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At a rhetorical level, the SDGs provide a unified global agenda, and their targets and indicators are believed to drive action for social and environmental transformation. However, what if the SDGs (and their specific goals and indicators) are more of a problem than a solution? What if they create the illusion of action through a depoliticised and technical approach that fails to address fundamental dilemmas of politics and power? What if this illusion continues to reproduce poverty, inequality, and environmental degradation? This paper addresses these questions through a focus on SDG 6.5.1 – the implementation of integrated water resources management (IWRM), measured on a 0-100 scale through a composite indicator. The paper presents an empirical analysis of SDG 6.5.1 reporting in Colombia, Ethiopia, India, Malaysia, and the UK, drawing on research from the Water Security and Sustainable Development Hub.1 An evidence review and series of expert interviews are used to interrogate the local politics of IWRM measurement, specifically three dilemmas of global composite indicator construction: (1) reductive quantification of normative and contested processes; (2) weak analysis of actually existing institutional capability, politics, and power; and (3) distracting performativity dynamics in reporting. The paper concludes that SDG 6.5.1 is an example of a 'fantasy artefact', and that in all countries in this study, IWRM institutions are failing to address fundamental and 'wicked' problems in water resources management. We find little evidence that these numbers, or the survey that gives rise to them, drive meaningful reflection on the aims or outcomes of IWRM. Instead, they tend to hide the actually-existing political and institutional dynamics that sit behind the complexity of the global water crisis.

IntroductionLow grade serous ovarian carcinoma (LGSOC) is a rare subtype of ovarian cancer (OC) that is challenging to treat due to its relative chemoresistance. Given that LGSOC patients often recur in the peritoneal cavity, novel intraperitoneal (IP) chemotherapy should be explored. Pressurized intraperitoneal aerosolized chemotherapy (PIPAC) is a method that has demonstrated peritoneal disease control in cancers with peritoneal metastases.MethodsNCT04329494 is a US multicenter phase 1 trial evaluating the safety of PIPAC in recurrent ovarian, uterine, and GI cancers with peritoneal metastases. This analysis describes the outcomes of a sub-cohort of four LGSOC patients treated with IP cisplatin 10.5 mg/m2, doxorubicin 2.1 mg/m2 PIPAC q4-6 weeks. Primary endpoints included dose-limiting toxicities (DLT) and incidence of adverse events (AE). Secondary endpoints were progression free survival (PFS) and treatment response based on radiographic, intraoperative, and pathological findings.ResultsFour patients with LGSOC were enrolled of which three were heavily pretreated. Median prior lines of therapy was 5 (range 2-10). Three patients had extraperitoneal metastases, and two patients had baseline partial small bowel obstructive (SBO) symptoms. Median age of patients was 58 (38-68). PIPAC completion rate (≥2 PIPACs) was 75%. No DLTs or Clavien-Dindo surgical complications occurred. No G4/G5 AEs were observed, and one G3 abdominal pain was reported. One patient had a partial response after 3 cycles of PIPAC and completed an additional 3 cycles with compassionate use amendment. Two patients came off study after 2 cycles due to extraperitoneal progressive disease. One patient came off study after 1 cycle due to toxicity. Median decrease in peritoneal carcinomatosis index between cycles 1 and 2 was 5.0%. Ascites decreased in 2 out of 3 patients who had ≥2 PIPACs. Median PFS was 4.3 months (1.7-21.6), median overall survival was 11.6 months (5.4-30.1), and objective response rate was 25%.ConclusionPIPAC with cisplatin/doxorubicin is well tolerated in LGSOC patients without baseline SBO symptoms. IP response was seen in 2 out of 3 patients that completed ≥2 PIPAC cycles. Further study of PIPAC for patients with recurrent disease limited to the IP cavity and with no partial SBO symptoms should be considered.

Bizarre parosteal osteochondromatous proliferations, also known as Nora’s lesions, are rare benign tumors with a high recurrence rate. They are often difficult to identify because of their similar appearance to other tumors. We describe a 25-year-old healthy female patient with bizarre parosteal osteochondromatous proliferations in an uncommon location on the pelvic ilium, presenting with unique clinical findings of abdominal pain and femoral paresthesia and showing atypical radiographic findings. To the best of our knowledge, this is one of the very few cases ever reported in the literature of Nora’s lesion in this particular location and possibly the first case ever with this specific presentation. The lesions’ radiographic images, combined orthopedic and general surgery procedures, and histological analysis are detailed. The patient’s continued 4-year follow-up has demonstrated no symptoms or evidence of recurrence.

BackgroundThe rise of depression, anxiety, and suicide rates has led to increased demand for telemedicine-based mental health screening and remote patient monitoring (RPM) solutions to alleviate the burden on, and enhance the efficiency of, mental health practitioners. Multimodal dialog systems (MDS) that conduct on-demand, structured interviews offer a scalable and cost-effective solution to address this need.ObjectiveThis study evaluates the feasibility of a cloud based MDS agent, Tina, for mental state characterization in participants with depression, anxiety, and suicide risk.MethodSixty-eight participants were recruited through an online health registry and completed 73 sessions, with 15 (20.6%), 21 (28.8%), and 26 (35.6%) sessions screening positive for depression, anxiety, and suicide risk, respectively using conventional screening instruments. Participants then interacted with Tina as they completed a structured interview designed to elicit calibrated, open-ended responses regarding the participants' feelings and emotional state. Simultaneously, the platform streamed their speech and video recordings in real-time to a HIPAA-compliant cloud server, to compute speech, language, and facial movement-based biomarkers. After their sessions, participants completed user experience surveys. Machine learning models were developed using extracted features and evaluated with the area under the receiver operating characteristic curve (AUC).ResultsFor both depression and suicide risk, affected individuals tended to have a higher percent pause time, while those positive for anxiety showed reduced lip movement relative to healthy controls. In terms of single-modality classification models, speech features performed best for depression (AUC = 0.64; 95% CI = 0.51–0.78), facial features for anxiety (AUC = 0.57; 95% CI = 0.43–0.71), and text features for suicide risk (AUC = 0.65; 95% CI = 0.52–0.78). Best overall performance was achieved by decision fusion of all models in identifying suicide risk (AUC = 0.76; 95% CI = 0.65–0.87). Participants reported the experience comfortable and shared their feelings.ConclusionMDS is a feasible, useful, effective, and interpretable solution for RPM in real-world clinical depression, anxiety, and suicidal populations. Facial information is more informative for anxiety classification, while speech and language are more discriminative of depression and suicidality markers. In general, combining speech, language, and facial information improved model performance on all classification tasks.

ABSTRACTIn the last decade, the European Commission (EC) developed an ambitious strategy to promote RRI across the Horizon 2020 Framework Programme for Research and Innovation (H2020). This effort resulted in a significant number of European-funded projects that substantially expanded the available knowledge of the theory, methods and implementation of RRI. However, various evaluations and studies revealed a limited and diffuse implementation of the concept. In this article, we aim to shed some light on this matter with a study covering eight programme lines of H2020 (ERC, MSCA, LEIT, FOOD, ENV, SEC, WIDENING and EURATOM). We employ an extensive policy document analysis and 112 semi-structured interviews carried out with various stakeholders. We argue that the limited implementation of RRI in H2020 is the result of conflicts with existing values, science cultures, economic objectives, restricted resources for its implementation and a lack of clarification around what RRI means.

ABSTRACTHow does the Social Lab methodology support participatory research? This paper provides an evidence-based analysis of experiences of 19 implemented Social Labs applying experiential learning cycles on the question of how to induce Responsible Research and Innovation in the Horizon2020 research funding scheme of the European Commission and beyond. It looks at the potentials of Social Labs to allow participation in research and innovation addressing societal challenges and contrasts empirical results with the theoretical conceptualisation of a scientific Social Lab methodology. It discusses drivers and barriers of engagement, and provides evidence for the impacts of experimental engagement on participation in the context of the labs, substantiated by concrete examples from some of these labs.

Abstract Objective Currently, there is no standard adjuvant treatment protocol for localized uterine leiomyosarcoma (uLMS) as clinical trials to address this question have been retrospective, underpowered, or undermined by slow accrual rates. The aim of this study is to determine the benefit of adjuvant chemotherapy for uLMS. Methods We reviewed the medical records of localized uLMS patients who had underwent adjuvant therapy after upfront surgery between 2000 and 2020. The cases were blinded for review. We evaluated the influence of various clinical characteristics and different types of adjuvant therapies on specific outcomes. Results Sixty‐eight patients (median age: 50 years) were included for analysis. Forty of 68 (58.8%) patients received adjuvant chemotherapy +/− radiation therapy and 25 patients (38.6%) did not receive any adjuvant therapy. At a median follow‐up time of 43.3 months, 45 patients (66.1%) had relapsed disease. The median disease‐free survival (mDFS) for all patients was 23.1 months. Patients who received any adjuvant treatment (chemotherapy and/or radiation) trended toward a longer mDFS compared with those who did not receive any adjuvant therapy (29.7 vs. 14.1 months, p = 0.26). Patients who received adjuvant chemotherapy alone had a longer, but nonstatistically significant mDFS compared with those who did not receive any adjuvant treatment (22.2 vs. 14.1 months, p = 0.18). Additionally, univariate analysis found that tumor size large than 10 cm, and a mitotic rate >10/10hpf were independent prognostic factors for worse DFS. Conclusions Though DFS was more favorable among those who received adjuvant therapy, it was not statistically significant, and thus based on this data adjuvant therapy for resected uLMS is still in question.

BackgroundCurrent depression, anxiety, and suicide screening techniques rely on retrospective patient reported symptoms to standardized scales. A qualitative approach to screening combined with the innovation of natural language processing (NLP) and machine learning (ML) methods have shown promise to enhance person-centeredness while detecting depression, anxiety, and suicide risk from in-the-moment patient language derived from an open-ended brief interview.ObjectiveTo evaluate the performance of NLP/ML models to identify depression, anxiety, and suicide risk from a single 5–10-min semi-structured interview with a large, national sample.MethodTwo thousand four hundred sixteen interviews were conducted with 1,433 participants over a teleconference platform, with 861 (35.6%), 863 (35.7%), and 838 (34.7%) sessions screening positive for depression, anxiety, and suicide risk, respectively. Participants completed an interview over a teleconference platform to collect language about the participants’ feelings and emotional state. Logistic regression (LR), support vector machine (SVM), and extreme gradient boosting (XGB) models were trained for each condition using term frequency-inverse document frequency features from the participants’ language. Models were primarily evaluated with the area under the receiver operating characteristic curve (AUC).ResultsThe best discriminative ability was found when identifying depression with an SVM model (AUC = 0.77; 95% CI = 0.75–0.79), followed by anxiety with an LR model (AUC = 0.74; 95% CI = 0.72–0.76), and an SVM for suicide risk (AUC = 0.70; 95% CI = 0.68–0.72). Model performance was generally best with more severe depression, anxiety, or suicide risk. Performance improved when individuals with lifetime but no suicide risk in the past 3 months were considered controls.ConclusionIt is feasible to use a virtual platform to simultaneously screen for depression, anxiety, and suicide risk using a 5-to-10-min interview. The NLP/ML models performed with good discrimination in the identification of depression, anxiety, and suicide risk. Although the utility of suicide risk classification in clinical settings is still undetermined and suicide risk classification had the lowest performance, the result taken together with the qualitative responses from the interview can better inform clinical decision-making by providing additional drivers associated with suicide risk.

Squamous cell carcinoma of the ovary (SCC) is a rare and aggressive disease and optimal treatment is unknown. Here we report the case of a 29- year-old woman who presented with abdominal pain and was ultimately found to have a multi-septate, gas containing pelvic mass with mixed fat, soft tissue, and calcified components concerning for a ruptured teratoma with fistulization to the distal ileum and cecum on imaging. Operative findings included a 20 cm pelvic mass arising from the right ovary with frank invasion into the ileum and cecum and dense adhesion to the anterior abdominal wall on surgical exploration. Pathologic specimens were remarkable for stage IIIC SCC of the ovary arising in a mature teratoma, with a tumor proportion score of 40%. She progressed on first line treatment with cisplatin, paclitaxel and pembrolizumab as well as second line treatment with gemcitabine and vinorelbine. She died nine months after her initial diagnosis.

Rhee, Pokrovskaya et al. utilize 3D electron microscopy of mouse jugular vein puncture wounds to reveal thrombi structured around localized, nucleated platelet aggregates that produced a vaulted thrombus capped by extravascular platelet adherence. As a result, the authors propose a “Cap and Build” paradigm of primary hemostasis.

Wolfram syndrome is a rare genetic disorder largely caused by pathogenic variants in the WFS1 gene and manifested by diabetes mellitus, optic nerve atrophy, and progressive neurodegeneration. Recent genetic and clinical findings have revealed Wolfram syndrome as a spectrum disorder. Therefore, a genotype-phenotype correlation analysis is needed for diagnosis and therapeutic development. Here, we focus on the WFS1 c.1672C>T, p.R558C variant, which is highly prevalent in the Ashkenazi Jewish population. Clinical investigation indicated that patients carrying the homozygous WFS1 c.1672C>T, p.R558C variant showed mild forms of Wolfram syndrome phenotypes. Expression of WFS1 p.R558C was more stable compared with the other known recessive pathogenic variants associated with Wolfram syndrome. Human induced pluripotent stem cell–derived (iPSC-derived) islets (SC-islets) homozygous for WFS1 c.1672C>T variant recapitulated genotype-related Wolfram syndrome phenotypes. Enhancing residual WFS1 function through a combination treatment of chemical chaperones mitigated detrimental effects caused by the WFS1 c.1672C>T, p.R558C variant and increased insulin secretion in SC-islets. Thus, the WFS1 c.1672C>T, p.R558C variant causes a mild form of Wolfram syndrome phenotypes, which can be remitted with a combination treatment of chemical chaperones. We demonstrate that our patient iPSC–derived disease model provides a valuable platform for further genotype-phenotype analysis and therapeutic development for Wolfram syndrome.

Hélene Landemore’s Open Democracy challenges today’s democracies to meet their legitimacy deficits by opening up a wide array of participatory opportunities, from enhanced forms of direct democracy, to internet crowdsourcing, to representation through random selection to a citizens’ assembly: “representing and being represented in turn” (p. xvii). Her aim: to replace citizen consent with citizen power. The critics advance both praise and misgivings. Joshua Cohen asks if Landemore's innovations are best understood as supplements or alternatives to the current system. Daniele Cammack argues for the significance of open mass meetings as well as smaller representative bodies. Peter Stone considers citizens’ assemblies inadequate for popular sovereignty. Christopher Achen warns of problems in accurate representation, through both self-selection into the lottery and domination in the discussion. Ethan Lieb argues that particular innovations are useful only in some contexts, and that in each citizens should learn their appropriate role responsibilities. Landemore responds by agreeing, clarifying and rebutting.

Abstract Background Once-daily, single-tablet regimens (STRs) have been associated with improved patient outcomes compared to multi-tablet regimens (MTRs). This study evaluated real world adherence and persistence of HIV antiretroviral therapy (ART), comparing STRs and MTRs. Methods Adult Medicaid beneficiaries (aged ≥ 18 years) initiating ART with ≥ 2 ART claims during the identification period (January 1, 2015–December 31, 2016) and continuous health plan enrollment for a 12-month baseline period were included. For STRs, the first ART claim date was defined as the index date; for MTRs, the prescription fill claim date for the last drug in the regimen was defined as the index date, and prescription fills were required to occur within a 5-day window. Adherence was assessed in 30-day intervals over a 6-month period, with adherence defined as having less than a 5-day gap between fills. Persistence was evaluated as median number of days on therapy and percent persistence at 12 months. Cox Proportional Hazard models were used to evaluate risk of discontinuation, controlling for baseline and clinical characteristics. Results A total of 1,744 (STR = 1290; MTR = 454) and 2409 (STR = 1782; MTR = 627) patients newly prescribed ART had available data concerning adherence and persistence, respectively. Average age ranged 40–42 years. The patient population was predominantly male. Adherence assessments showed 22.7% of STR initiators were adherent to their index regimens over a 6-month period compared to 11.7% of MTR initiators. Unadjusted persistence analysis showed 36.3% of STR initiators discontinued first-line therapy compared to 48.8% for MTR initiators over the 2-year study period. Controlling for baseline demographic and clinical characteristics, MTR initiators had a higher risk of treatment discontinuation (hazard ratio [HR] = 1.6, p

BackgroundEmergency departments (ED) are an important intercept point for identifying suicide risk and connecting patients to care, however, more innovative, person-centered screening tools are needed. Natural language processing (NLP) -based machine learning (ML) techniques have shown promise to assess suicide risk, although whether NLP models perform well in differing geographic regions, at different time periods, or after large-scale events such as the COVID-19 pandemic is unknown.ObjectiveTo evaluate the performance of an NLP/ML suicide risk prediction model on newly collected language from the Southeastern United States using models previously tested on language collected in the Midwestern US.Method37 Suicidal and 33 non-suicidal patients from two EDs were interviewed to test a previously developed suicide risk prediction NLP/ML model. Model performance was evaluated with the area under the receiver operating characteristic curve (AUC) and Brier scores.ResultsNLP/ML models performed with an AUC of 0.81 (95% CI: 0.71–0.91) and Brier score of 0.23.ConclusionThe language-based suicide risk model performed with good discrimination when identifying the language of suicidal patients from a different part of the US and at a later time period than when the model was originally developed and trained.

BackgroundIn patients with resectable colorectal liver metastases (CRLM), the role of pre- and postoperative systemic therapy continues to be debated. Previous studies have shown that circulating tumor DNA (ctDNA) analysis, as a marker of minimal residual disease, is a powerful prognostic factor in patients with nonmetastatic colorectal cancer (CRC). Serial analysis of ctDNA in patients with resectable CRLM could inform the optimal use of perioperative chemotherapy. Here, we performed a validation study to confirm the prognostic impact of postoperative ctDNA in resectable CRLM observed in a previous discovery study.Methods and findingsWe prospectively collected plasma samples from patients with resectable CRLM, including presurgical and postsurgical samples, serial samples during any pre- or postoperative chemotherapy, and serial samples in follow-up. Via targeted sequencing of 15 genes commonly mutated in CRC, we identified at least 1 somatic mutation in each patient's tumor. We then designed a personalized assay to assess 1 mutation in plasma samples using the Safe-SeqS assay. A total of 380 plasma samples from 54 patients recruited from July 2011 to Dec 2014 were included in our analysis. Twenty-three (43%) patients received neoadjuvant chemotherapy, and 42 patients (78%) received adjuvant chemotherapy after surgery. Median follow-up was 51 months (interquartile range, 31 to 60 months). At least 1 somatic mutation was identified in all patients' tumor tissue. ctDNA was detectable in 46/54 (85%) patients prior to any treatment and 12/49 (24%) patients after surgery. There was a median 40.93-fold (19.10 to 87.73, P < 0.001) decrease in ctDNA mutant allele fraction with neoadjuvant chemotherapy, but ctDNA clearance during neoadjuvant chemotherapy was not associated with a better recurrence-free survival (RFS). Patients with detectable postoperative ctDNA experienced a significantly lower RFS (HR 6.3; 95% CI 2.58 to 15.2; P < 0.001) and overall survival (HR 4.2; 95% CI 1.5 to 11.8; P < 0.001) compared to patients with undetectable ctDNA. For the 11 patients with detectable postoperative ctDNA who had serial ctDNA sampling during adjuvant chemotherapy, ctDNA clearance was observed in 3 patients, 2 of whom remained disease-free. All 8 patients with persistently detectable ctDNA after adjuvant chemotherapy have recurred. End-of-treatment (surgery +/- adjuvant chemotherapy) ctDNA detection was associated with a 5-year RFS of 0% compared to 75.6% for patients with an undetectable end-of-treatment ctDNA (HR 14.9; 95% CI 4.94 to 44.7; P < 0.001). Key limitations of the study include the small sample size and the potential for false-positive findings with multiple hypothesis testing.ConclusionsWe confirmed the prognostic impact of postsurgery and posttreatment ctDNA in patients with resected CRLM. The potential utility of serial ctDNA analysis during adjuvant chemotherapy as an early marker of treatment efficacy was also demonstrated. Further studies are required to define how to optimally integrate ctDNA analyses into decision-making regarding the use and timing of adjuvant therapy for resectable CRLM.Trial registrationACTRN12612000345886.

BackgroundBurkholderia pseudomallei is a Gram-negative bacterium found in soil and water in many tropical countries. It causes melioidosis, a potentially fatal infection first described in 1911 in Myanmar. Melioidosis is a common cause of sepsis and death in South and South-east Asia, but it is rarely diagnosed in Myanmar. We conducted a nationwide soil study to identify areas where B. pseudomallei is present.Methodology/principal findingsWe collected soil samples from 387 locations in all 15 states and regions of Myanmar between September 2017 and June 2019. At each site, three samples were taken at each of three different depths (30, 60 and 90 cm) and were cultured for B. pseudomallei separately, along with a pooled sample from each site (i.e. 10 cultures per site). We used a negative binomial regression model to assess associations between isolation of B. pseudomallei and environmental factors (season, soil depth, soil type, land use and climate zones). B. pseudomallei was isolated in 7 of 15 states and regions. Of the 387 sites, 31 (8%) had one or more positive samples and of the 3,870 samples cultured, 103 (2.7%) tested positive for B. pseudomallei. B. pseudomallei was isolated more frequently during the monsoon season [RR-2.28 (95% CI: 0.70-7.38)] and less in the hot dry season [RR-0.70 (95% CI: 0.19-2.56)] compared to the cool dry season, and in the tropical monsoon climate zone [RR-2.26; 95% CI (0.21-6.21)] compared to the tropical dry winter climate zone. However, these associations were not statistically significant. B. pseudomallei was detected at all three depths and from various soil types (clay, silt and sand). Isolation was higher in agricultural land (2.2%), pasture land (8.5%) and disused land (5.8%) than in residential land (0.4%), but these differences were also not significant.Conclusion/significanceThis study confirms a widespread distribution of B. pseudomallei in Myanmar. Clinical studies should follow to obtain a better picture of the burden of melioidosis in Myanmar.

Abstract Background Colorectal cancer is one of the most common cancers worldwide and is associated with high mortality when detected at a later stage. There is a paucity of studies from low and middle income countries to support the cost-effectiveness of colorectal cancer screening. We aim to analyze the cost-effectiveness of colorectal cancer screening compared to no screening in Ukraine, a lower-middle income country. Methods We developed a deterministic Markov cohort model to assess the cost-effectiveness of three colorectal cancer screening strategies [fecal occult blood test (FOBT) every year, flexible sigmoidoscopy with FOBT every 5 years, and colonoscopy every 10 years] compared to no screening. We modeled outcomes in terms of cost per quality-adjusted life-years (QALYs) over a lifetime time horizon. We performed sensitivity analyses on treatment adherence, test characteristics and costs. Analyses were conducted from the perspective of the Ministry of Health of Ukraine. Results The base-case lifetime cost-effectiveness analysis showed that all three screening strategies were cost saving compared to no screening, and among the three strategies, colonoscopy every 10 years was the dominant strategy compared to no screening with standard adherence to treatment. When decreased adherence to treatment was modeled, colonoscopy every 10 years was the most cost-effective strategy with an incremental cost-effectiveness ratio of $843 per QALY compared with no screening. Conclusion Our findings indicate that colorectal cancer screening can save money and improve health compared to no screening in Ukraine. Colonoscopy every 10 years is superior to the other screening modalities evaluated in this study. This knowledge can be used to concentrate efforts on developing a national screening program in Ukraine.

Summary: Background: In southeast Asia, antibiotic prescription in febrile patients attending primary care is common, and a probable contributor to the high burden of antimicrobial resistance. The objective of this trial was to explore whether C-reactive protein (CRP) testing at point of care could rationalise antibiotic prescription in primary care, comparing two proposed thresholds to classify CRP concentrations as low or high to guide antibiotic treatment. Methods: We did a multicentre, open-label, randomised, controlled trial in participants aged at least 1 year with a documented fever or a chief complaint of fever (regardless of previous antibiotic intake and comorbidities other than malignancies) recruited from six public primary care units in Thailand and three primary care clinics and one outpatient department in Myanmar. Individuals were randomly assigned using a computer-based randomisation system at a ratio of 1:1:1 to either the control group or one of two CRP testing groups, which used thresholds of 20 mg/L (group A) or 40 mg/L CRP (group B) to guide antibiotic prescription. Health-care providers were masked to allocation between the two intervention groups but not to the control group. The primary outcome was the prescription of any antibiotic from day 0 to day 5 and the proportion of patients who were prescribed an antibiotic when CRP concentrations were above and below the 20 mg/L or 40 mg/L thresholds. The primary outcome was analysed in the intention-to-treat and per-protocol populations. The trial is registered with ClinicalTrials.gov, number NCT02758821, and is now completed. Findings: Between June 8, 2016, and Aug 25, 2017, we recruited 2410 patients, of whom 803 patients were randomly assigned to CRP group A, 800 to CRP group B, and 807 to the control group. 598 patients in CRP group A, 593 in CRP group B, and 767 in the control group had follow-up data for both day 5 and day 14 and had been prescribed antibiotics (or not) in accordance with test results (per-protocol population). During the trial, 318 (39%) of 807 patients in the control group were prescribed an antibiotic by day 5, compared with 290 (36%) of 803 patients in CRP group A and 275 (34%) of 800 in CRP group B. The adjusted odds ratio (aOR) of 0·80 (95% CI 0·65–0·98) and risk difference of −5·0 percentage points (95% CI −9·7 to −0·3) between group B and the control group were significant, although lower than anticipated, whereas the reduction in prescribing in group A compared with the control group was not significant (aOR 0·86 [0·70–1·06]; risk difference −3·3 percentage points [–8·0 to 1·4]). Patients with high CRP concentrations in both intervention groups were more likely to be prescribed an antibiotic than in the control group (CRP ≥20 mg/L: group A vs control group, p