“There is no foot too small that it cannot leave an imprint on this world”

This link will take you to a very touching tribute written by a 16 year old to his little sister. It is a very personal essay, about his love for the girl who died at 6 weeks of age, but I have permission to link to it.

I love the phrase that they will put on her gravestone, which I have quoted as the title for this post.

I remember another child, a little one born with a muscle disease. We were never able to get him off respiratory support, every time we tried to stop his CPAP he would deteriorate, and eventually after 6 months in the NICU, he died.

My ‘traditional’, medical response was that the life had been of no value, the baby had never gone home, and never ‘contributed’. But, after his death the mother was so grateful that she had been able to spend time, cuddling and kissing her son, she thanked us for giving him those 6 months, those months when she could care for him, and love him. Six months that have no value when looked at from one direction, but are priceless from another.

That mother taught me a lot; she taught me that the value of a life is not measured in minutes, hours or days. It is not even measured in QALYs! Quality Adjusted Life Years are used in many calculations of such things as the cost-effectiveness of new medical interventions. A life of profound disability and short duration may have very few QALYs, but still have a big impact in this world.

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Predicting outcomes, but not before birth

One very important article that I failed to blog about last year when it came out is this one (Ambalavanan N, Carlo WA, Tyson JE, Langer JC, Walsh MC, Parikh NA, Das A, Van Meurs KP, Shankaran S, Stoll BJ et al: Outcome trajectories in extremely preterm infants. Pediatrics 2012.) It refers to an outcome prediction tool that can be applied after birth, that takes into account many different prognostic factors.

I think this is on the right lines. Prediction of outcomes before birth is so limited, so uncertain and so imprecise, except at the very extremes, that its value is limited. The only thing we can say with much certainty before birth is that if the baby survives their quality of life will be highly acceptable to them and their families, nearly 100% of the time.

So can we predict after birth, as time goes on, how a baby will turn out?

That is what this publication was all about. They took the data from the NRN of the NICHD (if you haven’t been into neonatology for long, that is the neonatal research network of the NIH institute for children) and constructed predictive models at 4 critical times. In the delivery Room, at 7 days, at 28 days of age and at 36 weeks post-menstrual age.  Those times were presumably chosen based on the structure of the NRN database.

At each time, by entering a number of different clinical factors you can calculate the probability that the baby will die, based on the relative impact of those individual factors, in previous babies in the database, on survival. Also a calculation of ‘neurodevelopmental impairment’, NDI, can be made and a combined likelihood of survival without ‘NDI’.

I think as far as predicting death is concerned, if the calculation gives a very high likelihood of death, then that might be an appropriate indication that it is time to mention the prognosis to the parents.

As for ‘NDI’, well I am going to get on my hobby-horse one more time (I am sure it won’t be the last):

A Bayley mental development index (MDI) at 18 to 22 months corrected age below 70 is not an impairment, and I wish the NRN would stop using this term. Most of the babies classified as ‘NDI’ are so classified because of a poor Bayley result. The majority of ex-preterm infants with a Bayley 2 are not cognitively impaired in the long term, as determined by IQ testing at early school age. The proportion of those with a Bayley (version 2) MDI <70 who are cognitively impaired, when tested later, varies between 20 and 33%. I think keeping parents informed about prognosis, and having on-going discussions with them is vitally important; but I really don’t know how to use the information about ‘NDI’, I think it would be a huge mistake to tell a parent that there is X risk of neurodevelopmental impairment, when much of that risk is due to developmental delay which will likely substantially improve with time.

There is an on-line calculator that you can use, but beware of the calculation of NDI, not only for the reasons I have given above, but also because it varies a lot in other populations. A publication from the Melbourne group in 2012 compared their results to what the previous NICHD calculator, (designed to be applied around birth and therefore only including sex, birth weight, steroids, multiple birth and gestation) came up with. The Melbourne groups results for mortality were similar but for developmental delay their figures were substantially lower. That may be in part because of the use of 24 month Bayleys by the Melbourne group, rather than 18 month score from the NICHD. The Melbourne group have already shown that there is an improvement in scores between 18 and 24 months (of around 4 points on average). As a result the 24 month scores are a bit more predictive of long term outcomes than the 18 month scores, but if you look at the graphs in that paper, you can see that they still are not very good as predictions. But most importantly, different populations, with different backgrounds may have differing long term outcomes, either because Australian babies are just much tougher, or for a whole host of other reasons.

Also to illustrate my point, in the Melbourne paper, at 24 months there were 4 babies who had ‘severe delay’ (which is an appropriate terminology) that is, a Bayley 2 MDI score below 50. Only one of these infants was severely impaired on IQ testing at 8 years. Even very, very low Bayley scores, and even at 24 months, are very poorly predictive of long-term impairments. We should be extremely careful about using outcome data based on early developmental testing for counseling or decision making.

I think we need confirmation and expansion of this kind of prognostic information, from other networks if possible, to refine the prognoses, especially for mortality, and if at all possible, for really important truly long term outcomes.

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HHS hearings, now available on-line

As John Lantos pointed out in a comment response to a previous post on this issue, the public hearings of the HHS which was set up to address consent issues in research comparing standards of care are now available on line. The HHS has created a Youtube playlist that you can access here.

I think Michael Carome and Alice Dreger must be on the same drugs, at least they seem to be involved in a ‘folie-à-deux’. Carome repeats the same nonsense about the standard of care for 24 to 25 weekers, he claims that the standard of care for such infants was to intubate them all and give them all life-saving surfactant. He seems to be completely impervious to the truth; if he had bothered actually talking to one of us, he could easily have found out that the majority of forward looking NICUs were already trying to keep babies from being intubated, and that the COIN trial had already shown that that was a very reasonable idea. So don’t watch his presentation unless you have got your BP under control.

There are however, some excellent presentations, some from individuals in neonatology, some for other physicians, some from other ethicists.

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Neonatal Updates #36

Shaw RJ, St John N, Lilo EA, Jo B, Benitz W, Stevenson DK, Horwitz SM: Prevention of traumatic stress in mothers with preterm infants: A randomized controlled trial. Pediatrics 2013. This looks really interesting, an RCT of a clinical psychologist led intervention to help mothers (what about the dads?!) cope with the stress of NICU and prevent depression. And it worked. There were fewer symptoms of trauma and less depression 4 to 5 weeks after birth for those parents who received the 6 sessions. Now I must admit that I don’t know what they actually did, it is described as ‘psychoeducation, cognitive restructuring, progressive muscle relaxation, and development of their trauma narrative. The intervention also incorporated material targeting infant redefinition’ (I only understand the relaxation bit). It was also apparently ‘highly manualized’ which I think just means all the stuff they were supposed to do was written down, in a manual. But, whatever they did, it worked in the short term, and if the benefits are prolonged then we all will have to get manualized.

Ganapathy V, Hay J, Kim J, Lee M, Rechtman D: Long term healthcare costs of infants who survived neonatal necrotizing enterocolitis: A retrospective longitudinal study among infants enrolled in texas medicaid. BMC Pediatrics 2013, 13(1):127. Two of the authors of this study are from Prolacta, but I must say, after being rude about one of their other studies, this looks quite reliable. Up to a year of age survivors of medical NEC have higher health care costs than controls and surgical NEC cases much more. Surgical cases continue to have higher costs out to 36 months.

Belsches TC, Tilly AE, Miller TR, Kambeyanda RH, Leadford A, Manasyan A, Chomba E, Ramani M, Ambalavanan N, Carlo WA: Randomized trial of plastic bags to prevent term neonatal hypothermia in a resource-poor setting. Pediatrics 2013. Full term babies in Zambia were put in plastic bags (don’t worry, just up to the armpits), in the first 10 minutes of life. They were less likely to be hypothermic at one hour, but that reduction was from 73% to 60%, so more needs to be done. Just in case you weren’t already aware, Dr Wally Carlo is one of my heroes, I don’t think he ever sleeps, but I am sure he doesn’t have time to write a blog!

McCarthy LK, Molloy EJ, Twomey AR, Murphy JFA, O’Donnell CPF: A randomized trial of exothermic mattresses for preterm newborns in polyethylene bags. Pediatrics 2013. If you aren’t in the field you may not realize that we already put preterm babies in plastic bags. For the same reason, to keep them warm. This trial from Dublin, which tends to be cooler than Zambia, but has the advantage of electricity, showed that you can keep preterm babies warm with plastic bags (and radiant heaters and incubators), and adding a special heat generating mattress doesn’t help, in fact it tends to overheat the little ones.

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Pluto, not just a planet anymore.

Or should that be, not even a planet…

One other thing I wanted to mention about the PLUTO trial is the entry criterion. The main entry criterion was the presence of clear lower urinary tract obstruction in a male fetus, if ‘the clinician was uncertain as to the optimum management.’

Now I understand the reason for that, but in fact, as I have been mentioning in many of my previous posts about SUPPORT’ it is implicit in the ethical principles guiding all trials. If the clinician is certain as to the optimum management, and one arm of the trial requires withholding that optimal management, then it would be morally indefensible to enroll a patient in that trial. The problem with using that as the main entry criterion, without other severity of illness criteria, is that it then become very difficult to extrapolate the results to other populations.

It really reminds me of the INNOVO trial. For that trial of rescue inhaled NO therapy in the preterm infant the main entry criterion was that ‘Infants of <34 weeks’ gestation, aged <28 days, and with severe respiratory failure requiring ventilatory support (and having had surfactant when appropriate) were eligible for trial entry if the responsible clinician was uncertain about whether an infant might benefit from iNO.’

That is ethically entirely defensible, but, I don’t know the varieties of opinion among neonatologists in the UK, and who they might feel would definitely benefit, or definitely not benefit from iNO. I do know that they randomized a desperately sick group of babies: the average OI at baseline was 32, which for a premie is really, really bad; and the mortality was about 60% (it wasn’t affected by NO by the way), proving that an OI of 32 in a premie is really, really, bad.

So the quality of the trial was very high, but how do we determine the external applicability? I now know that a premie in my NICU who is very sick and for whom an average neonatologist in the UK would not be sure about whether iNO was indicated, would probably not benefit from iNO. I actually have lots of other data about rescue iNO in the preterm, but if this was the main source of data I would find it very hard to know how to apply these results.

Now perhaps you could say that I don’t know much about the non-enrolled subjects in other trials either, which is true, and is a good reason for trying to collect as much data as we are allowed to on non-enrolled eligible subjects; but that will be tough to do unless we have objective eligibility criteria, to know who could qualify to be a subject, and what happened to them if they were not enrolled. That is one of the great benefits of the CONSORT approach, and why we should insist of having all of the CONSORT flow diagram data in reports of RCTs.

I also don’t know, in the specific instance of the INNOVO trial, how a caregiver could possibly have been certain, before doing the trial, whether or not a baby would benefit from iNO. Before INNOVO there was little data, mostly from very small trials, and absolutely no certainty at all about the role of iNO in rescue treatment of sick preterm babies. That is why I think it is preferable in such a circumstance to say, ‘we do not know if any preterm baby with an OI over 15 despite surfactant benefits from iNO, they will therefore all be eligible for randomization’ but with the understanding that if there is some specific circumstance which makes iNO either clearly indicated or clearly contra-indicated, under such a circumstance it is inappropriate to randomize the baby, and we should seek consent to collect data.

Incidentally the PLUTO group are collecting a lot of information about interventions and outcomes of other mothers/fetal pairs with the diagnosis in the participating centers, which will help to make it clear how representative the PLUTO results are in comparison with non- randomized patients.

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Who was Bayes, and what did he know about medical research?

I don’t have much detail to answer the first question: he was an 18th century English mathematician who wrote something about probability, that was published after he died. That publication described something called Bayes’ theorem which is a way of incorporating the prior probability of something happening with the evaluation of new data to arrive at an updated probability. (I think) (someone tell me if I am way off base….)

So if you can calculate the probability of something, then you take into account any new information that you find, and recalculate a new probability. In some ways this is how we operate all the time in daily life, but Bayes thought of new ways of doing the calculations.

Anyway, I have heard about incorporating Bayesian probability into clinical trial design for a while, but I don’t recall having seen many examples. The idea being that the usual way of doing a trial is to assume that the two arms of the trial have an equal probability of being preferable (which is sort of like the null hypothesis) then do the trial with a specified sample size, avoid looking at the data until the end of the trial (if possible, but with safeguards built-in, just in case) and then do a test of significance and declare that one arm of the trial was better, hence the benefit of treatment B is proven. A Bayesian trial explicitly incorporates prior probability into the design, encourages adaptive trial designs with flexible sample sizes, encourages repeated looks at the data as they are accumulating, and at the end produces a new posterior probability that treatment B is better than treatment A.

Which all sounds interesting, and I know there are examples of it actually being done, but I wasn’t aware of any perinatal trials.

Here though is a trial of antenatal intervention for urinary tract obstruction called the PLUTO trial. It was a multicenter RCT with a planned sample size of 150 women and their fetuses. After several years they were only able to randomize 31 mothers, so they had to stop the trial, as they probably ran out of both money and patience. Now as far as I can tell the trial team did not put anything about Bayesian analysis into the registration documents, nor the published protocol, but, given that the sample size was so small and the results therefore rather negative, they proceeded with an analysis using Bayes’ methods. They used some estimates of what they thought, before the trial, was the probability that antenatal shunting would be the better treatment, and then calculated the new probability that shunting is better by adding in the new data.

So what did they find in the trial? Seven of the 16 babies randomized to be shunted survived to one year of age; and 3 of the 15 randomized to be treated conservatively, with evaluation and treatment after birth, survived.

That shows what a bad condition this is, the fetuses were eligible in cases of visualisation of an enlarged bladder and dilated proximal urethra, bilateral or unilateral hydronephrosis, and cystic parenchymal renal disease, if the obstetrician was unsure of the best clinical management.

The CONSORT diagram below shows you how horrendously complicated it is to do and then analyze a trial like this.

pluto

So of the 16 allocated to shunting, 3 were not shunted, and 1 changed their mind and decided to terminate the pregnancy, and there were 3 treatment related pregnancy losses. Some of those allocated to conservative treatment got shunted anyway, and some others terminated. So how do you decide whether shunting was better or not? I know the ‘correct answer’ is an ITT analysis, you just calculate according to the numbers randomized into each group. But I think there is a good case to be made here for, at least, taking out of the analysis the non-procedure related terminations, which gives you 7/15 vs 3/13 survivors to 2 years. I think an analysis by procedure actually performed is interesting also, but you always have to be very careful, as you don’t know why the protocol violations occurred, it may because of clinical factors that might also influence prognosis. Anyway the ‘as-treated’ analysis shows 8/14 survivors who were shunted vs 2/14 conservative.

This is suggestive that maybe the shunting really did help, but it is clearly still a maybe.

The reasons for going into so much detail of this trial (apart from the fact that it is a trial that we really needed, and it is a great shame that they were unable to get a bigger sample) is that the authors then incorporate a Bayesian analysis, they determine a prior probability that shunting would be better, then add in the new results, and then calculate a new probability that shunting really improves survival. They calculate the prior probability as being 0.79 that shunting is preferable, and with the new trial data they state that the posterior probability is now 0.86.

So this is a Bayesian analysis of results a trial that was planned as a more conventional trial to determine superiority. My major problem with the analysis in this trial is that the prior probability is based on asking ‘experts’ what they thought. I think that even prior probabilities should be based on some sort of data, now having said that the prior observational data were actually more positive than the experts’ opinions, which just shows you how careful you have to be about observational data, it can be seriously biased.

Trials actually planned using Bayesian methods are also interesting. I know little about this, so I was pleased to find this document, it is a document reproducing what was taught to participants in a workshop on clinical research methods. It is a great introduction to what clinical research is all about, and there is quite a long and detailed section about Bayesian trial design.

I have been wondering about trials like the future lactoferrin trials, for example, if we try to calculate the likelihood that lactoferrin will prove to be very potent at preventing nosocomial infections (for which we actually have some hard data), and incorporate that into trial design, perhaps we can reduce the required sample size for future trials, and get an answer sooner.

By the way all the articles about Bayes use the same image, which probably isn’t him!

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10 Things Having A Preemie Has Taught Me About Life

One of the ‘parent of premie’ blogs that I read is ‘Cheering on Charlie’ from a parent of a 26 weeker who is now a beautiful little girl of about 16 months (just about 1 yr old corrected!).

I really appreciated one of her recent posts, so I thought I would send out a link:

10 Things Having A Preemie Has Taught Me About Life.

Her honesty and insights are refreshing.

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The fetal microbiome

One of the correspondents on the ‘phemonena’ website is Carl Zimmer, who has a newish column at the NY Times about the findings which show that the fetus is not sterile. This is not completely new, but I think it is still not well understood. I thought until recently that the fetus and placenta were bug-free, but data a couple of years ago about placental PCR analysis showing lots of bugs, especially from premature deliveries made it clear that I had been mis-informed.

This article is a good introduction for the non-specialist.

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New Book

image

I seem to have spent much of this year writing review articles of one type or another. One of them was for a new textbook on nutrition of the preterm neonate, edited by Sanjay Patole from Perth.

There are many excellent chapters, including an incisive evidence-based review of gastro-esophageal reflux in the newborn infant (author K J Barrington).

It has actually been published and printed very quickly, so it is quite up to date, and worth a look.

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Pre-SUPPORT, what did we really know?

One of the misplaced criticisms that have been made about the SUPPORT trial and the consent forms was that we should have known before the trial that there would be a difference in mortality, and that there would be a difference in retinopathy.

Is that true?

What was the actual state of knowledge before the oxygen saturation targeting trials? I wanted to give a brief description of the history, to explain in more detail to those who read this blog but who are not aware how little we knew before SUPPORT and the other O2 trials.

There had indeed been previous trials of different levels of oxygen, but they were from 2 separate, very different, eras in neonatal care. Among the first Randomized Controlled Trials (RCTs) in medical care of the newborn infant, the first group of trials of restricted versus liberal oxygen therapy included a total of just over 400 babies. They compared prolonged use of very high oxygen such as >80% in one trial, or >50% for at least 28 days in another, to an alternate approach of limiting oxygen therapy, usually by means of a maximum FiO2 that could be given. One of those trials for example only allowed any oxygen if the baby was cyanosed, and then the maximum that could be given at any time was 40%. So even if the baby was blue and bradycardic, an increase in oxygen concentration was not allowed.

At this time, assisted ventilation was not available, blood gases were difficult to perform (often giving results the nest day), there was no CPAP, babies were often starved for the first few days of life to avoid regurgitation even though there was no intravenous nutrition, and only infants who survived the first 2 days were entered into the largest of these studies; of course, the large majority of babies with significant lung disease had already died by that time.

The results of these trials were emphatic. Very prolonged, very high concentrations of oxygen caused retinal damage in moderately preterm infants. Such high oxygen treatment had become the standard of care despite a lack of evidence of safety or efficacy. Not only did the liberal oxygen groups have much more severe retinopathy of prematurity (RoP), there were no apparent adverse effects from restricted oxygen, specifically, despite what we would now consider inappropriate restrictions in the low O2 group, there was no increase in mortality. It may be that there was significant O2 toxicity in the high oxygen groups leading to pulmonary and other multi-organ injury to balance the adverse effects of the O2 restriction in the low oxygen groups. Or perhaps the studies were just too small to have the required power.

It was only later, using epidemiologic data, that there were suggestions that mortality may have been increased by restriction of oxygen. If it is indeed true, it may be because physicians began limiting oxygen exposure from the moment of birth, including during the first 2 days even though the strategy had never been tested during that interval. It may also be that the epidemiologic analysis was misleading, the paper by Cross (Cross KW: Cost of preventing retrolental fibroplasia? The Lancet 1973, 302(7835):954-956.) has been widely quoted, but the analysis is rather questionable, being based on projecting what the trends in neonatal mortality might have been if O2 had not been restricted.

I well remember reading, in the 1970’s, a newspaper article (I seem to remember it was in the Sunday Times) about the history of clinical trials which reported the horrific tale of the trial that had blinded 20 babies. I was shocked, as a teenager wanting to go into medicine, that doctors could do such terrible things. Of course the truth was that the blinded babies were in the usual treatment group, and the restricted oxygen group, the newer therapy, had less blindness and the trial saved the eyesight of many thousands of babies as a result. But the newspaper wasn’t about to let a little thing like the facts get in the way of a good story (clearly, this still happens!).

After this, manufacturers of incubators used to make them with holes in the sides, so that when you gave oxygen, usually just by attaching a tube to the oxygen inlet in the incubator and turning on the flow, the O2 concentration would stay below 40%. There was often a large red flag that became visible behind the incubator when you turned the mechanism to occlude those holes and risked exceeding 40%! Air/O2 mixers often required a manual override if you wanted to give more than 40% O2. I presume this was to try and shift the legal liability from the manufacturers to the doctors, if there was a case of RoP.

A few years later, when routine blood gas measurement became available, and other forms of medical supportive therapy were also developing, a second attempt was made to address oxygen therapy. This second wave of trials (more of a ripple) included only 2 studies, with a total of only 170 infants. The low oxygen groups had a PaO2 which was targeted to stay below 50 mmHg in one study or below 40 mmHg in the other (if a capillary blood sample was used the PO2 was kept below 35mHg), while it was kept around 100 mmHg in the comparison groups. Both studies suggested that aiming at a lower PO2 was safe, and seemed to lead to improved resolution of lung disease, in aggregate there was a slightly lower mortality in the babies who had more restricted oxygen therapy, which was not statistically significant. There was no effect on RoP in these trials, indeed by avoiding frank hyperoxia, there was no significant RoP in either group.

Interestingly Dr Usher noted in the report of his trial, only ever described in a book, and sadly never published in a peer-reviewed journal, (which makes it quite hard to get hold of, thanks to Lisa Askie for sending me a copy) that even the low oxygen group often needed more than the arbitrary limit of 40% oxygen.

And those were the only reliable controlled data available pre-SUPPORT. There never was an O2 targeting trial using continuous monitoring, even when transcutaneous PO2 monitoring was introduced the limits to be aimed for were selected arbitrarily. In the early 1980’s pulse oximetry was introduced for continuous monitoring. The direct continuous non-invasive measurement of hemoglobin oxygen saturation was a great advance. The main disadvantage of pulse oximetry is the difficulty in avoiding hyperoxia; as the devices are accurate to plus or minus 5%, a measured saturation of 94% could actually be a saturation of 99% and a very high PaO2, in the range shown to be associated with RoP. This was considered to be less important than the advantages of truly continuous monitoring. Several workers suggested keeping the saturation below 95% or below 94% to reduce the risk. However, the failure to perform early trials examining different goals of oxygen therapy with continuous monitoring meant that there was no clear understanding of what level of oxygen saturation to aim for, and whether any particular saturation range was better than another.

One center in the UK decided that, because preterm babies ‘should’ still be in the uterus, where their saturation might be as low as 70%, there was no need to give oxygen unless the saturation was below 70%. Others were worried that a saturation too low might affect pulmonary vascular relaxation and they therefore kept saturations much higher, some with no maximum limit at all.

After the provocative publication from the UK, which showed very little RoP and no apparent harms, in particular no higher mortality, there were a large number of observational studies, mostly showing advantages to the development of RoP of lower saturation targets, and none showing increased adverse effects, in particular none showed any increase in mortality with their lowered saturation targets, nor any augmentation in adverse neurological consequences in the long term. However, the saturation targets examined in those observational studies all varied, and in most the lower saturation limits were in the low 90’s. The reduction in retinopathy was thought to be due to a reduction in frank hyperoxia. Further reductions to the high 80’s were suggested as a way of reducing oxidative damage (then being more widely investigated as a causal factor in other conditions such as bronchopulmonary dysplasia and even intracranial bleeding), and perhaps further reducing the incidence of RoP, but it was not known if this would be effective or safe, nevertheless, based on the observational data and the very old studies some centers did take up even lower saturation ranges.

I must be clear, keeping the saturations below 95% was considered adequate to prevent hyperoxia, and seemed to probably reduce RoP. It was thought by some that oxygen was no longer a major culprit in the causation of RoP as long as hyperoxia was avoided, so there were many studies looking at other potential risk factors, hypocarbia, hypercarbia, blood transfusions, and inadequate nutrition were all considered to be possibly important (and may indeed be important). It was not at all clear whether or not dropping the saturation ranges even lower, to below 90%, would actually have any additional benefit in reducing RoP.

And retinopathy had become a problem again. Since the introduction of continuous monitoring much more immature babies were surviving, the kinds of babies tested in the 2 early groups of trials almost never developed retinopathy, it was mostly babies of 26 weeks gestation and below who were developing the condition, also universal retinal screening was refined, and was picking up many more cases.

This is the situation that led to the enormous variations in O2 saturation targeting. Some centers felt that a saturation of 90 to 95% was the best idea, largely avoiding hyperoxia, and not wanting to risk hypoxia. So they would have a unit routine. The alarm limits for all preterm babies in the NICU would be set to, say, 89 and 96. Then the nurse would adjust the oxygen delivered, sometimes every couple of minutes, to stay within the target range, and the alarms would frequently sound, when the baby passed beyond those limits. Every preterm baby in the NICU would have the same limits, until they no longer needed oxygen. As the babies’ lungs improve, they will often have saturations above 95% even without supplemental O2, sometimes up to 100%. So if the oxygen requirements drop to 21% O2, and the saturation is above the target limit, the high saturation alarm is switched off. Some babies in the NICU never need oxygen, they may right from the start have high saturations even in 21% oxygen. We accept this because the PaO2 of a baby in room air, 21%, cannot easily exceed about 105 mmHg. Which was considered safe. It is very rare for a baby who has never had supplemental oxygen to develop RoP, even though their saturations may be above 95% for their whole life.

Another center examining the same data would set their oximeter alarm limits to a lower range. With that approach fewer babies ever get supplemental oxygen, they will tend to come out of oxygen earlier, but they will continue to have the same saturation target whenever they need oxygen until they are nearly ready to go home.

Unfortunately, some families who participated in SUPPORT have been misled by pressure groups, consisting of doctors who have never worked in an NICU, and PhD ethicists who have never even set foot in an NICU or taken the trivial effort of talking to someone who has. One such family who spoke on the day of the recent OHRP meeting noted (I paraphrase) ‘I didn’t realize that if my baby was in the trial that they would not receive the usual care of adjusting the saturation range according to his needs’. Unfortunately, whoever told them that lied to them.

As part of the preparation for the conference in Sydney where I just presented, I pulled out the PowerPoint presentation that I gave several years ago, when we were planning the O2 trials, and I was asked to present the rationale for the COT, Canadian Oxygen Trial (I think it was at the annual Canadian Paediatric Society meeting). In that presentation were two slides, one was the claims of the doctors who were happy using higher saturations, the other included the claims and rationale of those of us who were advocating lower saturations. Both groups claimed that their favorite range would reduce death, reduce BPD, and reduce morbidity in the long term. The low saturation proponents were in addition claiming that retinopathy might be reduced, the high saturation groups were claiming that retinopathy would not be further affected by going lower!

Yes we really were completely unsure what ranges were the best.

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