An Alternative Solution in Wide-Awake Surgery: The Preston WALANT Mixture
Bibliographic record
Abstract
The COVID-19 outbreak continues to be a global health crisis of enormous magnitude riddled with disruption and uncertainty. This has had a significant impact on the delivery of both emergency and elective hand surgery worldwide. Limited access to the operating theater, coupled with a downgrade in anesthetic support, has driven the need to source innovative means of providing such vital services. For this purpose, wide-awake local anesthesia no tourniquet (WALANT) technique is witnessing a sharp increase in its implementation. The benefits of this technique to patient, surgeon and healthcare provider are well-established.[ 1 ] Amidst the current crisis, WALANT also provides a tool that minimizes the risk of viral transmission to airway specialists, especially at a time when safety of healthcare providers remains paramount.[ 2 ] The original description by Don Lalonde for WALANT uses local anesthetic (LA) at a concentration of 1% lidocaine/1:100,000ad. This premixed solution is readily available in the US and Canada.[ 1 ] In Europe, sourcing this mixture is more challenging. Premixed solutions of 1% lidocaine/1:200,000ad are more easily accessible, but this defeats the objective of having a higher concentration of adrenaline to maintain a clearer surgical field. Hong Kong and Brazil have premixed 2% lidocaine/1:200,000ad, Egypt 2% lidocaine/1,100,000ad, and Indonesia reportedly have 2% lidocaine/1:80,000ad. Moreover, no premixed solutions are allegedly available in Israel, China or Turkey.[ 3 ] This disparity is fascinating, especially since WALANT is practiced in all of these countries, albeit to a differing degree. In the United Kingdom, The British Society for Surgery of the Hand (BSSH) have recently released guidance on how to prepare a do it yourself (DIY) solution, whereby 20 mL 1% lidocaine is mixed with 0.1 mL adrenaline (1:1000), giving a 1:200,000ad concentration. This may be prone to error when aspirating such small volumes.[ 4 ] Alternatively, Marco Felipe in Brazil suggests 20 mL 2% lidocaine mixed with 0.4 mL 1:1000 adrenaline (1 mg/mL) provides 2% lidocaine/1:50,000ad. Mixing 20 mL with 20 mL saline gives 40 mL 1% lidocaine/1:100,000ad.[ 3 ] Although a potential solution, there is similarly a margin for error in drawing up the key component in adrenaline. Having performed over 300 procedures at our institution, we have sought a solution that is scalable for small-volume procedures. The “Preston WALANT mixture” combines readily available dental LA 2% lidocaine/1:80,000a (Lignospan, UK), 1% lidocaine/1:200:000a with 4.2% bicarbonate (80:20 ratio + 1 mL/10 mL bicarbonate; [ Fig. 1 ]). Indeed, the resultant 1.8% lignocaine/104,000ad possesses a higher concentration of lidocaine ([ Fig. 2 ]). Safe dosage depends upon the volume infiltrated (< 50 mL: 1/100,000; 50–100 mL: 0.5/200,000; 100–200 mL: 0.25/400,000) and the maximum dose of the Preston mixture in a 70 kg individual equates to 1.8 g/100 mL (490 mg total), giving a maximum volume of 27 mL or approximately 30 mL (with bicarbonate). We have found that this volume is sufficient for the majority of procedures. Invariably, for larger volume infiltration, it is entirely reasonable to prepare saline preparations similar to that described, since they harbor a lower concentration of lidocaine. Fig. 1 One of the advantages of dental local is it is readily available and can be withdrawn using the sheath from the filter needle ( A ). The sheath can be used a plunger as shown in ( B ). Fig. 2 Pictorial showing volume and concentrations of additives in a 10 mL syringe. This syringe requires less pressure for infiltration compared with a larger volume barrel and can be made up individually. The key advantage of the Preston mixture is its ease of scalability, and the rapidity at which it can be prepared. Considering the disparity in DIY mixtures and the availability of premixed agents, further research and collaboration is necessary to unpick which mixtures consistently provide a clearer field, if at all. There is no better time for this collaboration than during this pandemic, which is likely to witness widespread adoption of the WALANT technique. Publication History Article published online: 05 August 2020 © 2020. Society of Indian Hand & Microsurgeons. All rights reserved. Thieme Medical and Scientific Publishers Pvt. Ltd., A-12, 2nd Floor, Sector 2, Noida-201301 UP, India Thieme Medical and Scientific Publishers Private Ltd. A-12, Second Floor, Sector -2, NOIDA -201301, India
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".