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What “BIG DATA” Can Do forWhat “BIG DATA” Can Do for
Regional AnesthesiologistsRegional Anesthesiologists
Edward R. Mariano, M.D., M.A.S.Edward R. Mariano, M.D., M.A.S.
Associate Professor of AnesthesiologyAssociate Professor of Anesthesiology
Stanford University School of MedicineStanford University School of Medicine
Chief, Anesthesiology and Perioperative CareChief, Anesthesiology and Perioperative Care
Veterans Affairs Palo Alto Health CareVeterans Affairs Palo Alto Health Care
SystemSystem
@EMARIANOMD@EMARIANOMD
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Financial DisclosuresFinancial Disclosures
 Halyard (formerly I-Flow), B Braun –Halyard (formerly I-Flow), B Braun –
Unrestricted educational program fundingUnrestricted educational program funding
paid to my institutionpaid to my institution
The contents of the following presentationThe contents of the following presentation
are solely the responsibility of the speakerare solely the responsibility of the speaker
without input from any of the abovewithout input from any of the above
companies.companies.
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
How Do We Study Rare Outcomes?How Do We Study Rare Outcomes?
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Private DatabasesPrivate Databases
 Premier Perspective database (Charlotte,Premier Perspective database (Charlotte,
NC, USA)NC, USA)
 382, 236382, 236 patients in approx 400 US acutepatients in approx 400 US acute
care hospitals over 4 yearscare hospitals over 4 years
Memtsoudis SG, et al. Anesth 2013;118:1046Memtsoudis SG, et al. Anesth 2013;118:1046
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
American College of SurgeonsAmerican College of Surgeons
 Started in the Veterans HealthStarted in the Veterans Health
Administration in the 1980sAdministration in the 1980s
 Adopted and expanded by the AmericanAdopted and expanded by the American
College of Surgeons into NSQIPCollege of Surgeons into NSQIP
Schechter MA, et al. Surgery 2012;152:309Schechter MA, et al. Surgery 2012;152:309
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Prospective RegistriesProspective Registries
 ““AURORA” started with practices inAURORA” started with practices in
Australia and New Zealand – nowAustralia and New Zealand – now
internationalinternational
 Voluntary reportingVoluntary reporting
Barrington MJ, et al. RAPM 2009;34:534Barrington MJ, et al. RAPM 2009;34:534
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Potential Limitations of Big DataPotential Limitations of Big Data
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Potential Limitations of Big DataPotential Limitations of Big Data
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Anesthesia Type and MortalityAnesthesia Type and Mortality
 30-day mortality was lower30-day mortality was lower for neuraxial andfor neuraxial and
neuraxial/GA vs. GA alone for TKAneuraxial/GA vs. GA alone for TKA
 Most in-hospital complications were lowerMost in-hospital complications were lower
for neuraxial and neuraxial/GA vs. GA alonefor neuraxial and neuraxial/GA vs. GA alone
 Transfusion requirements lowest forTransfusion requirements lowest for
neuraxialneuraxial
Memtsoudis SG, et al. Anesth 2013;118:1046Memtsoudis SG, et al. Anesth 2013;118:1046
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Anesthesia Type and MortalityAnesthesia Type and Mortality
 No difference in 30-day mortalityNo difference in 30-day mortality betweenbetween
regional anesthesia and GAregional anesthesia and GA
 Regional anesthesia patients are moreRegional anesthesia patients are more
likely to have shorter operative time andlikely to have shorter operative time and
next-day dischargenext-day discharge
Schechter MA, et al. Surgery 2012;152:309Schechter MA, et al. Surgery 2012;152:309
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Anesthesia Type and MortalityAnesthesia Type and Mortality
 N=6009;N=6009; no difference in 30-day mortalityno difference in 30-day mortality
based on anesthesia typebased on anesthesia type
 Increased pulmonary complications andIncreased pulmonary complications and
length of stay for GA vs. spinal orlength of stay for GA vs. spinal or
local/MAClocal/MAC
Edwards MS, et al. J Vasc Surg 2011;54:1273Edwards MS, et al. J Vasc Surg 2011;54:1273
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Analgesia and Cancer RecurrenceAnalgesia and Cancer Recurrence
 Retrospective review of patients withRetrospective review of patients with
palpable breast lesions who underwentpalpable breast lesions who underwent
mastectomy and axillary clearance withmastectomy and axillary clearance with
PVB catheters x 48h vs. opioid IV PCAPVB catheters x 48h vs. opioid IV PCA
 Primary outcome: metastases or cancerPrimary outcome: metastases or cancer
recurrence over 2.5-4 year follow-up (fixedrecurrence over 2.5-4 year follow-up (fixed
time point)time point)
Exadaktylos AK, et al. Anesth 2006;105:660Exadaktylos AK, et al. Anesth 2006;105:660
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Analgesia and Cancer RecurrenceAnalgesia and Cancer Recurrence
 129 patients met inclusion criteria129 patients met inclusion criteria
– 50 patients received PVB (2 failures)50 patients received PVB (2 failures)
– 79 patients received IV PCA79 patients received IV PCA
 No demographic, tumor quality, orNo demographic, tumor quality, or
therapeutic differences between groupstherapeutic differences between groups
 Recurrence/metastasis rates:Recurrence/metastasis rates:
– 19/79 (24%) in IV PCA group19/79 (24%) in IV PCA group
– 3/50 (6%) in PVB group3/50 (6%) in PVB group
– p=0.013p=0.013
Exadaktylos AK, et al. Anesth 2006;105:660Exadaktylos AK, et al. Anesth 2006;105:660
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Analgesia and Cancer RecurrenceAnalgesia and Cancer Recurrence
 129 patients met inclusion criteria129 patients met inclusion criteria
– 50 patients received PVB (2 failures)50 patients received PVB (2 failures)
– 79 patients received IV PCA79 patients received IV PCA
 No demographic, tumor quality, orNo demographic, tumor quality, or
therapeutic differences between groupstherapeutic differences between groups
 Recurrence/metastasis rates:Recurrence/metastasis rates:
– 19/79 (24%) in IV PCA group19/79 (24%) in IV PCA group
– 3/50 (6%) in PVB group3/50 (6%) in PVB group
– p=0.013p=0.013
Exadaktylos AK, et al. Anesth 2006;105:660Exadaktylos AK, et al. Anesth 2006;105:660
Mechanism?
Preserving immune
competence?
Direct effect?
Indirect effect? Both?
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Cancer Recurrence andCancer Recurrence and
SurvivalSurvival
Myles PS, et al. BMJ 2011;342:d1491Myles PS, et al. BMJ 2011;342:d1491
 N=446; long-term follow-up of RCTN=446; long-term follow-up of RCT
subjects GA/epidural vs. GA/opioidsubjects GA/epidural vs. GA/opioid
 No difference in recurrence-free survivalNo difference in recurrence-free survival
or overall mortalityor overall mortality
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Cancer Recurrence andCancer Recurrence and
SurvivalSurvival
Myles PS, et al. BMJ 2011;342:d1491Myles PS, et al. BMJ 2011;342:d1491
 N=446; long-term follow-up of RCTN=446; long-term follow-up of RCT
subjects GA/epidural vs. GA/opioidsubjects GA/epidural vs. GA/opioid
 No difference in recurrence-free survivalNo difference in recurrence-free survival
or overall mortalityor overall mortality
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Cancer Recurrence andCancer Recurrence and
SurvivalSurvival
 14 studies met criteria EA±GA vs. GA14 studies met criteria EA±GA vs. GA
(including Cummings study, n=42,151)(including Cummings study, n=42,151)
 Improved overall survival with EAImproved overall survival with EA
 No difference in cancer recurrenceNo difference in cancer recurrence
Chen & Miao. PLOS ONE 2013;8:e56540Chen & Miao. PLOS ONE 2013;8:e56540
Cummings KC, et al. Anesth 2012;116:797Cummings KC, et al. Anesth 2012;116:797
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Chronic Pain after Breast SurgeryChronic Pain after Breast Surgery
 Survey of 479 women who underwentSurvey of 479 women who underwent
breast surgery over a 4-year periodbreast surgery over a 4-year period
 59% response rate59% response rate
 Prevalence of pain after >1 year postop:Prevalence of pain after >1 year postop:
– Mastectomy/reconstruction =Mastectomy/reconstruction = 49%49%
– Mastectomy alone =Mastectomy alone = 31%31%
– Augmentation =Augmentation = 38%38%
– Reduction =Reduction = 22%22%
Wallace MS, et al. Pain 1996;66:195Wallace MS, et al. Pain 1996;66:195
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Chronic Pain after Breast SurgeryChronic Pain after Breast Surgery
 Meta-analysis: 3 studies assessed thisMeta-analysis: 3 studies assessed this
outcome (n=167)outcome (n=167)
 All PVB-GA vs. GAAll PVB-GA vs. GA
 At 6 mos, RR=0.16, 95%CI (0.02-1.13)At 6 mos, RR=0.16, 95%CI (0.02-1.13)
– No difference (crosses 1)No difference (crosses 1)
 At 12 mos, RR=0.61, 95%CI (0.08-4.90)At 12 mos, RR=0.61, 95%CI (0.08-4.90)
– No difference (crosses 1)No difference (crosses 1)
Schnabel A, et al. BJA 2010;105:842Schnabel A, et al. BJA 2010;105:842
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Chronic Pain after ThoracotomyChronic Pain after Thoracotomy
 Incidence is approximatelyIncidence is approximately 50%50%
– 3-16% report pain as moderate-severe3-16% report pain as moderate-severe
 Heterogeneity in study designsHeterogeneity in study designs
 Many contributing factors: patients,Many contributing factors: patients,
surgical technique, pre- and postop painsurgical technique, pre- and postop pain
 To date,To date, no convincing evidenceno convincing evidence that PVBthat PVB
decreases chronic pain after thoracotomydecreases chronic pain after thoracotomy
Wildgaard & Kehlet. Eur J CTS 2009;36:170Wildgaard & Kehlet. Eur J CTS 2009;36:170
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Ultrasound and Patient SafetyUltrasound and Patient Safety
 Overall incidence of nerve injury due toOverall incidence of nerve injury due to
block=0.4 per 1000 blocksblock=0.4 per 1000 blocks
 Overall incidence of LAST=0.98 per 1000Overall incidence of LAST=0.98 per 1000
blocksblocks
 No difference with or without ultrasoundNo difference with or without ultrasound
Barrington MJ, et al. RAPM 2009;34:534Barrington MJ, et al. RAPM 2009;34:534
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
Ultrasound and Patient SafetyUltrasound and Patient Safety
 22 cases of LAST in 25,336 blocks (overall22 cases of LAST in 25,336 blocks (overall
incidence=0.87 per 1000)incidence=0.87 per 1000)
 LAST cases: 12/20,401 blocks with US vs.LAST cases: 12/20,401 blocks with US vs.
10/4745 blocks without US (10/4745 blocks without US (p=0.004p=0.004))
Barrington MJ, et al. RAPM 2013;38:289Barrington MJ, et al. RAPM 2013;38:289
Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists
SummarySummary
 Big data may offer means to study rareBig data may offer means to study rare
outcomes but has limitationsoutcomes but has limitations
 Anesthesia and analgesia choice mayAnesthesia and analgesia choice may
affect survivalaffect survival
 No convincing evidence to date thatNo convincing evidence to date that
analgesia affects cancer recurrence oranalgesia affects cancer recurrence or
persistent postsurgical painpersistent postsurgical pain
 Ultrasound may reduce incidence of LASTUltrasound may reduce incidence of LAST

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What Big Data Can Do for Regional Anesthesiologists

  • 1. What “BIG DATA” Can Do forWhat “BIG DATA” Can Do for Regional AnesthesiologistsRegional Anesthesiologists Edward R. Mariano, M.D., M.A.S.Edward R. Mariano, M.D., M.A.S. Associate Professor of AnesthesiologyAssociate Professor of Anesthesiology Stanford University School of MedicineStanford University School of Medicine Chief, Anesthesiology and Perioperative CareChief, Anesthesiology and Perioperative Care Veterans Affairs Palo Alto Health CareVeterans Affairs Palo Alto Health Care SystemSystem @EMARIANOMD@EMARIANOMD
  • 2. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Financial DisclosuresFinancial Disclosures  Halyard (formerly I-Flow), B Braun –Halyard (formerly I-Flow), B Braun – Unrestricted educational program fundingUnrestricted educational program funding paid to my institutionpaid to my institution The contents of the following presentationThe contents of the following presentation are solely the responsibility of the speakerare solely the responsibility of the speaker without input from any of the abovewithout input from any of the above companies.companies.
  • 3. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists How Do We Study Rare Outcomes?How Do We Study Rare Outcomes?
  • 4. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Private DatabasesPrivate Databases  Premier Perspective database (Charlotte,Premier Perspective database (Charlotte, NC, USA)NC, USA)  382, 236382, 236 patients in approx 400 US acutepatients in approx 400 US acute care hospitals over 4 yearscare hospitals over 4 years Memtsoudis SG, et al. Anesth 2013;118:1046Memtsoudis SG, et al. Anesth 2013;118:1046
  • 5. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists American College of SurgeonsAmerican College of Surgeons  Started in the Veterans HealthStarted in the Veterans Health Administration in the 1980sAdministration in the 1980s  Adopted and expanded by the AmericanAdopted and expanded by the American College of Surgeons into NSQIPCollege of Surgeons into NSQIP Schechter MA, et al. Surgery 2012;152:309Schechter MA, et al. Surgery 2012;152:309
  • 6. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Prospective RegistriesProspective Registries  ““AURORA” started with practices inAURORA” started with practices in Australia and New Zealand – nowAustralia and New Zealand – now internationalinternational  Voluntary reportingVoluntary reporting Barrington MJ, et al. RAPM 2009;34:534Barrington MJ, et al. RAPM 2009;34:534
  • 7. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Potential Limitations of Big DataPotential Limitations of Big Data
  • 8. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Potential Limitations of Big DataPotential Limitations of Big Data
  • 9. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Anesthesia Type and MortalityAnesthesia Type and Mortality  30-day mortality was lower30-day mortality was lower for neuraxial andfor neuraxial and neuraxial/GA vs. GA alone for TKAneuraxial/GA vs. GA alone for TKA  Most in-hospital complications were lowerMost in-hospital complications were lower for neuraxial and neuraxial/GA vs. GA alonefor neuraxial and neuraxial/GA vs. GA alone  Transfusion requirements lowest forTransfusion requirements lowest for neuraxialneuraxial Memtsoudis SG, et al. Anesth 2013;118:1046Memtsoudis SG, et al. Anesth 2013;118:1046
  • 10. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Anesthesia Type and MortalityAnesthesia Type and Mortality  No difference in 30-day mortalityNo difference in 30-day mortality betweenbetween regional anesthesia and GAregional anesthesia and GA  Regional anesthesia patients are moreRegional anesthesia patients are more likely to have shorter operative time andlikely to have shorter operative time and next-day dischargenext-day discharge Schechter MA, et al. Surgery 2012;152:309Schechter MA, et al. Surgery 2012;152:309
  • 11. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Anesthesia Type and MortalityAnesthesia Type and Mortality  N=6009;N=6009; no difference in 30-day mortalityno difference in 30-day mortality based on anesthesia typebased on anesthesia type  Increased pulmonary complications andIncreased pulmonary complications and length of stay for GA vs. spinal orlength of stay for GA vs. spinal or local/MAClocal/MAC Edwards MS, et al. J Vasc Surg 2011;54:1273Edwards MS, et al. J Vasc Surg 2011;54:1273
  • 12. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Analgesia and Cancer RecurrenceAnalgesia and Cancer Recurrence  Retrospective review of patients withRetrospective review of patients with palpable breast lesions who underwentpalpable breast lesions who underwent mastectomy and axillary clearance withmastectomy and axillary clearance with PVB catheters x 48h vs. opioid IV PCAPVB catheters x 48h vs. opioid IV PCA  Primary outcome: metastases or cancerPrimary outcome: metastases or cancer recurrence over 2.5-4 year follow-up (fixedrecurrence over 2.5-4 year follow-up (fixed time point)time point) Exadaktylos AK, et al. Anesth 2006;105:660Exadaktylos AK, et al. Anesth 2006;105:660
  • 13. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Analgesia and Cancer RecurrenceAnalgesia and Cancer Recurrence  129 patients met inclusion criteria129 patients met inclusion criteria – 50 patients received PVB (2 failures)50 patients received PVB (2 failures) – 79 patients received IV PCA79 patients received IV PCA  No demographic, tumor quality, orNo demographic, tumor quality, or therapeutic differences between groupstherapeutic differences between groups  Recurrence/metastasis rates:Recurrence/metastasis rates: – 19/79 (24%) in IV PCA group19/79 (24%) in IV PCA group – 3/50 (6%) in PVB group3/50 (6%) in PVB group – p=0.013p=0.013 Exadaktylos AK, et al. Anesth 2006;105:660Exadaktylos AK, et al. Anesth 2006;105:660
  • 14. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Analgesia and Cancer RecurrenceAnalgesia and Cancer Recurrence  129 patients met inclusion criteria129 patients met inclusion criteria – 50 patients received PVB (2 failures)50 patients received PVB (2 failures) – 79 patients received IV PCA79 patients received IV PCA  No demographic, tumor quality, orNo demographic, tumor quality, or therapeutic differences between groupstherapeutic differences between groups  Recurrence/metastasis rates:Recurrence/metastasis rates: – 19/79 (24%) in IV PCA group19/79 (24%) in IV PCA group – 3/50 (6%) in PVB group3/50 (6%) in PVB group – p=0.013p=0.013 Exadaktylos AK, et al. Anesth 2006;105:660Exadaktylos AK, et al. Anesth 2006;105:660 Mechanism? Preserving immune competence? Direct effect? Indirect effect? Both?
  • 15. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Cancer Recurrence andCancer Recurrence and SurvivalSurvival Myles PS, et al. BMJ 2011;342:d1491Myles PS, et al. BMJ 2011;342:d1491  N=446; long-term follow-up of RCTN=446; long-term follow-up of RCT subjects GA/epidural vs. GA/opioidsubjects GA/epidural vs. GA/opioid  No difference in recurrence-free survivalNo difference in recurrence-free survival or overall mortalityor overall mortality
  • 16. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Cancer Recurrence andCancer Recurrence and SurvivalSurvival Myles PS, et al. BMJ 2011;342:d1491Myles PS, et al. BMJ 2011;342:d1491  N=446; long-term follow-up of RCTN=446; long-term follow-up of RCT subjects GA/epidural vs. GA/opioidsubjects GA/epidural vs. GA/opioid  No difference in recurrence-free survivalNo difference in recurrence-free survival or overall mortalityor overall mortality
  • 17. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Cancer Recurrence andCancer Recurrence and SurvivalSurvival  14 studies met criteria EA±GA vs. GA14 studies met criteria EA±GA vs. GA (including Cummings study, n=42,151)(including Cummings study, n=42,151)  Improved overall survival with EAImproved overall survival with EA  No difference in cancer recurrenceNo difference in cancer recurrence Chen & Miao. PLOS ONE 2013;8:e56540Chen & Miao. PLOS ONE 2013;8:e56540 Cummings KC, et al. Anesth 2012;116:797Cummings KC, et al. Anesth 2012;116:797
  • 18. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Chronic Pain after Breast SurgeryChronic Pain after Breast Surgery  Survey of 479 women who underwentSurvey of 479 women who underwent breast surgery over a 4-year periodbreast surgery over a 4-year period  59% response rate59% response rate  Prevalence of pain after >1 year postop:Prevalence of pain after >1 year postop: – Mastectomy/reconstruction =Mastectomy/reconstruction = 49%49% – Mastectomy alone =Mastectomy alone = 31%31% – Augmentation =Augmentation = 38%38% – Reduction =Reduction = 22%22% Wallace MS, et al. Pain 1996;66:195Wallace MS, et al. Pain 1996;66:195
  • 19. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Chronic Pain after Breast SurgeryChronic Pain after Breast Surgery  Meta-analysis: 3 studies assessed thisMeta-analysis: 3 studies assessed this outcome (n=167)outcome (n=167)  All PVB-GA vs. GAAll PVB-GA vs. GA  At 6 mos, RR=0.16, 95%CI (0.02-1.13)At 6 mos, RR=0.16, 95%CI (0.02-1.13) – No difference (crosses 1)No difference (crosses 1)  At 12 mos, RR=0.61, 95%CI (0.08-4.90)At 12 mos, RR=0.61, 95%CI (0.08-4.90) – No difference (crosses 1)No difference (crosses 1) Schnabel A, et al. BJA 2010;105:842Schnabel A, et al. BJA 2010;105:842
  • 20. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Chronic Pain after ThoracotomyChronic Pain after Thoracotomy  Incidence is approximatelyIncidence is approximately 50%50% – 3-16% report pain as moderate-severe3-16% report pain as moderate-severe  Heterogeneity in study designsHeterogeneity in study designs  Many contributing factors: patients,Many contributing factors: patients, surgical technique, pre- and postop painsurgical technique, pre- and postop pain  To date,To date, no convincing evidenceno convincing evidence that PVBthat PVB decreases chronic pain after thoracotomydecreases chronic pain after thoracotomy Wildgaard & Kehlet. Eur J CTS 2009;36:170Wildgaard & Kehlet. Eur J CTS 2009;36:170
  • 21. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Ultrasound and Patient SafetyUltrasound and Patient Safety  Overall incidence of nerve injury due toOverall incidence of nerve injury due to block=0.4 per 1000 blocksblock=0.4 per 1000 blocks  Overall incidence of LAST=0.98 per 1000Overall incidence of LAST=0.98 per 1000 blocksblocks  No difference with or without ultrasoundNo difference with or without ultrasound Barrington MJ, et al. RAPM 2009;34:534Barrington MJ, et al. RAPM 2009;34:534
  • 22. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists Ultrasound and Patient SafetyUltrasound and Patient Safety  22 cases of LAST in 25,336 blocks (overall22 cases of LAST in 25,336 blocks (overall incidence=0.87 per 1000)incidence=0.87 per 1000)  LAST cases: 12/20,401 blocks with US vs.LAST cases: 12/20,401 blocks with US vs. 10/4745 blocks without US (10/4745 blocks without US (p=0.004p=0.004)) Barrington MJ, et al. RAPM 2013;38:289Barrington MJ, et al. RAPM 2013;38:289
  • 23. Big Data for Regional AnesthesiologistsBig Data for Regional Anesthesiologists SummarySummary  Big data may offer means to study rareBig data may offer means to study rare outcomes but has limitationsoutcomes but has limitations  Anesthesia and analgesia choice mayAnesthesia and analgesia choice may affect survivalaffect survival  No convincing evidence to date thatNo convincing evidence to date that analgesia affects cancer recurrence oranalgesia affects cancer recurrence or persistent postsurgical painpersistent postsurgical pain  Ultrasound may reduce incidence of LASTUltrasound may reduce incidence of LAST