Diet is a key component of the management of diabetes. Several studies suggest that patients receive insufficient and inadequate information. As a first step for developing an intervention for improving dietary advice in primary care, we aimed to explore patients’ experience of receiving dietary advice; their attitudes towards that advice; their perceived dietary advice needs, and any barriers faced in adopting a diet that supports the management of their diabetes.A qualitative study with three focus groups (20 purposively sampled participants) was conducted with adult primary care patients with Type 2 diabetes in 2016. A semi-structured topic guide was developed from the literature. The focus groups were audio recorded and transcribed. The data were analysed by emergent themes analysis. Data saturation was achieved in the third focus group.The majority of participants were given dietary advice in the form of a generic healthy eating leaflet from a Practice Nurse. Participants had their Haemoglobin A1c (HbA1c) reviewed regularly, but the results seemed not to be linked with review of dietary habits. The test was perceived as being a “pass or fail”, judgmental experience. Participants felt tested but not educated.Individuals with type 2 diabetes seem not to receive dietary advice according to their expectations. Information collected as part of the study can be used to inform the development of interventions aimed at improving dietary advice in this population. Type 2 diabetes is a major health concern worldwide. It is estimated that 8.5% of the world’s adult population was diabetic in 2014, of which 90% were type 2 diabetics . The dirHowever, the condition can be reversed. A recent trial found that 9 out of 10 people who followed a diet and lost over 15 kg put their type 2 diabetes into remission . EffectiCurrent National Institute for Health and Care Excellence (NICE) Guidelines advise that patients should receive structured nutritional education when they are first diagnosed, and this should be reinforced annually. Nutritional education should be provided in a personalised way, tailored to the patient’s particular needs and preferences and should be provided by qualified professionals .Despite these clear recommendations, in the UK, a study , found tEven when dietary advice is given, patients report dissatisfaction with what they perceive as generic lifestyle counselling , a lack Previous studies have focused either on newly diagnosed type 2 diabetics or advice from specific professional groups as part of a larger study on diabetes. This study focuses solely on perceptions of dietary advice from any healthcare professional, for patients with varying lengths of type 2 diabetes. The study aims to explore patients’ experience of the dietary advice they received from Healthcare Professionals in Primary Care; their attitudes towards that advice; their perceived dietary advice needs, and any barriers faced in adopting a diet that supports the management of their diabetes.An interpretive qualitative focus group study was conducted in primary care in England between January and February 2016. A purposive sampling strategy  was usedParticipants were approached through flyers with a reply slip. These flyers were worded in a neutral manner and were directed to all type 2 diabetic patients, who might be interested in discussing diet. No distinction was made in the recruitment, between those who were or were not satisfied with any previous dietary advice that they had received. On receipt of the reply slip, participants were contacted by the researcher to confirm eligibility (adults over the age of 18 with a diagnosis by a doctor of type 2 diabetes), and to explain the aims of the study. Potential participants were provided with a participant information sheet. If participants were willing to participate they were asked to sign a consent form and were subsequently invited to attend one of the focus groups. One individual declined the invitation to participate.A semi-structured topic guide was used in the focus groups, which had been developed from the literature review. The discussions started with a brief introduction of each participant about their diabetes, treatment and its duration. Subsequently, open questions assessed participants’ knowledge on healthy eating and their perception of the importance of the advised diet in the overall management of their diabetes. Follow-up questions were asked afterwards referring to the quality of the healthy eating advice received in primary care.Three focus groups were conducted in January and February 2016, in a private meeting room. Each focus group lasted for one hour. The groups were co-facilitated by an experienced pharmacist (MAA) and one or two other healthcare professionals, who were another pharmacist, a dentist and a retired nurse. The groups were audio recorded, with participants having confirmed agreement for recording. These recordings were then transcribed verbatim and each participant was assigned a participant identity code. The data were analysed manually by emergent themes analysis [The total sample consisted of 20 participants, 11 female and 9 male, aged between 40 and 89 years, across three focus groups. Some participants had been recently diagnosed, whilst others had been managing their conditions for up to 26 years. Treatment plans ranged from diet and lifestyle management only (45%), to oral antidiabetic drugs (40%), and insulin (15%) , someti“From the GP surgery all I have had is an “Eat Well Plate” thing that was out of date anyway. And I followed the advice they gave me when I was first diagnosed and it didn’t work for me anyway.” P1G1Patients desired one-to-one dietary advice, especially those who were on “diet only” as a treatment, and who had been diagnosed more recently. Patients felt that they needed to have a “genuine conversation” with their health providers about diet, rather than a generic leaflet on diet.A small number of patients were referred to local group sessions for dietary advice. Group sessions were seen as more helpful than leaflets, but they were not tailored to patients’ needs, they used the “Eat Well Plate”, were focused mostly on portion control, and took months to get an appointment. Financial cuts caused the cessation of the local group sessions. Most patients felt that regular support group meetings would be beneficial. Some patients had therefore found their own information and support by contacting diabetic or private weight loss organizations.I hadn’t eaten bacon for five years, and he said ‘there is no reason why you shouldn’t eat bacon’, but the information I got first said things like bacon and sausages are processed meat, you don’t want to have too much of it all.” P3G3“The generic eating advice tended to recommend savoury carbohydrates and fruit, which caused confusion for many participants: which types of carbohydrates and sugars, does it matter how food is cooked, and how much is a portion? As a consequence some participants latched on to certain “food rules” without understanding the rationale.Participants were also confused by contradictory dietary messages received from various healthcare professionals and changes in advice over time.“Perhaps more training is needed on this front with diabetic specialist nurses and dieticians, they need to be given more instruction from their mentors or whoever as to what they should and should not be telling people.” P3G2The majority of dietary advice was from Practice Nurses, with very occasional advice from a GP or dietitian. Dietary advice was not included in the six-monthly reviews with Practice Nurses. Patients doubted that Practice Nurses were adequately trained in nutrition. This perception was exacerbated by some nurses who read out advice to patients “textbook style”. One participant was put off by an “un-charming, dictator style” nurse.Rigid “ten minute rule” appointments were not seen as sufficient to allow patients to discuss their diet. Patients desired consultations with healthcare professionals where they could discuss their particular requirements one-to-one and not feel pressured by the time limit.If my figures are ok, she will say fine thank you, good bye basically. But I am happy with that because I have passed the test so to speak, so I can go on to the next one. It’s like going back to school.” P4G2“Participants had regular diabetic reviews every six or twelve months. The cholesterol and Haemoglobin A1C (HbA1c) results were of particular interest to patients, who wanted to know their “numbers”, but were often confused about what a particular number might mean. The numbers seemed detached from their diet and patients wanted an explanation of how they should modify their diet in light of the numbers. Participants clearly felt that their “blood sugar test” was more than a clinical test; they were being tested and judged on their behaviour. In two of the three focus groups participants spontaneously made “school” analogies.If she gave me a number I wouldn’t really know what it meant, was it good, bad or indifferent. As long as she is happy with what I am doing I suppose I am happy with what I am doing. But I know I could do better. It sounds like my old school report, ‘could do better’.” P6G1“You either pass or fail, and if you fail you get the wagging finger.” P3G2“Some patients were satisfied with their regular reviews, but still not with their dietary advice.There was a perception of cost cutting with some reviews having been reduced from six-monthly to annually. Also, blood glucose meters and strips were not available on prescription, which prevented patients from being aware of the impact of their diet on their condition. Many participants felt that their GP surgeries were driven by their bonus instead of their patients’ needs, and they compared it to Scotland and Wales, where they thought that more money was spent per patient.You can always tell a diabetic when they are peering at labels.” P8G1“Participants felt that knowing about food types and portions was not sufficient to enable them to make effective changes to their diets. They wanted to know more about interpreting food labels. Many had learnt from external sources about the dangers of low fat products being high in sugars.But I find it hard to pick an interesting menu all the time, it’s very hard shopping so I do keep to certain items whether they are all ok or not I don’t know.” P4G2“Participants also wanted advice on how to combine foods together as menus and how to modify their existing diet rather than starting from scratch. They found this easier if they were already used to dietary modifications, for example being vegetarian. Many participants found it a challenge to create a varied diet and struggled with the costs of healthy eating.What I found as well is some of the things they recommend you eat are above your budget, things like you can eat are beyond your reach sometimes.” P3G3“Another challenge was fitting in diabetic dietary requirements with other co-morbidities, for example requiring low fibre for Irritable Bowel Syndrome. Preparing healthy food takes time and energy, which was a problem for one participant with fatigue caused by anaemia and another who was not able to stand for long periods of time.“But because like P4G3 I just adore beer I have to really fight hard just to buy a half with a meal rather than a pint, very occasionally I will have a pint.” P1G3Older patients seemed to be the most reluctant to change long-standing dietary patterns that they enjoy and could feel it is too late to change habits even if that meant dying early. Many patients felt they were allowed to deviate from their diet when they were on holiday or during a festivity. They perceived they were entitled to have some treats from time to time, and that healthcare professionals allow them to do so.Some motivations to modify diet were the desire to avoid long-term conditions; fear of long-term consequences and dislike of taking more medicines or being put on insulin.For the majority of participants dietary advice was given in the form of a generic healthy eating leaflet by a Practice Nurse. Although participants had their HbA1c reviewed regularly, the results seemed to not be linked to a review of dietary habits. Participants felt tested but not educated.Participants’ preference was for an individualised approach and a genuine conversation with a healthcare professional, and went as far as to identify the following issues: basic food categories, types of carbohydrates, portion size, recognition of the cost of healthy food for the individual, discussion about compatibility with co-morbidities, interpreting food labels, meal and menu planning and a link between their “blood sugar results” and their diet so that they could modify diet as required.These patient requests are in line with current guidelines , howeverThis study confirms findings from previous research showing that most diabetic patients do not receive dietary advice that is tailored to them as an individual , 12, 14.A previous study  found thThere have been very few in-depth studies in the United Kingdom exploring patients’ views on nutritional advice requirements in primary care. Therefore, this study has added valuable knowledge to this area.The use of qualitative methods enabled the in-depth exploration of patients’ perceptions and experiences, in order to identify the types of dietary advice that they feel they need to enable and empower them to make lasting improvements to their diets and control of their diabetes. The study included participants with varying durations of diabetes, and the setting in a non-healthcare location allowed access for those who are less engaged with healthcare systems.. However, views were consistent across all the focus groups and saturation of themes was achieved in the third focus group. The study was limited to one geographical location due to the self-funded nature of the study. However, flyers were available for people to collect in diverse local settings in order to obtain a maximum demographic diversity, and the study was promoted on the Diabetes UK website for two months; therefore, people outside the location could also attend. A basic level of literacy was required to understand the flyer and participant information sheets and therefore this may have excluded patients with poorer literacy, who may have had different views about the adequacy of dietary advice.Limitations include the relatively low number of participants, which may affect the generalisability of the findingsStandard practice for the delivery of dietary advice for type 2 diabetics should be re-considered. Crucially dietary information should be delivered in an educational manner that genuinely enables patients to apply it to their lives. This study has identified patient requests for both the content of dietary advice and the manner in which advice is given. Further work would be needed to explore the logistics of delivering advice within specific contexts from the perspectives of healthcare professionals.As for research implications, consideration of the themes identified in the analysis was found to be compatible with Bloom’s work  and thisIdeally this individualised educational approach would be delivered within the context of a genuine conversation with a nutritionally trained professional, with sufficient time.Effective dietary advice plays a crucial role in the treatment of diabetes. However, the extent and quality of dietary advice given to individuals with type 2 diabetes, seems to fall short of the standards set in guidelines, and does not meet the requirements of patients. Participants were having their HbA1c reviewed regularly, but the results seemed to not be linked to a review of dietary habits. The test was perceived as being a “pass or fail”, judgmental experience. Participants felt tested but not educated.Dietary advice tended to consist of a generic leaflet on healthy eating and was not tailored to diabetes. Participants expressed a preference for an indvidualised approach and a genuine conversation with a healthcare professional to enable them to understand food types, make appropriate changes to their diets that fitted with their life circumstances, and to be able to adjust diet in response to changes in HbA1c levels.This information on patients’ views about the nature of dietary knowledge and skills that would empower individuals to make improvements to their self-management of diabetes could be used to inform the development of interventions aimed at improving dietary advice in this population.


A tool for measuring neck pain in patients with dizziness is needed to further investigate the relationship between the two symptoms. The objective of this study was to examine the reliability and validity of a hand‐held pressure algometer in measuring pressure pain threshold (PPT) in different cervical regions of dizzy patients.PPT was measured at two bilateral standardized sites of the neck by a trained physiotherapist in 50 patients with dizziness. Intraclass correlation coefficients (ICC) were calculated for intrarater and test–retest reliability. Concurrent validity was assessed by measuring the association between PPT and the American College of Rheumatology (ACR) tender points at each site and with the numeric pain rating scale (NPRS).R = −0.52 to −0.66).Almost perfect intrarater (ICC = 0.815–0.940) and within‐session test–retest (ICC = 0.854–0.906) reliability was found between the measures. On each site, a low PPT predicted a positive ACR tender point at each site (OR = 0.864–0.922). Last, we found a statistical inverse relationship between the PPT and the NPRS (The study shows that a pressure algometer is a reliable tool for measuring PPT in the neck of dizzy patients. Further, the PPT correlates significantly with other subjective measures of pain indicating that it may be a useful tool for further research. The interpretation of pain intensity on such a scale is complicated by the fact that self‐reported pain is affected not only by the level of organic tissue damage but also by psychosocial factors Melzack, . The AmeThe aim of this study was to examine the reliability of a pressure algometer in different cervical regions in patients with dizziness, and its concurrent validity to other measures of pain. We examined the intrarater reliability of three consecutive measurements and the within‐session test–retest reliability of a pressure algometer at the upper and lower neck in patients with dizziness. In addition, we examined the association between PPT, ACR tender points, and NPRS.22.1This study was conducted at a department of otorhinolaryngology, head, and neck surgery of a Norwegian university hospital. The department receives approximately 1,200 patients yearly referred due to dizziness or balance problems. Consecutive patients with dizziness aged 18–67 years were recruited from July to September 2017. Exclusion criteria were physical or language barriers in performing the tests or filling in the study questionnaires. The department is a quaternary referral centre for patients with vestibular schwannomas and for divers investigated for neuro‐otological disorders, and these two patient groups were excluded in order not to bias the results. The study protocol was approved by the Regional Committee for Medical and Health Research Ethics of South‐Eastern Norway (REK 2017/783). Participation was based on written informed consent.2.2The ACR tender point count is a validated method for assessing widespread pain by applying pressure to nine defined bilateral tender points across the body  were recorded at the previously described four cervical sites (UN and LN), starting left at the suboccipital site and ending right on the intertransverse space at C5–C6. Approximately 30 s separated measurement of the same site. After approximately 30 min, two more measurements (PPT4 and PPT5) at each site were recorded using the same procedure.The PPT was measured by a trained physiotherapist, with a Wagner FDX‐25 device  on the upper four ACR tender points. The pressure algometer has linear response to force application between 0 and 1,300 kilopascal (kPa). The device has a 1‐cm2.4no pain and 10 represents the worst imaginable pain.Patients reporting neck pain were asked to rate their neck pain during the two last weeks on an 11‐point scale. The NPRS has previously shown adequate reliability and validity in patients with chronic pain conditions, including neck pain  as described by Bland & Altman . The difference between a subject's measurement and the true value would be expected to be less than 1.96 Sw for 95% of observations. The minimal detectable change (MDC) was calculated at the 90% level with the formula Sw × √2 × 1.64 . There were 19 males (38%) and 31 females (62%). Neck pain was reported by 22 participants (44%). Descriptive statistics are reported in Table 3.1w, and MDC for the intrarater and test–retest reliability are presented in Table Intrarater and test–retest reliability was examined by ICC 1.1. We found that the highest intrarater reliability was obtained between PPT2 and PPT3 in the first session at each site, disregarding the first measurement. There was an almost perfect reliability on all sites between these two measures. The test–retest showed an almost perfect reliability between PPT3 of the first test session and PPT5 at the retest session. The reliability was approximately the same irrespective of whether or not the patients reported neck pain. Performing the same analysis with ICC 1.3 showed no deviations in ICC values, indicating that no systematic errors were present. The ICC values, S3.2p = 0.011, UN right OR = 0.922, 95% CI , p = 0.018, LN left OR = 0.864, 95% CI , p = 0.009, LN right OR = 0.874, 95% CI , p = 0.010. The analysis adjusted for age and gender is shown in Table As PPT2 and PPT3 had the highest reliability, the mean of these two measures was used to examine relationships with ACR tender points and NPRS. Using binary logistic regression, PPT in each of the four sites predicted a positive outcome at the equivalent ACR tender point: UN left, OR = 0.918, 95% CI , R = −0.62, p = 0.002), UN right , LN left , and LN right . The adjusted analysis with multiple linear regression is shown in Table Using linear regression, there was a significant association between PPT and NPRS at UN left  has been found at the suboccipital site in women with chronic neck pain (Ylinen et al., w compared with the overall means indicate that measurement properties were acceptable for intrarater reliability, with the Sw ranging from 19.2 to 37.0 kPa, and for test–retest; ranging from 29.9 to 38.0 at the different sites. No previous studies have examined Sw at these sites, making the interpretation and comparison difficult. The reliability was similar regardless of whether or not patients reported neck pain, indicating that the presence of symptoms does not adversely affect the reliability of the results. The MDC for the intrarater session ranged from 44.5 to 86.1 kPa and from 69.4 to 88.2 kPa in the test–retest session at the different sites. The differences between the two sessions were smaller in our study, compared with the study by Walton et al. (The highest intrarater reliability was found between the second and third measurements, and the highest test–retest reliability was found between the last two measurements. Previous studies using other sites show somewhat conflicting results with regard to ICC comparison between trials (Balaguier, Madeleine, & Vuillerme, n et al. , which fThe ACR tender point count is a well‐known clinical examination often used in patients with widespread pain (Limer et al., There was a significant inverse association between PPT and NPRS in the patients reporting neck pain. These findings are interesting because PPT is influenced by both the examiner's execution of the test and the patient's interpretation, whereas the NPRS is only affected by the patient's own interpretation of pain intensity. Thus, our results suggest that the PPT associates with the patient's own experience of pain, which is an important observation when considering the use of PPT in further studies. The PPT has the additional advantage to being able to differentiate regions in the neck, which is difficult with the NPRS. The associations between PPT, ACR tender points, and NPRS were not significantly influenced by age or gender. Males and females have been found to differ with regard to pain thresholds (Fillingim, King, Ribeiro‐Dasilva, Rahim‐Williams, & Riley, A potential limitation of the study was that the time interval between the test–retest conditions was only 30 min and that there was only one examiner. The result cannot be generalized to longer time intervals or tests made by different examiners. The strength of this study was the sufficient sample size and that there were no systematic errors in the measurements, making the results more applicable. Using the ACR tender points as measurement sites for PPT enabled us not only to examine the relationship between the two methods but also to measure pain at standardized sites in different regions of the neck.4.1This study shows that a pressure algometer can be used to reliably measure PPT in both the upper and lower cervical regions in patients suffering from dizziness, indicating that it may be a useful tool for further research on the level of pain threshold in the neck in this patient group. The results may contribute to future studies of the relationship between neck pain and dizziness.


Introduction: Postoperative delirium and pain are common complications in adults, and are difficult both to prevent and treat. Obstructive sleep apnea (OSA) is prevalent in surgical patients, and has been suggested to be a risk factor for postoperative delirium and pain. OSA also might impact pain perception, and alter pain medication requirements. This protocol describes an observational study, with the primary aim of testing whether OSA is an independent predictor of postoperative complications, focusing on (i) postoperative incident delirium and (ii) acute postoperative pain severity. We secondarily hypothesize that compliance with prescribed treatment for OSA  might decrease the risk of delirium and the severity of pain.Methods and analysis: We will include data from patients who have been enrolled into three prospective studies: ENGAGES, PODCAST, and SATISFY-SOS. All participants underwent general anesthesia for a non-neurosurgical inpatient operation, and had a postoperative hospital stay of at least one day at Barnes Jewish Hospital in St. Louis, Missouri, from February 2013 to May 2018.  Patients included in this study have been assessed for postoperative delirium and pain severity as part of the parent studies. In the current study, determination of delirium diagnosis will be based on the Confusion Assessment Method, and the Visual Analogue Pain Scale will be used for pain severity. Data on OSA diagnosis, OSA risk and compliance with treatment will be obtained from the preoperative assessment record. Other variables that are candidate risk factors for delirium and pain will also be extracted from this record. We will use logistic regression to test whether OSA independently predicts postoperative delirium and linear regression to assess OSAs relationship to acute pain severity. We will conduct secondary analyses with subgroups to explore whether these relationships are modified by compliance with OSA treatment. It is estimated that 20% of the general population suffers from OSA3, and among adults with OSA, up to 75% are unaware of the diagnosis5. Of relevance to perioperative medicine, there is also a high OSA prevalence in surgical patients3. In common with the general population, many of these patients are unaware they have OSA7. Also of note, prevalence of sleep apnea often varies by type of surgery; for example, prevalence in the bariatric surgery population is estimated to be 70%9. OSA prevalence combined with ignorance of diagnosis is cause for concern given the wide range of health consequences. OSA has been causally implicated in an assortment of both acute and chronic disorders. Acutely, OSA has been associated with disrupted sleep, tiredness, and episodic hypoxia and hypercapnia during sleep11. Chronically, OSA has been linked to a multitude of co-morbidities, including ischemic heart disease and stroke12, hypertension14, arrhythmias16, aortic dissection18, chronic fatigue19, pulmonary hypertension21, diabetes22, and respiratory acidosis with compensatory metabolic alkalosis24.Obstructive sleep apnea (OSA) is the most common form of sleep-disordered breathing. OSA is characterized by repetitive, functional collapse of the airway leading to cyclical decrements or cessations of airflow during sleep26. For example, following various surgical procedures, patients with OSA probably have more respiratory, cardiac, and neurologic complications30, as well as increased postoperative infections31. Unsurprisingly surgical patients with OSA therefore have a higher transfer rate to the ICU28, increased stay in the ICU31, and increased overall length of hospital stay28.OSA is becoming a growing concern in the perioperative period, as there is increasing evidence linking OSA to adverse postoperative outcomes34. A causal link between OSA and delirium would be clinically important given the negative outcomes associated with postoperative delirium. In the DSM-5, delirium is defined as a disturbance in attention, awareness, and cognition that develops over a short period of time and over the course of a day, fluctuates in severity35. In older adults, the incidence of postoperative delirium ranges from 10–70%, depending on the type of surgery36. Patients who experience postoperative delirium often require an extended stay in the intensive care unit37, subsequently report decreased quality of life38, and might be at increased risk for accidental falls, long-term cognitive decline and death after hospital discharge39. Thus, postoperative delirium is associated with a considerable burden on patients and their families, and an increase to society in the overall cost of healthcare41.Of particular relevance to the research focus of this protocol, certain aspects of OSA such as recurrent hypoxemia, systemic inflammation, and sleep disruption have been associated with altered pain processing and incident delirium47, including interleukin-1β, interleukin-6, and tumor necrosis factor, all of which might induce excessive sensitivity to pain48. Consistent with these studies clinical evidence, including compelling data from burn victims, suggests that interrupted and inadequate sleep promotes hyperalgesia49. Furthermore, Khalidet al. showed that treatment with continuous positive airway pressure (CPAP) in adults with OSA dampened their sensitivity to painful stimuli50. Thus, whether or not people with OSA have increased pain sensitivity might to some extent depend on how effectively they are treated. To complicate matters further, people with OSA, especially if they experience episodic hypoxemia during sleep, reportedly have increased susceptibility to the respiratory depressant effects of opioid medications52. Thus, since opioids are the mainstay of therapy for severe postoperative pain, it can be especially difficult to provide safe and adequate analgesia to surgical patients with OSA.The reported impact of OSA on postoperative pain and pain perception poses further challenges to clinicians and patients. Adequate postoperative analgesia is an important component of recovery, and pain negatively impacts quality of life. Mechanistic evidence in various populations suggests that sleep deprivation promotes up-regulation of cytokinesThe objectives of this study are to investigate further the relationships between OSA on the one hand, and common postoperative complications such as pain and delirium on the other hand. We hypothesize that patients with OSA experience more severe postoperative pain and have a higher incidence of postoperative delirium. We further hypothesize these negative outcomes might be mitigated by compliance with OSA treatment.This protocol describes a retrospective study, investigating the relationship between OSA as a risk factor, and postoperative delirium and acute postsurgical pain severity as adverse outcomes. The three parent studies from which the data are being obtained for the current study have all been approved by the Human Research Protection Office (HRPO) at Washington University, and patients enrolled in all three studies provided written informed consent. The HRPO has also provided approval for this current study. Data will be aggregated from the Systematic Assessment and Targeted Improvement of Services Following Yearlong Surgical Outcomes Surveys Study ; the Electroencephalography Guidance of Anesthesia to Alleviate Geriatric Syndromes study ; and the Prevention of Delirium and Complications Associated with Surgical Treatments study .57.The PODCAST trial investigated if a single subanesthetic dose of ketamine could decrease postoperative incident delirium. There was no significant difference in delirium incidence across the three treatment groups . Additionally, there was no apparent difference in reported pain between the three groups. However, to be conservative, we will adjust for PODCAST group allocation in the regression models in the current study. To control for potential effects of the ENGAGES intervention , we will adjust our regression model for this randomization. For greater detail regarding the three parent studies, please review previously published protocols and literatureWe will include an estimated 1,500 patients in our primary analysis. Of the 672 patients randomized for the multicenter PODCAST trial, we will include only patients recruited from Washington University in St. Louis. The study population will be comprised of roughly 100 patients from PODCAST and an estimated 1,200 patients from the ENGAGES trial. SATISFY-SOS is a large scale outcomes survey study, and we will be using a subset of roughly 200 patients enrolled in SATISFY-SOS who completed daily delirium and pain assessments during hospital stay.Patients ≥ 18 years who underwent general anesthesia for a non-neurosurgical inpatient operation at Barnes Jewish Hospital in St. Louis, Missouri, from February 2013 to May 2018, will be included in our analysis. Patients had a postoperative hospital stay of at least one day. The main outcomes of interest will include postoperative delirium and pain, assessed daily until postoperative day 3. The primary aims of this study are to investigate whether OSA is an independent predictor of postoperative delirium and acute postsurgical pain severity. We will conduct secondary analyses with subgroups to explore whether these associations are modified by compliance with OSA treatment. We are also interested in evaluating if OSA status is related to postoperative opioids given during hospital stay. Thus, we will secondarily explore the relationship between OSA risk and total inpatient opioid use through postoperative day 3.60.This protocol is compliant with published guidelines for observational study protocols, and the conduct and reporting of this study will adhere to the RECORD and STROBE guidelines for observational studiesInclusion criteria:(i) Enrollment in the SATISFY-SOS, ENGAGES, or PODCAST study;(ii) Postoperative stay of at least 1 day following surgery at Barnes Jewish Hospital(iii) General anesthesia for elective surgical proceduresExclusion criteria:(i) Neurosurgery(ii) Age <18i. Baseline Data. Patients undergoing elective surgery are routinely screened at the Center for Preoperative Assessment and Planning at Barnes Jewish Hospital in St. Louis, Missouri, where detailed medical history is collected and screening tests are administered, including the STOP-BANG  test for OSA risk. Baseline characteristics will be extracted via electronic chart review and will include but are not limited to: age, sex, race, ethnicity, smoking history, alcohol use (average per week), STOP-BANG criteria, OSA status, and pre-existing medical conditions.ii. Delirium assessment method. Delirium is one of the primary outcomes of this study and will be determined using validated delirium assessments implemented by a small group of rigorously trained research assistants. Delirium for the parent studies was assessed predominantly using the Confusion Assessment Method (CAM)62. If patients were unwilling to complete the full CAM, the 3D-CAM was used. The 3D-CAM was developed as a method to more efficiently screen patients for delirium. It consists of a subset of the questions used in the CAM, as well as CAM scoring items that are based on patient behavior . With this approach, the 3D-CAM is intended to only take 3 minutes. For critically ill patients, most often found in the intensive care unit, the CAM-ICU was used to assess delirium63.In the PODCAST trial, Delirium was assessed twice daily (morning and afternoon with at least 6 hours between assessments), while in the other trials, delirium was assessed once daily between 1pm and 8pm. We will include only the afternoon delirium assessments from PODCAST patients so all patients included in analysis were assessed during the same time frame. Although patients were assessed for delirium on postoperative day zero at least 2 hours after surgery, we will not include this assessment because of potential residual general anesthetic effects. We will adjust for the use of certain medications, such as preoperative midazolam, median volatile anesthetic concentration , intraoperative ketamine, and intraoperative opioids .The presence of delirium will be defined as a positive CAM during any postoperative assessment through postoperative day 3. In order to qualify for a diagnosis of delirium, the following three criteria must be met: 1) either acute onset OR a fluctuating course; 2) inattention; and 3) either disorganized thinking OR altered level of consciousness. A patient will be considered positive for delirium if the patient is recorded to have had a single instance of delirium during their postoperative stay.iii. Pain Assessment Method. Pain during hospital stay will be assessed using the Visual Analogue Scale (VAS), a validated pain assessment instrument that has been widely used in adult populations65. Patients are asked to indicate on a line 100mm in length the severity of their pain in three different situations: 1) at rest, 2) taking a deep breath or coughing, and 3) moving . The patient’s mark is then measured with a ruler and recorded in mm. For our analysis, we will incorporate the highest pain score recorded on any postoperative assessment as our value of interest. As postsurgical pain is often dependent on the type of surgery, we will adjust for type of surgery in our statistical model, as well as other confounding variables described in the methods below.iv. OSA Classification. For the primary analysis  and information on OSA status for approximately 1,500 patients. We estimate that 300 (~20%) of these patients will have incident postoperative delirium. We will have patient reported pain outcomes for all participants. We will use logistic and linear regression, including potential confounder variables, to test for an independent association between OSA as a risk factor and postoperative delirium and pain severity as outcomes of interest. We estimate that it will be appropriate to include up to 25 variables in each of the regression models.67. REDCap is a secure, web-based application designed to support data capture for research studies, providing: 1) an intuitive interface for validated data entry; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for importing data from external sources.All electronic data collected during this study, as well as the SATISFY-SOS, ENGAGES, and PODCAST databases, are hosted on a firewall-secured network server. This server is managed and maintained by the IT team of the Department of Anesthesiology, and is securely housed behind two locked doors in the departmental offices. The Project Informaticist, Data Manager, and Director(s) are the only individuals with full access to these password-protected and encrypted databases. Delirium and pain assessments are first completed using paper surveys, which are then securely stored in locked cabinets within the department. Results are entered into a Research Electronic Data Capture (REDCap) tool hosted at Washington University School of Medicine in St. Louisi. Statistical considerations. Continuous variables will be graphically evaluated with histograms, boxplots, and q-q plots, and numerically with measures of skewness, kurtosis, and Kolmogorov-Smirnov tests. Outliers will be excluded, and approximate normality will be ensured before parametric statistics are applied. Perioperative variables will be described with mean ± SD, median [IQR], and numbers/proportions, as appropriate. Differences in patient and other perioperative factors between groups will be evaluated with chi-squared, t-tests, ANOVA, Kruskal-Wallis, and/or Wilcoxon-Mann-Whitney tests, as appropriate. Multiple imputation methods will be used for patients’ missing variables, but participants with missing outcomes will be excluded from analysis.ii. Delirium. Logistic Regression will be used to assess the relationship between OSA as a risk factor and incident postoperative delirium as an outcome. For our analyses, we will include no more than 1 variable for every 10 outcomes. With an estimated incident postoperative delirium rate of 20%, we plan to include up to 25 pre-specified candidate predictor variables in the primary regression models, including the most clinically relevant interaction terms. Variables for our primary analysis have been selected based on existing evidence, and will likely include: OSA status; Age; Sex; Type of Surgery; Charlson Comorbidity Index; Procedural Cardiac Risk; ASA physical status; Alcohol use; preoperative midazolam use; median volatile anesthetic concentration ; intraoperative ketamine use; intraoperative opioids ; and anesthesia time in minutes. We will also include a history of any of the following comorbidities: COPD or Asthma; Stroke; Dementia or Mild Cognitive Impairment; Visual or hearing Impairment; Depression or Anxiety; Chronic Pain; and Diabetes Mellitus. We hope to include BMI and age independently of the OSA risk classification since they are continuous variables, and their inclusion in the regressions might improve the models. We also hope to include the variable ‘tiredness’ in the models since this particular symptom could plausibly independently predict both delirium and pain. However, there may be statistical limitations (i.e. collinearity) preventing inclusion of some of these variables. If so, we may exclude some variables and describe our adjustments in the manuscript.iii. Pain. Linear Regression will be used to examine OSA’s potential relationship to postoperative pain. For this analysis, the outcome is continuous rather than binary, and will apply to all 1,500 patients. It will be reasonable to include up to 25 pre-specified candidate predictor variables in the linear regression models, including interaction terms. As risk factors for delirium and pain are overlapping, the same candidate predictor variables will be used in this regression. Sensitivity analyses will be conducted to address limitations regarding pain. Since it is important to consider delirious patients might be unable to report pain accurately, we plan to conduct a sensitivity analysis with pain as the outcome, excluding all the patients who were diagnosed with postoperative delirium. We also hope to explore any potential relationship between OSA risk and total postoperative opioids given during hospital stay . Additionally, since our primary analysis will not consider duration of severe pain or distinguish between rest and provoked pain, we plan to conduct a sensitivity analysis with median provoked pain during hospital stay (up to postoperative day 3) as the outcome. The responses to two VAS questions (pain when (i) taking a deep breath or coughing, and (ii) moving ) will be compiled to represent provoked pain during hospital stay.We expect that patients with a high risk of OSA will experience greater postoperative pain severity, and have a higher risk for postoperative delirium following surgical procedures. For our secondary analyses, we propose that these adverse outcomes might be modified by compliance with CPAP treatment. We predict patients with diagnosed OSA who do not use prescribed CPAP will experience a higher incidence of delirium and increased pain. We also expect a step-wise increase in these adverse outcomes (delirium incidence and pain severity) when analyzing patients based on their STOP-Bang assessment groups (high risk vs. intermediate risk vs. low risk).OSA is a common and frequently undiagnosed perioperative problem. This observational study will help to clarify whether or not OSA is an independent predictor of postoperative incident delirium and acute postoperative pain. Secondary analyses may show if these adverse outcomes might be modified by compliance with OSA treatment.34. This study will have important strengths compared to the existing literature; most notably the database including routine structured preoperative screening for OSA, and postoperative delirium and pain assessments on a broad surgical population. The researchers who collected data for this study were all expertly trained in administering delirium and pain assessments. In an effort to improve methodological rigor, we have pre-specified independent variables for regression models, and have described our statistical analyses.In this study, we will attempt to replicate the reported finding showing that OSA is an independent predictor of postoperative delirium and acute postsurgical pain severityThis study will also have important limitations. Although we will have thorough medical histories routinely collected from preoperative clinic assessments, we will not know severity of OSA or other comorbidities. In common with any observational study, this study will be unable to distinguish association from causation. In particular, if we do find in this study that OSA is associated with either increased delirium incidence or pain severity, we will not be able to determine (i) whether OSA is causally implicated or (ii) whether there is another explanatory factor associated with both OSA and these outcomes. Regarding the outcome of delirium, this study will address on the crude association with incident delirium as a binary outcome. It might be more important to focus on either the duration or severity of delirium. Regarding pain, it is important to consider that delirious patients might be unable to report pain accurately. This limitation is common to all studies evaluating postoperative pain. To mitigate this to an extent, we plan to conduct a sensitivity analysis with highest VAS pain score as the outcome, excluding all the patients who were diagnosed with postoperative delirium. Also in relation to pain, our primary outcome will be most severe pain reported in postoperative days 1–3. This approach will not consider duration of severe pain or distinguish between rest and provoked pain. To mitigate this to an extent, we plan to conduct a sensitivity analysis exploring median provoked pain through postoperative day 3 as the outcome. Additionally, it will be important to include analgesic medication as potential confounders in the regression analyses, and accurate data on these might not be available.68, it is possible that certain opioids (e.g. morphine) are safer than others  for patients with OSA in terms of their propensity to provide analgesia rather than to cause respiratory depression. We hope to use the foundational work proposed in this observational study to guide the design of such trials and clinical plans, with the goals of reducing postoperative delirium and acute postoperative pain severity for the large number of patients at risk due to OSA.In conclusion, while likely providing stronger evidence regarding the impact of OSA on postoperative delirium and pain, this study might also discern interventional strategies for treatment and prevention. For example, in relation to delirium, we could test perioperative delirium prevention bundles in patients with OSA or we could investigate whether preoperative initiation of CPAP treatment decreases this complication. The role of CPAP therapy in relation to improved analgesia should also be clarified. Regarding pain, we could further develop analgesic plans especially for surgical patients with OSA, such as emphasizing regional analgesia or non-opioid analgesics. We could also implement procedures intended to improve the safety of patients with OSA receiving respiratory depressant medications in the perioperative period. With emerging knowledge about biased signaling with opioidsThe data referenced by this article are under copyright with the following copyright statement: Copyright: © 2018 Strutz P et al.Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).No data is associated with this article. I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Thank you for submitting this interesting study protocol aiming to investigate the relationship between OSA and postoperative delirium as well as pain severity. This protocol targets an important and clinically meaningful research question, and is overall well written and designed. We invite the authors to consider the following questions and suggestions:Please address the question as to whether the patients are studied from a historical cohort. If so, how do you control for the effects of previously studied interventions ) ? How do you discriminate between lingering medication effects and delirium early on during postoperative day 1?We suggest considering to additionally use the SPOSA score which was recently published in order to classify patients according to OSA risk . Advantage is you can apply this to bigger observational cohorts without measuring neck circumference etc. Maybe you can better justify the patient flow. The SATISFY-SOS study aims to enroll 36000 patients. Please provide information that helps understand as to why you expect to have complete data for ~1300 patients only. Looks like you also want to use data from two other studies additionally with enrollment targets of additional 600 and 1200 patients? How do you account for patients with undiagnosed OSA that may have been treated with CPAP for other respiratory diseases such as COPD, acute lung injury, neuromuscular disorders etc.? Confounder control: Please consider including comorbidities such as COPD, asthma and neuromuscular disorders in the context of higher risk for intraoperative hypoxemia or respiratory failure; duration of surgery/time under anesthesia in addition to surgery type and some type of measure for procedural complexity such as a risk quantification score  into your statistical modelFor sure you should control for age and BMIConsider including pre-prescribed drugs especially neuroleptics/antipsychotics if you can get these dataPerhaps also consider accounting for different anesthetic protocols used during surgery such as TIVAs, volatile anesthetics, opioid use, ketamine use Did you consider using multiple imputation methods for missing data?We like the suggested sensitivity analyses.Statistical models:  We have read this submission. We believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however we have significant reservations, as outlined above. Thank you, Dr. Eikermann and Dr. Timm, for your feedback on our study protocol.  We sincerely appreciate your time and thoughtful suggestions.  Along with submitting our revised protocol, we directly address your suggestions and questions below.  Please address the question as to whether the patients are studied from a historical cohort. If so, how do you control for the effects of previously studied interventions ) ?We have included more details about our cohort under the “Study Design” section.  Briefly, yes the patients are studied from a historical cohort, and we have improved our model to adjust for randomization group from the previously studied interventions.  Although the PODCAST trial did not have significant findings, we agree that controlling for group allocation provides a more robust analysis. How do you discriminate between lingering medication effects and delirium early on during postoperative day 1?We have added details regarding our delirium assessments under “Data collection: Delirium assessment method.”  All POD 1 assessments were administered in the afternoon between 1pm and 8pm. Patients were assessed on POD 0; however we are excluding these assessments because of potential lingering general anesthetic effects. We are also now adjusting our model for the use of certain medications, such as preoperative midazolam, median volatile anesthetic concentration , intraoperative ketamine, and intraoperative opioids .   We suggest considering to additionally use the SPOSA score which was recently published in order to classify patients according to OSA risk . Advantage is you can apply this to bigger observational cohorts without measuring neck circumference etc.Thank you for this suggestion! We are unable to incorporate the SPOSA score for this cohort because of limiting factors with electronic medical data.  However, we are excited about this new model and the ability to classify OSA risk in larger cohorts, especially when neck circumference is unavailable.     Maybe you can better justify the patient flow. The SATISFY-SOS study aims to enroll 36000 patients. Please provide information that helps understand as to why you expect to have complete data for ~1300 patients only. Looks like you also want to use data from two other studies additionally with enrollment targets of additional 600 and 1200 patients?We have included more details about patient flow under the “Study Design” section. We now hope to include all 1200 patients from the ENGAGES trial.  Of the ~600 patients in the PODCAST study, we will include those patients recruited through Washington University in St. Louis (roughly 100 patients).  Although SATISFY-SOS aims to enroll a large number of patients, only 200 of those patients received daily inpatient delirium and pain assessments.     How do you account for patients with undiagnosed OSA that may have been treated with CPAP for other respiratory diseases such as COPD, acute lung injury, neuromuscular disorders etc.? The data to classify patient reported CPAP use comes from routine questions that are part of our OSA screening done in our pre-operative clinic. Specifically, we ask patients who have been diagnosed with OSA if they are prescribed CPAP  and if they use their CPAP. Unfortunately in this study, we are unable to account for patients with undiagnosed OSA who may have been treated with CPAP for other respiratory diseases. This has the potential to decrease any difference in outcomes we may see between the study groups and bias our findings towards the null hypothesis (H0= no difference in outcomes between the groups).  This would be a limitation of our secondary sub-group analysis, which we would discuss in our manuscript.    Confounder control: Please consider including comorbidities such as COPD, asthma and neuromuscular disorders in the context of higher risk for intraoperative hypoxemia or respiratory failure; duration of surgery/time under anesthesia in addition to surgery type and some type of measure for procedural complexity such as a risk quantification score  into your statistical modelFor sure you should control for age and BMIConsider including pre-prescribed drugs especially neuroleptics/antipsychotics if you can get these dataPerhaps also consider accounting for different anesthetic protocols used during surgery such as TIVAs, volatile anesthetics, opioid use, ketamine use Did you consider using multiple imputation methods for missing data?We like the suggested sensitivity analyses.Statistical models:Thank you for these suggestions- they have helped us improve our statistical models. We will include COPD, asthma, and anesthesia time in minutes; however we will not be able to include history of neuromuscular disorders or pre-prescribed drugs. Additionally, we will adjust our models for medications used during surgery. We are still hopeful to include age and BMI, but collinearity may prevent us from incorporating these variables independently. We will explain any statistical limitations in the manuscript. Again, thank you for your time and your suggestions!     This study proposes to retrospectively examine data previously collected from 3 prospective studies to test whether OSA is an independent predictor of postoperative delirium and acute postoperative pain severity. The study is described as ‘observational’ however, the study examines data that was already collected, and so I believe the title should be adjusted to reflect this a retrospective study. The incidence of delirium varies depending on the type of surgery and is lower than 20% for some elective surgeries. The type of surgery included should be mentioned. Whether the patients may have a history of chronic pain should be included. As well, although the patients had a history of using CPAP, ideally, whether the patients were compliant with the use of CPAP while in hospital and the number of hours of CPAP use should be reported.We have read this submission. We believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Thank you, Dr. Wong and Dr. Chung, for your feedback on our study protocol.  We sincerely appreciate your time and thoughtful suggestions.  Along with submitting our revised protocol, we would like to directly address some suggestions.  We will be including type of surgery as an independent variable in our regression models, and we will also be adjusting our analysis for a history of chronic pain.  We agree with your suggestion to report hospital CPAP use.  Unfortunately, we do not have that information available to us and are unable to provide a more robust measure of CPAP adherence- a limitation we would discuss in our manuscript. Again, thank you for your time.


Patients with knee osteoarthritis (OA) who are obese have problems performing land-based exercises. The reduced joint stress associated with aquatic exercise may benefit these patients. This study aimed to develop an underwater treadmill (UTM) machine that is affordable and suitable for use in developing countries, and to evaluate its efficacy in decreasing pain and increasing functional improvement.2 were recruited. The UTM exercise protocol was 30 min/session, 3 days/week, for 4 weeks. The main outcomes were NRS pain score, 6-min walk distance (6MWD), quadriceps strength (QS) and body weight. Those outcomes were evaluated at baseline and at week 4.Clinical testing of the UTM machine was performed in an outpatient setting at Siriraj Hospital during January–June 2017. Patients with knee OA, aged 50–85 years, numerical rating scale (NRS) ≥5/10, and body mass index (BMI) ≥25 kg/m 2. Most patients (65.0%) developed bilateral knee OA, used pain medication (56.7%), and engaged in regular knee exercise (73.3%). Of the 30 enrolled patients, 6 withdrew. All of the remaining 24 patients attended all 12 sessions. The mean difference between baseline and the end of the study was − 2.3  for NRS pain; 34.9 m  for 6MWD; and, 1.8 kg  for QS. Concerning adverse events, 4 patients (15.4%) developed muscle pain, 2 patients (7.7%) had joint pain, and 1 patient (3.9%) withdrew due to severe knee pain. Two-thirds of patients described themselves as being ‘very satisfied’ with UTM exercise, and approximately 90% of participants rated their symptoms as ‘improved’ or ‘much improved’.The UTM was constructed with safety, ergonomically designed and user-friendly control panel with push button for emergency stopping. Thirty patients were included for clinical testing. The mean age was 62.8 years, and almost all were female. The mean BMI was 28.9 kg/m 4-week exercise with UTM can significantly improve NRS pain, 6MWD, and QS. UTM could be an alternative treatment for patients with knee OA who are obese due to small size, durability, and ecofriendly design as an exercise modality. Knee osteoarthritis (OA) is the most common degenerative disease of the musculoskeletal system worldwide. Overweight and obese older adults are the most likely subpopulation to develop knee OA. The prevalence of knee OA among older adults living in the community in Thailand was reported to be 34.5–45.6% . Knee OAMany studies have investigated the effect of aquatic exercise. Roper, et al. studied the effect of aquatic treadmill exercise in 14 patients with knee OA. That study had a cross-over design that compared between aquatic and land treadmill exercise for 1 week (3 sessions). They found that aquatic treadmill exercise improved angular velocity and decreased pain compared to land treadmill exercise . Mackay-In 1996, Mangione, et al. suggested using a land treadmill with body weight support in older adults with OA, but this type of exercise/therapy could not relieve pain . AquaticThe aim of this project was to design, develop, and clinically test a UTM that is both affordable and suitable for use in developing countries. UTM development-related information is presented in the supplementary file. The UTM was developed and assembled at the Department of Mechanical Engineering, Faculty of Engineering, Kasetsart University, Bangkok, Thailand, and it was installed at the Department of Rehabilitation Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand. Clinical testing of the UTM machine was performed in an outpatient setting during January to June 2017. This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. This study was approved by the Institutional Review Board of Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand (COA no. Si 185/2013). All recruited participants provided written informed consent.2) [Participants were recruited via publicly displayed printed posters that introduced and described the study. Participants with knee OA who satisfied all of the inclusion criteria and none of the exclusion criteria were recruited. The inclusion criteria were patients with knee OA, aged 50–85 years, numerical rating scale (NRS) ≥5 (range: 0–10), and body mass index of Asian obese population (BMI ≥25 kg/m2) . PatientThe primary outcome was NRS pain score, and the secondary outcomes included 6-min walking distance (6MWD), body weight, and quadriceps strength. NRS pain score ranges from 0 to 10, with a higher score representing a higher level of pain intensity . 6MWD isThe sample size for this study was calculated using NRS pain score from a study by Dias, et al. , with 90t-test was used to analyze the mean differences between baseline and end of the study for primary and secondary outcomes with normally distributed data. Per-protocol analysis was used to analyze the outcomes. A p-value of less than 0.05 was considered statistically significant for all tests. SPSS Statistics  was used to perform all statistical analyses.Baseline demographic, anthropometric, and clinical characteristics of study participants are presented as mean ± standard deviation  or median and range  for continuous data, and as number and percentage for categorical data. Paired The design and construction details of the UTM machine are presented in the supplementary file, and the UTM specification and design characteristics are shown in Fig. 2. Two-thirds of patients had an education level below bachelor’s degree. More than half of patients (65.0%) developed bilateral knee OA, used pain medication (56.7%), and engaged in regular knee exercise (73.3%). Some used knee support (40.0%), and a few used gait aids (13.3%). Of the 30 enrolled patients, 6 (20%) withdrew from the study due to inconvenience (n = 4), lost contact (n = 1), and severe knee pain (n = 1)  for NRS pain; 34.9 m  for 6MWD; and, 1.8 kg  for quadriceps strength.Mean NRS pain score, body weight, 6MWD, and quadriceps strength at week 0 and week 4, and the mean difference between pre- and post-treatment using per-protocol analysis are shown in Table Concerning adverse events (AE) that occurred after recruitment (including patients lost due to AE), 4 patients (15.4%) developed muscle pain, 2 (7.7%) had joint pain, and 1 3.9%) was lost to follow-up due to severe knee pain. No study participants reported falling, joint swelling, or fatigue  of our findings, we found that UTM therapy could reduce the mean NRS pain score (mean difference: 2.3), which was a greater reduction than that reported by Farrar, et al. (mean difference: 2.0) . HoweverRegarding complaints of musculoskeletal pain, 15.4% of patients reported muscle pain, and 7.7% of patients described having joint pain. These adverse events may be due to inadequate warm-up, and/or to excessive muscle stress. Participants have to exercise against water resistance during continuous walking, and one-fourth of our patients did not exercise regularly before entering the study. Therefore, therapists should emphasize the importance of warm-up before commencing UTM exercise.The aim of this study was to assess the applicability and efficacy of the UTM, which was developed by our team. A sample size of 30 patients was calculated based on previous study . Since oThis study has some mentionable limitations. First, the non-randomized design of our study renders it vulnerable to selection bias. In addition, the grade of evidence was considered low in this study due to its pre-post design. However, this study design was adopted to facilitate the collection of preliminary data prior to testing using a randomized controlled design. Second, due to reasons that included transportation availability, travel distance, disability-related challenges, and frequency of hospital visits per week, 20% of our study population withdrew from this study. This substantial reduction in sample size may have introduced selection bias, and may have given our study insufficient statistical power to identify all significant differences and associations. Third, most participants in this study were female, and this may limit the generalizability of our findings to males. This difference between males and females in our study may be due to a higher reported prevalence of knee OA in females than in males (39.8% vs. 22.6% respectively) . Fourth,Aquatread”. It is a low-cost, small footprint, ecofriendly therapeutic/exercise modality that can provide aquatic exercise to older obese patients with knee OA via continuous treadmill walking. Since its installation over 2 years ago, Aquatread is still functioning fully to its design and performance specifications. With regard to user satisfaction, most participants described being satisfied to very satisfied, and their global improvement rating increased from improved to much improved after beginning use of the Aquatread. Taken together, these findings may support the benefit of underwater treadmill for treatment of patients with knee OA who are obese. As recommended by the study of Bartels, et al., aquatic exercise could be used during the initial phase of exercise program [The author-designed UTM profiled in this study was given the name “ program .Aquatread therapy had no significant effect on body weight. Although adverse events were reported by 7 patients (1 of those withdrew from the study due to severe knee pain), two-thirds of patients described themselves as being ‘very satisfied’ with Aquatread, and approximately 90% of participants rated their symptoms as ‘improved’ or ‘much improved’. After 2 years of use, Aquatread continues to function reliably and deliver according to its designed performance specifications.The UTM profiled in this report was designed, fabricated, and clinically tested by the authors of this study. Of the 4 measured parameters, NRS pain, 6MWD, and quadriceps strength were all significantly improved at the end of the study. However,


Background: While total knee arthroplasty (TKA) is a reliable treatment for advanced knee arthritis, up to 19% of patients after TKA remain dissatisfied, especially with residual pain. A less known source of medial knee pain following TKA is infrapatellar saphenous neuroma. Ultrasound-guided local treatment with hydrodissection and corticosteroid injection is an effective short-term solution. Our primary aim was to evaluate the durability of local treatment by comparing numeric pain scores for medial knee pain after TKA at pretreatment, one month following treatment, and midterm follow-up. A secondary aim was to identify associations of patient characteristics with degree of change in numeric pain score. Methods: Retrospective chart review was performed to identify patients who had symptomatic infrapatellar saphenous neuroma following TKA and were treated with ultrasound-guided local treatment by hydrodissection and corticosteroid injection between January 1, 2012, and January 1, 2016. Those with follow-up less than three years were excluded. Patients who were unable to return for midterm follow-up were called. Numeric pain scores for the medial knee were recorded. Patient demographics, medical history, revision TKA status, number of prior knee surgeries, narcotic use, psychiatric disorders, and current tobacco use were also collected.Results: Of 32 identified patients, 29  elected to participate in this study with a mean (SD) follow-up of 4.6 (0.8) years. The median (range) pretreatment pain score was 9 (5-10). After local treatment, the median (range) numeric pain score was significantly lower at both one-month and midterm follow-up . The initial response to treatment was durable given that the difference between one-month and midterm follow-up scores was not significant (P=0.47). Advanced age was associated with less overall pain relief from pretreatment to midterm follow-up, while female sex, history of fibromyalgia, and TKA revision prior to treatment were associated with worsening pain from one-month to midterm follow-up (P<0.05). Conclusions: Patients who underwent ultrasound-guided local treatment with hydrodissection and corticosteroid injection for painful postoperative infrapatellar saphenous neuroma following TKA experienced significant numeric pain score reduction. Pain relief remained consistent from 1onemonth to midterm follow-up. Level of Evidence: Level IV, Case Series Total knee arthroplasty (TKA) is a reliable surgical option for patients with tricompartmental knee arthritis for whom nonsurgical treatment has failed. In the United States, the rise in annual rates of primary TKA is matched with an increase in revision TKA . Common Although selective surgical neuroma excision is a possible solution with 84% of patients reporting good-excellent outcomes, nonsurgical management with ultrasound-guided local treatment with hydrodissection combined with corticosteroid injection has also been shown to be an effective short-term solution ,3. The lThe primary aim of our study was to compare numeric pain scores for medial knee pain after TKA at pretreatment, one month following treatment, and midterm follow-up. The secondary aim was to identify associations of patient characteristics with degree of change in numeric pain score. In this retrospective chart review approved by the Institutional Review Board, we identified patients diagnosed with symptomatic infrapatellar saphenous neuromas following TKA who were then treated with ultrasound-guided hydrodissection and corticosteroid injection between January 1, 2012, and January 1, 2016. Through chart review, diagnosis of infrapatellar saphenous neuroma was confirmed with preprocedural criteria of chronic medial-sided knee pain, history of ipsilateral TKA, lack of radiculopathy or neuropathy, or other documented sources of pain following TKA, such as loosening, infection, or malalignment. All patients had Tinel’s test producing point tender medial knee discomfort. The ultrasound-guided treatment was performed as described by Clendenen et al., using a 12-4 MHz transducer and a portable ultrasound. The infrapatellar branch of the saphenous nerve was identified and confirmed using electrical stimulation [The most recent numeric pain score was recorded from the chart review of patients with a follow-up greater than three years. Those who were identified as candidates for our study but were unable to return for midterm follow-up were called. After obtaining consent, the current numeric pain score  for medial knee was recorded. Patient demographics, medical history, revision TKA status, number of prior knee surgeries, narcotic use, psychiatric disorders, and current tobacco use were also collected. Continuous variables were summarized with the sample median and range. Categorical variables were summarized with number and percentage of patients. Comparisons of medial knee visual analog scale (VAS) pain score prior to treatment, at one month following treatment, and at midterm follow-up between three and six years after treatment were made using paired Wilcoxon signed-rank tests. Associations of patient characteristics with degree of change in medial knee VAS pain scores from pretreatment to midterm follow-up and from one-month follow-up to midterm follow-up were evaluated using Spearman’s correlation test  or a Wilcoxon rank-sum test . No adjustment for multiple testing was made in these exploratory analyses, and P-values less than 0.05 were considered as statistically significant. All statistical tests were two sided. Statistical analyses were performed using R Statistical Software .Of 32 patients, 29 were identified , with a median age of 65.9 (range: 34.7-79.8) years and a body mass index of 32.6 (range: 20.2-41.3), participating in this study with a mean (SD) follow-up of 4.6 years (range: 3-6)  is important to consider. Additionally, due to the retrospective design, there were no control group in our study.Ultrasound-guided local treatment with hydrodissection and corticosteroid injection is a safe and effective minimally invasive option for painful infrapatellar saphenous neuroma following TKA. Patients in this case series experienced significant numeric pain score reduction after hydrodissection and corticosteroid injection. Pain relief remained consistent from one-month to midterm follow-up.


No study has investigated the associations of migraine with pain symptoms over a ten-year period among outpatients with major depressive disorder (MDD). This study aimed to investigate this issue.At baseline, the study enrolled 290 outpatients with MDD and followed-up the patients at six-month, two-year, and ten-year time points. MDD and anxiety comorbidities were diagnosed using the Structured Clinical Interview for DSM-IV-text revision. Migraine was diagnosed based on the International Classification of Headache Disorders. The bodily pain subscale of the Short Form 36 (SF-BP) and the pain subscale (PS) of the Depression and Somatic Symptoms scale were also used. Generalized Estimating Equation models were employed to investigate the longitudinal impacts of migraine on pain symptoms.MDD patients with migraine had lower SF-BP and higher PS scores than those without. Depression, anxiety, and headache indices were significantly correlated with SF-BP and PS scores. The higher the frequency of migraine, the more often patients suffered from pain symptoms. Patients with migraine at all investigated time points suffered from pain symptoms most of the time (ranging from 60.0% to 73.7%) over the 10 years. After controlling for depression and anxiety, migraine was independently associated with a decreased SF-BP score (by 8.93 points) and an increased PS score (by 1.33 points).Migraine was an important comorbidity associated with greater severities of pain symptoms during long-term follow-up. Migraine treatment should be integrated into the treatment of depression to improve pain symptoms and quality of life in the pain dimension. Painful physical symptoms and depression interact with each other , 2. MajoMDD, migraine, anxiety, and pain symptoms mutually affect each other –12. For Nearly half of patients with MDD have comorbid migraine , 21. MDDSeveral studies have investigated the associations of migraine with pain symptoms –24. HoweThis study was performed in the psychiatric outpatient clinics of the Chang Gung Memorial Hospital at Linkou, a medical center in northern Taiwan. At baseline (January 2004 to August 2007), consecutive outpatients who fulfilled the following three criteria were considered eligible subjects: 1) 18−65 years of age; 2) no antidepressants or other psychotropic drugs administered within the previous four weeks; and 3) met the DSM-IV-TR criteria for MDD and were experiencing a current major depressive episode (MDE) . MDD andAt baseline, 290 subjects were enrolled. These patients were followed-up at the six-month, two-year, and ten-year points. The ten-year follow-ups were performed from August 2014 to December 2016. The study was approved by the Institutional Review Board of the Chang Gung Memorial Hospital. Based on the guidelines regulated in the Declaration of Helsinki, written informed consent was obtained from all subjects.At baseline, all subjects completed a structured headache intake form, which reported headache patterns over the past year and included headache intensity, frequency, location, duration, aggravation by physical activities, phonophobia, photophobia, nausea, vomiting, precipitating factors, painkiller use, and aura. Then, an experienced headache specialist, who was blind to other results, interviewed all subjects and made headache diagnoses. This procedure was also performed at the two-year and ten-year follow-up points. At the six-month follow-up, diagnosis of migraine was taken as the baseline diagnosis.At baseline and the two-year follow-up point, headache was diagnosed based on the International Classification of Headache Disorders, 2nd edition (ICHD-2) . At the At each time point, subjects who fulfilled the criteria of migraine without aura (MO) and/or migraine with aura (MA) were classified as the “migraine” group, while the other subjects were categorized as the “non-migraine” group. The intensity and frequency of headaches were assessed at baseline and the three follow-up points. We used the visual analog scale (VAS) to evaluate the average headache intensity in the past week, rated from 0 (no pain) to 10 (pain as severe as I can imagine), and recorded the frequency of headache days.One psychiatrist, who was blind to other psychiatric data and headache diagnoses, used the Structured Clinical Interview for DSM-IV-TR Axis I Disorders to diagnose the following anxiety comorbidities: panic disorder, agoraphobia, specific phobia, social phobia, post-traumatic stress disorder, obsessive–compulsive disorder, and generalized anxiety disorder . SubjectThe bodily pain subscale of the Short Form-36 (SF-BP) and the pain subscale (PS) of the Depression and Somatic Symptoms Scale (DSSS) were used to evaluate the pain dimension of HRQoL and pain severities, respectively –35. The To understand the longitudinal course of pain symptoms in the past 10 years, subjects were requested to report the percentages of time during which they had suffered the following pain symptoms in the past 10 years: headache, back pain, shoulder and/or neck pain, and general muscle pain.The Hamilton Depression Rating Scale (HAMD) and the anxiety subscale of the Hospital Anxiety and Depression Scale (HADS-A) were used to evaluate depression and anxiety, respectively –37. The The native language of our subjects was Chinese. The reliability and validity of the Chinese versions of the three administered scales  have been established , 33–35.Subjects were followed-up at the time points of 6 months, 2 years, and 10 years after baseline enrollment. The SF-BP, PS, and HADS-A were administered at the three follow-up points, and the HAMD was evaluated by the same psychiatrist.During the ten-year period, subjects might have quit pharmacotherapy or accepted pharmacotherapy intermittently. Pharmacotherapy was not controlled at the three follow-up points. At the index month of the follow-up point, patients who were not receiving pharmacotherapy were classified into the “without pharmacotherapy (in the index month)” group, whereas patients who were receiving pharmacotherapy were classified as the “with pharmacotherapy (in the index month)” group. This classification was used to avoid the confounding effects of pharmacotherapy in statistical analysis.t test, Mann-Whitney U test, Kruskal-Wallis H test, Pearson’s correlation, Spearman’s correlation, and Chi-square test were used in appropriate situations.All statistical analyses were performed using SPSS for Windows 20.0. The independent Generalized Estimating Equation (GEE) models with robust error estimation and an unstructured covariance matrix were used to estimate the differences in SF-BP and PS scores between patients with and without migraine. The dependent variables were the SF-BP and PS scores. Initially, 10 variables were placed into the GEE model as independent variables, including six variables at baseline  and four variables at each follow-up point . Then, insignificant factors were removed from the GEE model one by one until all independent factors were significant.P value of < 0.05 was taken to indicate statistical significance, and Bonferroni correction was used in appropriate situations.A two-tailed p = 0.04). At the six-month and two-year time points, the percentage of subjects who attended follow-up was over 80%. At the ten-year follow-up point, approximately half of the subjects attended follow-up appointments. Of the subjects who did not complete the ten-year follow-up assessment (n = 153), 34.1% (n = 99) were unable to be contacted by phone or mail; 16.9% (n = 49) refused to participate in the follow-up; 1.0% (n = 3) had expired due to medical diseases; and 0.7% (n = 2) had their psychiatric diagnosis shifted to schizophrenia.For clarity, the labels “(B)”, “(6 M)”, “(2Y)” and “10Y)” are used to represent data collected at baseline, and at the six-month, two-year, and ten-year follow-up points, respectively. At baseline, 290 subjects were enrolled. Table 0Y” are uTable n = 149) of the subjects had at least one anxiety disorder, including 12.1% (n = 35) with panic disorder, 11.7% (n = 34) with agoraphobia, 22.1% (n = 64) with specific phobia, 27.6% (n = 80) with social phobia, 10.7% (n = 31) with post-traumatic stress disorder, 9.3% (n = 27) with obsessive-compulsive disorder, and 5.5% (n = 16) with generalized anxiety disorder. Compared with the subjects without anxiety disorders, a higher percentage of the subjects with anxiety disorders had comorbid migraine .At baseline, 51.4%  as compared with those without.Patients with migraine at the two-year and 10-year follow-up points had a longer total duration of pharmacotherapy  in patients with pharmacotherapy.Table (6M) and anxiety (6M and 10Y) in patients without pharmacotherapy, and the severity of depression (10Y) in patients with pharmacotherapy.Patients with migraine had a higher headache intensity and frequency than patients without migraine after Bonferroni correction Table . Patientp <  0.001) correlated with the severities of depression and anxiety, as well as the headache indices, at all four time points. The correlations of the SF-BP score with depression (correlation coefficient (r) ranged from − 070 to − 0.41), anxiety (r = − 0.59 to − 0.24), and headache intensity (r = − 0.59 to − 0.41) and frequency (r = − 0.54 to − 0.33) were negative. The correlations of the PS score with depression (r = 0.67 to 0.37), anxiety (r = 0.57 to 0.27), and headache intensity (r = 0.63 to 0.49) and frequency (r = 0.60 to 0.43) were positive.The SF-BP and PS scores were significantly , neck and/or shoulder , back , and general muscles  were significantly  correlated with the SF-BP and PS scores at the four time points.The mean (± SD) percentages of time spent suffering pain in the head, neck and/or shoulder, back, and general muscles in the past 10 years were 30.2 ± 28.0, 47.0 ± 31.5, 32.6 ± 30.5, and 29.8 ± 30.8, respectively. The self-reported percentages of time spent with pain in the head  (group III) spent the highest percentage of time with the four pain symptoms (ranging from 60.0% to 73.7%), followed by patients with migraine at any two of the three points (group II). In contrast, patients without migraine at the three time points (group 0) had the lowest percentage of time spent with pain. In the post hoc analysis, significant differences between groups were noted for headache , neck/shoulder pain , back pain (group 0 vs. group II and III) and general muscle pain .Figure Migraine was a significant factor associated with the SF-BP and PS scores after controlling for demographic variables, anxiety disorders at baseline, the severities of depression and anxiety at the same time points, and pharmacotherapy Table . CompareMigraine was a significant factor associated with the two pain indices after controlling for depression, anxiety, pharmacotherapy, and other factors Table . CompareTwo points are worth noting: 1) The patients in group III had the highest percentage of time spent with pain in the past 10 years  Migraine is associated with sensory hypersensitivity . PatientSome limitations or bias should be addressed. 1) Approximately half of the subjects did not attend the ten-year follow-up appointment. Patients who refused to continue to participate in the study or who were unable to be contacted might be associated with a greater severity of depression, which may have caused bias. 2) The interval between the two-year and ten-year follow-up points was long. Unequal follow-up intervals might have caused bias. Frequent follow-up is required in future studies. 3) Due to memory bias, the self-reported percentage of time spent suffering pain in the past 10 years might be not very accurate. Although the self-reported percentages of time with pain were gross estimations, the self-reported indices were significantly correlated with the SF-BP and PS scores at all time points. 4) Although pharmacotherapy was included in the GEE model, the kind and amount of medication were not controlled, because the study was of an observational design. 5) The study excluded MDD patients with other chronic medical diseases at baseline and did not monitor whether these medical diseases and factors related to cardiovascular risk had developed at the follow-up points. In future studies, medical comorbidities should be monitored at follow-up, because these comorbidities might influence the pain threshold .After controlling for depression, anxiety and other factors, migraine was independently associated with a poorer HRQoL in the pain dimension and more severe pain symptoms among patients with MDD. During the ten-year study period, the higher the frequency of migraine, the more often patients with MDD suffered from pain symptoms. Migraine prevention should be integrated into the treatment of depression, because simultaneous treatment of depression and migraine might help to improve pain symptoms and the score in the pain dimension of the HRQoL. Physicians should employ therapeutic strategies, including pharmacotherapy, cognitive behavioral therapy, and relaxation techniques, for the simultaneous treatment of depression and migraine.


Symptom is still indispensable for the stratification of chest pain in the emergency department. However, it is a sophisticated aggregation of several aspects of characteristics and effective combination of those variables remains deficient. We aimed to develop and validate a chest pain symptom score (CPSS) to address this issue.The CPSS may help stratifying acute undifferentiated chest pain in ED.Patients with non‐ST segment elevation chest pain and negative cardiac troponin (cTn) over 3 hours after symptom onset were consecutively recruited as the derivation cohort. Logistic regression analyses identified statistical predictors from all symptom aspects for 30‐day acute myocardial infarction (AMI) or death. The performance of CPSS was compared with the symptom classification methods of the history variable in the history, electrocardiograph, age, risk factors, troponin (HEART) score. This new model was validated in a separated cohort of patients with negative cTn within 3 hours.P < 0.001). In the derivation (n = 1434) and validation (n = 976) cohorts, the expected and observed event rates were well calibrated (Hosmer–Lemeshow test P > 0.30), and the c‐statistics of CPSS were 0.72 and 0.73, separately, significantly better than the previous history classifications in HEART score (P < 0.001). Replacing the history variable with the CPSS improved the discrimination and risk classification of HEART score significantly (P < 0.001).Seven predictors in four aspects of chest pain symptom were identified. The CPSS was an independent predictor for 30‐day AMI or death (The effective combination of isolated variables was meaningful to make the most stratification value of symptoms. This model should be considered as part of a comprehensive strategy for chest pain triage. However, in some predict scores, some symptom components were assessed with electrocardiograph (ECG) and cTn in the logistic regression as isolated variables,As we all know, cTn can be detected firstly 3 to 4 hours after AMI occurs due to its kinetic profile of releasing. However, negative cTn over 3 hours after symptom onset was not safe enough to rule out events.22.1This is a prospective cohort study of acute non‐ST segment elevation chest pain in the urban ED of the Qilu Hospital of Shandong University , and in the rural ED of the People's Hospital of Wenshang County from 24 August 2015 to 30 September 2017. The derivation cohort consisted of patients enrolled consecutively with negative initial cTn over 3 hours after symptom onset. And the validation cohort comprised chest pain patients with negative cTn within 3 hours after symptom onset. This study has been approved by the ethics committee at these two hospitals. Written informed consent was obtained from all participants.2.2Any patient aged 18 or older, with acute nontraumatic chest pain occurring within the past 24 hours, and with negative initial cTn testing, was consecutively recruited.Acute symptoms of myocardial ischemia, such as upper extremity, mandibular, or epigastric discomfort, or an ischemic equivalent such as dyspnea or fatigue, were also considered as chest pain according to the American Heart Association case definitions.Negative cTn indicated that the value of initial testing was under the 99th percentile upper reference limit (URL), specific to the assay used by each site. The contemporary cTnI assays arranged by emergency physicians in their daily work were used to determine the eligibility of enrollment in the derivation and validation cohorts.Patients were excluded if they had ST‐elevation myocardial infarction (STEMI), or they were unable or unwilling to provide informed consent.2.3pm to 8 am.Data collection was prospectively conducted on a standardized case report form by trained research assistants, according to the standard definitions for each candidate variable from a published data dictionary.Follow‐up was conducted by trained research assistants through telephone interviews at 30 days after enrolment, to acquire information about major adverse cardiac events (MACE) and hospital attendances.Calculation methods for the history and other variables of HEART score have been described in previous articles.2.4The primary outcome was the composite end point of death from all causes and AMI, including the index AMI and subsequent AMI, during the 30 days after presentation to the ED. Each event in MACE was independently adjudicated by two senior cardiologists of clinical events committee using all available clinical records according to the international standardized definitions,2.5P value ≤0.2 were eligible to enter the stepwise multiple logistic regression. Separate multivariable logistic regression models were developed for each section of symptom profile. The variables with P < 0.05 in each section entered the next multiple logistic analysis and those with P < 0.05 were retained in the final model , diagnosis of STEMI (225), deficiency of ECG (58), and loss to follow‐up (12). Finally, 2410 patients remained for derivation (1434) and validation (976) of the CPSS. There was no missing data regarding the presence or absence of symptom profiles in any patient. In derivation cohort, there were 93 (6.5%) patients with adjudicated MACE in 30 days after presentation. Twelve patients (0.8%) died from all causes and 89 (6.2%) were diagnosed with AMI (75 index AMI). And in validation cohort, MACE occurred in 153 (15.7%) patients, including 12 (1.2%) death and 149 (15.3%) AMI (142 index AMI)   Figure A.P < 0.001) with values at 0.57, 0.53, 0.61, and 0.60 separately , significantly better than the different history classifications (H1~H4) of the HEART score (P < 0.001)  (Table The HEART score with CPSS replacing the history variable executed greater discrimination (AUC) than the standard HEART scores with different history measurements  Figure B. And bo1) Table .P = 0.33)  Figure .4In this study, we developed a CPSS to assist in the prediction of 30‐day AMI or death in acute undifferentiated chest pain presenting to the ED with negative initial cTn over 3 hours after symptom onset. The CPSS served as an independent predictor and performed excellent in both the derivation and validation cohort. Moreover, the CPSS combined with the HEART risk score improved the discriminatory capacity of the old model and allowed the classification of risk levels significantly better. To our knowledge, this is the first attempt to derivate and validate the statistical combination of symptom features for diagnosis or prediction of AMI/death in chest pain patients.This CPSS compromised seven predictors in four aspects of chest pain symptom. The substernal pain, left arm pain, diaphoresis, and vomiting were shown to be significant predictors of AMI in accordance with other studies.Using the same measurements with the history variable of HEART score, the CPSS improved the discrimination and risk classification significantly. In general, the symptom variables were integrated into a predictive score or decision rule for clinical use.For risk stratification of chest pain in ED, the CPSS could add predictive information to the negative cTn as an independent predictor. Consistent with the kinetic profile of cTn releasing,4.1This study also had several limitations. Firstly, the CPSS was developed from the ED chest pain patients in two hospitals of Shandong province in China. Although urban and rural hospitals were both covered and external validation was carried out in the same hospitals, the external generalization of the CPSS to wider patients should be determined by further studies in heterogeneous groups. Secondly, the HEART score was a very good reference substance here, but whether the CPSS‐HEART should be used in clinical practice needs more assessments. Since symptom merely plays a certain part of roles in the diagnosis/prognosis of chest pain, the integration with other significant predictors is prerequisite, such as demographic characteristics, medical history, risk factors, ECG, and cardiac markers. The combination of these components and the weights for selected variables require many explorations. Thirdly, considering that the sensitivity of the hs‐cTn is different from the contemporary cTn in patients assessed within 3 hours after onset of symptoms, we will take further evaluations based on the central testing of the hs‐cTn to assess the performance of the CPSS.5The CPSS performed well to assist in the prediction of 30‐day AMI or death in acute undifferentiated chest pain presenting to the ED with negative initial cTn, better than the different symptom classification methods of the HEART score. And the HEART score with CPSS replacing the history variable executed greater discrimination and reclassification than the standard HEART scores. This demonstrated that the effective combination of isolated variables was meaningful to make the most diagnostic or predictive value of symptoms and made preparations for the development of complete stratification models with medical history, risk factors, symptoms, ECG, and troponins for chest pain triage.The authors declare no potential conflict of interests.Yuguo Chen, Jiali Wang, and Feng Xu contributed to the initiation, planning, and conduction of the study. Wen Zheng, Jingjing Ma, Guangmei Wang, He Zhang, and Jiaqi Zheng conducted the study supervision. Wen Zheng and Shuo Wu did the analysis and interpretation of data. Wen Zheng drafted the manuscript.Figure S1. Flowchart for developing the chest pain symptom score using logistic regressions.Click here for additional data file.Table S1. Four history classification methods of the HEART score.Click here for additional data file.