Episode Transcript
[00:00:03] Speaker A: Welcome to your Cases on Hold, a JBJS podcast hosted by Antonia Chen and Andrew Stonefield.
[00:00:10] Speaker B: Here we discuss the science of each issue of JBJS with an additional dose of entertainment and pop culture.
[00:00:17] Speaker A: Take us with you in the gym, on the commute, or most certainly whenever your case is on.
[00:00:27] Speaker B: Welcome back to another episode of youf Case is on Hold.
Welcome to episode number 90. We're here in the middle of September bringing you some interesting information from jbjs.
As per usual, everything here in Our opinions are our own and do not represent anyone else on the JBJS Editorial Board or anything else else through jbjs. I'm Antonia Chen, Executive Editor at jbjs.
[00:00:52] Speaker A: And I have here I'm Andrew Schoenfeld, Associate Editor for Statistics and Methods at the journal awesome.
[00:01:00] Speaker B: And we are sponsored by JB JS cme. So we've said it once, we said it a million times. The CME credits are awesome. If you're looking for CME credits, JBDS is a good way to go and you can get it comprehensively across the board. So get your learn on JBJS CME Going to start with Top of the pile. The 90th anniversary of the American Board of Orthopedic Surgery is by lstein. It's permanently free.
Next we have what's New in Hip Surgery by Howard et al. Permanently free.
Efficacy and Safety of Orthobiologics for Lumbar Spine Fusion A systematic review and network meta analysis by Ambrosio. There's a commentary and it's permanently free. It's meta analysis there Obituary Clem Sledge, one of the greats. He was at Brigham and Women's Hospital for a long period of time. He recently passed away and has led an incredible legacy in the World of Orthopedics 1930-2025 and this is permanently free.
AOA Critical Issue Symposium Allyship in Action by Peterson Bridging Health Literacy Gaps in spine care using ChatGPT4.02 to improve patient education Materials by Nasser et al.
Development of a Spine surgery center of Excellent Rationale, Design, Implementation and Assessment of outcomes by Daniel Zett, Al PROMIS and Odi. Tools Clinically useful Markers of abnormal MRI findings in pediatric patients with back pain by Dev Kumar for 30 days free the smallest worthwhile effect is a promising alternative to the MCID in estimating proms for adult idiopathic scoliosis patients by Lu et al. This is permanently free. We're going to be coming up with more and more prompts. Things like we have an ncid. Now, it's the smallest worthwhile effect, so think of your different acronyms to be able to elucidate your different proms.
Minimize medial soft tissue release with bone recut adjustment improves short term outcomes. Compare with medial release and posterior stabilized total knee arthroplasty by Tasudol. It's also permanently free.
Intraoperative bone perfusion assessment using fluorescence imaging in a simulated fracture model. Effects of osteotomy and periosteal disruption on bone perfusion during amputation by Tang et al.
Enhanced detection using deep learning technology of medial meniscal posterior horn ramp lesions in a patient with ACL injury by park et al.
Cement mantle screws and periprosthetic hip fracture fixation near well fixed femoral stems meaning not impact. Short term femoral stem survivorship by Shaw et al.
And finally, from the asymptomatic flat foot to progressive collapsing foot deformity. Peritalar subluxation is the main driver of symptoms by Decisernetto et al.
Without further ado, we're going to go into our headlines here. Dr. Schoenfeld is gonna talk about the association between race, ethnicity and spinal fusion outcomes in a managed healthcare model by Guppy et al. There's a visual summary and it's free for 30 days.
[00:04:08] Speaker A: Yes. So this is a study in the area of healthcare disparities. It's been a while since we touched on an article in this important health services research paradigm. It's also an article that involves spine surgery and it's been a while since I presented a spine surgery paper, so I want to take the opportunity to do that.
[00:04:31] Speaker B: Very proud of you for that.
[00:04:32] Speaker A: Oh, thank you.
I'm really pushing the envelope here in my comfort zone in terms of trying these things like areas that I'm really not that familiar with.
You can send the trophy that I will receive from you in the mail.
[00:04:49] Speaker B: And it comes with a participation certificate too.
[00:04:51] Speaker A: Yeah. Wonderful, wonderful. Full disclosure. So there are two authors on this paper, myself included, who are on the current editorial board of JBGs. Heather Prentice, who's also an associate editor for methods, and Dr. Guppy was the first author. This is work that was conducted out of the Southern California Permanente Medical Group and Registry that they have there through kaiser Permanente. And Dr. Guppy used this in part for his, like, thesis capstone project when he was in the MPH program at Harvard School of Public Health, for which I was his faculty mentor. So there's a lot of, like, intersections and connections on this project that I feel you know, we need to mention up front, I don't think that's really going to take away very much from anything that I'm going to say about this research effort. It is very interesting in studying the landscape of racial, ethnic and health care associated disparities for, for different minority groups or populations that struggle to access affordable and efficient healthcare services and resources. We chose spinal fusion as the substrate in which to study this because it is one of the fastest growing spine surgical interventions in the last 20 years.
We've had several points over the course of my career where from a health services research standpoint, we said, all right, this is it. You know, this is the apogee of spine fusion and we're going to see a downturn from here.
And for whatever reason, spine fusion just continues to grow. And it's probably if you're just going to break down spine surgery into the buckets of like elective fusion, just decompression alone. And then like the other things that are more urgent or emergent, spine fusion is the largest overall and certainly continues to grow in the Medicare population.
So this study used the Kaiser Permanente Registry, and that's as many are aware, an integrated HMO that covers 12.5 million members throughout a swath of the United States. So it's not just on the west coast like a lot of people think, Colorado, Georgia, Hawaii, the Mid Atlantic states, Northern California, Oregon, Southern California and Washington. So I mean, obviously there is more of a West Coast Pacific leaning, but you do have Mid Atlantic US States, Georgia in particular, and Colorado. So this is very akin to getting together a number of statewide inpatient data sets or something like that to help build something that does have national translational capacity. And I would argue that that is the case here because the structure of Kaiser Permanente is such that you're really getting a broader cross section of the US in terms of patient age because of their Medicare product, and then also racial, ethnic, educational, vocational, occupational characteristics than you would if you're using like Pearl Diver, if you're using Trinet X data sets such as that, and if you're using Medicare data, then it's just patients 65 and older. By and large, if you're using a statewide inpatient or any kind of statewide registry data set, it's only going to be patients within that state. And depending on the characteristics of the state, there may not be good national translational capacity or scope to apply that more broadly. So I think some of those really important health care research, health policy considerations are addressed by using the Kaiser Data.
And when we talk about in the current, there are probably some different philosophies on this, but I think it's important to point out when we're talking about in the current iteration of US health care, where disparities really tend to arise, I believe is in the areas of access and in the areas of healthcare segregation. Are there other areas that contribute to healthcare disparities? Yes. Not saying that those two are alone, but I'm just saying if you would look at any adverse outcome driven by healthcare disparity and you were able to do a root cause analysis and drill down to sort of what is the foundational element that the healthcare system would have control over. That's another important caveat. It's going to be in the areas of access and healthcare segregation, I believe. And just for those listeners we've discussed healthcare segregation in the past, but for those listeners who are not that familiar with the term, what healthcare segregation means is that there can be a variety of mechanisms responsible and those mechanisms may be different in different sectors and areas of the country. But what healthcare segregation means is that patients of, be it minority or lower socioeconomic status or a status that puts them at risk for inferior healthcare outcomes at baseline basically have the means or the ability to navigate to a higher performing healthcare center. And they're basically funneled into lower performing facilities. Be it just the facilities themselves are lower financially resourced. The providers that work there are lower volume providers, less experienced with the procedures that they're doing. And that's both on a provider and a hospital front. And all of these are just going to sort of culminate in sort of what we have described in other work that we're working on as the death spiral for healthcare services. In a challenged resource environment, you have a sicker population with more comorbidities that cannot access other care they're working with and being treated by providers who have lower volume, lower resources that just increases the risk for inferior outcomes. You get the inferior outcomes, then they're are insurance based or government based or third party based penalties associated with that that further impacts the financial resources that affects the system as a whole in terms of also trickle down effect on the primary care services that are provided to these patients. And then you're back to now a sicker population that has further challenges and obstacles and roadblocks to getting care. And then they're back in the system. So it's just the cycle that continues to repeat itself and we wanted to see how this would be impacted through the universal care parameters afforded by Kaiser Permanente. Now the study includes over 40,000 patients who are undergoing spinal fusion.
We broke this down, as is in the Kaiser registry, to black, African American patients, Hispanic patients and Asian patients. Things are better in Kaiser Permanente. The bottom line is that there certainly is not complete equity in terms of outcomes across the populations that they serve. African American black patients had a lower reoperation risk and that was also evident for Hispanic and Asian patients, which is great. But black and Hispanic patients had a higher likelihood of an ED visit within 90 days. And that's usually a marker for either access or, you know, when you have an ED visit without readmission, that's usually a marker for access or can also be, you know, that there were some disparities or differences in communication or difficulty establishing with your provider. It's basically a process marker for their issues in terms of post operative care delivery that could be optimized and then a higher likelihood of readmission within 90 days observed for black patients, which also in some respects can go in line with that when you're having readmissions, but not necessarily associated with reoperations.
So at the end of the day, despite equal access and a managed healthcare system, which should have a lot and does, we know, have better operational controls on all of these parameters, the study continued to show some disparities among care received by black and Hispanic patients in the Kaiser system. The study also does show that as compared to historical performance, the managed care network does do a better job reducing disparities. We saw this also in studies that we have done using the universal health system afforded by the military health system and their insurance product tricare. So there's good face validity there. What the research aspect of this, that this speaks to is that, you know, this is an opportunity within Kaiser itself to look at in a more granular way what are the etiologies for the increased ED visits and readmissions. And if those can be tamped down, certainly quality of care overall can be improved. And we may have something of a primer or template through which to use as a prism to address the ongoing disparities that exist in broader aspects of health care delivery in this space.
[00:14:05] Speaker B: Completely agree. And I think some of it's like ED visits are education as well too, right? So if, you know, people are more likely to be engaging in that, you can talk to and be like, you know, you have increased pain, you don't need to go to the emergency room, right. Call our number here, you will see you in the clinic right away, that sort of stuff. But that that education takes time and some of it's cultural. Right. You're like, well, you know, my parents went to the ed, my grandparents went to ed. You know, like, I'm going to go to the ed and I'll get seen. Or I'm more likely to get seen because they don't feel heard somewhere else. All these sorts of things kind of play into it. But at least, as you said, it raises awareness of this context, so makes a lot of sense.
[00:14:39] Speaker A: Absolutely.
[00:14:40] Speaker B: All right, so I'm going to talk about not total knee replacements, but total knee adjacent because we're talking about meniscectomies. But will investigators enroll particular subjects in a randomized controlled trial, a mixed method study to gauge investigator equipoise in a trial of surgery versus non autopilot therapy in patients with meniscal tear and persistent pain following physical therapy.
This is by Katz et al. It's from the laboratories mostly at Brigham and Women's Hospital.
I was not part of the study. And they also collaborated with their surgeons and other clinicians at Buffalo. There's infographic about it.
We all know that conducting research is really hard and recruiting patients for randomized controlled trials is some of the hardest research to do. That's why it's so hard to accomplish. These randomized controlled trials and these large trials that do recruit a lot of patients are really incredible and to be very much applauded.
Sometimes it's the patient, they don't want to participate in the study. Sometimes the clinician patients may not want to participate in the study. And some clinicians may not want to enroll certain patients in studies if they think that they'll end up in a certain arm of the study or they don't want them to end up in a certain arm of the study. So the term clinical equipoise is not something that we commonly use in practice or in research even. It suggests that if the evidence base and consensus among expert clinicians suggest that both treatments are acceptable, it is ethical for the clinician to randomize the patient to any arm of the study.
But if clinician investigators consistently fail to enroll eligible subjects, trial findings might be biased. So you want to have equipoise, but there's sometimes that equipoise may not exist in a study. The investigators assessed investigator equipoise for enrolling subjects in a planned randomized controlled trial of surgery versus enhanced non operative therapy for adults greater than equal to 45 years old with a meniscal tear and knee osteoarthritis who remain symptomatic after completing a course of physical therapy. They use explanatory mixed methods of study with quantitative vignette components and explanatory quantitative component and they reported methods using the correct research criteria so subjects for this randomized controlled trial in the future, subjects in arm one will undergo a arthroscopic partial mastectomy. The second arm will receive only non operative treatment. Now remember, they've already failed physical therapy. They get non operative. They continue to get physical therapy, home exercises. They also get intra articular corticosteroid injections, oral medications and regular phone calls from the research team. To provide encouragement and foster self efficacy they created 20 they originally created 30 hypotheses hypothetical situations two of them end up being the same so they had 29 hypothetical subjects based on features that may make some clinicians reluctant to role patients in RCTs. Of this specific RCT there were 13 different features that were looked at. One was age 2 sex 3 BMI 4 pain duration 5 pain severity 6 clicking and popping symptoms 7 physical function 8, 8 joint line tenderness 9 KL radiographic grade 10 whether the tear was a bucket handle tear, 11 the compartment with the tear, 12 bone marrow lesions on magnetic resonant imaging and 13 whether the tear fragment was lodged in the medial gutter. There's 15 clinicians who participated in this 13 of them were orthopedic surgeons and two were orthopedic physician assistants and the voting options were three. The first one was yes, randomize this patient, no, don't randomize you prefer surgery for this patient or no don't randomize prefer non operative therapy for this patient.
The results were there were eight visiting votes so it had 427 vignettes. The clinicians were willing to enroll 71% of the patients into the trial.
Three clinicians were willing to roll less than 50% of vignettes and one rater was was willing to roll 100% of vignettes and seven raters were willing to roll greater than or equal to 83%.
Clinicians were willing to enroll just 39% of vignettes with bucket handle tears. In logistic regression analysis, a bucket handle tear and kellgren Lawrence Grade 3 radiographs were independently associated with the clinician's unwillingness to randomize.
The qualitative analysis confirmed that clinicians believed that bucket handle tear should be managed operatively, whereas greater age, severe OA, inability to walk 200 yards and higher body mass index had clinicians voting towards more non operative therapy as opposed to operative therapy. I Found this study actually pretty interesting because when we design clinical trial studies, our inclusion exclusion criteria typically are based on things like lab values or contraindications to things or you're not going to treat it. But rarely is it on clinician equipoise. And I've definitely been part of studies where I say, yeah, I don't want this patient to participate in the study because I'm really worried that they should actually be getting X, Y, X instead of Z. And so I'd rather not randomize in the study. Or I did a study where patients would get home versus outpatient physical therapy after totally replacement and most patients wouldn't participate in the study because they didn't want outpatient physical therapy, they wanted home physical therapy.
This is a very interesting methodology so that clinicians can identify who should be engaged in discussions and interventions to support equipoise. And it can also help inform the development of these exclusion criteria. For example, in this study, now will they exclude bucket handle tears? Because most clinicians won't enroll into it and to increase the proportion of eligible subjects referred for enrollment in certain studies. Now, that said, as per usual, when it comes to these randomized controlled trials, the more exclusion criteria that you put in it, the less more real world applicable it becomes because you're looking at a very specific subset of patients.
But it's an interesting topic that we don't typically talk about. So I think it was worth presenting and discussing this and bringing this to light. I'd love to have your take on it as a methodology guru.
[00:20:48] Speaker A: Well, I don't make any claims to being a guru of any type, but obviously, as you mentioned earlier, many of the individuals on this paper are either colleagues or clinicians that work in the department that I currently work in and that you previously worked in, some of whom are also, you know, previously members of the division where you were the chief.
And you and I both have worked on a number of projects with Jeff Katz, who was previously on the editorial board of JBJS and also was my research mentor in the early stages of my research career.
So this is the concept is something that really I think is necessary to do before doing a randomized controlled trial. And I think a lot of times it just sort of happens organically.
The team that's putting together an rct, for example, is going to say, you know, are we okay with randomizing patients to procedure A or procedure B?
Which ones are we not? And that's part of how you figure out your inclusion and exclusion criteria. This is certainly a More measured and careful and erudite way, and you're showing a proof of concept. I think sometimes this is necessary to do in certain contexts. We did it previously for spinal metastases, which is like a high.
We did it for spinal metastases, but we did it to make the case that you shouldn't have RCT for spinal metastases. That surgeons do not have sufficient clinical equipoise to say, oh, this patient could be treated with radiation or non operative, or this patient requires surgical intervention. But sometimes you're trying to demonstrate to the funder, the nih, whoever it may be, that there really is no clear cut, predetermined pathway for these kinds of patients. And it's a conceptual exercise and academic exercise that lays the foundation for the ultimate randomized controlled trial.
That said, I found the clinical relevance to be very superficial and basically just like complete, like non sequiturs, like orthopedic surgeons play crucial roles in randomized controlled trials. Oh, okay, I didn't know that.
All right. And randomized controlled trials are the foundation of clinical practice guidelines. Oh, I didn't know that.
And they play crucial roles in that because they enroll patients from their practices.
Did we need this study to tell us that? No, I don't think so. And then they say, this article examines clinician equipoise, a key determinant of the willingness of clinicians to enroll eligible patients in trials. Well, if you wrote like an editorial or a review article on clinician equipoise, which maybe is something that's useful for our community, I guess you could say that. But this is supposed to be a study, and the clinical relevance of the study should not be about clinician equipoise, because that's not the purpose of the study. The purpose of the study wasn't to examine clinician equipoise, it was to use clinician equipoise.
Right. As a pivotal component of this two pronged foundational element of a randomized controlled trial. So you had them working through the vignettes. You're not proving clinician equipoise. You're not studying clinician equipoise per se, other than studying it in the context of this investigator driven trial of surgery versus non operative therapy in subjects with meniscal tear. And also I think without, you know, as like, so if somebody saw this and was like, oh, I want to do this for clinician equipoise in ankle fractures or in hip fractures or in any other kind of aspect of orthopedic surgery, the first Thing is, I don't think that there's going to be uniform appetite to see follow on studies like this in all different areas of orthopedics. And second, it's very hard to do this well unless you have a group like this with a lot of very.
There's the psychometric properties of your vignettes. There's, you know, pilot testing of the vignettes to make sure that what the reader is getting is actually what the author wants them to understand about the vignette. So there's really. It's not just, hey, we did a survey and here's what a bunch of people that we surveyed said and now we're going to write up a paper about it. Don't. Cautionary tale. Don't. Don't do that.
[00:25:22] Speaker B: I was going to say, like, this is interesting to turn something that you're probably doing as part of the study into a study, but I agree that you could do this for every single study and that will not be publishable.
Now I'm going to go into total joint arthroplasty. But this is the your cases on hold featurette. So not because I said or the.
[00:25:41] Speaker A: Vignette, it could be the your cases on hold vignette. There's clinical equipoise around putting a case on hold.
[00:25:48] Speaker B: This is true, we can have a discussion about that is one of the criteria for that.
So this is talking about weight loss before total knee arthroplasty was not associated with decreased post operative risk by se.
It's a study out of Mayo and surgeons often recommend weight loss for patients with obesity before total knee arthroplasty with a go BMI of 35 or 40. Typically most places go with 40. In some places they went down to 35, especially in like the UK and standardized care like that. However, it's unknown whether preoperative weight loss affects outcomes. So the purpose of the study was to determine how many patients with obesity lost weight before total neoplasty, to identify weight loss predictors and to evaluate if preoperative weight loss affected postoperative outcomes. Given the Mayo database, they had over 23,000 primary total knee arthroplasties between 2002 and 2019 and identified 3,665 patients who had a BMI of greater than 30.
That's actually not a lot for being in Rochester, Minnesota. I thought in that timeframe to only have that percentage of patients who had bmi greater than 30 and this was measured 1 to 24 months before surgery and then their weight Loss was the time before surgery, one to 24 months before and the weight measured at surgery and they use a definition of obesity but of the cutoff of 30. But again as I was saying, some people use 35, 40, 45, even 50 for BMI cutoffs. The mean patient age was 68. 59% of patients were female. The mean BMI of patients undergoing surgery in this patient cohort was 36. 6. The range was 21 to 64.
So prior to two years of followup, 60 knees underwent revisions. 57 patients did die.
There were 307 additional patients who had less than two years of follow up. The mean follow up for the remaining 3241 cases was 6 years. Range of minimum of 2 to 20 years.
Weight change was calculated as a difference because I talked about the before and afterwards. The the authors group patients by preoperative weight change to those who maintained preoperative weight. So maintaining preoperative weight was defined less than or greater than 5 pounds and then gained weight, gained greater than 5 pounds, lost 5 to 10 pounds, lost 10 to 20 pounds and lost greater and equal to 20 pounds before surgery. They did univariable linear regressions evaluating weight loss predictors and then univariable and multivariable logistic regressions and Cox proportional hazard models were used to evaluate the impact of preoperative weight change on these clinical factors. Discharge length, stay operative time, periprosthetic joint infections, complications, revisions and reoperations.
Overall, 20% of patients gained greater than equal to 5 pounds before surgery, 39% maintained weight, 17 lost 5 to 10 pounds, 15% lost 10 to 20 pounds and 9% lost greater than equal to 20 pounds before total knee arthroplasty. Mean weight change overall was 4.4 pounds. For those who did lose weight, the mean weight loss was 11.5 pounds. For those who gained weight, the mean weight was approximately 10 pounds. So pretty equal gain or loss depending on which direction you went.
Only 20% of patients with a preoperative BMI of greater than 4040 achieved a BMI of 40 and it took a mean of 1.3 years. So patients say how long is it going to take? In this study population they said 1.3 years.
Male patients lost slightly more weight, 4.6 versus female portions was 4.3. So it's 0.3 pounds difference, not a huge difference on the cusp of statistical significance, which is a whole different discussion in of itself, no differences in weight change from multiple comorbidities. However, as age and initial BMI increased where Surgeries occurred in later years or when the patient was older. Where older patients were more likely to lose weight, the survivorship free revision at 10 years was 96%.
Losing 10 to 20 pounds and having a higher preoperative BMI were associated with an increased risk of revision.
Older age of surgery was associated with a decreased risk of revision for reoperation. 10 years survivorship free reoperation was 89%.
Univariate analysis found that increasing age had a decreased risk of reoperation. Not surprising. As you get older you're not likely to undergo surgery. Prior bariatric surgery was associated with an increased risk of reoperation for infection. In univariate analysis, losing 10 to 20 pounds was actually worse and an increased risk of PGI. So is greater Charleston Comorbidity index. So more comorbidities meant more higher likelihood of having a PGI and greater preoperative BMI had a greater risk of PGI.
Based on multivariate analysis, losing 1020 pounds compared to maintaining weight was associated with the increased risk of PJI patients with increasing CCI score and higher preoperative BMI had higher risk of PGI with multivariate analysis.
Finally, gaining five pounds was associated with increased risk of longer hospital length of stay and risk of complications.
In multivariable analysis, gaining greater than 5 pounds was associated with an increased risk of complications.
So in conclusion is few patients lost weight before surgery, but we don't know is how many patients were actually encouraged to lose weight. For my patients who are BMI of 30, I don't encourage them to lose weight. If they're BMI 35, I don't encourage them lose it. If they're just at 40, I might say it's good to maintain it below 40, but I don't ask them to lose weight. It's only when patients that have BMI greater than 40 that I actually ask them to lose weight. So it may not be surprising if patients don't lose weight if there's no intervention or encouragement to do so.
And also the setting of BMI greater than 30 was pretty low.
Losing weight before total neuretoplasty didn't result in improved outcomes, but it wasn't stratified for higher BMI patients per se.
So just the amount of weight loss versus the percentage of weight loss or the BMI final BMI or were not taken into account in this analysis. So you know surgery it's good to maintain a healthy weight. But I do question the efficacy of applying this study only because of the metrics used with Just pure weight loss prior to surgery.
[00:32:04] Speaker A: I agree with everything that you said. This is obviously from the Mayo registry. It's a large data set and they have 24,000 patients roughly over a 17 year time window over which probably the, I would wager the focus, interest and sensitivity to patient weights on both sides have changed dramatically, I would say, from myself thinking back to 2002 when I was a fourth year medical student, and then all the way through residency and now so many years after the fact, how people handle weight in the office, talking to patients, the idea of cutoffs that are a little bit bit more universal or broadly accepted, we'd say, than maybe they were 23 years ago.
I think the biggest problem with this work here is that the way they present like the narrative and it could be just the way I'm reading it, if you read it differently, definitely jump in. But the way it's written to me, they, they, they talk about patients, you know, these many patients with this particular characteristic. So, for example, only 20% of patients with a preoperative BMI of greater than equal to 40 achieved a BMI of less than 40.
But there's a big caveat there that's not being mentioned. That's not all comer patients, that's patients who then went on to get a total knee arthroplasty.
And so there's a huge selection and indication bias here that it's not effectively addressed in their analytic plan. And in some ways the way they write the paper, it sort of ignores it.
And I think that that's a problem. Right. So every one of these patients was selected to have surgery whatever their weight was before or after. And those patients who came in and were deemed to be poor surgical candidates based on their weight, we'll say, and they said, no, we're not doing the surgery for you. You haven't lost enough weight, you haven't done this or you haven't done that, whatever the determinations were, or they were told to lose weight and they said, well, if I can't lose weight, I'm not coming back.
And they never showed up again because they didn't lose weight. You don't know anything about those patients. Or maybe they lost weight and then they said, oh, my knees feel better, I don't want the surgery. You don't know anything about those patients.
This is. Of patients who are ultimately selected to have surgery, only 20% of those with the preoperative BMI achieved 1 of less than 40. Then your point is very well taken about patients are likely Only going to be motivated to change their weight through internal or external factors. Internal obviously being they want to engage in weight loss for whatever reason. External being a provider tells them it's not healthy for you to be at this weight or it's not acceptable for you to be at this weight for us to move forward with the treatment that you want and a change needs to happen. So like you said, if they're at 30 and you know they feel good with where they're at and their primary care doctor is like, you're, you're fine. And their surgeon is like, yeah, this is no problem to move forward. Why would you expect that there would be any kind of change?
It's really only in the group that I think patients 40 and over are where you start to see clinicians saying, we can't really do this surgery right now. We need to have you look at weight loss. And the other problem is I think that, I know they said, they said that this time window, I'm not familiar with the literature there cited, but they said that the preoperative weight measured at 1 to 24 months before surgery and the weight measured at surgery and the 1 to 24 month time period was selected to be consistent with prior literature.
So I don't know what prior literature they're like, I didn't go and look at reference 18 to see what that article said or what it is that informs or how it informs what they did, but there's weight loss and then there's stable weight loss. And the patient who lost 10 pounds between in the last 30 days.
Right. Or more. That's a big red flag.
And it's different if somebody showed up in the clinic, in the clinical practice from 24 months ago and their, their last encounter. So they had a visit at 24 months and let's say they were 200 pounds and now they are seen one month before surgery and they're 150 pounds. Right. So they lost 50 pounds, but they lost that over the course of like a year and a half without seeing you. And they did it with a GLP1 or something like that. That's a totally different situation from somebody who was £200 45 days ago, shows up for surgery and is £150 and they can't, you know, they're not sure. Maybe there are other medical issues going on, something that might be undiagnosed, that might then put you at an increased risk for complications. Those things are not effectively unpacked in their approach. I would also say from a Method standpoint, BMI and change in BMI is going to be non parametric, meaning that it would not be expected to be in a normal distribution.
And I don't support the linear regression analysis that they used as a result.
I also think, I don't understand why they do the univariable and then the multivariable. Like it's, it's not clearly conveyed the rationale for the univariable. If it was done just to like find statistically significant factors that they then put in their multivariable analysis. I'm not too fond of that.
I mean ultimately what they're saying, they're including the multivariable analyses. Age, sex, CCI surgery year, history of bariatric surgery and preoperative BMI.
I think that mean the change one to 24 months prior. Like they have it in parentheses. So I'm inferring here that they mean the change.
You know, that you could have reached that with a conceptual model. You didn't need the univariable studies to inform that.
So, you know, I think that there's some good face validity for the five pound increase. Again with, with the big caveat that the surgeons saw that had that information and said yeah, we're good to go. Still we're not going to not do the surgery. Right.
The other piece, the 10 to 20 pound loss associated with an increased risk of PJI.
I think that may not be an independent factor, but there may be other parameters around it. Particularly since based on the study design, I don't think there's good comprehension around how long were the patients at the weight that they had the surgery at, how rapid was the weight loss and what were the clinical factors associated with in driving that weight loss?
[00:38:58] Speaker B: Agree.
All right, I'm going to go to some honorable mentions.
[00:39:02] Speaker A: Yeah, I think we're running out of time.
[00:39:03] Speaker B: We are here so good to behavior intervention to foster healthy lifestyle physical activity after complex lumbar surgery. A randomized controlled trial by all There's a commentary.
The authors tested a multi component behavior intervention administered in surgical practices to increase lifestyle walking after recuperating from surgery involving greater than equal to three lumbar levels or fusion. This intervention was started three months after surgery with control patients being compared to case patients who received the intervention. Endpoints are 12 months after intervention and this behavioral intervention was effective. Increasing lifestyle walking after recuperation from complex lumbar surgery retention in this study was 92%. 72% of all patients reported that being in the study did not affect spine syndromes and 28% reported that being in the study actually made them feel their symptoms were better.
Impact of childhood obesity on capital femoral epiphysis Morphology A large scale automated 3D CT study and potential implications for skiffy pathogenesis by Navias et al. And there's a commentary on it. The precise pathological mechanisms through which obesity increases the risk of slipped capital femoral epiphysis remains unclear and this study looked at children with obesity who had demonstrated smaller epiphyseal tubercle height, greater posterior epiphyseal tilt and reduced superior cupping compared with children of normal weight. These anatomical differences may contribute to the increased risk of SCFI in patients with obesity and offer potential imaging markers for early identification and risk stratification.
Finally, coronal and sagittal balance following posterior spinal fusion for adolescent idiopathic scoliosis by Turtle et al. Achieving and maintaining global spinal balance is a crucial goal in posterior spinal fusion for AIs. The purpose of the study was to characterize the evolution of global balance after posterior spinal fusion for aisle they looked at standing two view radiographs, both AP and lateral and they retained at the first erect visit, six months, one year, two years and five years with a subset of patients that actually got 10 year follow up. They developed a novel CASH classification system which stands for coronal and sagittal harmony. The initial post operative evaluation showed essentially no improvement with only 55.6% achieving optimal balance of this CAT cash. Call it a zero at the first direct visit. Subsequent follow up demonstrated steady improvement with 82% reaching optimal balance at 5 years and 88% at the 10 year mark, allowing one to trace the balance trajectory both in the coronal and sagittal planes after posterior spinal fusion and adolescent idiopathic scoliosis.
Hope you enjoy your time here, Hope you learned a bunch and we look forward to seeing you next time.
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[00:42:02] Speaker B: Love it.
