Currently, the 5-year survival rate remains poor for patients with metastatic colorectal cancer (mCRC), and the purpose of therapy is to prolong survival while maintaining the quality of life. Trifluridine/tipiracil, an oral drug combining trifluorothymidine and a thymidine phosphorylase inhibitor, is indicated as salvage therapy for mCRC patients who have progressed after all available regimens. Combination of local treatments with systemic therapy such as trifluridine/tipiracil represents an apt management strategy for mCRC patients.A 72-year-old man diagnosed with stage IV rectal adenocarcinoma (KRAS mutation) with peritoneal carcinomatosis and liver metastases developed resistance to 2 lines of treatment  within 5 months.Refractory stage IV rectal adenocarcinoma.Systemic treatment of trifluridine/tipiracil has been given for approximately 15 months in addition to radiotherapy, Yttrium-90 radioembolization, and trans-arterial chemoembolization for peritoneal and liver metastases.After 15 months, the patient was still taking trifluridine/tipiracil for disease control with a good quality of life.Trifluridine/tipiracil plus other appropriate local therapy may significantly prolong patients survival with a satisfactory quality of life for patients with refractory mCRC. The favorable safety profile of trifluridine/tipiracil renders it a suitable option to be combined with other local therapies for metastatic lesions. For patients with stage IV CRC who develop resistance or are intolerant to first- and second-line therapies, only limited treatment options are currently available.Colorectal cancer (CRC) remains the third most common cancer and is one of the leading causes of cancer-related deaths worldwide.,6 Although regorafenib and trifluridine/tipiracil are placed on the same position for the treatment algorithm, these 2 drugs differ in their mechanisms of action. While regorafenib is a multi-targeted tyrosine kinase inhibitor that blocks multiple kinases involved in tumor angiogenesis and oncogenesis, trifluridine/tipiracil is an oral combination of trifluridine, a nucleoside metabolic inhibitor, and tipiracil, a thymidine phosphorylase inhibitor, in a molar ratio of 1:0.5. Trifluridine can incorporate into DNA and interferes with DNA synthesis, resulting in inhibition of cell proliferation. In the presence of tipiracil, the anti-tumor activity of trifluridine is augmented through inhibiting its metabolism by thymidine phosphorylase.,9Both regorafenib  and trifluridine/tipiracil  were approved by the United States Food and Drug Administration (FDA) and Taiwan Food and Drug Administration (TFDA) to treat patients with metastatic CRC (mCRC) who have been previously treated with fluoropyrimidine-, oxaliplatin- and irinotecan-based chemotherapy, as well as a targeted therapy with anti-vascular endothelial growth factor (VEGF) monoclonal antibodies (bevacizumab/ramucirumab), and if RAS wild-type, anti-epidermal growth factor receptor (EGFR) monoclonal antibodies (cetuximab/panitumumab).,10–12 Although studies have shown that regorafenib and trifluridine/tipiracil have comparable efficacy, regorafenib was associated with more quality-of-life-impairing toxicities as compared with trifluridine/tipiracil.,14 For this reason, the favorable safety profile of trifluridine/tipiracil renders it a relatively more suitable drug to be combined with other treatments in a third-line setting.The efficacy of regorafenib and trifluridine/tipiracil have been demonstrated in 4 randomized phase III trials.Herein, we reported a case of metastatic rectal adenocarcinoma in whom the resistance to the first- and second-line treatments developed quickly within 5 months, which implied that the disease was aggressive and rapidly progressive. It is encouraging that he has survived for almost 2 years with a good quality of life after diagnosed with stage IV mCRC and received the initial 2 lines of standard treatment with bevacizumab/irinotecan/S-1 and bevacizumab/oxaliplaitn/infusional 5FU/leucovorin. With this brief case report, we discussed the effectiveness of trifluridine/tipiracil in disease control and its strength in combination with local therapy for refractory mCRC.2A 72-year-old male with Eastern Cooperative Oncology Group (ECOG) performance status of 1 was originally diagnosed with stage IIIB (cT3N2M0) rectal adenocarcinoma in 2012. Following treatments of concurrent chemoradiotherapy (CCRT) and abdominoperineal resection (APR), the postoperative pathologic finding revealed a stage of ypT2N0M0, and the cancer possessed a KRAS G13D mutation and a wild-type BRAF. There was no evidence of disease recurrence during the subsequent follow-up period.Nevertheless, in December 2016, the disease had advanced to stage IV with liver metastases and peritoneal carcinomatosis, as confirmed by computed tomography (CT) images  to the left peritoneal carcinomatosis in May 2017, and the symptom of tarry stool was resolved afterward. Subsequently, Yttrium-90 (Y90) radioembolization (2.1GBq) treatment for liver metastases was conducted in early August 2017 due to limited options left for subsequent treatments. After the procedure, most liver metastases in both lobes improved  only reimburses the treatment of regorafenib for patients with mCRC after they fail standard intravenous chemotherapy with certain targeted therapies (bevacizumab or cetuxitmab if RAS wild-type). However, with concerns of slightly increased bleeding risk that might be caused by regorafenib when the patient had GI bleeding history, trifluridine/tipiracil was given instead of regorafenib at a reduced dosage of 40 mg BID in September 2017. Four months after taking trifluridine/tipiracil, follow-up CT scan showed liver metastases became smaller, which reflected the therapeutic efficacy of the treatments  were only several months. With the exception of some patients with confined and completely resectable tumors, the purpose of therapy for stage IV CRC is generally to prolong life expectancy while maintaining a satisfactory quality of life.Although the age-standardized mortality rate of CRC has been declining in the past 2 decades, the 5-year survival rate in patients diagnosed with advanced CRC remains poor.,18 Even in the subgroup analysis, mCRC patients received FOLFIRI plus bevacizumab as first-line regimen showed a median progression-free survival of 8.9 months (95% CI 7.3–11.4) or longer .,20 Thus, failing 2 frontline therapies within 5 months suggests the patient had a rapidly progressive disease. Nevertheless, the combined treatment of trifluridine/tipiracil and local therapies showed encouraging therapeutic effects. Until submission of the present report, the patient has survived for over 2 years after the diagnosis of mCRC. In contrast to the median progression-free survival of 2.0 months  in the trifluridine/tipiracil group reported in the pivotal study, the present case had a stable disease for 7 months after the initiation of trifluridine/tipiracil administration, which may be attributable to the local therapies performed for the metastases during the trifluridine/tipiracil treatment period.In this report, we described a patient who quickly developed resistance to 2 lines of major treatments. According to the results of recent randomized clinical trials, a median progression-free survival of approximately ten months in patients treated with bevacizumab-combined first-line chemotherapy was reported.Optimizing the cost-effectiveness is an indispensable part of disease management. The benefits of each treatment option have to be weighed against all possible risks. Following the local radiotherapy for peritoneal carcinomatosis, procedures such as TACE, radiofrequency ablation (RFA), and Y-90 radioembolization are among the choices for treating liver metastases. To maximize cost-benefit ratio based on the patients insurance coverage and to minimize discomfort/suffering of the procedures involved, the patient agreed to receive Y-90 radioembolization under the recommendation of our multidisciplinary team.P = .0052), respectively, for regorafenib and 7.1 vs 5.3 months , respectively, for trifluridine/tipiracil.,10 Although the 2 drugs provide survival benefits of a similar magnitude, the adverse reaction profiles are in favor of trifluridine/tipiracil.,14,21 After a thorough explanation of possible and anticipated risks, the patient chose to receive trifluridine/tipiracil as his third-line treatment. During the 15-month treatment of trifluridine/tipiracil, the dosages of trifluridine/tipiracil were modified according to the patients physiological condition and were greatly affected by the patients private insurance policy. As mentioned previously, the Taiwan NHI only reimburses regorafenib, but not trifluridine/tipiracil, in certain conditions. The average cost of trifluridine/tipiracil is approximately $6,450 per month. In this regard, despite that the recommended dose for this patient was approximately 55 mg BID based on his body surface area, the starting dosage was only 40 mg BID due to aforementioned reasons. Without considering the frequency, the patient received an overall of 80.52% of the recommended dose. When the treatment duration and frequency of administration were considered, he only received 51.24% of the recommended dose. It suggests that, for patients who possess polychemotherapy refractory mCRC, and in the presence of KRAS mutation, an appropriate combination of local and systemic treatments may provide survival benefit with a good quality of life, despite the dosage of trifluridine/tipiracil was considerably less than its recommended dose. At the last visit, the patient continued trifluridine/tipiracil treatment at 55 mg BID, and the disease was considered stable.For the patient population who have progressed after all available chemotherapeutic regimens, only regorafenib and trifluridine/tipiracil are left as treatment options currently. Based on the results of phase III studies , the median overall survival in the treatment and placebo groups were 6.4 vs 5.0 months  at the first-cycle was significantly associated with longer median overall survival. Moreover, Hamauchi et al also suggested that trifluridine/tipiracil-induced neutropenia was associated with better disease control rate, and could be a surrogate marker for adjusting adequate trifluridine/tipiracil dose.The patients body weight declined substantially during the first 2 lines of chemotherapy, after which the body weight increased and maintained stable during the trifluridine/tipiracil treatment period, despite that the patient experienced trifluridine/tipiracil-related adverse events (AEs) including nausea, decreased appetite, and neutropenia (these AEs were among the most common reported adverse reactions to this medication).4,14 Moreover, the patients prescribing trifluridine/tipiracil were more likely to adhere to their treatment as compared with those taking regorafenib. Collectively, the case reported here suggests that trifluridine/tipiracil plus local treatments might be a feasible therapeutic combination for patients who have progressed after 2 lines of major therapy.The National Comprehensive Cancer Network (NCCN) guideline version 3.2018 recommends trifluridine/tipiracil, regorafenib, or best supportive care for mCRC patients refractory to first- and second-line treatments. While both trifluridine/tipiracil and regorafenib are considered salvage regimens, the side effect profile of trifluridine/tipiracil renders it a more favorable option to be applied in combination with other local therapies in the third-line setting.5The case report has been waived for the ethical approval by the standard of the Research Ethics Committee of National Taiwan University Hospital. Written informed consent was obtained from the patient before the publication of this case report and accompanying images.Conceptualization: Yu-Lin Lin.Formal analysis: Kao-Lang Liu, Been-Ren Lin.Resources: Kao-Lang Liu, Been-Ren Lin.Supervision: Been-Ren Lin.Visualization: Kao-Lang Liu, Been-Ren Lin.Writing – original draft: Yu-Lin Lin.Writing – review & editing: Yu-Lin Lin, Kao-Lang Liu, Been-Ren Lin.


The measurement of gait characteristics during a self-administered 2-minute walk test (2MWT), in persons with multiple sclerosis (PwMS), using a single body-worn device, has the potential to provide high-density longitudinal information on disease progression, beyond what is currently measured in the clinician-administered 2MWT. The purpose of this study is to determine the test-retest reliability, standard error of measurement (SEM) and minimum detectable change (MDC) of features calculated on gait characteristics, harvested during a self-administered 2MWT in a home environment, in 51 PwMS and 11 healthy control (HC) subjects over 24 weeks, using a single waist-worn inertial sensor-based smartphone. Excellent, or good to excellent test-retest reliability were observed in 58 of the 92 temporal, spatial and spatiotemporal gait features in PwMS. However, these were less reliable for HCs. Low SEM% and MDC% values were observed for most of the distribution measures for all gait characteristics for PwMS and HCs. This study demonstrates the inter-session test-retest reliability and provides an indication of clinically important change estimates, for interpreting the outcomes of gait characteristics measured using a body-worn smartphone, during a self-administered 2MWT. This system thus provides a reliable measure of gait characteristics in PwMS, supporting its application for the longitudinal assessment of gait deficits in this population. Multiple sclerosis (MS) is a chronic autoimmune inflammatory disease of the central nervous system , which cMS diagnosis is based on established clinical and magnetic resonance imaging (MRI) criteria  yet to dThe 2-minute walk test is a validated alternative to the 6-minute walk test . The disAdvances in inertial-sensor technology combined with the widespread adoption of commercially available smartphones, has made the ubiquitous monitoring of human body movement, using body-worn inertial-sensors, more possible than ever before. To date, to the best of our knowledge, no study has demonstrated that temporal, spatial and spatiotemporal gait characteristics can be successfully measured using a single sensor at the waist in an MS cohort, during an unsupervised, self-administered test. We thus hypothesize that instrumentation of the 2MWT performed in the person’s home environment, with a body-worn inertial-sensor based smartphone, can potentially reveal gait characteristics related to MS disease state, without a supervising clinician or a laboratory. Identifying when a patient’s behavior has changed due to an intervention, through the use of body-worn sensors, has the potential to expand the armamentarium beyond the traditional clinical endpoints. Interpreting this change requires two benchmarks: the minimum detectable change (MDC), and the minimal important difference (MID). The MDC is the minimum magnitude of change required to be 95% confident that the observed change between measurements reflects true change and not measurement error . The MIDMDC is thus a prerequisite that allows clinicians and researchers to explain change scores in successive measurements reasonably . The objExtensive details on the trial protocol, inclusion/exclusion criteria and ethical approval are available in the study by Midaglia et al.  with theThis cross-sectional study examined the longitudinal inter-session test-retest reliability and MDC of gait characteristics harvested during the self-administered 2MWT in PwMS and HCs. In total, 76 PwMS and 25 HCs were enrolled in the study. PwMS were included if they had a diagnosis of MS and an EDSS score of 0.0 to 5.5 (inclusive). The EDSS  is a 10-At enrolment/baseline, PwMS and HCs were provided with a preconfigured smartphone and were asked to perform the 2MWT daily over a 24-week period. For each test, participants are first presented with safety questions, given instructions how to perform the test and how to attach the smartphone, Participants were provided with a Samsung Galaxy S7 smartphone by the study investigator. The Samsung Galaxy S7 contains the LSM6DS3 from STMicroelectronics. The LSM6DS3 is a micro-electro-mechanical systems inertial monitoring unit (IMU) that contains factory calibrated tri-axial accelerometer and gyroscope sensors. The Samsung Galaxy S7 samples used a variable sampling rate of approximately 100 Hz. The smartphone’s sensor data were encrypted before wireless transmission to a secure database for subsequent data analysis before gait features were exported, Data analysis was performed in Python 3.6. The data harvested during each 2MWT were first resampled using a Blackman window to create a regular sampling rate, then filtered using a zero-phase 2nd order Butterworth filter  at a cutThe location of the smartphone was inferred based on the smartphone orientation during each 2MWT. If a landscape orientation was detected, a waist worn location was assumed.Walking bouts were identified through thresholding of the standard-deviation of the vector-magnitude of the tri-axial accelerometer signals, using a non-overlapping rolling window of 1-second. Walking was detected if the signal exceeded a threshold of 1.0.The following gait characteristics were measured for each 2MWT recorded only at the waist (trouser pocket location excluded); step/stride length , step/stThe calculation of these gait characteristics is extensively described in , along wDuring the gait cycle, the initial contact  and final contact  events, were identified from the Gaussian continuous wavelet transform of the vertical accelerometer signal, o excluded. If multiple gait bouts were detected, gait characteristics computed for each walking bout were compiled for each 2MWT. Inertial sensor gait data were segmented into straight line walking bouts, of minimum 10 s, with turns greater than 45The following features were computed for each gait characteristic during each 2MWT. To calculate variability, the variance for all steps/strides (left and right separately) was calculated and combined . Left anht steps . The folht steps . The median of each gait feature, calculated during individual 2MWTs, was harvested during a 14-day period of tests, with a minimum of three tests required. This constituted one session and was compiled for each participant. A 14-day period was chosen to reduce day-to-day/weekend-weekday fluctuations and variations in the daily test schedule/location which are all irrelevant for longer MS disease progression.Test-retest reliability was assessed using the second  and subsequent complete 14-day session per subject. This was performed using a two-way mixed effect model with absolute agreement for a single rater/measurement intra-class correlation coefficient, ICC  . ReliabiThe standard error of measurement (SEM) reflects the precision of the measurement instrument . The SEMe change . The MDCe change  was calcThe SEM and MDC can be expressed as percentages that are independent of the units of measurement. This allows comparison on the amount of random error between measurement features, as Equation (4):rvations . SEM% varvations  as no clA total of 4854 tests were recorded from the waist  from 101 participants. Baseline demographics are described in p = 0.569) between the quantity of 2MWTs performed during each 14-day session by PwMS  and HCs  and no significant difference (p = 0.235) between the total walking bout length during each 2MWT performed by PwMS  and HCs . Algorithm execution computation time  were included to assess test-retest reliability, presented in For PwMS, of the 48 temporal gait features, 2 were excellent (ICC > 0.9), 31 were good to excellent (ICC > 0.75), 3 were moderate to excellent and 11 were moderate to good, For HCs, of the 48 temporal gait features, 1 was excellent (ICC > 0.9), 16 were good to excellent (ICC > 0.75), 21 were moderate to excellent, 3 were poor to good and 17 were poor to excellent, For PwMS, For HCs, This study evaluated the between-session test-retest reliability, SEM and MDC of a comprehensive set of gait features harvested during a self-administered 2-minute walk test, using a single smartphone attached to the front of the waist in PwMS and HCs. ICC values for test-retest reliability were similar to those reported in other assessments of gait in PwMS using body-worn IMUs ,15 and fThe SEM was used to assess the measurement precision of the gait features and the MDC to detect the minimal threshold of change above the 95% confidence interval (CI) for each feature. These measures represent the limit for the smallest change that indicates a real or detectable improvement rather than measurement error for people with MS, thus, making it particularly useful for gauging the effects of an intervention or rehabilitation .Small or low SEM values for gait characteristics indicate that measurements are stable and reproducible over time, thus indicating the precision of the measurement system . AngelinLearmonth et al.  demonstrDecavel et al.  reportedThe obtained SEM and MDC values can be considered as valid measurement threshold references for their respective gait characteristics when measured using a single body-worn smartphone, during an unsupervised self-administered 2MWT, performed in the person’s home environment. Future further studies in this domain should examine the, clinically relevant, MID for outcomes of these gait characteristics, as they are currently lacking. Knowledge of these MID values would assist in the clinical interpretation of the indices for the measurement errors found in this study. This will help clinicians and researchers reasonably and confidently determine real change, between repeated session measurements, for PwMS evaluated using a body-worn smartphone during a self-administered 2MWT.Future work will determine the accuracy of this algorithm using ground truth data harvested from an MS cohort. Future work will also examine the criterion validity of these gait characteristics, measured in an MS cohort, with reported outcomes from clinical observational rating scales  and timed functional assessments . In addition, variations in inertial sensor data measured using different smartphones do exist , future These findings indicate that gait analysis performed on inertial sensor data harvested during a self-administered 2MWT using a single smartphone, attached to the front of the waist, provides both accurate and reliable measurements of selected spatial, temporal and spatiotemporal characteristics of gait in PwMS and HCs. The ICC, SEM and MDC values recorded for this measurement system are also comparable to existing clinically accepted outcome measures for gait evaluation. These findings have meaningful implications for clinicians and researchers who use body-worn IMU-based measurement systems to evaluate gait deficits in PwMS.


They estimated that, compared with prescribing full-dose abiraterone, routinely prescribing low-dose abiraterone in India would save 182 million USD annually. On an individual patient level, the mean savings would be approximately 2.5 times the per capita income of Indians. We believe that the practice of routinely prescribing low-dose abiraterone should not be restricted to low- and middle-income countries but should be considered across the world, including in the United States.2Patel et al3 The number of unique Medicare beneficiaries who were prescribed abiraterone increased from 14,188 in 2013 to 19,090 in 2017, as did the cost per 30-day refills, which increased from $6,383 in 2013 to $9,224 in 2017. The aggregate cost paid by Medicare in 2017 was approximately $935 million. Standardizing prescribing to low-dose abiraterone could potentially result in an annual approximate savings of $700 million. Notably, these data do not include commercial payers.To estimate the possible savings associated with prescribing low-dose abiraterone in a high-income country like the United States, we analyzed Medicare part D drug spending and utilization data for abiraterone from 2013 to 2017. These data come from a deidentified publicly available database, which includes approximately 70% of Medicare beneficiaries enrolled in part D.4 This proof-of-concept trial was inspired by preclinical studies on the pharmacokinetics of abiraterone depicting a 5- to 7-fold increase in serum levels of abiraterone with a low-fat diet and an approximately 10- to 17-fold increase when coadministered with a high-fat diet.6 The primary endpoint of this phase II trial was biochemical—log change in prostate-specific antigen at 12 weeks—not clinical, although the median progression-free survival, decreases in androgen levels, and adverse events of any grade were similar across arms. Importantly, both the prostate-specific antigen response and the time to progression were comparable to previous studies.7 Other validated mCRPC endpoints  have not been studied yet.8 This simple strategy is now increasingly relevant, as abiraterone was recently shown to improve survival in the metastatic castrate-sensitive prostate cancer (mCSPC) setting9 as well and received US Food and Drug Administration approval for this indication in February 2018.10 With expanding use in mCSPC,9 a major opportunity exists to lower drug costs by administering the lower dose with food. The National Comprehensive Cancer Network guideline notes the cost savings associated with low-dose abiraterone, which might reduce financial toxicity and improve compliance. The drug is priced at approximately $10,000 per month in the United States for standard treatment but is manufactured and sold in India for approximately one fortieth of this US price (approximately $240 per month).1Low-dose abiraterone is listed as an option in the National Comprehensive Cancer Network guideline for treating metastatic castration-resistant prostate cancer (mCRPC) on the basis of a phase II trial that found that low-dose abiraterone (250 mg/day) given with a low-fat breakfast was noninferior to standard-dose abiraterone  while fasting.In summary, low-dose abiraterone represents a strategy that could be associated with notable cost savings, even in high-income countries, such as the United States. High-income countries must learn from initiatives in low- and middle-income countries, just like the reverse; that is the ultimate goal of global collaborations.


Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation of CT scans for differentiation of COVID-19 findings from other clinical entities. Here we show that a series of deep learning algorithms, trained in a diverse multinational cohort of 1280 patients to localize parietal pleura/lung parenchyma followed by classification of COVID-19 pneumonia, can achieve up to 90.8% accuracy, with 84% sensitivity and 93% specificity, as evaluated in an independent test set  of 1337 patients. Normal controls included chest CTs from oncology, emergency, and pneumonia-related indications. The false positive rate in 140 patients with laboratory confirmed other (non COVID-19) pneumonias was 10%. AI-based algorithms can readily identify CT scans with COVID-19 associated pneumonia, as well as distinguish non-COVID related pneumonias with high specificity in diverse patient populations. Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lung disease. Here, the authors present a multinational study on the application of deep learning algorithms for COVID-19 diagnosis against multiple lung conditions as controls. The exact mortality, prevalence, and transmission dynamics remain somewhat ill-defined in part due to the unique challenges presented by SARS-CoV-2 infection, such as peak infectiousness at or just preceding symptom onset and a poorly understood multi-organ pathophysiology with dominant features and lethality in the lungs4. The rapid rate of spread has strained healthcare systems worldwide due to shortages in key protective equipment and qualified providers5, partially driven by variable access to point-of-care testing methodologies, including reverse transcription polymerase chain reaction (RT-PCR). As rapid RT-PCR testing becomes more available, challenges remain, including high false negative rates, delays in processing, variabilities in test techniques, and sensitivity sometimes reported as low as 60–70%7.Coronavirus Disease 2019 (COVID-19) has become a global pandemic with an exponential growth rate and an incompletely understood transmission process. The virus is harbored most commonly with little or no symptoms, but can also lead to a rapidly progressive and often fatal pneumonia in 2–8% of those infected9. While challenges continue with rapid diagnosis of COVID-19, frontline radiologists report a pattern of infection that is somewhat characteristic with typical features including ground glass opacities in the lung periphery, rounded opacities, enlarged intra-infiltrate vessels, and later more consolidations that are a sign of progressing critical illness. While CT and RT-PCR are most often concordant9, CT can also detect early COVID-19 in patients with a negative RT-PCR test9, in patients without symptoms, or before symptoms develop or after symptoms resolve11. CT evaluation has been an integral part of the initial evaluation of patients with suspected or confirmed COVID-19 in multiple centers in Wuhan China and northern Italy15. A recent international expert consensus report supports the use of chest CT for COVID-19 patients with worsening respiratory status or in resource constrained environments for medical triage of patients who present with moderate–severe clinical features and a high pretest probability of COVID-1916. However, these guidelines also recommend against using chest CT in screening or diagnostic settings in part due to similar radiographic presentation with other influenza-associated pneumonias. Techniques for distinguishing between these entities may strengthen support toward use of CT in diagnostic settings.Computed tomography (CT) is a test that provides a window into pathophysiology that could shed light on several stages of disease detection and evolution18. AI models are often severely limited in utility due to homogeneity of data sources, which in turn limits applicability to other populations, demographics, or geographies. This study aims to develop and evaluate an AI algorithm for the detection of COVID-19 on chest CT using data from a globally diverse, multi-institution dataset. Here we show robust models can be achieve up to 90% accuracy in independent test populations, maintaining high specificity in non-COVID-19 related pneumonias, and demonstrating sufficient generalizability to unseen patient populations/centers.Due to the rapid increase in number of new and suspected COVID-19 cases, there may be a role for artificial intelligence (AI) approaches for the detection or characterization of COVID-19 on imaging. CT provides a clear and expeditious window into this process, and deep learning of large multinational CT data could provide automated and reproducible biomarkers for classification and quantification of COVID-19 disease. Prior single center studies have demonstrated the feasibility of AI for the detection of COVID-19 infection, or even differentiation from community acquired pneumoniaIn total, 2724 scans from 2617 patients were used in this study, including 1029 scans of 922 patients with RT-CPR confirmed COVID-19 and lung lesions related to COVID-19 pneumonia. This includes one scan from one patient who was confirmed to have COVID-19 from the SUNY cohort. Of these, 1387 scans from 1280 patients were utilized for algorithm development, and 1337 patients were utilized for algorithm testing and evaluation. The split of data in training, validation, and test datasets can be seen in Table Model classification accuracy was evaluated individually by disease cohort , where patients underwent CT the same day as initial positive PCR (China), but also included advanced disease, such as inpatient hospitalization settings at physician’s discretion . Furthermore, the inclusion of patients undergoing routine clinical CT scans for a variety of indications including acute care, trauma, oncology, and various inpatient settings was designed to expose the algorithm to diverse clinical presentations. Here we achieved 0.949 AUC in a testing population of 1337 patients resulting in 90.8% accuracy for classification of COVID-19 on chest CT.Preliminary studies indicate chest CT has a high sensitivity for detection of COVID-19 lung pathology and several groups have demonstrated the potential for AI-based diagnosis, reporting as high as 95% detection accuracies16. In Hubei Province, China, CT scans were used extensively and at presentation, in an effort to quickly diagnose, isolate, and contain the spread of the outbreak. Multiple studies have reported a high degree of sensitivity for chest CT in the diagnosis of COVID-19 pneumonia14. However, multiple radiology and thoracic professional associations in the US and the UK have recommended against using chest CT for screening or for the routine diagnosis of COVID-19, in part due to the potential for overlap with other high prevalence entities such as influenza pneumonia. In this study, the algorithm has a high specificity in such a setting of 93%. Sub-analysis within varying clinical indications for CT scanning demonstrated lower false positive rates in populations undergoing imaging for oncologic diagnosis and follow-up compared with acute and trauma care. Notably, this performance was consistent in the subgroup of RT-PCR confirmed influenza pneumonia, which included cases with H1N1. Thus, given the challenges in confidently distinguishing between COVID-19 associated pneumonia and other types of pneumonia, there may be a role for AI in CT-based diagnosis, characterization, or quantification of response. Performance was observed to be highest in patient cohorts from centers utilizing CT earlier in diagnostic pathway, while settings utilizing CT in cases with advanced pneumonia demonstrated poorer detection sensitivity. Further work regarding the diagnostic utility of this algorithm in the setting of early vs. advanced COVID-19 related pneumonia is warranted.The use of CT scans for the purpose of diagnosing COVID-19 pneumonia has been somewhat controversialWe also sought to maximize the generalizability from a technical standpoint. To reduce the effect of body habitus and extra-thoracic pathology, a lung segmentation algorithm was used to localize to chest cavity and ensure the classification algorithm was focused on the lungs and excluded the presence of factors outside the patient (such as isolation bags around the patients in Hubei). All classification models were trained utilizing an aggressive augmentation scheme to minimize over-fitting. While slice-based or hybrid 3D models demonstrated high validation accuracies, the simpler model utilizing single 3D volumes produced the most generalizable framework. Experiments testing the algorithm generalizability demonstrated 79.8% sensitivity could be achieved when the cohort of patients from Japan were excluded from training and only used in testing to evaluate model performance in an unseen domain. While the model performance exhibited a moderate decrease in sensitivity, it appeared to generalize well given the variabilities in CT acquisition and in clinical considerations across multi-nation cohorts. Prospective validation is certainly needed prior to making definitive statements on the performance of this AI system and potential improvements on slice-based and hybrid models to yield more desirable results.21. Given that viral infectiousness can often predate symptoms, CT plus RT-PCR is likely a more accurate and sensitive strategy than either alone, although this is somewhat speculative11. Delayed RT-PCR or limitations in access or availability could also make CT testing more attractive for specific subsets of patients or in a resource constrained environment, such as persons under investigation for exposure history or contact tracing, triage for resource utilization, prognosis, or to assist with isolation compliance, although this is speculative. Finally, our AI algorithm aims to classify chest CT scans as positive vs. negative for COVID-19 pneumonia and in positively classified CT scans, it delivers a saliency map for visualization of AI-associated predictions. While useful for general visualization of AI output, this does not delineate COVID-19 burden, which may be more accurately depicted by segmentation algorithms.There are several limitations to this study. Model training was limited to patients with positive RT-PCR testing and COVID-19 related pneumonia on chest CT in order to differentiate between COVID-19 related disease and other pathologies. However, CT is often negative despite positive RT-PCR test22. The prevalence in our constructed testing set was 24%, which may be representative of some outbreak dynamics at the time of writing. We were limited in truly evaluating the generalizability of this model to an independent population, as our positive and negative cases were derived from separate populations. It is also important to note the prevalence and testing conditions of COVID-19 positive patients varied by cohort. In Japan, the patients were a mixture of incidental Diamond Princess cruise ship exposures or community acquired COVID-19, with a diverse multinational population, but all were all PCR positive with CT lesions. In Italy, CT scans practice varied from acute care screening to mainly inpatients, or at the discretion of the treating physician, commonly later in the disease process. In Hubei Province, China, CT scans were routinely obtained on the same day as a positive RT-PCR in an acute setting/fever clinics during the initial outbreak period. RT-PCR was positive in all patients but was not a requisite for the diagnosis of COVID-19 at that time, which could be made with CT and exposure history during peak prevalence during the outbreak.The test success metrics are highly dependent upon pretest background prevalence, and testing practices may vary according to exposure rates and phase of pandemicIn conclusion, an AI system derived from heterogeneous multinational training data delivers acceptable performance metrics for the classification of chest CT for COVID-19 infection. While CT imaging may not necessarily be actively used in the diagnosis and screening for COVID-19, this deep learning-based AI approach may serve as a standardized and objective tool to assist the assessment of imaging findings of COVID-19 and may potentially be useful as a research tool, clinical trial response metric, or perhaps as a complementary test tool in very specific limited populations or for recurrent outbreaks settings.Patients with COVID-19 infection confirmed by RT-PCR undergoing CT evaluation for diagnosis or evaluation of infection were identified for study inclusion at four international centers: (1) 700 patients from The  Xiangyang NO.1 People’s Hospital Affiliated Hospital of Hubei University of Medicine in Hubei Province, China, (2) 147 patients from the Self-Defense Forces Central Hospital, Tokyo, Japan, 3) 130 patients from San Paolo Hospital, Milan, Italy, and (4) 16 patients from Cà Granda Ospedale Maggiore Policlinico Milano, Milan, Italy. Study inclusion criteria included positive findings for COVID-pneumonia by expert radiologist interpretation and minimum technical requirements. Summary characteristics of each institutional cohort of patients meeting study criteria are provided in Table  130 pati23. Summary of dataset inclusion is provided in Table A balanced control population was identified from two institutions and one publicly available dataset. The control group weighed multiple clinical indications for chest CT and confounding diagnoses, such as RT-PCR or microbiology proven non-COVID-19 pneumonias from bacteria, fungi, and non-COVID viruses, as well as cancer staging and diagnosis, emergency care, and other clinical indications for chest CT imaging. These datasets are individually described, by institution and indication, in Table The design and workflow of the classification algorithm is shown in Fig. 24. In order to address the challenges from GGO/consolidation patterns, the network trained with LIDC dataset consisting of 1018 images and 95 in-house CT volumes from a training set defined in Table The lung segmentation model was trained using the AH-Net architecture25. Images were clipped to HU range  and cropped to bounding box fitting to the maximum dimensions of lung regions with an extended 5 voxel buffer. For the full 3D model, the entire lung region (without masking) was resampled to size 192 × 192 × 64 for training and inference. For the hybrid model, images were resampled to resolution 1 mm × 1 mm × 5 mm and sub-crops of 192 × 192 × 32 were sampled from lung regions, applying mask to obtain lung-only tissue, at a frequency of 6 crops/patient for training and 15 crops/patient at inference. These implementations are shown in Fig. Both the hybrid 3D and full 3D models used in this study were based on a Densnet-121 architecture adapted to utilize 3D operations  compared to original 2D implementation26. Algorithm development was implemented in Tensorflow and code is publicly available as part of the NVIDIA Clara Train SDK on NGC27.Data augmentation was performed to avoid bias of center-specific characteristics, and included image intensity and contrast adjustment, introduction of random gaussian noise, flipping, and rotation. Within each mini batch, data were sampled to ensure class balance between COVID and non-COVID groups. Attention/activation maps to visualize regions within the image utilized for prediction were generated using Grad-CAM methodClassification performance was evaluated by overall accuracy, positive predictive value, negative predictive value, sensitivity, and specificity for correctly distinguishing between COVID-19 vs. any other condition. Summary statistics of false positive predictions (incorrectly labeling as COVID-19) were reported separately for pneumonia cohorts and all-comer/any-indication cohorts. Hold out test sets were identified for each model with attention to the ability to translate models across demographics and disease stages.Reproducibility of the training schema and generalizability of resultant models were assessed by removing the cohort of COVID-19 patients from Tokyo, Japan from training and validation datasets. Models were retrained utilizing identical algorithm configuration and hyperparameters as the original models. Overall performance, as well as accuracy specific to Japan cohort, were reported and used for evaluation.Further information on research design is available in the Supplementary InformationReporting Summary


Ctgf knockout (FbCtgf KO) mouse line in which the expression of Ctgf in the DEPN is eliminated. In this study, we adopted a pentylenetetrazole (PTZ)-induced seizure model and found similar severity and latencies to death between FbCtgf KO and WT mice. Interestingly, there was a delay in the seizure reactions in the mutant mice. We further observed reduced c-fos expression subsequent to PTZ treatment in the KO mice, especially in the hippocampus. While the densities of astrocytes and microglia in the hippocampus were kept constant after acute PTZ treatment, microglial morphology was different between genotypes. Our present study demonstrated that in the FbCtgf KO mice, PTZ failed to increase neuronal activity and microglial response in the hippocampus. Our results suggested that inhibition of Ctgf function may have a therapeutic potential in preventing the pathophysiology of epilepsy.Connective tissue growth factor (CTGF) plays important roles in the development and regeneration of the connective tissue, yet its function in the nervous system is still not clear. CTGF is expressed in some distinct regions of the brain, including the dorsal endopiriform nucleus (DEPN) which has been recognized as an epileptogenic zone. We generated a forebrain-specific  Seizures are the result of neuronal hyperactivity that causes involuntary behavioral changes, such as twitching of the limbs, while epilepsy is a chronic condition characterized by repetitive seizures and is one of the most common neurological disorders . VariousConnective tissue growth factor (CTGF), also known as Cyr61/CTGF/NOV (CCN) family protein 2 (CCN2), is a 36 to 38 kDa cysteine-rich secreted protein. CCN family members are multifunctional proteins that can facilitate a number of physiological functions such as growth factor binding and interactions among extracellular matrix and cell surface proteins ,8. HowevEmx1-Cre; Ctgfflox/flox, FbCtgf KO) mouse line. In these mutant mice, the Ctgf gene is eliminated from the excitatory neurons in the forebrain structures [Ctgf KO mice, indicating a paracrine function of CTGF [Ctgf KO mouse model provides an excellent opportunity to explore the interactions between neurons and glia in the pathophysiology of epilepsy [To decipher the role of CTGF in the nervous system, we generated a forebrain-specific Ctgf knockout  paradigm to induce seizures in control and Fbl models ,28,29,30Ctgf knockout (FbCtgf KO) mice, the expression of Ctgf protein was abolished  and tonic-clonic seizures  were similar between control and KO mice , their latencies to death were measured. There was no difference between groups . Throughout the observation period, the overall seizure behaviors (excluding death) were not affected by the removal of Ctgf  = 4.178; p = 0.008). This result suggested a delay in the seizure reaction in the FbCtgf KO mice and a reduction of sensitivity in PTZ-induced seizure paradigm in these mutants.Seizure scores were assessed through 30 min after PTZ administration. The latencies to generalized clonus  in the brain in these mice. Acute treatment with 30 mg/kg PTZ did not alter the expression of c-fos while 50 mg/kg PTZ injection induced c-fos expression in the cortex in both control and Fb KO mice A. We mea KO mice B. In PTZCtgf is normally expressed in the DEPN , we alsoIn the insular, perirhinal and entorhinal cortices, acute PTZ treatment elevated c-fos expression in both control and KO mice, but the levels in KO mice were much lower than those in control mice . In our Ctgf KO mice -immunohistochemistry A. The deCtgf in the forebrain structures, including the DEPN. We found delayed seizure response, reduced c-fos expression and lack of microglial activation following acute PTZ injection in FbCtgf KO mice. Our findings suggest a novel target for preventing the pathophysiology of epilepsy.In the present study, we demonstrated, the first time, the PTZ-induced seizures and cellular responses in mice lacking CTGF is a small extracellular matrix (ECM)-associated fast turnover protein, critical for modulating multiple biological functions such as proliferation, differentiation, adhesion, migration, apoptosis and ECM remodeling ,37,38. CCtgf KO mice [Ctgf in either kidney or heart that showed no fibrosis phenotypes [Ctgf could be executed by the expression of Cre which is driven by a designated promoter. This system could provide a powerful tool to decipher the role of Ctgf in a region- or cell type-specific manner.CTGF could also integrate extracellular cues by modulating the bindings of growth factors with ECM component  with its conserved cysteine-rich functional domains and execute signaling transduction to the downstream molecules . However KO mice  and tranenotypes . In our CTGF is normally expressed in the nervous system including the olfactory bulb, cortical layer VIb and DEPN. However, the function of CTGF in the brain is not well understood ,44,45,46CTGF is expressed in the DEPN which is located deep in the piriform cortex and composed of densely packed multipolar cells . DEPN haFollowing acute PTZ challenge, seizures were induced in both control and KO mice to a similar extent. However, the peak of seizures was delayed by 5 min in KO mice than that in control mice, indicating a higher threshold for seizure induction in these mutant mice. We are further examining this hypothesis using a PTZ-kindling paradigm.Ctgf KO mice following PTZ treatment, the index of neural activity, c-fos expression, was less prominent in these mutants. In FbCtgf KO mice, PTZ failed to significantly elevate c-fos expression in the DEPN, implying a role of CTGF in modulating neuronal activity or excitability. However, since Ctgf gene has been removed before its native expression in these mutants, the role of Ctgf in the morphogenesis of DEPN neurons and network formation during neural development cannot be excluded.In addition to the delayed onset of seizure-related behaviors in FbCtgf KO mice, PTZ induced c-fos expressions were not significantly increased in all these regions, suggesting an DEPN-derived Ctgf-mediated gating mechanism in this DEPN-entorhinal-hippocampus pathway. On the other hand, DEPN neurons project to the perirhinal cortex which might serve as a gate-keeper to other cortical regions including the cingulate and insular cortices [Ctgf KO mice, PTZ-induced c-fos expression is relative moderate or insignificant, the consequential excitotoxicity might be spared in the limbic structures. Effort should be made to elucidate the structural and functional changes in the brains of PTZ-treated FbCtgf KO mice.DEPN neurons project to the entorhinal cortex, the gate of the hippocampal formation . Interescortices ,15. AlonCtgf KO mice. Our results demonstrated that the acute reaction of DG microglia following PTZ treatment correlated well with the index of neuronal activity. Given the deletion of Ctgf was only operated in forebrain excitatory neurons, we believed the activation of microglia is resulted from PTZ-enhanced neuronal activity. Microglial activation may augment synaptic pruning, alter synaptic transmission and excitation/inhibition balance that lead to the development and aggravation of epilepsy [Glial cells in the brain could respond to various stimuli and the status of these cells is highly associated with neuronal activity ,19,20. Iepilepsy . In thisIn this study, we characterized the PTZ-induced seizure reactions in mice lacking Ctgf in the forebrain. We proposed that following PTZ injection, DEPN-derived Ctgf may play a permissive role that allows the propagation of aberrant neural activity in the brain, especially the limbic structures. In contrast, deletion of Ctgf in the DEPN might alter the gating of neural signal propagation. Therefore, a possible strategy of limiting seizure-related neuropathy through the inhibition of CTGF function is worthwhile for further evaluation.loxp-floxed Ctgf sequence (Ctgfflox/flox) were crossed with Emx1-Cre mice in which the expression of Cre recombinase is driven by the promoter of Emx1 in forebrain excitatory neurons [Emx1-Cre; Ctgfflox/flox mice were generated and designated as forebrain-specific Ctgf knockout (FbCtgf KO) mice [Ctgf KO mice and their littermates  were used. Animals were bred and kept in the Laboratory Animal Center of the College of Medicine, National Taiwan University, under a 12-h light/dark cycle (lights on at 08:00) with free access to food and water. Genotypes of the mice were examined using PCR-based protocol [Mice of C57BL/6 background carrying  neurons . Emx1-CrKO) mice . In thisprotocol  and animCtgf KO mice aged 3–5 months were intraperitoneally injected with different doses of PTZ  or vehicle  during 13:00–15:00. The behaviors of mice were recorded by a camera in front of the box for half an hour. The seizure profile was scored by experienced examiners blind to the genotypes. Normal locomotor activity was scored as 0, hypoactivity was 1, partial clonus was 2, generalized clonus was 3 and tonic-clonic seizures was 4 [Adult male control and Fbes was 4 . Two hou2O2 to block the endogenous peroxidase activity and transferred to a PBS-based blocking solution containing 4% normal goat serum , 4% bovine serum albumin  and 0.4% Triton X-100 . After blocking, sections were incubated with primary antibodies, such as goat anti-CTGF , rabbit anti-c-fos , rabbit anti-S100β , rabbit anti-GFAP  or rabbit anti-Iba1  antibodies in 10% blocking solution overnight. After washing, the sections were incubated with biotinylated secondary antibodies  and avidin-biotin peroxidase complex . Finally, sections were reacted with 3,3′-diaminobenzidine (with 0.01% H2O2 in PBS) and mounted. For control experiments, we omitted the use of primary antibodies and the immunoreactive signals were neglectable.Two hours after saline or PTZ injection, mice were overdosed with 150 mg/kg sodium pentobarbital and transcardially perfused with 0.1 M PBS, followed by 4% paraformaldehyde. Whole brains were then harvested and postfixed overnight in the same fixative. Brain sections of 30 μm thick were cut using a vibratome , reacted with 1% HThe densities of c-Fos-positive nuclei, S100β-positive astrocytes and Iba1-positive microglia were quantified by measuring the number of cells within a counting frame (150 μm × 150 μm) in given brain regions using the ImageJ software . To evaluate the index of astrocyte activation, the relative area of GFAP-positive signal in the counting frames was quantified.Iba1-immunostained microglia were examined and image stacks were taken under a microscope equipped with the Stereoinvestigator system  at 40× magnification using 1 μm z-steps. Microglia with definite cell bodies and processes were reconstructed and analyzed with FracLac plugin for ImageJ. Skeleton and fractal analyses were performed as described .p-values of ANOVA reached statistically significant (p < 0.05), t-tests with Bonferroni correction were performed to evaluate which experimental groups presented significant effects. Values are represented as the mean ± standard error of mean (SEM).All data were subjected to two-way ANOVA using SPSS  to examine the interaction between treatment and genotype. When the


Physical activity (PA) level is associated with multiple health benefits during early childhood. However, inconsistency in the methods for quantification of PA levels among preschoolers remains a problem.This study aimed to develop PA intensity cut points for wrist-worn accelerometers by using machine learning (ML) approaches to assess PA in preschoolers.Wrist- and hip-derived acceleration data were collected simultaneously from 34 preschoolers on 3 consecutive preschool days. Two supervised ML models, receiver operating characteristic curve (ROC) and ordinal logistic regression (OLR), and one unsupervised ML model, k-means cluster analysis, were applied to establish wrist-worn accelerometer vector magnitude (VM) cut points to classify accelerometer counts into sedentary behavior, light PA (LPA), moderate PA (MPA), and vigorous PA (VPA). Physical activity intensity levels identified by hip-worn accelerometer VM cut points were used as reference to train the supervised ML models. Vector magnitude counts were classified by intensity based on three newly established wrist methods and the hip reference to examine classification accuracy. Daily estimates of PA were compared to the hip-reference criterion.In total, 3600 epochs with matched hip- and wrist-worn accelerometer VM counts were analyzed. All ML approaches performed differently on developing PA intensity cut points for wrist-worn accelerometers. Among the three ML models, k-means cluster analysis derived the following cut points: ≤2556 counts per minute (cpm) for sedentary behavior, 2557-7064 cpm for LPA, 7065-14532 cpm for MPA, and ≥14533 cpm for VPA; in addition, k-means cluster analysis had the highest classification accuracy, with more than 70% of the total epochs being classified into the correct PA categories, as examined by the hip reference. Additionally, k-means cut points exhibited the most accurate estimates on sedentary behavior, LPA, and VPA as the hip reference. None of the three wrist methods were able to accurately assess MPA.This study demonstrates the potential of ML approaches in establishing cut points for wrist-worn accelerometers to assess PA in preschoolers. However, the findings from this study warrant additional validation studies. Accelerometry has been widely accepted as the gold standard to measure physical activity (PA) in free-living settings ,2 includHowever, cut points from wrist-derived data are sparse for preschool-age children ,12. JohaMachine learning (ML) algorithms are increasingly being used to translate accelerometer outputs to meaningful PA metrics . Recent Combining ML techniques and wrist-worn accelerometers may help address the low compliance caused by the challenges in wearing hip-worn accelerometers ,21 and tA total of 61 healthy children, aged 3-5 years, who were enrolled in a Head Start program (HS), were recruited to participate in the study in Fall 2018; in San Antonio, Texas. The HS is a federally funded program that serves children from low-income families through academic, health, nutrition, and family service programs . Their pThis study was reviewed and approved by the Institutional Review Board of the University of Texas at San Antonio.For 3 consecutive days, the children wore two triaxial accelerometers  that collected raw accelerometry data at a sampling frequency of 30Hz (30 observations per second for each axis) from 9 AM to 2 PM, following a previously published protocol . On the The hip-reference cut points for assessing PA intensity were adopted from Butte et al  based onThree ML models, two supervised and one unsupervised, were used to establish three different sets of wrist-worn accelerometer VM cut points as the new wrist methods to assess PA in preschoolers . SuperviThe VM count for each epoch for each participant was categorized into a PA level based on each of the three sets of newly established wrist-worn accelerometer cut points and the hip reference, resulting in four separate PA level designations. Standard classification measures of sensitivity, specificity, false-negative rate, and false-positive rate were calculated to assess the discriminative ability of each method to correctly classify PA levels. Cohen kappa values were calculated to test the agreement between hip- and four wrist-derived measures, k-means, ROC, OLR, and Johansson’s cut points. Daily amount of time in each PA level was also calculated and compared against PA estimates from the hip-worn accelerometer. Univariate analysis of covariance was conducted to compare mean daily time in each PA intensity level for each of the wrist-worn ML-based cut points versus the hip reference and the Johansson’s cut points.All study participants were 3-5 years old, and more than 80% (29/34) of them were of Hispanic ethnicity . Hip accThe three ML models grouped accelerometer counts differently and developed three sets of wrist-worn accelerometer VM cut points  and were comparable to the performance of Johansson et al  cut poinIn terms of classifying LPA, only the k-means LPA cut point resulted with sensitivity and specificity values greater than 50%. While the specificity value for k-means LPA cut point (76.81%) was similar to the Johansson cut point (75.69%), it had a much lower sensitivity value.None of the three wrist methods were able to distinguish MPA as indicated by the low sensitivity and kappa values, although the k-means MPA cut point had the highest sensitivity (48.42%) and kappa value (0.19). OLR and k-means cut points also had low sensitivity values for identifying VPA . Although the ROC cut point exhibited sensitivity and specificity values of 79%, the low kappa value (0.11) indicated that there was a low agreement between this method and the hip reference. When MPA and VPA were grouped together, the k-means cut points demonstrated higher sensitivity (68.37%), specificity (86.58%), and kappa values (0.35) than the other two wrist methods.In general, k-means cut points resulted in sensitivity and specificity values above 50% for predicting sedentary behavior, LPA, and MVPA, with an acceptable kappa value for overall agreement (0.40).This study applied wrist derived VM data to assess PA in preschoolers based on three ML models. In the supervised ML models, the ROC analysis and OLR model were able to distinguish VM counts into each PA intensity level by reading the intensity label of each epoch as assigned by the gold standard hip reference. As an unsupervised ML model, k-means cluster analysis successfully grouped accelerometer count values into four PA clusters. When examining the agreement and comparing PA estimates from the wrist data compared with the hip reference, the k-means cluster analysis had the best performance among three ML models tested. Additionally, the k-means method of assigning PA levels had better agreement with the hip reference than the previously published cut points developed by Johansson et al .Our results showed that cut points derived from the k-means cluster analysis produced better agreement with the gold standard hip reference than the other two ML approaches across all sedentary behavior and PA intensity levels, as indicated by sensitivity, specificity, and kappa values. K-means sedentary behavior, LPA, and VPA cut points showed the highest similarity to the hip reference on estimating PA time. Additionally, the estimated percent time in sedentary behavior, LPA, and MVPA by the k-means wrist reference method was comparable to the findings by Jones et al , who adoOne reason that the k-means method had superior performance could be that the use of unlabeled data for calibration may result in less biased cut points for classifying epochs into PA levels . During Similarly, the nature of the activities generating the calibration data may also influence the performance of the machine learning methods. For example, Butte et al  used 11 Our results showed that all wrist-based methods had difficulty in accurately assessing MPA. One possible explanation for this issue is that there is no consensus on what types of activities can represent MPA for this age group . For exaThis study has several limitations. First, participants in this study were from low-income minority families and, therefore, accelerometer counts collected from the study sample might not represent the activity patterns of the general population. Previous studies have shown that young children from low-income minority families had a significantly lower motor performance and are less active during a preschool day compared to children from higher income families ,42. HoweThis study demonstrated the potential of ML techniques to distinguish PA intensity levels, with the exception of MPA, in preschool-age children. Cut point established from k-means cluster analysis was comparable to the hip-reference criterion in predicting sedentary behavior. Although PA estimates from k-means cluster analysis of wrist-worn accelerometers were acceptable as compared to the hip reference, the finding needs to be replicated using ground truth activities in free-living setting.


Recent case studies show that the SARS-CoV-2 infectious disease, COVID-19, is associatedwith accelerated decline of mental health, in particular, cognition in elderlyindividuals, but also with neurological and neuropsychiatric illness in young people.Recent studies also show a bidirectional link between COVID-19 and mental health in thatpeople with previous history of psychiatric illness have a higher risk for contractingCOVID-19 and that COVID-19 patients display a variety of psychiatric illnesses. Riskfactors and the response of the central nervous system to the virus show large overlapswith pathophysiological processes associated with Alzheimer’s disease, delirium,post-operative cognitive dysfunction and acute disseminated encephalomyelitis, allcharacterized by cognitive impairment. These similarities lead to the hypothesis that theneurological symptoms could arise from neuroinflammation and immune cell dysfunction bothin the periphery as well as in the central nervous system and the assumption thatlong-term consequences of COVID-19 may lead to cognitive impairment in the well-being ofthe patient and thus in today’s workforce, resulting in large loss of productivity.Therefore, particular attention should be paid to neurological protection during treatmentand recovery of COVID-19, while cognitive consequences may require monitoring. et al. contemplated the similarities of risk factors,neuroinflammatory processes and potential neurological consequences between COVID-19 andAlzheimer’s disease/post-operative cognitive dysfunction. The observations yield theassumption that long-term consequences of COVID-19 may lead to cognitive impairment evenin young individuals, affecting today’s workforce and eventually resulting in productionloss.Meier   The outbreak of the new coronavirus (SARS-CoV-2) in late 2019 has since risen to over 76million confirmed cases today, leading to pneumonia and death in 1.2m of infectedindividuals globally . Thehigh transmissibility of the virus quickly led to a world-wide pandemic affecting every agegroup, and the rapid increase in confirmed cases as well as asymptomatic transmission renderthe prevention and control of COVID-19 extremely difficult. Increased age (>40),cardiovascular disease, diabetes, chronic respiratory diseases and cancer have beenidentified as risk factors for respiratory symptoms and death  is the leading causeof mortality of COVID-19. Research suggests that it may not be the infection fatality . It is afatality . Once infatality . InfectiFurthermore, acute disseminated encephalomyelitis affects brain and spinal cord and oftenresults from a minor infection, activating immune cells to attack myelin sheets of neuronsand has been identified in the context of COVID-19 (Concern for long-term cognitive impairment resulting from a SARS-CoV-2 infection stemsfrom research in delirium and post-operative cognitive dysfunction (POCD) in surgerypatients. Data from animal and human studies led to assume that peripheral surgical traumamay cause CNS inflammation via the disruption of the blood–brain barrier (BBB), leading todisruption of neural activity and resulting in memory dysfunction and cognitive decline.Peripheet al., 2020) and from Korea (www.cdc.org).Two studies, one from the UK  and itsprotease BACE1 (beta-amyloid cleaving enzyme 1) or beta-secretase are both internalizedthrough clathrin mediated and cholesterol/raft mediated pathways and in the earlyendosomes, where the pH is conducive for the proteolytic activity of BACE1, APP is cleavedby BACE1 and then subsequently by γ-secretase to release the amyloid peptide in the earlyendosomes .SimilarTaken together, striking similarities in inflammatory response, cytokine storm, vascularrisk factors, small vessel cerebrovascular disease, the disruption of the BBB, andcognitive impairment as a consequence seem to form a common denominator of post-operativedelirium (POD)/POCD and Alzheimer’s disease with COVID-19. From case studies we know thatboth elderly and younger patients can suffer from neuronal consequences of COVID-19,whether or not they underwent a severe disease course , global working hours declined by4.5% (ca. 130 million full-time jobs in a 48 h working week) in the first quarter of 2020,compared to pre-crisis situation, and were up to 10.5% lower in the second quarter, whilelower-middle-income countries are expected to register the highest rate of hours lost12.5%; . UrgentGauging potential production loss due to neurological consequences of COVID-19 in thelabour force at this stage is unpredictable. More data are required to identify theincidence rate of neurological disorders related to the SARS-CoV-2 infection in youngerpeople and whether the effects are reversible. Furthermore, it will be necessary to followthe cases that suffered from neurological disorders over multiple years in order toestablish whether any premature cognitive impairment appears related to the infection.However, when looking at data from TBI, which frequently appears in younger individualsand leads to cognitive decline and production loss, median production losses due to earlyretirement are estimated to be around 1.35 M USD per patient (Lockdown, social distancing, isolation and working from home, or traumatic events such asdeath of friends and relatives and not being able to be close to them certainly hasimpacted each and everyone’s mental state and caused surges in depression, anxiety,restlessness, stress and other psychiatric symptoms, at least during the initial phases ofthe COVID-19 pandemic (Case studies showing neuronal death in the context of COVID-19 in young people with a lightcourse of the disease are proposing a somber scenario with potential long-term consequencesof cognitive impairment, given that it may affect both older and younger people. Mental andneurological disorders independent of COVID-19 consequences cause multiple trillion lossesin lost output. Under the assumption that COVID-19 may affect and eventually cognitivelyimpair the current labour force, massive financial damage would extend manifold to multipletrillions through production loss, aside from putting an additional strain on the healthcaresystem and public health costs. Hope remains that a treatment for COVID-19 will be foundsoon, and should the disease mechanisms between COVID-19, POD/POCD and Alzheimer’s diseaseturn out to be as similar as currently assumed, a desirable side effect of these medicationsmay benefit elderly patients post-surgery and with dementia, while keeping our labour forcecognitively healthy.Data sharing is not applicable to this article as no new data were created or analysed inthis study.No funding or grants were received for this manuscript.The authors report no competing interests.


Background: The purpose of this prospective, investigator-initiated feasibility study is to evaluate the efficacy and safety of nonablative, cryogen-cooled, monopolar radiofrequency (CMRF) treatment for stress urinary incontinence (SUI).Materials and Methods: Subjects meeting all the inclusion and exclusion criteria were enrolled and divided into two groups. Subjects in Group 1 received a single SUI treatment, and subjects in Group 2 received two SUI treatments ∼6 weeks apart. Follow-up visits are planned for 1, 4, 6, and 12 months post-treatment. At each study visit, subjects are asked to perform a 1-hour pad-weight test (PWT) and to complete the Urogenital Distress Inventory-6 (UDI-6), Incontinence Impact Questionnaire-Short Form (IIQ-7), and International Consultation on Incontinence Modular Questionnaire-Urinary Incontinence-Short Form (ICIQ-UI-SF) questionnaires. In addition, subjects completed 7-day bladder voiding diary and safety assessments.Results: Preliminary data indicate an improvement in SUI symptoms and quality of life for subjects, as determined by validated SUI-related patient-reported outcomes and the objective 1-hour PWT, with a >50% reduction in pad weight for 68.8% of the Group 1 subjects and 69.2% of the Group 2 subjects at 6 months. Initial review of the bladder voiding diaries suggests that subjects are having fewer urine leakage episodes per day. In addition to efficacy, the CMRF Viveve System was well tolerated and safe.Conclusions: The endpoints evaluated indicate an improvement in SUI symptoms and quality of life. The sustained benefit of the CMRF vaginal treatment at 6 months suggests potential use as a nonsurgical approach to treat SUI. Patients with ISD leak urine because the urethral sphincter does not effectively seal off the inner muscle of the bladder. Urethral hypermobility refers to the movement of the female urethra that occurs due to weakened pelvic floor muscles. In reality, many women have a mixed presentation.Urinary incontinence is the involuntary loss of urine. There are two major types of female urinary incontinence: urgency urinary incontinence and stress urinary incontinence (SUI). Urgency incontinence is the complaint of involuntary loss of urine associated with the sudden need to pass urine.3 Furthermore, SUI can greatly impact a woman's health and quality of life.4 Depending on the severity of incontinence, some women may choose to avoid social or religious gathering, physical exercise, travel, and even sex.6SUI affects many women; especially during pregnancy, after childbirth, and during menopause. More than 55% of women who have delivered a child vaginally will show symptoms of SUI and are twice as likely to suffer from long-term SUI when compared with cesarean delivery.7 but long-term compliance and sustainability is difficult.8 Pharmacologic intervention9 or injectable bulking agents10 offer additional conservative treatment options but may pose efficacy or safety issues.11 At the other end of the treatment spectrum is surgery with mesh or a sling. Although synthetic sling placement has a proven success rate,12 complications of mesh surgery can occur, negatively impacting many patients. In addition, surgery often comes with several risks, including infection, voiding dysfunction, and anesthetic concerns,13 leading many women to use surgery as a last resort for treatment. The large gap between conservative and highly invasive treatment options presents an opportunity to provide more effective and less-invasive treatments for women suffering from SUI.There are various treatment possibilities for women suffering from SUI; however, the current options have many limitations. Conservative, first-line treatment options include simple diet and exercise changes, and pelvic floor muscle training. Some women may find benefit from these,15 In addition, RF devices have been used to treat a variety of health-related issues, including SUI.16 However, these precedent devices are no longer commercially available as there have been some concerns about their safety profile.17–19 The Viveve System, a cryogen-cooled monopolar RF device, has a well-documented safety profile and has previously been used to treat sexual dysfunction.20 The device delivers monopolar RF with cryogen cooling to protect the upper epithelial layers of the mucosa while also enabling energy to reach the deeper tissue layers, resulting in volumetric heating of important connective tissue.Radiofrequency (RF) energy has previously been used in various mucosal tissues, including pharynx, skin, cornea, and vagina.Recently, a pilot study at the Allan Centre in Calgary, Canada using the Viveve System to treat women with SUI reported a >90% improvement from baseline in SUI symptoms and quality of life (data on file). Following those positive results, this larger investigator-initiated early feasibility study is being conducted to further evaluate the use of the Viveve System to treat SUI. This study includes the objective 1-hour pad-weight test (PWT) in addition to subjective patient-reported outcome measures.This investigator-initiated feasibility study is a single-site, randomized, unblinded trial that is ongoing.21 Women were excluded from the trial who were currently pregnant or discontinued breast feeding <6 months before enrollment; had a condition/illness that may confound the results of urinary incontinence assessment, including an abnormal pelvic examination, greater than stage II pelvic organ prolapse, or were morbidly obese; had a history of genital fistula or a thin rectovaginal septum (<2 cm); had a previous energy-based device treatment in the genitourinary area; and/or were taking any new medication that affects urination  with a normal pelvic examination who were diagnosed with mild-to-moderate SUI as defined by the 1-hour PWT (1–50 g leakage).rination .15 was modified to provide additional energy to the tissue beyond the introitus for support of the urethra to improve SUI. A total of 220 pulses of 90 J/cm2 was applied during the treatment procedure. The treatment area was divided into quadrants of the vaginal introitus with the area directly beneath the urethra excluded. Each quadrant was treated with five consecutive passes of five locations of pulses for a total of 25 pulses per quadrant. The remaining 20 pulses are distributed equally in quadrants 1 and 4. If a subject was assigned to Group 2 (two SUI treatments), the treatment protocol was repeated 6 weeks after the initial treatment.Subjects meeting the inclusion and exclusion criteria were randomized to receive either one or two treatments using a random number generator; odd numbers were placed into Group 1 and even numbers were placed into Group 2. The Viveve system protocol for sexual functionA sham group was not included in the study design as this was a pilot study to obtain the first objective data using the Viveve Treatment, SUI protocol. In addition, the manufacture of a sham tip would have been cost prohibitive at this stage in the investigation.The sample size (37 subjects) for this early feasibility study was determined based on considerations of such a feasibility study, confidence in outcome measures, and research risks, including the risk that the study aims may not be achieved.21 7-day bladder voiding diary and validated patient-reported outcome measures , was administered at the screening visit and at 1, 4, and 6 months post-treatment. These will also be completed at the final visit at 12 months. Adverse events and concomitant medications were collected at each of the follow-up visits.The standardized 1-hour PWT,etc.) that the subject completes after ingestion of a set amount (500 mL) of sodium-free liquid. Subjects are asked to wear preweighed pads during the assessment. The pad is weighed again at the completion of the series of activities to determine the amount of leakage.The 1-hour PWT is a standardized series of activities  guidelines. Health Canada clearance was also obtained for this investigator-initiated study. Documentation and data management were conducted in a manner that aligns with local ethics review board guidelines.Between June and November 2017, 37 subjects were included in the study. Twenty-one and 14 subjects were randomized to receive one or two treatments, respectively; 2 subjects dropped out of the study before treatment. Twenty-nine subjects completed the baseline and 6-month follow-up visit. 25 is also comparable between groups. Overall mean change from baseline showed a decrease of 73% for all subjects.Mean 1-hour pad-weight values are presented in 23  as early as 1-month post-treatment23 . By 6-moe.g., rock climbing) post-treatment.Subjects report a decrease in leakage episodes per day as soon as 1-month post-treatment . By 6 moNo unanticipated or serious adverse events have been reported in the trial to date. All other events were mild. One patient reported a urinary tract infection (UTI). The UTI occurred between the treatment visit and 1-month follow-up. The subject was treated with 1 week of antibiotics. The investigator assessed the UTI as unrelated to treatment.This early feasibility study highlights the promising efficacy and safety of the Viveve System for the treatment of SUI. The results show continued benefit out to 6 months post-treatment, the time point assessed to date, for all subjects. Although the results are encouraging, caution should be exercised when interpreting the data since this is a small study and lacks a control group. A larger scale, randomized, blinded, sham-controlled study is warranted.26 In addition, the lack of a study-wide retention plan and unblinded nature of the study could account for the larger dropout rate from Group 1 (n = 5) versus Group 2 (n = 1). Interestingly, of the five women who dropped out of Group 1 before 6-month visit, all had improvement from baseline on the 1-hour PWT at their last measured visit; and two of the five had no leakage at all (0 g of leakage on the 1-hour PWT). Furthermore, based upon the Viveve System's proposed mechanism of action, which includes fibroblast activation and restoration of connective tissue of the lamina propria tissue layer,27 and what is known about collagen restoration, a second RF treatment done later  may provide even greater benefit to women. A larger number of subjects, another study including a sham treatment group, a longer follow-up period, or a longer28 time between treatments may be necessary to determine the differences between one or two treatments and the optimal timing. Of note, this study will continue out to 12 months to assess safety and efficacy.While the objective pad-weight data are similar between treatment groups, the subjective, SUI-related patient-reported outcome measures show slight differences in the mean composite scores, with Group 2 reporting decreased scores at almost all time points. This could be due to a lower baseline value for Group 2; or also because this was an unblinded study, therefore subjects knew whether they received one or two treatments. An analysis of 130 clinical trials showed a significant placebo effect in studies with continuous subjective outcomes, however little to no placebo effect for objective measures.29–32 This early feasibility study also includes validated SUI- and quality of life-related subjective questionnaires  as study endpoints with >70% of women experiencing improvement (reduction from baseline) at 6 months. In addition, an earlier pilot study demonstrated the efficacy of the Viveve System for the treatment of SUI out to 12 months, with >90% response rate . Although the IIQ-7 and ICIQ-UI-SF scores slightly increased from 4 to 6 months, the change was minimal and not clinically significant.33Although other RF devices are currently claiming to help treat SUI, no other studies with a nonablative, monopolar RF device have demonstrated a decrease in SUI symptoms as evaluated by objective measures (1-hour pad test and voiding diary) sustained out to 6-months post-treatment.34 This incurs increased time and monetary cost to the patient, and increases the potential for a decrease in treatment compliance. It should also be noted that the Viveve System has a well-established safety profile. To date, thousands of women have been treated globally for sexual dysfunction with only mild adverse events reported.36 In the previously published, large-scale, randomized-controlled clinical trial using the Viveve System, the active and sham groups reported similar numbers of adverse events.20 In addition, recent ovine studies have confirmed tissue temperatures that would result in cellular responses related to the observed clinical outcomes with no thermal damage to the vaginal tissue following multiple pulses in the same area .These promising results were achieved with one treatment. Other RF devices require multiple (3+) sessions, typically at 1-month intervals.While this article summarizes data from an early investigator-initiated feasibility study, the results include the first 6-month objective outcome data for the vaginal RF treatment for SUI. The Viveve treatment shows promise as a viable option for patients searching for minimally invasive nonsurgical treatments. Initial experience merits a larger scale, randomized, blinded, and sham-controlled study to investigate this treatment for SUI.


This nonrandomized controlled trial assesses whether implementation of a nurse-led, patient-centered tool kit for fall prevention was associated with a reduction in rates of falls and fall-related injuries in 3 academic medical centers in Boston and New York City. Is a fall-prevention tool kit that engages patients and families associated with a reduction in falls?In this nonrandomized controlled trial including 37 231 patients from 14 medical units within 3 academic medical centers, an interrupted time series found that implementation of a fall-prevention tool kit was associated with a statistically significant 15% reduction in overall inpatient falls and a 34% reduction in injurious falls.The findings suggest that tools to support patient engagement throughout hospitalization in the fall-prevention process may be associated with a reduction in falls and fall-related injuries. Falls represent a leading cause of preventable injury in hospitals and a frequently reported serious adverse event. Hospitalization is associated with an increased risk for falls and serious injuries including hip fractures, subdural hematomas, or even death. Multifactorial strategies have been shown to reduce falls in acute care hospitals, but evidence for fall-related injury prevention in hospitals is lacking.To assess whether a fall-prevention tool kit that engages patients and families in the fall-prevention process throughout hospitalization is associated with reduced falls and injurious falls.This nonrandomized controlled trial using stepped wedge design was conducted between November 1, 2015, and October 31, 2018, in 14 medical units within 3 academic medical centers in Boston and New York City. All adult inpatients hospitalized in participating units were included in the analysis.A nurse-led fall-prevention tool kit linking evidence-based preventive interventions to patient-specific fall risk factors and designed to integrate continuous patient and family engagement in the fall-prevention process.The primary outcome was the rate of patient falls per 1000 patient-days in targeted units during the study period. The secondary outcome was the rate of falls with injury per 1000 patient-days.P = .01) and an adjusted 34% reduction in injurious falls .During the interrupted time series, 37 231 patients were evaluated, including 17 948 before the intervention  and 19 283 after the intervention . There was an overall adjusted 15% reduction in falls after implementation of the fall-prevention tool kit compared with before implementation (2.92 vs 2.49 falls per 1000 patient-days ; adjusted rate ratio 0.85; 95% CI, 0.75-0.96; In this nonrandomized controlled trial, implementation of a fall-prevention tool kit was associated with a significant reduction in falls and related injuries. A patient–care team partnership appears to be beneficial for prevention of falls and fall-related injuries.NCT02969343ClinicalTrials.gov Identifier:  Our team developed the Fall Tailoring Interventions for Patient Safety (TIPS) tool kit, a nurse-led, evidence-based fall-prevention intervention that uses bedside tools to communicate patient-specific risk factors for falls and a tailored prevention plan. The tool kit provides care team members with the information they need to routinely engage in the fall-prevention process.12 In a randomized clinical trial within a single health care system, Fall TIPS reduced patient falls by 25%, but there was no difference noted in fall-related injuries.13 A follow-up case-control study suggested that falls within the intervention units were largely attributable to patients’ nonadherence to their fall-prevention plan14 and that further strategies are needed for engaging patients in the 3-step fall-prevention process during hospitalization.A previous study16 The project was divided into the 5 following iterative phases using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework17  design using knowledge gained in phase 1 to plan a patient-centered Fall TIPS tool kit with multiple modalities19; (3) development using participatory design, rapid prototyping, computer modeling, and simulation methods to construct the patient-centered Fall TIPS tool kit19; (4) implementation and pilot testing of the tool kit in patient care units20; and (5) evaluation of the association of the tool kit with patient activation.21 The end result was a tool kit that included high-tech and low-tech Fall TIPS modalities, can be used by nursing staff and integrated into various hospital workflows, and supports patient activation and engagement in the 3-step fall-prevention process.21 Modalities included (1) a laminated paper poster,19 (2) a tool kit integrated with the electronic health record (EHR),13 and (3) an electronic bedside screen (e-bedside) display.20 From September 2014 to September 2015, unit staff were involved in developing, refining, and piloting the intervention, testing its association with patient activation in the fall-prevention plan  proNCT02969343) used a stepped-wedge design (TREND) reporting guideline.22This nonrandomized controlled trial , site 2 , and site 3  between November 1, 2015, and October 31, 2018. The purpose was to evaluate the tool kit’s effectiveness and compare the rates of falls and falls with injury from a 21-month preintervention period and a 21-month postintervention period . Site 1 20 An 11-by-17-inch laminated Fall TIPS poster was displayed at the bedside and used color-coded clinical decision support to link the Morse Fall Scale9 risk factors to evidence-based interventions. Nurses completed the poster with a dry-erase marker at admission and during each shift with the patient and family (if available) and posted it at the bedside. Using the Fall TIPS EHR-integrated tool kit, nurses identified patient-specific risk factors using the Morse Fall Scale,9 and clinical decision support automatically linked each risk factor with the appropriate preventive interventions. Nurses could further tailor prevention plans based on their knowledge of the patient. Once completed, posters (8.5 × 11 in) detailing the risk factors and fall-prevention plan were generated and printed from the EHR system, hung at the bedside (sites 2 and 3), or automatically displayed on the bedside computer screensaver  and reviewed with the patient and family at admission and during each shift.In collaboration with unit leadership, the study team assigned the month when the intervention would go live between September 2015 and November 2016 based on the modality selected and associated constraints . Previou19 In brief, study staff engaged leadership at institutional and care-unit levels through presentations on the evidence supporting Fall TIPS. We used a peer-champion model of existing unit-based nursing staff for education and training.19 Nurse champions who completed competency training were involved in continuous engagement of staff nurses, monitoring of fidelity, and reinforcement, with the intention of successful integration of the intervention into practice.19 Study staff visited study units to provide training during the go-live week.19 Unit-based nurse champions measured adherence to the protocol with patient engagement audits consisting of 3 questions: (1) Is the Fall TIPS poster updated with the correct patient information? (2) Can the patient/family express their fall risk factors? and (3) Can the patient/family express their fall-prevention plan? Based on continuous feedback from unit champions, barriers to adoption and spread were addressed.19 After the go-live date, nurse champions completed 5 random audits per month and provided peer feedback to the nurses caring for the audited patients.Methods for stakeholder engagement and implementation in study units are described elsewhere.The primary outcome measure was the overall rate of patient falls per 1000 patient-days during the study period. The overall rate of falls with injury per 1000 patient-days was the secondary outcome. Data on falls and resulting injury levels are routinely recorded in an event reporting system at all participating hospitals and were used in the analysis.The association between the intervention and the rate of patient falls and falls with injury per 1000 patient-days on the unit was analyzed using Poisson regression (for rates) estimated with overdispersion via generalized estimating equations to account for clustering within a unit using an exchangeable correlation for patients within the same unit. In the Poisson regression models, we fit segmented lines for the 2 periods (before and after intervention) to test for the statistical significance of observed changes in the fall rates in the interrupted time series associated with the intervention. In the Poisson regression model for rates with clustering by unit, we adjusted for the following patient-level characteristics: sex (as classified in the EHR), race/ethnicity, insurance (public or private), age at admission, and binary Charlson Comorbidity Index score (0-1 or ≥2). For the Poisson regression parameters to be interpreted as log rate ratios, unit length of stay was used as an offset term with Poisson modeling.In a secondary analysis to assess whether the changes before vs after intervention differed by age group (younger than 65 years vs 65 years or older), we fit the adjusted Poisson regression model for rates with an interaction between age group and period. In another secondary analysis to assess whether the changes from before the intervention to after the intervention differed by site, we fit the adjusted Poisson regression model for rates with an interaction between site and period.P < .05 using a 2-sided test. We used SAS statistical software, version 9.4 (SAS Institute), for the analyses.24Patient characteristics in the 2 periods are presented as means for continuous variables and proportions for categorical variables. Balance in patient characteristics in the 2 periods was assessed using standardized differences. All analyses used the intention-to-treat principle. Statistical significance was set at 24 Nevertheless, to protect against possible confounding, we adjusted for all demographics in the interrupted time-series analyses. There were no statistically significant trends from month to month within the preintervention or postintervention periods in relation to falls or falls with injury. Therefore, we compared adjusted rates across the preintervention and postintervention periods. After Fall TIPS implementation, site 1 had a mean compliance rate of 86% on the 3-question audit, and sites 2 and 3 had mean compliance rates greater than 95%. This translated into a clinically significant patient-centered Fall TIPS intervention in all study units.20The study included 37 231 patients and 277 655 patient-days; 17 948 patients were included in the preintervention period and 19 283 in the postintervention period . PatientP = .01). In the subanalysis by age, the decrease in falls was largest for patients younger than 65 years; units achieved an 18% reduction in patient falls in this age group in the postintervention period  vs a 10% reduction for patients age 65 and older , with the latter difference not being statistically significant.In the adjusted analysis, the overall fall rate in study units decreased from 2.92 falls per 1000 patient-days  before implementation to 2.49 falls per 1000 patient-days  in the postintervention period. After adjustment for demographics in the Poisson regression model, study units using the patient-centered Fall TIPS tool kit achieved a 15% reduction in patient falls in the postintervention period . The rate ratios for falls and injurious falls before and after the intervention are shown in P = .004) vs a 19% reduction for patients younger than 65 , with the latter difference not being statistically significant.In the adjusted analysis, the overall injurious fall rate in study units decreased from 0.73 injurious falls per 1000 patient-days  before implementation to 0.48 injurious falls per 1000 patient-days  in the postintervention period. After adjustment for demographics in the Poisson regression model, study units achieved a 34% reduction in overall falls with injury in the postintervention period . Others have shown that if the two 95% CIs overlap, it does not mean that the 2 groups are not significantly different.35We assessed the effectiveness of the patient-centered Fall TIPS tool kit within existing institutional infrastructures and workflows. One limitation is that support from hospital leadership and unit champions, communication channels, timing of implementation, and nurse and patient adherence to the protocol were variables that could not be fully controlled. We had originally planned to randomize the go-live dates for site 2 , but the20 Various modalities of the tool kit allow for integration into existing clinical workflows in diverse hospital settings. This tool kit appears to addresses the gap among nursing assessment of fall risk, tailored fall-prevention interventions, and engagement of patients throughout the fall-prevention process.36In this nonrandomized controlled trial, implementation of a nurse-led, patient-centered fall-prevention tool kit was associated with reduced rates of falls and injurious falls. The fall-prevention tool kit helped link patient-specific risk factors to interventions most likely to prevent a fall.