A biomimetic elastomeric robot skin using electrical impedance and acoustic tomography for tactile sensing

Human skin perceives physical stimuli applied to the body and mitigates the risk of physical interaction through its soft and resilient mechanical properties. Social robots would benefit from whole-body robotic skin (or tactile sensors) resembling human skin in realizing a safe, intuitive, and contact-rich human-robot interaction. However, existing soft tactile sensors show several drawbacks (complex structure, poor scalability, and fragility), which limit their application in whole-body robotic skin. Here, we introduce biomimetic robotic skin based on hydrogel-elastomer hybrids and tomographic imaging. The developed skin consists of a tough hydrogel and a silicone elastomer forming a skin-inspired multilayer structure, achieving sufficient softness and resilience for protection. The sensor structure can also be easily repaired with adhesives even after severe damage (incision). For multimodal tactile sensation, electrodes and microphones are deployed in the sensor structure to measure local resistance changes and vibration due to touch. The ionic hydrogel layer is deformed owing to an external force, and the resulting local conductivity changes are measured via electrodes. The microphones also detect the vibration generated from touch to determine the location and type of dynamic tactile stimuli. The measurement data are then converted into multimodal tactile information through tomographic imaging and deep neural networks. We further implement a sensorized cosmetic prosthesis, demonstrating that our design could be used to implement deformable or complex-shaped robotic skin.

OP0142 COMPARISON OF ATTAINMENT AND PROTECTIVE EFFECTS OF THE LUPUS LOW DISEASE ACTIVITY STATE IN PATIENTS WITH NEWLY DIAGNOSED VERSUS ESTABLISHED SLE - A MULTICENTRE PROSPECTIVE STUDY

Background

Lupus low disease activity state (LLDAS) attainment has been reported to be associated with reduced damage accrual, flare, and mortality, as well as improved quality of life, in cohorts of SLE patients with established disease. Whether these associations are present in recent-onset disease is less well known.

Objectives

To evaluate the associations of LLDAS attainment with outcomes in patients with recent onset SLE.

Methods

Data from a 13-country longitudinal SLE cohort (ACR/SLICC criteria) were collected prospectively between 2013 and 2020 using standard templates. Organ damage and flare were captured using SLICC Damage Index and SELENA-SLEDAI Flare Index, respectively. LLDAS was defined as Golder et al., 2019 [1]. An inception cohort was defined based on duration since SLE diagnosis<1 year at enrolment. Patient characteristics between inception and non-inception cohorts were compared using Wilcoxon rank-sum (continuous variables) or Pearson’s Chi-squared tests (categorical variables). Survival analyses were performed to examine the association between LLDAS attainment and damage accrual and flare.

Results

The study cohort included 4,106 patients of whom 680 (16%) were recruited within 1 year of SLE diagnosis (inception cohort). Compared to the non-inception cohort, inception cohort patients were significantly younger, had higher disease activity (SLEDAI-2K and physician global assessment), used more glucocorticoids and immunosuppressants but had less organ damage at enrolment and only 88 (13.6%) patients accrued damage during a median 2.2 years follow-up (Table 1).

Table 1.Non-inception cohortInception cohortp-valuen=3426n=680Age at enrolment (years), median [IQR]40 [31, 51]33 [25, 44]<0.001Age at diagnosis (years), median [IQR]28 [21, 38]33 [25, 43]<0.001SLE duration at enrolment (years), median [IQR]10 [5, 16]1 [0, 1]<0.001Study duration (years), median [IQR]2.5 [1.0, 5.4]2.2 [0.9, 3.7]<0.001Females, n (%)3155 (92.1%)623 (91.6%)0.68Asian ethnicity, n (%)3037 (89.1%)595 (88.1%)0.49Prednisolone (PNL) use - ever, n (%)2865 (83.6%)620 (91.2%)<0.001Time adjusted mean (TAM)-PNL, median [IQR]5.0 [2.2, 8.6]6.2 [3.2, 10.3]<0.001Cumulative PNL (g), median [IQR]3.4 [0.5, 9.7]3.8 [1.1, 8.5]0.26Anti-Malarial use - ever, n (%)2669 (77.9%)569 (83.7%)<0.001Immunosupressant use -ever, n (%)2367 (69.1%)521 (76.6%)<0.001AMS (TAM-SLEDAI-2K), median [IQR]2.8 [1.2, 4.6]3.1 [1.6, 5.0]0.002TAM-PGA, median [IQR]0.4 [0.2, 0.7]0.4 [0.3, 0.8]<0.001Mild/moderate/severe flare ever, n (%)1789 (52.2%)391 (57.5%)0.012Organ damage accrual, n (%)629 (20.8%)88 (13.6%)<0.001LLDAS at baseline, n (%)1730 (50.5%)195 (28.7%)<0.001LLDAS-ever (at least once), n (%)2637 (78.2%)492 (73.9%)0.014≥50% time in LLDAS (LLDAS-5), n (%)1612 (50.6%)256 (41.1%)<0.001

Significantly fewer inception cohort patients were in LLDAS at enrolment than the non-inception cohort (29% vs. 51%, p<0.001). However, 74% of inception and 78% of non-inception cohort patients achieved LLDAS at least once during follow-up. Limiting analysis only to patients not in LLDAS at enrolment, time to first LLDAS attainment was assessed: inception cohort patients were 60% more likely to attain their first LLDAS (HR = 1.60 (95%CI: 1.40, 1.82), p<0.001) than non-inception cohort patients. LLDAS attainment was significantly protective against flare in the inception (HR, 95% CI) and non-inception (HR, 95% CI) cohorts. Trends towards protection against damage accrual in association with LLDAS in the inception cohort were not significant.

Conclusion

LLDAS attainment is protective from flare in recent onset SLE. Significant protection from damage accrual was not observed, due to low rates of damage accrual in the first years after SLE diagnosis.

References

[1]Golder, V., et al., Lupus low disease activity state as a treatment endpoint for systemic lupus erythematosus: a prospective validation study. The Lancet Rheumatology, 2019. 1(2): p. e95-e102.

Acknowledgements

We thank all patients participating in the Asia Pacific Lupus Collaboration (APLC) cohort, and all data collectors for their ongoing support for APLC research activities.

The APLC has received unrestricted project grants from AstraZeneca, BMS, Eli Lily, Janssen, Merck Serono, and UCB to support data collection contributing to this work.

Disclosure of Interests

Vera Golder: None declared, Rangi Kandane-Rathnayake: None declared, Worawit Louthrenoo: None declared, Yi-Hsing Chen Speakers bureau: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, GSK, Astra& Zeneca, Sanofi, MSD, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Consultant of: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, GSK, Astra and Zeneca, Sanofi, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Gilead, Grant/research support from: Yes. Clinical trials and/or research grants from Pfizer, Norvatis, BMS, Abbevie, Johnson & Johnson, Roche,Sanofi, Guigai, Roche, Boehringer Ingelheim, UCB, MSD, Astra-Zeneca,Astellas, Gilead, Jiacai Cho: None declared, Aisha Lateef: None declared, Laniyati Hamijoyo Speakers bureau: Pfizer, Novartis, Abbot, Shue Fen Luo: None declared, Yeong-Jian Jan Wu Speakers bureau: Pfizer, Lilly, Novartis, Abbvie, Sandra Navarra Speakers bureau: Pfizer, Johnson & Johnson, Novartis, Astellas, Grant/research support from: Astellas, Johnson & Johnson, Leonid Zamora: None declared, Zhanguo Li Speakers bureau: Eli, Lilly, Novartis, GSK, AbbVie, Paid instructor for: Pfizer, Roche, Johnson, Consultant of: Lilly, Pfizer, Grant/research support from: Pfizer, Yuan An: None declared, Sargunan Sockalingam Speakers bureau: Yes. Pfizer, Roche, Novartis, Grant/research support from: Roche and Novartis, Yasuhiro Katsumata Speakers bureau: Chugai Pharmaceutical Co., Ltd., Glaxo-Smithkline K.K., and Sanofi K.K., Masayoshi Harigai Speakers bureau: MH has received speaker’s fee from AbbVie Japan GK, Ayumi Pharmaceutical Co., Boehringer Ingelheim Japan, Inc.,Bristol Myers Squibb Co., Ltd., Chugai Pharmaceutical Co., Ltd., Eisai Co., Ltd., Eli Lilly Japan K.K., GlaxoSmithKline K.K., Kissei Pharmaceutical Co., Ltd., Pfizer Japan Inc., Takeda Pharmaceutical Co., Ltd., and Teijin Pharma Ltd, Consultant of: MH is a consultant for AbbVie, Boehringer-ingelheim, Bristol Myers Squibb Co., Kissei Pharmaceutical Co.,Ltd. and Teijin Pharma., Grant/research support from: MH has received research grants from AbbVie Japan GK, Asahi Kasei Corp., Astellas Pharma Inc., Ayumi Pharmaceutical Co., Bristol Myers Squibb Co., Ltd., Chugai Pharmaceutical Co., Daiichi-Sankyo, Inc.,Eisai Co., Ltd., Kissei Pharmaceutical Co., Ltd., Mitsubishi Tanabe Pharma Co., Nippon Kayaku Co., Ltd., Sekiui Medical, Shionogi & Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co., Ltd., and Teijin Pharma Ltd., Yanjie Hao: None declared, Zhuoli Zhang Speakers bureau: Norvatis, GSK, Pfizer, BMDB Basnayake: None declared, Madelynn Chan Speakers bureau: AbbVie, Novartis, Consultant of: Advisory Board member for Pfizer, Eli-Lilly, Jun Kikuchi: None declared, Tsutomu Takeuchi Speakers bureau: AbbVie AYUMI Pharmaceutical Corp. Bristol-Myers Squibb Chugai Pharmaceutical Co, Ltd. Daiichi Sankyo Co., Ltd. Eisai Co., Ltd. Eli Lilly Japan, Gilead Sciences, Inc. Mitsubishi-Tanabe Pharma Corp. Pfizer Japan Inc. Sanofi K.K., Consultant of: Astellas Pharma, Inc. Chugai Pharmaceutical Co, Ltd. Eli Lilly Japan, Mitsubishi-Tanabe Pharma Corp., Grant/research support from: AbbVie Asahikasei Pharma Corp. Chugai Pharmaceutical Co, Ltd. Mitsubishi-Tanabe Pharma Corp. Sanofi K.K, Sang-Cheol Bae: None declared, Sean O’Neill Paid instructor for: Advisory board member for GSK, Fiona Goldblatt: None declared, Shereen Oon: None declared, Kathryn Gibson Speakers bureau: UCB, Consultant of: Novartis – co-chair for NSW and steering committee member for ARISE meeting Feb 2021

Janssen Pharmaceuticals – advisory board, Grant/research support from: Novartis, Employee of: Eli Lilly, Kristine Ng Speakers bureau: speaker fees and advisory board (Abbvie, Novartis, Janssen), Annie Law: None declared, Nicola Tugnet: None declared, Sunil Kumar: None declared, Cherica Tee: None declared, Michael Tee: None declared, Yoshiya Tanaka Speakers bureau: Daiichi-Sankyo, Eli Lilly, Novartis, YL Biologics, Bristol-Myers, Eisai, Chugai, Abbvie, Astellas, Pfizer, Sanofi, Asahi-kasei, GSK, Mitsubishi-Tanabe, Gilead, Janssen, Grant/research support from: Daiichi-Sankyo, Eli Lilly, Novartis, YL Biologics, Bristol-Myers, Eisai, Chugai, Abbvie, Astellas, Pfizer, Sanofi, Asahi-kasei, GSK, Mitsubishi-Tanabe, Gilead, Janssen, C.S. Lau Shareholder of: Pfizer, Sanofi and Janssen, Mandana Nikpour Speakers bureau: Actelion, GSK, Janssen, Pfizer, UCB, Paid instructor for: UCB, Consultant of: Actelion, Boehringer Ingelheim, Certa Therapeutics, Eli Lilly, GSK, Janssen, Pfizer, UCB, Grant/research support from: Actelion, Astra Zeneca, BMS, GSK, Janssen, UCB, Alberta Hoi Consultant of: AH is on the advisory board for Abbvie and GSK, Grant/research support from: AH has received research support from AstraZeneca, GSK, BMS, Janssen, and Merck Serono, Eric F. Morand Speakers bureau: AstraZeneca, Paid instructor for: Eli Lilly, Consultant of: AstraZeneca, Amgen, Biogen, BristolMyersSquibb, Eli Lilly, EMD Serono, Genentech, Janssen, Grant/research support from: AstraZeneca, BristolMyersSquibb, Eli Lilly, EMD Serono, Janssen

The Potential Impact and Usability of the Eighth Edition TNM Staging Classification in Oral Cavity Cancer

AIMS

In the current eighth edition head and neck TNM staging, extranodal extension (ENE) is an adverse feature in oral cavity squamous cell cancer (OSCC). The previous seventh edition N1 with ENE is now staged as N2a. Seventh edition N2+ with ENE is staged as N3b in the eighth edition. We evaluated its potential impact on patients treated with surgery and postoperative intensity-modulated radiotherapy (IMRT).

MATERIALS AND METHODS

OSCC patients treated with primary surgery and adjuvant (chemo)radiotherapy between January 2005 and December 2014 were reviewed. Cohorts with pathological node-negative (pN-), pathological node-positive without ENE (pN+_pENE-) and pathological node-positive with ENE (pN+_pENE+) diseases were compared for local control, regional control, distant control and overall survival. The pN+ cohorts were further stratified into seventh edition N-staging subgroups for outcomes comparison.

RESULTS

In total, 478 patients were evaluated: 173 pN-; 159 pN+_pENE-; 146 pN+_pENE+. Outcomes at 5 years were: local control was identical (78%) in all cohorts (P = 0.892), whereas regional control was 91%, 80% and 68%, respectively (P < 0.001). Distant control was 97%, 87%, 68% (P < 0.001) and overall survival was 75%, 53% and 39% (P < 0.001), respectively. Overall survival for N1 and N2a subgroups was not significantly different. In the seventh edition N2b subgroup of pENE- (n = 79) and pENE+ (n = 79) cohorts, overall survival was 67% and 37%, respectively. In the seventh edition N2c subgroups, overall survival for pENE- (n = 17) and pENE+ (n = 38) cohorts was 65% and 35% (P = 0.08), respectively. Overall, an additional 128 patients (42% pN+) were upstaged as N3b.

CONCLUSIONS

When eighth edition staging was applied, stage migration across the N2-3 categories resulted in expected larger separations of overall survival by stage. Patients treated with primary radiation without surgical staging should have outcomes carefully monitored. Strategies to predict ENE preoperatively and trials to improve the outcomes of pENE+ patients should be explored.

POS0028 DEFINING THE PREVALENCE OF UNMET NEED IN SLE: DATA FROM A LARGE MULTINATIONAL LONGITUDINAL SLE COHORT

Background:

The recent prospectively validated definition of the lupus low disease activity state (LLDAS) allows characterisation of patients not achieving a treatment goal, providing impetus for an analysis of unmet needs in SLE using formal definitions. Other recently described definitions of high disease burden include disease activity over time, high disease activity status (HDAS) episodes, and the combination of high disease activity, serological activity and glucocorticoid (GC) use (HDAS+SA+GC).

Objectives:

To determine the prevalence of formal categories of unmet need, and the association of these with adverse outcomes, in SLE.

Methods:

Data from a 13-country longitudinal SLE cohort (ACR/SLICC criteria) were collected between 2013 and 19 using standard templates. Unmet need was defined as (i) patients never attaining LLDAS defined as in Golder et al., 2019 [1], (ii) having persistently active disease (time adjusted mean SLEDAI-2K (AMS) > 4), (iii) ever exhibiting high disease activity status (HDAS; SLEDAI-2K ≥10[2]), or (iv) ever exhibiting all of SLEDAI≥10, serological activity, and glucocorticoid use (HDAS+SA+GC)[3]. Health-related quality of life (HRQoL) was assessed using SF36 (v2) surveys and damage accrual using SLE Damage Index (SDI).

Results:

3,384 SLE patients were followed for 30,313 visits over median [IQR] 2.4 [0.4, 4.3] years. 53% of all visits were not in LLDAS; 813 patients (24%) never achieved LLDAS during observation. Median AMS was 3.0 [1.4, 4.9] and 34% of patients had AMS > 4 throughout the study. 25% of patients had at least one episode of HDAS, representing 8% of visits. 702 patients (21%) had at least one episode of HDAS+SA+GC, representing 8% of visits. Each of never-LLDAS, AMS>4, ever-HDAS, and ever-HDAS+SA+GC were associated with significantly greater number of physician visits, higher mean glucocorticoid dose, lower HRQoL and higher mortality. 31%, 58% and 83% of never-LLDAS, AMS>4, and ever-HDAS patients respectively were also HDAS+SA+GC on at least one occasion.

Conclusion:

Data from a multinational longitudinal SLE cohort indicate that unmet need, defined by LLDAS-never, AMS>4, HDAS, or HDAS+SA+GC, is prevalent in SLE, and that these definitions are associated with poor outcomes.

References:

[1]Golder, V., et al., Lupus low disease activity state as a treatment endpoint for systemic lupus erythematosus: a prospective validation study. The Lancet Rheumatology, 2019. 1(2): p. e95-e102.

[2]Koelmeyer, R., et al., High disease activity status suggests more severe disease and damage accrual in systemic lupus erythematosus. Lupus Sci Med, 2020. 7(1).

[3]van Vollenhoven, R.F., et al., Belimumab in the treatment of systemic lupus erythematosus: high disease activity predictors of response. Annals of the Rheumatic Diseases, 2012. 71(8): p. 1343-1349.

Acknowledgements:

The APLC acknowledges all the Data Collectors and Patients for their valuable contributions to research.

Disclosure of Interests:

Rangi Kandane-Rathnayake: None declared, Worawit Louthrenoo: None declared, Alberta Hoi Consultant of: Abbvie and GSK, Grant/research support from: AstraZeneca, GSK, BMS, Janssen, and Merck Serono, Vera Golder: None declared, Yi-Hsing Chen Speakers bureau: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, AstraZeneca, Sanofi, MSD, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Consultant of: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, AstraZeneca, Sanofi, MSD, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Gilead, Grant/research support from: Pfizer, Norvatis, BMS, Abbevie, Johnson & Johnson, Roche, Sanofi, Guigai, Roche, Boehringer Ingelheim, UCB, MSD, Astra-Zeneca, Astellas, Gilead, Shue Fen Luo: None declared, Yeong-Jian Jan Wu Speakers bureau: Pfizer, Lilly, Novartis, Abbvie, Aisha Lateef: None declared, Jiacai Cho: None declared, Laniyati Hamijoyo Speakers bureau: Pfizer, Novartis, Abbot, Chak Sing Lau Shareholder of: Pfizer, Sanofi, and Janssen, Sandra Navarra Speakers bureau: Pfizer, Johnson & Johnson, Novartis, Astellas, Grant/research support from: Astellas, Johnson & Johnson, Leonid Zamora: None declared, Zhanguo Li Speakers bureau: Eli, Lilly, Novartis, GSK, AbbVie, Paid instructor for: Pfizer, Roche, Johnson., Consultant of: Lilly, Pfizer, Grant/research support from: Pfizer, Yuan An: None declared, Sargunan Sockalingam Speakers bureau: Pfizer, Roche, Novartis, Grant/research support from: Roche and Novartis, Yasuhiro Katsumata Speakers bureau: Chugai Pharmaceutical Co., Ltd., Glaxo-Smithkline K.K., and Sanofi K.K., masayoshi harigai Speakers bureau: AbbVie Japan GK, Ayumi Pharmaceutical Co., Boehringer Ingelheim Japan, Inc.,Bristol Myers Squibb Co., Ltd., Chugai Pharmaceutical Co., Ltd., Eisai Co., Ltd., Eli Lilly Japan K.K., GlaxoSmithKline K.K., Kissei Pharmaceutical Co., Ltd., Pfizer Japan Inc., Takeda Pharmaceutical Co., Ltd., and Teijin Pharma Ltd., Consultant of: AbbVie, Boehringer-ingelheim, Bristol Myers Squibb Co., Kissei Pharmaceutical Co.,Ltd. and Teijin Pharma., Grant/research support from: AbbVie Japan GK, Asahi Kasei Corp., Astellas Pharma Inc., Ayumi Pharmaceutical Co., Bristol Myers Squibb Co., Ltd., Chugai Pharmaceutical Co., Daiichi-Sankyo, Inc.,Eisai Co., Ltd., Kissei Pharmaceutical Co., Ltd., Mitsubishi Tanabe Pharma Co., Nippon Kayaku Co., Ltd., Sekiui Medical, Shionogi & Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co., Ltd., and Teijin Pharma Ltd., Yanjie Hao: None declared, Zhuoli Zhang Speakers bureau: Norvatis, GSK, Pfizer, Jun Kikuchi: None declared, Tsutomu Takeuchi Speakers bureau: AbbVie AYUMI Pharmaceutical Corp. Bristol-Myers Squibb Chugai Pharmaceutical Co, Ltd. Daiichi Sankyo Co., Ltd. Eisai Co., Ltd. Eli Lilly Japan, Gilead Sciences, Inc. Mitsubishi-Tanabe Pharma Corp. Pfizer Japan Inc. Sanofi K.K., Consultant of: Astellas Pharma, Inc. Chugai Pharmaceutical Co, Ltd. Eli Lilly Japan, Mitsubishi-Tanabe Pharma Corp., Grant/research support from: AbbVie, Asahikasei Pharma Corp. Chugai Pharmaceutical Co, Ltd. Mitsubishi-Tanabe Pharma Corp. Sanofi K.K., BMDB Basnayake: None declared, Fiona Goldblatt: None declared, Madelynn Chan Speakers bureau: AbbVie, Novartis, Consultant of: Pfizer, Eli-Lilly, Kristine Ng Speakers bureau: Abbvie, Novartis, Janssen, Sang-Cheol Bae: None declared, Shereen Oon: None declared, Sean O’Neill Consultant of: GSK, Kathryn Gibson Speakers bureau: UCB, Consultant of: Novartis, Janssen, Grant/research support from: Novartis, Sunil Kumar: None declared, Nicola Tugnet: None declared, Yoshiya Tanaka Speakers bureau: Daiichi-Sankyo, Eli Lilly, Novartis, YL Biologics, Bristol-Myers, Eisai, Chugai, Abbvie, Astellas, Pfizer, Sanofi, Asahi-kasei, GSK, Mitsubishi-Tanabe, Gilead, Janssen, Grant/research support from: Abbvie, Mitsubishi-Tanabe, Chugai, Asahi-Kasei, Eisai, Takeda, Daiichi-Sankyo, Mandana Nikpour Speakers bureau: Actelion, GSK, Janssen, Pfizer, UCB, Paid instructor for: UCB, Consultant of: Actelion, Boehringer Ingelheim, Certa Therapeutics, Eli Lilly, GSK, Janssen, Pfizer, UCB, Grant/research support from: Actelion, Astra Zeneca, BMS, GSK, Janssen, UCB, Eric F. Morand Speakers bureau: AstraZeneca, Paid instructor for: Eli Lilly, Consultant of: AstraZeneca, Amgen, Biogen, BristolMyersSquibb, Eli Lilly, EMD Serono, Genentech, Janssen, Grant/research support from: AstraZeneca, BristolMyersSquibb, Eli Lilly, EMD Serono, Janssen.

O15: DISRUPTION OF THE BLOOD-SPINAL CORD BARRIER PREDICTS PERMANENT PARAPLEGIA AFTER THORACOABDOMINAL AORTIC ANEURYSM REPAIR

Introduction

Paraplegia post-thoracoabdominal aortic aneurysm (TAAA) repair remains both a devastating and poorly understood complication. We related temporal changes in cellular and protein composition of cerebrospinal fluid (CSF) to neurological outcomes after TAAA repair to gain mechanistic insights driving paraplegia.

Method

Patients undergoing TAAA repair (open or endovascular) with a CSF drain were prospectively recruited between 2016-2018. CSF was collected pre-operatively and 24-hourly until removal. Daily neurological examinations were performed by blinded neurologists to the study. CSF cell content was characterised by flow cytometry and proteome analysed by tandem-mass-tag proteomics. An in-vivo rat model was modified using 15 minutes of aortic occlusion to produce consistent paraplegia. Rats were analysed neuro-behaviourally and histologically.

Result

CSF was analysed from 52 patients (age: 70.27+/-11.4; 66% male; open (n=9), endovascular (n=43)). 12 developed paraplegia of whom 5 remained permanently-paraplegic. Demographics were comparable between paraplegics, those who recovered and without post-op neurology. Permanent paraplegia was associated with a significant infiltration of CSF CD45+ leucocytes (P&lt;0.0001). Levels of ADVS-1 was &gt;3-fold higher in permanent-paraplegics CSF versus those who recovered (P=0.0008). ADVS-1 &gt;15ng/ml predicted permanent paraplegia with 100% specificity. Pre-treatment with ADVS-1 inhibition significantly improved walking (&lt;0.001) and increased astrocytic staining in the lateral corticospinal, reticulospinal and rubrospinal tracts versus controls (P=0.03, 0.04, 0.04 respectively).

Conclusion

Permanent paraplegia is associated with shedding of ADVS-1 from parenchymal cord into CSF and blood/spinal-cord barrier disruption leading to cord oedema/leucocyte infiltration. Pre-treatment with ADVS-1 inhibition led to neurobehavioural and histological improvements offering translational hope for this devastating complication.

Take-home message

ADVS-1 is a novel biomarker of paraplegia where accurate biomarkers have proven challenging but more importantly it has proven a therapeutic target with genuine translational potential.

Analysis of local invasion and regional spread in malignant sublingual gland tumour: Implications for surgical planning

Malignant tumours arising from the sublingual glands are very rare, and the extent and frequency of local invasion or regional spread in malignant sublingual gland tumour (MSLT) has not been fully studied due to the disease rarity. To provide comprehensive features of local and regional spread of MSLT, we reviewed 20 surgical cases for detailed pathological analyses among 26 cases diagnosed as having primary MSLT. Adenoid cystic carcinoma (ACC) was the most common pathological subtype, followed by mucoepidermoid carcinoma. Disease-free and overall survivals at 5 years were 76.1 % and 77.7 %, respectively. High-grade malignant tumours and grade 2-3 ACC accounted for 41.7 % and 85.7 %. Clinical and pathological extraparenchymal extensions were found in 34.6 % and 80.0 %, respectively. Tumour invasion to the lingual nerve and submandibular gland/ductal system were also detected in 40.0 % and 28.6 %. The incidences of lingual nerve invasion in ACC and ACC ≥4 cm were 30.8 % and 42.9 %. Regional nodal involvement occurred in seven of 26 cases, and all metastatic lymph nodes were found in neck levels Ib and IIa. In summary, a significant portion of MSLT cases consisted of high-grade tumours and grade 2-3 ACC; therefore local invasion into adjacent structures should be cautiously evaluated in cases of MSLT.

Phenotyping right heart function for prognosticating heart failure

Funding Acknowledgements

Type of funding sources: None.

Background

Right heart failure has been shown to portend poor prognosis. The pathophysiology of right heart function is complex, as right ventricular (RV) function is easily affected by preload and afterload.

Purpose

To test the hypothesis that machine learning would detect heterogeneity in right heart function and improve risk stratifications in a heart failure population

Methods

This study included 403 heart failure patients who had a history of hospitalization for decompensation. Patients were excluded if they had primary heart valve disease or pericardial disease or a previous cardiac surgery. Hierarchical clustering was undertaken on right heart variables (RV strain, right ventricular systolic pressure (RVSP), vena contracta of tricuspid regurgitation (TR) and diameter of inferior vena cava) to identify homogenous groups of patients with similar profiles of the variables. Cox hazard analysis was used to elucidate the benefit of clustering over each variable for prognosticating heart failure. Endpoint was hospitalization for worsening heart failure.

Results

Cluster analysis identified three groups with distinct right heart function. Cluster 1 (n = 191) represented patients with preserved RV function and low RVSP (figure A).  On the other hand, cluster 2 (n = 144) had reduced RV function and low RVSP, while cluster 3 (n = 68) had preserved RV function and high RVSP, associated with severe TR and high central venous pressure. The latter 2 clusters carried worse outcome than cluster 1 (p &lt; 0.001, figure B). Cox hazard analysis demonstrated that, although the addition of each right heart variable to baseline model constructed from left heart variables did not improve predictive power, clusters predicted events with a hazard ratio of 1.566, independent from and incremental to the left heart variables (Figure C).

Conclusion

Cluster analysis identified two distinct phenotypes of right heart failure that were associated with adverse outcomes. This data-driven phenotyping can help in categorizing right heart failure and better prognosticating heart failure.

Abstract Figure.

Phase Angle and Frailty Are Important Prognostic Factors in Critically Ill Medical Patients: A Prospective Cohort Study

OBJECTIVES

To investigate whether phase angle (PhA) measured by bioelectrical impedance analysis (BIA) and frailty are associated with the outcomes of critical illnesses.

DESIGN

A single-center prospective cohort study.

SETTING

Medical intensive care unit (ICU) in Seoul National University Hospital, Seoul, Republic of Korea.

PARTICIPANTS

97 patients who were admitted to the medical ICU.

MEASUREMENTS

On admission, PhA was measured by BIA, and frailty was assessed by the Korean Modified Barthel Index (KMBI) scoring system. Patients were classified according to PhA and KMBI scores, and their impact on the outcomes of critical illnesses was evaluated.

RESULTS

The patients' mean age was 62.4 ± 16.4 years, and 56 of the patients (57.7%) were men. Having a high PhA above 3.5 at the time of ICU admission was associated with lower in-hospital mortality (adjusted OR 0.42, p = .042), and a shorter duration of ICU stay (5.6 days vs. 9.8 days, p = .016) compared to those with a low PhA. Other indices measured by BIA were not significantly associated with outcomes of critical illnesses. Frailty (KMBI > 60) was associated with more mechanical ventilation days (2.3 days vs. 7.1 days; p = .018).

CONCLUSION

Both PhA and frailty are important prognostic factors predicting the outcomes of critical illnesses. Low PhA scores were associated with increased mortality and a longer duration of ICU stay, and frailty was associated with more mechanical ventilation days.

Presenting stage and risk group in men dying of prostate cancer

Introduction

Prostate cancer remains the 3rd leading cause of cancer-related mortality in Canadian men, and yet screening for prostate cancer continues to be controversial because the majority of men diagnosed with prostate cancer do not die of the disease. It also remains uncertain whether treatment of cases that can be treated with curative intent alters the mortality rate. There are very few studies describing the presenting stage, risk groups, and survival after diagnosis for men dying of prostate cancer in the literature. In this study, we explored these characteristics for all men who died of prostate cancer in British Columbia between 2013 and 2015.

Methods

The population-based BC Cancer databases were used to identify all patients diagnosed between January 2013 and December 2015 who died of prostate cancer. Patient, tumour, and treatment characteristics were collected, and the risk grouping for each tumour was determined. The proportion of cases in each risk group at the time of diagnosis was determined. Survival time from diagnosis to death was calculated for all patients and for each risk group using the Kaplan-Meier method.

Results

A total of 1256 patients died of prostate cancer. Of patients who presented with metastatic disease, 57.2% presented with a Gleason score of 8 or more, compared with only 35.7% of patients who presented with nonmetastatic disease (p < 0.0001). The presenting stage and risk group of those dying of prostate cancer were as follows: 32% metastatic disease, 3% regional (defined as node-positive), 39% localized high risk, 9% localized intermediate risk, 4% localized low risk, 6% localized not otherwise specified, and 7% unknown. Therefore, 80.3% of those with a known risk group presented with either localized high-risk, regional, or metastatic disease at diagnosis. The median survival times from diagnosis to death were 12 years for localized low-risk, 10 years for localized intermediate-risk, 6.5 years for localized high-risk, 4 years for regional, and 1.7 years for metastatic disease at diagnosis.

Conclusions

This population-based analysis demonstrates that patients with localized high-risk, regional, or metastatic disease at diagnosis constitute the overwhelming majority of patients who die of prostate cancer in British Columbia. Unless these disease states can reliably be identified at an earlier low- or intermediate-risk localized state in the future, it is unlikely that treatment of localized low- and intermediate-risk cancer will have an impact on survival. Furthermore, patients with de novo metastatic disease had identifiable risk factors of a higher prostate-specific antigen and Gleason score. Further studies are required to confirm these results.

Deep-learning algorithms for the interpretation of chest radiographs to aid in the triage of COVID-19 patients: A multicenter retrospective study

The recent medical applications of deep-learning (DL) algorithms have demonstrated their clinical efficacy in improving speed and accuracy of image interpretation. If the DL algorithm achieves a performance equivalent to that achieved by physicians in chest radiography (CR) diagnoses with Coronavirus disease 2019 (COVID-19) pneumonia, the automatic interpretation of the CR with DL algorithms can significantly reduce the burden on clinicians and radiologists in sudden surges of suspected COVID-19 patients. The aim of this study was to evaluate the efficacy of the DL algorithm for detecting COVID-19 pneumonia on CR compared with formal radiology reports. This is a retrospective study of adult patients that were diagnosed as positive COVID-19 cases based on the reverse transcription polymerase chain reaction among all the patients who were admitted to five emergency departments and one community treatment center in Korea from February 18, 2020 to May 1, 2020. The CR images were evaluated with a publicly available DL algorithm. For reference, CR images without chest computed tomography (CT) scans classified as positive for COVID-19 pneumonia were used given that the radiologist identified ground-glass opacity, consolidation, or other infiltration in retrospectively reviewed CR images. Patients with evidence of pneumonia on chest CT scans were also classified as COVID-19 pneumonia positive outcomes. The overall sensitivity and specificity of the DL algorithm for detecting COVID-19 pneumonia on CR were 95.6%, and 88.7%, respectively. The area under the curve value of the DL algorithm for the detection of COVID-19 with pneumonia was 0.921. The DL algorithm demonstrated a satisfactory diagnostic performance comparable with that of formal radiology reports in the CR-based diagnosis of pneumonia in COVID-19 patients. The DL algorithm may offer fast and reliable examinations that can facilitate patient screening and isolation decisions, which can reduce the medical staff workload during COVID-19 pandemic situations.