Additional file 1 of Days at home alive after major surgery in patients with and without diabetes: an observational cohort study

Additional file 1: Table S1. Univariate and multivariable logistic regression for low DAH30 with ICD-10 codes as proxy for comorbidity. Table S2. Univariate and multivariable logistic regression for one year mortality with ICD-10 codes as proxy for comorbidity. Fig. S1. Kaplan Meier curve for one year mortality for DM 1 vs nondiabetics. Fig. S2. Kaplan Meier curve for one year mortality for DM 2 vs nondiabetics

Additional file 1 of Postoperative analgesia for upper gastrointestinal surgery: a retrospective cohort analysis

Additional file 1. a Post-operative morphine requirements. b.  Post-operative rest pain. c Post-operative dynamic pain

Implementing PROMS for elective surgery patients: feasibility, response rate, degree of recovery and patient acceptability

 Background: Patient reported outcome measures (PROMs) engage patients in co-evaluation of their health and  wellbeing outcomes. This study aimed to determine the feasibility, response rate, degree of recovery and patient  acceptability of a PROM survey for elective surgery. Methods: We sampled patients with a broad range of elective surgeries from four major Australian hospitals to evaluate (1) feasibility of the technology used to implement the PROMs across geographically dispersed sites, (2) response  rates for automated short message service (SMS) versus email survey delivery formats, (3) the degree of recovery at  one and four weeks post-surgery as measured by the Quality of Recovery 15 Item PROM (QoR-15), and (4) patient  acceptability of PROMS based on survey and focus group results. Feasibility and acceptability recommendations were  then co-designed with stakeholders, based on the data. Results: Over three months there were 5985 surveys responses from 20,052 surveys (30% response rate). Feasibility  testing revealed minor and infrequent technical difculties in automated email and SMS administration of PROMs  prior to surgery. The response rate for the QoR-15 was 34.8% (n=3108/8919) for SMS and 25.8% (n=2877/11,133)  for email. Mean QoR-15 scores were 122.1 (SD 25.2; n=1021); 113.1 (SD 27.7; n=1906) and 123.4 (SD 26.84; n=1051)  for pre-surgery and one and four weeks post-surgery, respectively. One week after surgery, 825 of the 1906 responses  (43%) exceeded 122.6 (pre-surgery average), and at four weeks post-surgery, 676 of the 1051 responses (64%)  exceeded 122.6 (pre-surgery average). The PROM survey was highly acceptable with 76% (n=2830/3739) of patients  rating 8/10 or above for acceptability. Fourteen patient driven recommendations were then co-developed. Conclusion: Administering PROMS electronically for elective surgery hospital patients was feasible, acceptable and  discriminated changes in surgical recovery over time. Patient co-design and involvement provided innovative and  practical solutions to implementation and new recommendations for implementation. Trial Registration and Ethical Approval ACTRN12621000298819 (Phase I and II) and ACTRN12621000969864 (Phase  III). Ethics approval has been obtained from La Trobe University (Australia) Human Research Ethics Committee  (HEC20479). </p

Patient judgement of change with elective surgery correlates with patient reported outcomes and quality of life

Obtaining pre-surgery PROM measures is not always feasible. The aim of this study was to examine if self-reports of change following elective surgery correlate with change scores from a validated PROM (15-item Quality of Recovery (QoR-15)). This cross-sectional study across 29 hospitals enrolled elective surgery patients. PROMs were collected one-week pre-surgery, as well as one- and four-weeks post-surgery via an electronic survey. We examined associations between patient “judgement of change” at one and four-weeks after surgery and the actual pre-to post-surgery PROM change scores. A total of 4177 surveys were received. The correlation between patient judgement of change, and the actual change score was moderately strong at one-week (n = 247, rs = 0.512, p < 0.001), yet low at four-weeks (n = 241, rs = 0.340, p < 0.001). Patient judgement was aligned to the direction of the PROM change score from pre- to post-surgery. We also examined the correlation between the QoR-15 (quality of recovery) and the EQ-5D-5L (QOL). There was a moderately strong positive correlation between the two PROMs (n = 356, rs = 0.666, p < 0.001), indicating that change in quality of recovery was related to change in QOL. These findings support the use of a single “judgement of change” recall question post-surgery. </p

Additional file 1 of Tranexamic acid alters the immunophenotype of phagocytes after lower limb surgery

Additional file 1: Supplementary Figure 1. Gating strategy used to identify myeloid cells. Supplementary Figure 2. Gating strategy used to identify B cells. Supplementary Figure 3. Gating strategy used to identify NK cells. Supplementary Figure 4. Comparison of results for TXA-treated patients in the randomised and after the randomised recruitment. Supplementary Figure 5. Plasmin-antiplasmin (PAP) complex as a readout for plasmin generation

Supplementary Material from Preoperative β-Blockade with Propranolol Reduces Biomarkers of Metastasis in Breast Cancer: A Phase II Randomized Trial

Supplementary Material</p

Additional file 1 of Comparison of 6-month outcomes of sepsis versus non-sepsis critically ill patients receiving mechanical ventilation

Additional file 1. The electronic supplement includes additional information about the study including methods and results, participating sites, missing data, adjusted and unadjusted analyses, the flowchart of included participants, trajectory of long-term outcomes and incidence of disability

Additional file 1 of The impact of COVID-19 critical illness on new disability, functional outcomes and return to work at 6 months: a prospective cohort study

Additional file 1: Electronic Supplementary Appendix to The COVID-Recovery Study