolume calculation technique. An optical sensor was placed in a medical dropper to record number of counted-drops, the Mean Absolute Percent Error from the test is reported ±3.96% for measuring 35 ml of liquid compared with the ISO standard. The second prototype was developed with multi-sensors, including photo interrupter sensor, infrared proximity sensor, and ultrasonic sensor, to detect the dripping and urine flow. However, the optical sensor still provided the most accuracy of all. The final prototype is based on the combination of optical sensor for detecting drops to calculated urine flow rate and its volume, and weight scales to measurement the weight of collected urine in a commercial urine meter. The prototype also provides an alert in two scenarios; when the urine production is not met the goals, and when the urine container is almost full, the system will automatically generate alarms that warn the nurse. Series of experimentation tests have been conducted under consultant of medical professional to verify the proper operation and accuracy in the measurement. The results are improved from the previous prototype. The mean error found of this version is 1.975% or ≈ ±1.215 ml. when measure 35ml of urine under the average density value of urine (1.020). These tests confirm the potential application of the device by assisting nurse to monitor urine output with the accuracy in the measurement. The use of the Cloud based technology has not been previously reported in the literature as far as can be ascertained. These results illustrated the capability, suitability and limitation of the chosen technology

Evaluation of an automatic urinometer including use of silicone oil to decrease biofilm formation due to proteinuria, hemoglobinuria and bacterial growth

Background: A new capacitance-based automatic urinometer (AU) facilitates continuous urine output (UO) measurement, which may help to predict and diagnose acute kidney injury (AKI). To prevent mismeasurement due to bacterial, albumin or free hemoglobin biofilm, a water-soluble capsule with silicone oil has been integrated in the device. Aims: To assess: the performance of a new capacitance-based AU in adult patients in a cardiothoracic intensive care unit (ICU) and compare it with a manual urinometer (MU) in regard of bias, precision, temporal deviation and to evaluate the staff’s opinion of the AU (Study I); a modified capacitance-based AU in comparison with an MU regarding measuring bias among patients ≤10 kg in a pediatric intensive care unit and to evaluate the staff’s opinion of the AU (Study II); whether a silicone oil-coated polypropylene plastic surface, as used in an AU, may reduce early microbial biofilm formation and to identify the silicone oil target; to compare polypropylene with polystyrene and low with medium viscosity silicone oil regarding the propensity to impede biofilm formation (Study III); if silicone oil added to the measuring chamber of the AU may prevent the rise in capacitance due to albumin or free hemoglobin biofilm, allowing the device to function for longer periods of time (Study IV). Methods: Study I-II were prospective observational cohort studies, whereas Study III-IV were experimental prospective in vitro studies. Study I: 34 postoperative patients had their hourly UO registered with either an AU (n=220) or an MU (n=188), which were validated by cylinder measurements and analyzed using the Bland-Altman method. The temporal deviation of the MU measurements was recorded (n=108) and at the end, the nursing staff (n=28) evaluated the AU. Study II: The hourly diuresis was measured using either an AU (n=127) or an MU (n=83) in 12 children (weight ≤10 kg) and validation was carried out using a measuring cylinder. Thereafter, the nursing staff (n=18) evaluated the AU. Study III: Clear flat-bottomed wells of either polypropylene or polystyrene were pretreated with silicone oil of low or medium viscosity, after which a panel of microbes, including common uropathogenic bacteria and Candida albicans, were added. The plates were left for 3 days and the amount of biofilm formation was assessed using the crystal violet assay. Study IV: A solution of Ringer’s acetate mixed with either albumin or free hemoglobin was run through an AU with either a water-soluble capsule with silicone oil (n=20) or not (n=20) and the derived 400-500 capacitance measurements, respectively, were retrieved from the AU device and analyzed. Results: Study I: The AU had a smaller mean bias (+1.9 mL) than the MU (+5.3 mL) (p<0.0001). Defined by their limits of agreements (±15.2 mL AU vs. ±16.6 mL MU, p=0.11), the measurement precision of the two urinometers were similar. The AU had inherently no temporal deviation, whereas the mean temporal deviation of the MU was ±7.4 minutes (±12.4%) (p<0.0001). The nursing staff rated the AU significantly higher than the MU in terms of user-friendliness, measuring reliability, efficacy and safety. Study II: The AU and the MU had a mean bias of −1.1 mL (CI, -0.6 to -1.5) and -0.6 mL (CI, ±0.0 to -1.2) respectively (p=0.21). The participating staff considered the AU significantly easier to learn, use and handle compared with the MU. Study III: Polypropylene plastic exhibited less biofilm growth than polystyrene. Silicone oil, irrespective of viscosity, significantly decreased biofilm formation by common uropathogenic bacteria, including ESBLproducing and multi-drug resistant strains, as well as C. albicans. E. coli curli fimbriae were established as the main focus of silicone oil. Study IV: The mean increase in capacitance with albumin 3 g/L group was 257±96 without and 105±32 with silicone oil, respectively, during 24 hours. After ten hours of registration, differences between the two albumin groups reached statistical significance. For the free hemoglobin groups (0.01 g/L), the mean increase in capacitance was 190±174 with silicone oil and 324±78 without. A significant difference between the free hemoglobin groups was seen after 20 hours and onwards. Conclusions: For adult postoperative patients, the AU was non-inferior to the MU with regard to measuring precision and significantly better than the MU in terms of bias and temporal deviation (Study I); for children weighing ≤10 kg, the urinometers were comparable in performance (Study II); staff consistently appraised the AU significantly higher than the MU in terms of user-friendliness, reliability, safety and efficacy (Study I and II). Both low and medium viscosity silicone oil coating of a polypropylene surface decreased biofilm formation from common uropathogenic bacteria including Candida albicans and the biofilm-promoting factor curli fimbriae was identified as a plausible target (Study III); coating of the capacitance measurement membrane of the AU by albumin or free hemoglobin significantly disturbed the capacitance measurement capability of the AU, and this could be prevented by incorporating silicone oil in the device (Study IV)

Aiming for Zero: Creating a Culture of Safety and Improving CAUTI Outcomes in the Microsystem

Abstract Problem: Catheter-associated urinary tract infection (CAUTI) remains the leading cause of hospital-acquired infection (HAI) despite being preventable. CAUTI increases the length of stay, morbidity, mortality, readmissions, and costs. There is also increasing antimicrobial resistance in pathogens causing CAUTI. Thus, reducing HAIs such as CAUTI should be a priority for every institution. Context: The microsystem for this CAUTI quality improvement project is a 24-bed adult medical-telemetry unit in an acute care teaching hospital with excessive CAUTI. This project aims to improve the unit’s CAUTI standardized infection ratio (SIR) from a baseline of 2.54 to 1.75 by October 2020. A SIR of 1.75 for the microsystem translates to zero CAUTI events per month during the project timeline. Interventions: The quality improvement project has three themes of intervention. The first theme of interventions is the provision of CAUTI prevention education to frontline staff. The second theme of interventions is to reduce infection by the daily review of patients with an indwelling urethral catheter (IUC) and a requirement to notify the physician when the IUC is no longer indicated, or an alternative can be used. A visual tracking board for the prompt removal of IUC and a smart phrase in the electronic medical record (EMR) was created to standardized communication between nurses and physicians regarding urinary catheter necessity. The third theme of intervention is to reduce misdiagnosis due to colonization by using the organization\u27s regional urine culture algorithm for sending urine cultures from patients with an IUC. Measures: A family of measures for the project was developed. The outcome measures for the project are the CAUTI Standardized Infection Ratio (SIR) and number of CAUTI events per month during the project timeline. Results: By the end of the project, the microsystem achieved zero monthly CAUTI events and a CAUTI SIR score of 1.73. Conclusions: Implementing the interventions led to the achievement of zero CAUTI events, thus preventing harm to patients. The interventions are also incorporated in the daily processes of the microsystem and, therefore, sustainable. Keywords: catheter associated urinary tract infection, daily review of urinary catheters, visual tracking board, urine culture algorith

An investigation into the effects of commencing haemodialysis in the critically ill

&lt;b&gt;Introduction:&lt;/b&gt; We have aimed to describe haemodynamic changes when haemodialysis is instituted in the critically ill. 3 hypotheses are tested: 1)The initial session is associated with cardiovascular instability, 2)The initial session is associated with more cardiovascular instability compared to subsequent sessions, and 3)Looking at unstable sessions alone, there will be a greater proportion of potentially harmful changes in the initial sessions compared to subsequent ones. &lt;b&gt;Methods:&lt;/b&gt; Data was collected for 209 patients, identifying 1605 dialysis sessions. Analysis was performed on hourly records, classifying sessions as stable/unstable by a cutoff of &gt;+/-20% change in baseline physiology (HR/MAP). Data from 3 hours prior, and 4 hours after dialysis was included, and average and minimum values derived. 3 time comparisons were made (pre-HD:during, during HD:post, pre-HD:post). Initial sessions were analysed separately from subsequent sessions to derive 2 groups. If a session was identified as being unstable, then the nature of instability was examined by recording whether changes crossed defined physiological ranges. The changes seen in unstable sessions could be described as to their effects: being harmful/potentially harmful, or beneficial/potentially beneficial. &lt;b&gt;Results:&lt;/b&gt; Discarding incomplete data, 181 initial and 1382 subsequent sessions were analysed. A session was deemed to be stable if there was no significant change (&gt;+/-20%) in the time-averaged or minimum MAP/HR across time comparisons. By this definition 85/181 initial sessions were unstable (47%, 95% CI SEM 39.8-54.2). Therefore Hypothesis 1 is accepted. This compares to 44% of subsequent sessions (95% CI 41.1-46.3). Comparing these proportions and their respective CI gives a 95% CI for the standard error of the difference of -4% to 10%. Therefore Hypothesis 2 is rejected. In initial sessions there were 92/1020 harmful changes. This gives a proportion of 9.0% (95% CI SEM 7.4-10.9). In the subsequent sessions there were 712/7248 harmful changes. This gives a proportion of 9.8% (95% CI SEM 9.1-10.5). Comparing the two unpaired proportions gives a difference of -0.08% with a 95% CI of the SE of the difference of -2.5 to +1.2. Hypothesis 3 is rejected. Fisher’s exact test gives a result of p=0.68, reinforcing the lack of significant variance. &lt;b&gt;Conclusions:&lt;/b&gt; Our results reject the claims that using haemodialysis is an inherently unstable choice of therapy. Although proportionally more of the initial sessions are classed as unstable, the majority of MAP and HR changes are beneficial in nature

Low-power Wearable Healthcare Sensors

Advances in technology have produced a range of on-body sensors and smartwatches that can be used to monitor a wearer’s health with the objective to keep the user healthy. However, the real potential of such devices not only lies in monitoring but also in interactive communication with expert-system-based cloud services to offer personalized and real-time healthcare advice that will enable the user to manage their health and, over time, to reduce expensive hospital admissions. To meet this goal, the research challenges for the next generation of wearable healthcare devices include the need to offer a wide range of sensing, computing, communication, and human–computer interaction methods, all within a tiny device with limited resources and electrical power. This Special Issue presents a collection of six papers on a wide range of research developments that highlight the specific challenges in creating the next generation of low-power wearable healthcare sensors