Medical Student ElectiveArjun Chandna

Georgetown & Lethem Public Hospitals, Guyana

January – February 2011

Background to the electiveI recently spent six weeks working in Guyana on my medical elective. I chose tovisit Guyana for many reasons. I was keen to visit South America and aftersearching the WHO website, a few countries disease profiles interested me, one ofwhich was Guyana. Whilst I can converse in rudimentary Spanish, I am not able totake a medical history and I felt I would gain most from my elective if I undertookit in a predominantly English speaking country.

Before setting off I had very little idea as to what to expect. Guyana is visited byfew tourists so finding information about the country, from the Internet or the oneavailable guidebook, was difficult. A significant part of the disease burden isinfectious diseases, particularly HIV/AIDS. I was looking forward to learningabout how these present, particularly their interaction with pregnancy. Inaddition, many conditions that are common in the UK are also prevalent inGuyana, but present much later. I was looking forward to learning about theadvanced presentations of common conditions and the florid clinical signs thatoften accompany this.

I spent half my time in Georgetown, the capital of Guyana, working in the publichospital, which is the major referral centre for the country. I was attached to theobstetric and gynaecology department and was able to witness first-hand thechallenges facing women’s healthcare. A striking difference between the UK andGuyana was that whilst in the UK pregnancy is a healthy period of a woman’s life,in Guyana the strains of pregnancy (both physical and financial) often accentuateunderlying health problems, for example, malnutrition, hypertension, filariasisand diabetes.

In Lethem, I spent time working with an NGO, Remote Area Medical, whoprovide outreach medical services to the people living in the Guyanese savannahs.

This work focuses largely on sexual health education, HIV-testing, basic antenatalcare, eye screening and diabetes and hypertension monitoring.

In Georgetown I was also able to carry out my intended elective research project:investigating neurological dysfunction in pre-eclampsia using a technique calledsaccadometry. I present my results below. My two current career interests areneurology and obstetrics. This project enabled me to experience the practise ofthese disciplines in a new and challenging environment.

Overall my elective was a wonderful experience, which has fuelled my desire tospend a significant amount of my professional career working abroad.

Word Count: 2731 (excluding figures and references)

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IntroductionPre-eclampsia and the consequences thereof remain a leading cause of maternaldeath particularly in the developing world. Neurological dysfunction, fromhyperreflexia to eclamptic seizures, is an important yet poorly characterised part ofthe disease phenotype. Saccadic reaction time is known to be an excellentbiomarker for general neurological function. In addition, parallels between corticalcontrol of saccadic reaction time and spinal stretch reflexes (often deranged in pre-eclampsia) exist. For this reason, we investigated whether neurologicaldysfunction in pre-eclampsia is amenable to detection using saccadometry.

MethodsA head-mounted infrared oculometer was used to record 900 saccadic latencytrials from women pre- and post-delivery in the obstetric unit of GeorgetownPublic Hospital, Guyana. The pre- and post-delivery reaction times werecompared for each woman.

ResultsReaction times pre- and post-delivery were significantly different in all womenrecorded from. In 75% (3/4) of cases the whole distribution was significantlydifferent (p < 0.05) and in the remaining 25% (1/4) the median latency wassignificantly different (p < 0.05).Insufficient data was collected to compare normal pregnancy and pre-eclampticdistributions.

DiscussionThis study demonstrates altered neurological functioning pre- and post-delivery innormal pregnancies. This alteration may be due to the delivery process or thepregnant state itself (with the change post-delivery representing a return toneurological baseline). Due to problems with data collection it is not yet possible toanswer the primary question of this study as to whether neurological dysfunctionin pre-eclampsia is amenable to detection using saccadometry.

IIINNNTTTRRROOODDDUUUCCCTTTIIIOOONNNPre-eclampsia occurs in 3-14% of pregnancies (Irminger-Finger, et al., 2008) and isthe fourth leading cause of maternal death, accounting for 12% of maternalmortality worldwide (WHO, 2005). Improving maternal health was one of eightMillennium Development Goals committed to by countries at the United NationsMillennium Summit.

Despite its serious consequences, the pathophysiology of pre-eclampsia is stillincompletely understood and hence prophylactic treatment is difficult to provide.Current management centres upon detection of cardinal signs (pregnancy-inducedhypertension and proteinuria) and control of blood pressure until delivery of fetusand placenta is appropriate.

Pre-eclampsia is characterised by pregnancy-induced hypertension, proteinuriaand peripheral and central oedema – the first two characteristics being mostdiscriminative in clinical diagnosis. In addition pre-eclamptic women often haveabnormal neurology, most commonly hyperreflexia.

Work by Sherrington (1924) illustrated the central role of the cerebral cortex incontrolling the gain of spinal stretch reflexes (Liddell and Sherrington, 1924).Given that eclampsia, a much-feared sequelae to pre-eclampsia, is a manifestationof severe cerebral dysfunction, it is reasonable to predict that hyperreflexiaexhibited by pre-eclamptic women may be of cerebral origin. In fact, aretrospective study from 2008 found that 16 of 22 eclamptic seizures werepreceded by hyperreflexia (Boudaya, et al., 2008). Techniques that quantitativelymeasure neurological function may therefore be useful in detecting early changesin pre-eclampsia. Unfortunately it is not easy to get robust, quantitative measuresof hyperreflexia.

In recent years it has become apparent that an excellent quantitative biomarker forgeneral neurological function can be provided by saccadic reaction time (RT). Thesaccadic system is a microcosm of the brain itself (Carpenter, 2004) and hencesubtle changes in neurological function are readily detected by studying RTdistributions. This is due in part to the fact that neural networks spanning wideareas of the cortex are implicated in the control of saccades. In particular, thesaccadic machinery in the superior colliculus is subject to tonic cortical inhibition

in a manner not dissimilar to cortical inhibition of spinal reflexes (Hikosaka andWurtz, 1983).

RT studies have been used to investigate Huntington’s disease and Parkinson’sdisease with great success (Antoniades, et al., 2007; Michell, et al., 2006). Inaddition, ongoing work investigating a potential role in traumatic brain injury(Pearson et al., 2007) is showing promising results.

There are also many practical advantages of using RT. Measurement is non-invasive with a portable, infrared oculometer and as we make three saccades persecond, large amounts of data can be collected without the risk of fatigue thatmanual response tasks are exposed to. Our detailed understanding of the saccadicsystem has facilitated comprehensive theoretical modelling, which in turn allowsputative mechanistic conclusions to be drawn from observed changes in reactiontime. One such model, LATER (Linear Approach to Threshold with Ergodic Rate),is discussed in this study (Carpenter and Williams, 1995). Finally, recording RT isrelatively cheap compared with other techniques used to assess neurologicalfunction and thus it is an attractive option for developing countries where theburden of pre-eclampsia is largest (WHO, 2005).

This is the first study that aims to investigate neurological dysfunction in pre-eclamptic women in a manner permitting quantitative analysis.

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Participant recruitmentPre-eclampsia sufferers were recruited from Georgetown Public Hospital (GPH),Guyana in January 2011. Participants were asked to give informed consent. Alllocal ethical procedures were adhered to. The number of cases in the study perioddetermined the sample size.

Diagnosis of pre-eclampsia was according to the following criteria:1. Pregnancy-induced hypertension2. Dipstick-positive proteinuria

Participants were excluded if they were:1. Aged < 16 years or > 40 years2. Suffering with a medical disorder other than pre-eclampsia3. Using medication (other than vitamin supplements) during pregnancy

Study designWe performed a longitudinal study comparing RT distributions pre- and post-delivery in pre-eclampsia sufferers. We also carried out identical recordings (pre-and post-delivery) in age- and gestation-matched normal pregnancy controls.

Data Collection

A miniaturised, head-mounted, infrared reflection oculometer (12 bit resolution,sampling rate 1kHz, low-pass filtered at 250Hz, signal-to-noise ratio 45dB) wasused to measure 100 horizontal saccades. The device is comfortable and requires

Figure 1. A saccadometer in situ. The blue nose-piece is adjustable to ensure that infra-redemitters and detectors are aligned with the participant’s sclera. The three lasers are visible atthe top of the apparatus.

no head restraint since the target display moves with the head. The oculometer hasthree low-power red lasers that projected high contrast 13 cd.m2 target dots onto alight-coloured background, subtending 0.1°, in a horizontal line at ± 10° to themidline; to a first approximation these angles are independent of the distancebetween subject and background. Participants sat 1m from a blank, non-reflectivescreen.

Each trial began with the presentation of a central target, which, after a randomforeperiod (1-2s), disappeared at the same time as a target to either the left or right(chosen at random to prevent anticipation) appeared. The target remained for200ms after a resultant correct saccade, or for 1s (with an incorrect or absentresponse), whichever was shorter. Participants were instructed to track themovement of the target with their eyes as quickly as possible withoutcompromising accuracy. The device is self-calibrating, using five preliminary trialsto each side. The same procedure was used for controls to minimise bias. A further100 trials were recorded after delivery.

SACCADE

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Figure 2. Schematic illustration of the experimental protocol. Participants were required tofixate a central target (fixation indicated by a dashed circle, target by red spot). After a randomfore-period (1-2s) the spot would move 10° horizontally, either left or right (in this case to theright). The participant was required to look at (make a saccade to) the new target location. Thetime between target onset and response onset was recorded as the saccadic latency (RT).The next trial began with the target returning to the central location.

Difficulties with data collectionAt the time of data collection a government investigation into the maternal deathrate at GPH made recording from women, particularly sick women (those withpre-eclampsia) difficult. Whilst it was possible to collect data from normalpregnancies (800 saccades from 4 women) only 1 woman (100 saccades) with pre-eclampsia was recorded from pre-delivery.

AnalysisThe software application LatencyMeter automatically eliminated trialscontaminated by blinks, head movements and inattention: computerising thisprocess removed observer bias. The data were then exported to the applicationSPIC, that analysed the data, provided estimates of the underlying LATERparameters, and generated reciprobit plots.

The two fundamental parameters (see Discussion for interpretation) are themedian, µ, and standard deviation, σ, of the main distribution of reciprocallatencies. For some, but not all, individuals a small sub-population of early

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Figure 3. Schematic showing the graphical manipulation from a frequency-histogram (A) toa reciprobit plot (D). A) A frequency-histogram showing the positively skewed distribution ofsaccadic latency. B) Using a reciprocal scale on the abscissa indicates that the reciprocal oflatency may be normally distributed. C) This is further supported by a sigmoidal curvedemonstrated on a cumulative histogram, D) and finally verified by the straight line when aprobit scale is used on the ordinate axis.Figures adapted from www.cudos.ac.uk/LATER.html

saccades was seen, distinct from the main distribution, which can be characterisedby a third parameter, its standard deviation, σE.

Pre- and post-delivery distributions were compared using a Kolmogorov-Smirnovtest. In addition the median of each distribution was compared using a Student’spaired t-test.

RRREEESSSUUULLLTTTSSSKolmogorov-Smirnov one-sample tests showed that for all participants, observeddistributions conformed (p > 0.05) to the recinormal distribution predicted byLATER, justifying the description of all distributions by means of the three LATERparameters, µ, σ and σE.

Four normal pregnancy patients were recorded from. In each case the median,whole distribution or both were significantly different (p < 0.05) pre- and post-delivery. Their distributions are shown below.

Patient Age Gestation Parity Delivery Anaesthetic Complication Time Post-delivery Medical History

1 22 40+1 0 NVD Entonox - 6h -

2 24 38+2 1 NVD Entonox PPH = 550ml 30h -

3 25 37+6 1 NVD Entonox - 17h -

4 28 39 2 NVD Entonox - 22h -

5 27 37 1 N/A N/A N/A N/A Previous PIH

Latency (ms)

Figure 4. Reciprobit plot for patient 1illustrating significant differencebetween RT distributions pre- (red)and post-delivery (blue), p < 0.001.The median latency is alsosignificantly different between thetwo groups, p = 0.010.

Table 1. Tabulated data for the 5 participants. Patients 1 to 4 were normal pregnancies recordedfrom pre- and post-delivery. Their age, gestation and parity are recorded along with deliverymethod, anaesthetic, complications and the time the post-delivery recording was carried out.Patient 5 had pre-eclampsia and was only recorded from pre-delivery.

Latency (ms)

Figure 5. Reciprobit plot for patient 2illustrating significant differencebetween RT distributions pre- (red)and post-delivery (blue), p = 0.007.The median latency is notsignificantly different between thetwo groups, p = 0.808.

Latency (ms)

Figure 6. Reciprobit plot for patient 3illustrating significant differencebetween RT distributions pre- (red)and post-delivery (blue), p = 0.046.The median latency is notsignificantly different between thetwo groups, p = 0.275.

Latency (ms)

Figure 7. Reciprobit plot for patient 4illustrating no significant differencebetween RT distributions pre- (red)and post-delivery (blue), p = 0.088.The median latency is significantlydifferent between the two groups, p =0.018.

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Due to the difficulties collecting data it has not been possible to answer theprimary question of this study: to determine whether neurological dysfunctionassociated with pre-eclampsia is amenable to detection using saccadometry.However, the results suggest, somewhat unexpectedly, that the delivery process orthe pregnant state itself may affect neurological function. Given the preliminarynature of the results, discussion at this stage is tentative, however a number ofobservations can be made.

Before further discussion it is useful to have a framework within which theseresults can be interpreted. As previously noted, RT is an excellent biomarker forgeneral neurological function. In fact, RT is equivalent to decision time (Carpenter,2004) and hence decision-making models have been used to characterise RTdistributions with much success. The simplest of these models (Nakahara, et al.,2006), LATER, will be used in this discussion.

LATER proposes a decision signal rising at rate r. Trial-by-trial this rate variesabout a median (µ) and standard deviation (σ). Different conditions can alter theshape of the decision profile. Reducing θ, either by increasing S0 (altering the priorprobability of a certain hypothesis (Carpenter and Williams, 1995)), or lowering ST

(placing increased importance on the urgency of response (Reddi and Carpenter,

The LATER Model

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Figure 8. The LATER Model. The initial decision signal (S0) represents a prior probability thata particular hypothesis is true. Accumulation of sensory information updates this probability, atrate r, and the decision signal rises or falls depending on whether the information is supportiveof the initial hypothesis. A decision (for our purposes, a saccade) is made once the signalreaches a threshold level (ST).

2000)), causes clockwise swivel about the infinite time axis on the reciprobit graph.Providing more supportive information increases r and, whilst maintaining theslope, causes a parallel leftward shift (Reddi, et al., 2003).

LATER also offers an explanation for the subpopulation of early responses seen insaccades, characterised by their distinct σE. Their latencies are consistent with aputative subcortical pathway through the superior colliculus. It could be that asecond collicular LATER unit is usually suppressed by cortical inhibition, butoccasionally it reaches threshold first, triggering an early saccade. This hypothesisis supported by the fact that a distracting task increases the proportion of earlyresponses (Halliday and Carpenter, in submission).

Alterations in reaction time distributionsAll four patients have significantly different RT pre- and post-delivery. Themedian, whole distribution or both are significantly different pre- and post-delivery in the same individual. In 75% (3/4) of cases the whole distribution issignificantly different. The remaining case, patient 4 (figure 7), has a significantlydifferent median RT pre- and post-delivery. In addition, they demonstrate a clearshift in their whole distribution. It is therefore likely that with more trials (forexample, 200 saccades pre- and post-delivery) the difference in the wholedistributions may also achieve significance.

This finding is important because whilst RT distributions are idiosyncratic, theyare remarkably consistent within an individual. Hence, the finding suggests analteration in neurological functioning pre- and post-delivery.

At this stage it is difficult to comment on how or why the distributions arechanging. Whilst 200 trials per patient allow effective analyses of changes withinan individual, it is difficult to comment on population trends with a sample of 4patients. Within our cohort, different patients demonstrate swivel and shift andmedian RT sometimes increases and sometimes decreases post-delivery. With alarger sample, trends in swivel vs. shift or the different parameters may becomeapparent, allowing putative mechanistic interpretation in the context of LATER orother decision-making models.

Further workMeaningful further work will require the collection of more data. As previously

stated, this may reveal how RT distributions are changing and in turn, decision-making models would allow speculation as to why. At birth there are a number ofchanges occurring (hormonal, psychological, physical) and any or all of thesecould contribute to the altered neurological function that has been suggested. Itwill also be important to examine how the other parameters, σ and σE, are affectedin order to fully characterise how the distributions are changing.

Further work should be carried out with a refined methodology. Firstly, moretrials should be recorded at each session to increase the statistical power of theanalyses. Secondly, post-delivery recording time should be standardised. It isimportant to consider lingering effects of anaesthesia on the brain and ensure thatrecording is undertaken after these have worn off. One explanation for the slightlyodd shape to the RT distribution of patient 1 is that the post-delivery recordingwas at 6 hours. Finally, consideration should be given to carrying out a controlstudy pre- and post-delivery by caesarean section. Most pre-eclamptic deliveriesare likely to be by caesarean and hence it will be important to have a baseline tocompare these results to.

This study has revealed that delivery or pregnancy itself may alter neurologicalfunction. Hence, recordings in pre-eclamptic patients will not be straightforwardto interpret: potential changes in the pre-eclamptic population must be comparedto changes in normal deliveries. It may be particularly interesting to investigateany change in early saccades (σE). The cortex normally suppresses these but giventhe impaired suppression of spinal reflexes in pre-eclampsia (evidenced byhyperreflexia) there may be salient changes in this parameter.

Finally, given that pregnancy may affect neurological function, it may be useful tocharacterise this more thoroughly. One method for doing this could be to performsaccadometry regularly throughout pregnancy, ideally starting prior toconception.

SummaryThis study has been unable to answer the primary question: is neurologicaldysfunction in pre-eclampsia amenable to detection using saccadometry.However, it has demonstrated, albeit preliminarily, that the delivery process or thepregnant state itself may be associated with altered neurological function. There ismuch scope for further work in this field.

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1. Irminger-Finger, I., 2008. Pre-eclampsia: a danger growing in disguise. Int JBiochem Cell Biol., 40(10),1979-83

2. World Health Organisation, 2005. The world health report 2005 – Make everymother and child count, Geneva: World Health Organization

3. Liddell, E., 1924. Reflexes in Response to Stretch (Myotatic Reflexes.Proceedings of the Royal Society of London. Series B, Containing Papers of aBiological Character, Vol. 96, No. 675, pp. 212-242

4. Boudaya, F., 2008. Eclampsia: epidemiological aspects and management of28 patients. Tunis Med., Jul;86(7):685-8

5. Carpenter, RHS., 2004. The saccadic system: a neurological microcosm.Advances in Clinical Neuroscience and Rehabilitation, 4:6-8

6. Hikosaka, O., 1983. Visual and Oculomotor Functions of Monkey SubstantiaNigra Pars Reticulata. I. Relation of Visual and Auditory Responses toSaccades. Journal of Neurophysiology, Vol. 49, No. 5

7. Antoniades, CA., 2007. Saccadometry: a new tool for evaluating pre-symptomatic Huntington patients. Neuroreport, 18:1133-6

8. Michell, AW., 2006. Saccadic latency distributions in Parkinson's diseaseand the effects of L-dopa. Experimental Brain Research, 169:237-45

9. Pearson, BC., 2007. Saccadometry: the possible application of latencydistribution measurement for monitoring concussion. British Journal ofSports Medicine. 41:610-2

10. Carpenter, RHS., 1995. Neural computation of log likelihood in the controlof saccadic eye movements. Nature, 377:59-62

11. Nakahara, H., 2006. Extended LATER model can account for trial-by-trialvariability of both pre- and post-processes. Neural Networks, 19:1027-1046

12. Reddi, B.A.J., 2000. The influence of urgency on decision time. NatureNeuroscience, 3, 827-831

13. Reddi, B.A.J., 2003. Accuracy, Information, and Response Time in a SaccadicDecision Task. Journal of Neurophysiology, 90, 3538-3546

14. Halliday, J., In submission. Audio-verbal distraction leading to over-fast,inaccurate saccadic responses: implications for driving and a possibleneural mechanism.

This project would not have been possible without the support of the Royal College ofObstetricians & Gynaecologists, UCL Medical School, Amulree Bursary, the Royal Free Association,the Wellcome Trust, the Wellbeing of Women and the British Dental & Medical Students’ Trust.