Comparison of parkin’s score and new Ballards core in gestational age assessment of neonate

 

 

 

Thepointscanbegivenwhentheresistanceisfeltasfollows:

 

Point	-1	0	1	2	3	4
Location Description	Heelis at the levelof theear	Heel is at the level of thenose	Heel is at the level of thechin	Heelis at the levelof the nipple	Heelisat the level of the umbilicus	Heelisat the level of the femoral crease

 

Textureoftheskin.

Skin of newborn matures with the development of baby. In the earlier stages of development, the skin of newbornlooks very transparent and adheres closely. As time progresses, it becomes smoother and gradually toughens. In the final stages, the fetal skin shrinks, develops red rashes, and flakes off. Over time, the developing fetus forms a protective layer called vernix caseosa, which becomes more visible as pregnancy progresses. As gestationnearsitsend,theinfantstartstopassmeconium.Thissubstance can sometimes irritate the skin, leading to a rough, leathery, or cracked skintexture.

 

Score	-1	0	1	2	3	4	5
SKIN	Sticky, friable, transparent	gelatinous, red, translucent	smoot hpink, visible veins	superficial peeling &/or rash, few veins	cracking, pale areas, rare veins	parchment, deep cracking, no vessels	leathery, cracked, wrinkled

 

Lanugoofthe skin:

The fetus's entire body is shrouded in a fine layer of hair referred to as Lanugo. In the early stages of development, lanugo is absent. It starts to appear around the sixth month of gestation. Over time, it becomes more abundant, and by the 7thmonth, it generally covers the upper back and shoulder. As the pregnancy continues, the fetus gradually takes on a flexed posture. Simultaneously, there is a thinning of lanugo, which typically affects the lower back and the lumbo-sacral area. In fully Term baby has no lanugo present over skin.

Factors such as metabolic, familial, hormonal and nutritional aspects has effect on quantity and distribution of lanugo in newborns for a certain gestational age. Babies born to mothers with diabetes often display a unique lanugo distribution, particularlyon the upper back and earsas gestation nears its conclusion. It is important to assess thescore appropriately

 

A. Footcreases:

The presence of creases on the sole of the foot depends on how mature the fetus is. In the initial stages of pregnancy, there are no footcreases present in the fetus. As the pregnancy continues, the fetus within uterusis in flexed posture. This condition, superimposed with dehydration, results in the development of the plantar crease. Thisfirst involves the upper section of the foot and gradually extends to the heel as the fetus matures completely.

 

Thesuitableboxcanbechosenbasedonthefoot creases.

score	-2	-1	0	1	2	3	4
Plantar Surface	<40 mm (heel- toe)	40–50 mm (heel- toe)	>50 mm, no crease	faint red marks	anterior transverse crease only	Creases ant. 2/3	creases over entire sole

B.MeasurementofFootlength:

 

Determining the foot length is significant factor that can be relevant for newborns, particularly in cases where the foot crease is not appropriate, such as with very premature infants. This can be achieved by measuring the distance with tape from the great toes to the tip of the heel. It is essential to measure with the foot fully extended.

 

Thescoringmethodisasfollows:

Point	LengthofFoot
-2	<40mm
-1	Between40mmand50mm
0	>50mm

 

Measurementofbreastsize:

Breast tissue growth is a significant factor in maturity assessment of a newborn.Thebreasttissuedevelopment iscontingentuponvariouselements, including the hormonal status of the mother and the nutritional status of the newborn.

 

Procedure:

Measure the breast mass in millimeters by holding the breast mass between the thumb and the index finger. The points are outlined as follows:

Point	Description
-1	Whenthenippleis indiscernible
0	Whenthenippleishardlynoticeable
1	Whenthebreastbudisnot palpable
2	Whenthebreastbuddiameteris1-2mm
3	Whenthebreastbuddiameteris3-4mm
4	Whenthediameterofthebreastbudisabove5mm

 

 

Caution: If there isa disparityin themass of the breastbud oneitherside, itis recommended to choose the larger one. Gynecomastia in infants caused by maternal hormonal effects generally manifests within two days post-delivery.

 

Earfirmness:

The ears firmness of baby is dependent on the volume of ear cartilage. The amount and configuration of ear cartilage depends on the baby's maturation and gestation. The two key features that should be highlighted are the ear recoil and the ear cartilage distribution and thickness.

Procedure:

Assessing the thickness of ear by gently palpate the cartilage of the baby. The following step is to evaluate the flexibility of the ear fold by molding

 

it into an unusual shape and observing its recoiling. In the early stages, there is no recoiling of the ear fold, and the ear remains flat due to the absence of cartilage formation. As maturity advances, the speed of recoiling also increases. Additionally, the curvature of the ear fold improves with the development of well-formed cartilage. Depending upon the score, respective box is selected.

 

 

Sign	-1	-2	0	1	2	3	4
Eye/Ear	lids fused loosely	lids fused tightly	lids open, pinna flat, stays folded	sl. curved pinna; soft; slow recoil	well- curved pinna; softbut ready recoil	formed &firm, instant recoil	thick cartilage, ear stiff

 

 

v.b.Eyeliddevelopment:

 

The maturation of eyelids can additionally be included in the assessment of a newborn's maturity status. In this context, we will observe whether the eyelids of the newborn baby are capable of being opened or not.

Procedure:

 

By gently applying pressure over the eyelid when the eyelids are stucked together. It is to be done when the baby is calm and not crying.

Point	Description
-2	Thefusedeyelidsaredifficulttoseparateduringtheearlyperiodof maturation
-1	Asmaturityincreases,thosefusedeyelidscouldbepartlyseparable
0	Attheendofmaturation,eyelidsarekept open

Accordingtotheabovescoringmethods,anappropriateboxis selected

Genitals–Male

In male newborn, the gonads commence their differentiation along the specified pathway. Gonadal development depends upon the maturation of the newbornandtheinfluenceofhormones.Duringtheseventhmonth,the gonad begins its descent along the gubernaculum into the inguinal canal. During early eighth month, the gonads are located within the inguinal canal. By the end of this month, the gonads extend into the superior ring of inguinal canal. During the descent of the male gonads, the scrotal skin gradually develops with increase in pigmentation and rugosities with the maturation. In the early stages of pregnancy, the male gonads have not yet descended, resulting in a scrotum that appears empty with a reduced number of rugosities and pigmentation. As maturation advances, the gonads descend, and the skin of scrotal shows more pigmentation and greater rugosities. The scrotum's size also increases and becomes pendulous. Generally, the gonads will descend slightly earlier on the left side in comparison to the right side.

 

For undescended gonads, if the condition occurs on one side, the evaluation may rely on the unaffected side. However, if both sides are affected, the scoring will correspond to the other variables employed in the newborn assessment

 

genitals –Female

The examiner here maintains the infant's leg in a semi flexed with little abducted position. In preterm female babies, the clitoris is distinctlyprominent, and the labia is flat. With maturation, the external genitalias expand, leading to the labia majora eventually becoming large enough to entirely enclose the clitoris and labia minora. Following these findings, the appropriate square is selected, and scoring is performed

 

Aims and objectives

I.                  TheaimofthestudyistocomparetheaccuracyofParkin’sscore(PS)and New Ballard score (NBS) to assess the gestational age (GA) in newborns.

 

II.                 Todetermine theaccuracyof Parkins score in assessmentof gestational age of babies with Last menstrual period (LMP)/1STtrimester USG.

III.               TodeterminetheaccuracyofNewBallardScoreinassessmentofgestational age with last menstrual period (LMP)/1STtrimester USG.

IV.               TocompareanddeterminetheaccuracyofParkin’sScorewithNewBallard Score in assessment of gestational age with LMP/1STtrimester USG

 

197 new born from gestational age between 27-44 weeks were included in our study. Their maternal age distribution is given in table 1.

Table1:AgeDistributionofMothersofStudySubjects

 

Age in Mean±SD: 26.48±3.72

 

Table 1 shows the age distribution of mothers in the study, with the majority (46.70%)fallingin the26-30age group,followed by39.60% in the21-25 group. The mean maternal age was 26.48 ± 3.72 years, indicating a relatively young cohort. Very few mothers were ≤20 or ≥36 years old, suggesting these age groups were underrepresented.

Figure1:AgeDistributionofMothersofStudySubjects

 

 

Table2:DistributionofStudySubjectswithrespectto Gender

 

Gender	Numberof Patients	%ofpatients   (n=197)	95%CIof%
Male	128	65.00	58.08–71.92
Female	69	35.00	28.08–41.92

 

 

Table          2 describes   newborn                  gender              distribution,   with                         males     (65.00%) outnumbering females (35.00%).

 

Figure2:DistributionofStudySubjectswithrespecttoGender

 

 

Table3:DistributionofStudySubjectswithrespecttoBirth Weight

 

BirthWeightin mean±SD:2.59±0.57

 

Table 3categorizes birth weight, with most newborns (65.00%) appropriate for gestationalage(AGA).However, 30.46% were smallfor gestationalage (SGA), highlighting a notable proportion with potential growth restrictions

 

 

 

 

 

 

Figure3:DistributionofStudySubjectswithrespecttoBirthWeight

 

 

Table4:DistributionofStudySubjectswithrespecttoModeof Delivery

 

 

Table 4 outlines the mode of delivery, with a high rate of cesarean sections (LSCS, 75.63%) compared to vaginal deliveries (24.37%), suggesting a preference or medical necessity for surgical deliveries in this cohort.

Figure4:DistributionofStudySubjectswithrespecttoModeofDelivery

 

 

Table5:DistributionofMothersofStudySubjectswithrespecttoGravida Status

Gravida	Numberof Patients	%ofpatients   (n=197)	95%CIof%
1	82	41.62	34.78-48.46
2-3	97	49.24	42.22-56.26
4-5	13	6.60	3.06-10.14
>5	5	2.54	0.32-4.76

 

 

Table 5 presents the gravida status of mothers, revealing that nearly half (49.24%) had 2-3 pregnancies, while 41.62% were primigravida (first pregnancy). A small proportion (6.60%) had 4-5 pregnancies, and only 2.54% had more than five, indicating most mothers were either first-time or had limited prior pregnancies

 

 

Fig5:DistributionofMothersofStudySubjectswithrespecttoGravida Status

 

 

Table6:DistributionofStudySubjectswithrespecttoPeriodofGestation by LMP

POGinMean±SD:37.37±2.71

 

Table 6displays the period of gestation (POG) by last menstrual period (LMP). The majority (50.76%) delivered at term (37-40 weeks), while 24.37% were late preterm (>34-<37 weeks). The mean POG was 37.37 ± 2.71 weeks, aligning with typical gestational ranges

 

 

 

 

 

Fig6:DistributionofStudySubjectswithrespecttoPeriodofGestationby LMP

 

 

Table 7: Distribution of MotherofStudySubjectswithrespectto Gestational Hypertension

 

 

Table 7highlights gestational hypertension prevalence, which was low(4.06%).The vastmajority(95.94%)hadnohypertension, suggestingitwasnot a major factor in this cohort.

 

Fig7:DistributionofMotherofStudySubjectswithrespecttoGestational Hypertension

 

 

Table8:DistributionofStudySubjectswithrespecttoMeconium-Stained Labor (MSL)

 

 

Table8indicatesthatMSLwasrare(2.54%),withmostdeliveries(97.46%) unaffected, implying minimal fetal distress in this population.

 

Fig8:DistributionofStudySubjectswithrespecttoMeconium-Stained Labor (MSL)

 

 

Table9:DistributionofStudySubjectswithrespectto Oligohydramnios

 

 

 

Table 9 shows oligohydramnios was uncommon (1.52%), with 98.48% of cases unaffected, suggesting it was not a significant complication in the study.

 

Fig9:DistributionofStudySubjectswithrespectto Oligohydramnios

 

Table 10:DistributionofStudySubjectswithrespecttoPROM

PROM	Numberof Patients	%ofpatients   (n=197)	95%CIof%
Present	3	1.52	0.00–3.24
Absent	194	98.48	96.76–100.00

 

 

Table 10reports that premature rupture of membranes (PROM) was rare (1.52%), with almost all cases (98.48%) unaffected, indicating low risk for infection or preterm delivery.

 

Figure10:DistributionofStudySubjectswithrespecttoPROM

 

Table11:DistributionofMotherofStudySubjectswithrespectto Hypothyroidism

 

 

Table 11reveals hypothyroidism was present in 13.71% of mothers, a notable proportion; while 86.29% were unaffected, suggesting thyroid dysfunction may warrant further investigation.

 

Figure11:DistributionofMotherofStudySubjectswithrespectto Hypothyroidism

 

Table12:DistributionofMotherofStudySubjectswithrespectto Gestational Diabetes Mellitus (GDM)

 

 

Table 12 shows gestational diabetes mellitus (GDM) was uncommon (3.55%), with 96.45% unaffected, indicating low metabolic disorder prevalence in the cohort.

 

Figure12:DistributionofMotherofStudySubjectswithrespecttoGDM

 

 

Table13:DistributionofStudySubjectswithrespecttoOtherAssociated Disease/Event

Associated Disease/Event	Numberof Patients	%ofpatients   (n=197)	95%CIof%
Anaemia	6	3.05	0.63%–5.47%
Pre-eclampsia	2	1.02	0.00%–2.43%
TB	2	1.02	0.00%–2.43%
Thrombocytopenia	2	1.02	0.00%–2.43%
NCIAB	4	2.03	0.08%–3.98%
PlacentaPrevia	3	1.52	0.00%–3.02%
RHIncompatibility	3	1.52	0.00%–3.02%
HepatitisBPositive	1	0.51	0.00%–1.51%
Beta Thalassemia	1	0.51	0.00%–1.51%
CHD	1	0.51	0.00%–1.51%

 

 

Table 13lists other associated diseases, with anaemia (3.05%) being the most common. Otherconditions(e.g., pre-eclampsia, TB)wererare (<2%),indicating low comorbidity prevalence overall

 

CHD		1.00
BetaThalassemia		1.00
HepatitisBPositive		1.00
RHIncompatibility				3.00
PlacentaPrevia				3.00
NCIAB					4.00
Thrombocytopenia			2.00
TB			2.00
Pre-eclampsia			2.00
Anaemia						6.00
	0	2		4		6
NumberofPatients

 

Figure13:DistributionofStudySubjectswithrespectto Associated Disease/Event

 

 

Table14:ComparisonofGestationalAgewithrespecttoLastMenstrual Period(LMP),ParkinsScore (PS),andNewBallardScore(NBS)(n=197)

 

Table 14 compares gestational age (GA) estimates derived from the Last Menstrual Period (LMP), Parkins Score (PS), and New Ballard Score (NBS). The mean GA by LMP (37.37 ± 2.71 weeks) closely aligns with PS (37.44 ± 2.37 weeks), as indicated by a non-significant paired t-test (p=0.5409), suggesting strong agreement between these methods. However, NBS (36.04 ± 2.44weeks)significantlyunderestimatedGAcomparedtobothLMP(p<0.0001) and PS (p<0.0001). This discrepancy raises concerns about NBS's reliability in accurately assessing GA when LMP is the reference standard

 

Figure14:ComparisonofGestationalAgewithrespecttoLastMenstrual Period (LMP), Parkins Score (PS), and New Ballard Score (NBS) (n=197)

 

Table 15:Comparison of CategoricalGestational Age with respect to Last MenstrualPeriod(LMP),ParkinsScore(PS),and NewBallardScore(NBS) (n=197)

Method	NumberofPatients(%)
	Pre-Term   (<37Wks)	Term   (37-40Wks)	Post-Term   (>40Wks)
LMP	70 (35.53)	100(50.76)	27(13.71)
ParkinsScore(PS)	57(28.93)	133(67.51)	7 (3.55)
NBSScore	106(53.81)	87 (44.16)	4 (2.03)
Chi-SquareTest(LMP   vsPS)	0.0001
Chi-SquareTest(LMP   vs NBS)	<0.0001
Chi-SquareTest(PS   vs NBS)	<0.0001

 

Table 15 categorizes GA into pre-term, term, and post-term groups acrossLMP, PS, and NBS. While LMP classified 35.53% as pre-term, PS and NBS showeddifferingproportions(28.93%and53.81%,respectively).Chi-square

tests revealed highly significant differences (p<0.0001) between all methods, particularlywithNBSoverestimatingpre-termcasescomparedtoLMP.This suggests that while PS may align more closely with LMP in categorical classification, NBS exhibits poor validity, misclassifying a substantial number of cases, particularly by overestimating pre-term births.

 

Figure 15: Comparison of Categorical Gestational Age with respect to LastMenstrualPeriod(LMP),ParkinsScore(PS),andNewBallardScore (NBS) (n=197)

 

 

Table16:AccuracyofParkinsScoreinPredictingPre-TermGestational Age (<37 Weeks) with LMP as Standard

GA(LMP)	GA(ParkinsScore)
	<37Weeks	≥37Weeks
<37Weeks	49(TP)	21(FN)
≥37Weeks	8(FP)	119(TN)

 

 

 

Table17:AccuracyofNBSScoreinPredictingPre-TermGestational Age (<37 Weeks) with LMP as Standard

GA(LMP)	GA(NBS Score)
	<37Weeks	≥37Weeks
<37Weeks	64(TP)	6(FN)
≥37Weeks	42(FP)	85(TN)

Table 18: Comparison of Accuracy of Parkins and NBS Score for predicting Pre-Term Delivery with LMP as Gold Standard

Statistic	ParkinsScore	NBSScore
Sensitivity	70.00%	91.43%
Specificity	93.70%	66.93%
PositivePredictive Value	85.96%	60.38
NegativePredictive   Value	85.00%	93.41
Accuracy	85.28%	75.63

 

Table 18evaluates theaccuracyof PSand NBS in predictingpre-term GA (<37 weeks) using LMP as the gold standard. PS demonstrated higher sensitivity (70.00%) and specificity (93.70%) compared to NBS (91.43% sensitivity, 66.93% specificity). However, NBS's high sensitivity came at the cost of lower specificity, leading to more false positives. PS also outperformed NBS in positive predictive value (85.96% vs.60.38%)andoverall accuracy(85.28% vs. 75.63%). These results indicate that PS is a more reliable and valid tool for GA estimation, whereas NBS, despite its sensitivity, lacks precision and may overdiagnose pre-term cases.

 

Thefigure16 illustratesthecorrelationbetween GAfrom ParkinsScoreandGA from LMP using a scatter plot with a trend line. The data points are distributed around the trend line, indicatinga strongpositive correlation, as reflectedbythe Pearson correlation coefficient (r = 0.8219) with a 95% confidence interval (CI) of 0.7706 to 0.8626. The R squared value of 0.6755 suggests that approximately67.55%of the variance in GAParkins Score can beexplained by GA LMP. Additionally, the statistically significant p-value (less than 0.0001) reinforces the reliability of this correlation. This figure highlights the strong association between these two measures, which may be valuable for further research or clinical applications.

Figure16:CorrelationofGAfromParkinsScorewithGAfromLMP

 

Figure17:CorrelationofGAfromNBSScorewithGAfrom LMP

 

Pearsonr:0.7797;95%CI:0.0.7182to0.8291

 

Rsquared:0.6080, P(two-tailed):<0.0001

 

The Pearson correlation coefficient (r = 0.7797) with a 95% confidence interval (CI) of 0.7182 to 0.8291 suggests a significant relationship between the two variables. The R squared value of 0.6080 implies that approximately 60.80% of the variance in GA NBS Score can be explained by GA LMP. Additionally, the statistically significant p-value (less than 0.0001) reinforces the reliability of this correlation

 

Figure18:CorrelationofGAfromNBSScorewithGAfromParkinsScore

The present study evaluated clinical, radiological and peri-operative predictors of poor functional outcome in 53 patients undergoing ORIF for ankle fractures. At 6 months, 71.7% of patients had good functional outcome (OMAS ≥60), while 28.3% had poor outcome, and multivariate analysis identified age >50 years, BMI ≥28 kg/m², trimalleolar fractures, syndesmotic injury, delay to surgery ≥7 days and postoperative infection as independent predictors of poor function (Tables 5–8).These findings are consistent with contemporary literature that highlights both patient-related and injury-/treatment-related factors as key determinants of long-term recovery after ankle fractures.[7,9]

In our cohort, the mean age was 41.8 ± 13.6 years, with nearly three-quarters of patients below 50 years and a clear male predominance (64.2%).This pattern reflects the high exposure of middle-aged, working-age men to outdoor and high-risk activities. Court-Brown and Caesar similarly reported that ankle fractures are common in adults, with a large burden in the middle-aged population even though incidence rises further in the elderly.[14] The mean BMI of 27.4 kg/m² in our series indicates that most patients were overweight, and comorbidities such as diabetes (20.8%), hypertension (26.4%), smoking (32.1%) and alcohol use (28.3%) were frequent. These comorbidities and lifestyle factors have been repeatedly associated with poorer functional and patient-reported outcomes after ankle fractures in prognostic studies.[7,9]

Slip or fall was the most common mechanism of injury (54.7%), followed by road-traffic accidents (39.6%), indicating a mixture of low- and high-energy trauma typical for ankle fractures.Weber B (47.2%) and Weber C (41.5%) fractures predominated, and almost 80% of fractures were bi- or trimalleolar, with syndesmotic injury present in 35.8% and Grade I–II open fractures in 11.3%. This distribution mirrors other ORIF series, where unstable Weber B/C and multi-malleolar fractures form the majority of surgically treated injuries.[9,8] Syndesmotic disruption and complex fracture patterns (e.g. trimalleolar injuries) have consistently been linked with inferior long-term function and higher rates of complications and reoperation.[7,9]

Most patients (67.9%) underwent surgery within 7 days of injury, while 32.1% had delayed fixation (≥7 days). Fixation of the posterior malleolus was required in 22.6% and syndesmotic fixation in 35.8% (mainly screw fixation), reflecting adherence to current principles of stabilising the posterior tibial plafond and distal tibiofibular joint in unstable patterns. Intraoperative complications were rare (5.7%).

These figures are comparable with other prospective cohorts where careful soft-tissue assessment and standardised techniques minimise intraoperative adverse events.[7,8] Early weight-bearing (≤3 weeks) was initiated in 39.6% of patients, with the remainder progressing later, according to fracture stability and soft-tissue status. Superficial and deep wound infections occurred in 7.5% and 3.8% of cases, respectively, and malunion/malreduction was seen in 11.3%. The mean radiological union time was 13.4 ± 2.1 weeks.These rates are within the ranges reported in the literature, where infection after ankle ORIF typically occurs in 4–10% and malalignment in 5–15% of patients.[15,16]

Functional scors improved substantially over time. Mean OMAS increased from 52.4 ± 14.2 at 3 months to 71.6 ± 15.8 at 6 months, and AOFAS scores from 63.8 ± 11.5 to 78.4 ± 12.7 over the same period. At 6 months, 71.7% of patients achieved a good functional outcome (OMAS ≥60), whereas 28.3% were categorised as having poor outcome (OMAS <60).This pattern of meaningful improvement between 3 and 6 months is in line with other outcome studies that show continued recovery well into the first postoperative year.[7,9] Balaji et al. reported comparable mean OMAS and AOFAS scores at 6 months in their prospective cohort of surgically treated unstable ankle fractures, confirming that our overall functional results are broadly similar to other Indian and international experiences.[8]

When patients were stratified into good and poor outcome groups, those with poor outcome were significantly older (49.6 vs. 38.9 years) and had higher BMI (29.0 vs. 26.7 kg/m²). They also had a higher prevalence of diabetes (40% vs. 13.1%) and smoking (53.3% vs. 23.6%). These observations align with the findings of Audet et al., who reported that increased BMI, tobacco and alcohol use, and medical comorbidities were associated with worse patient-reported outcomes at mid-term follow-up after ankle fractures.[7] Lorente et al., in a recent systematic review, likewise concluded that advanced age, high BMI, diabetes and smoking are consistent predictors of poorer function and health-related quality of life.[9]

Complex fracture configurations were strongly associated with poor outcome in our series. Patients with poor outcome more frequently had Weber C fractures (66.7% vs. 31.6%) and trimalleolar fractures (60% vs. 21.1%), and syndesmotic injuries were also significantly more common (60% vs. 26.3%). Delayed surgery ≥7 days occurred in 60% of the poor outcome group compared with 21.1% of the good outcome group. These results corroborate earlier evidence that fracture complexity and syndesmotic disruption are important prognostic factors. Audet et al. found that more severe fracture patterns and fracture-dislocations were associated with lower functional scores.[7] Balaji et al. similarly showed that unstable patterns (often Weber C and bimalleolar/trimalleolar fractures) and less-than-optimal radiographic restoration were linked with poorer outcomes in their prospective cohort.[8] The negative impact of surgical delay on outcome in our study is also consistent with the wider literature. Studies emphasise timely fixation, once soft tissues permit, to reduce swelling-related complications and to facilitate accurate reduction; delays have been associated with higher infection rates and worse functional recovery.[8,15]

Postoperative infection and malreduction/malunion were markedly over-represented in the poor outcome group: any infection occurred in 26.7% vs. 5.2%, and malreduction/malunion in 26.7% vs. 5.2% of patients. Ovaska et al. showed that deep infection after internal fixation of ankle fractures can have catastrophic consequences, with diabetes, smoking, alcohol abuse and malreduction significantly increasing the risk of treatment failure and long-term disability.[15] Our findings echo this, underlining that meticulous soft-tissue handling, strict asepsis, precise reduction and early detection and management of complications are critical for preserving function.

On multivariate logistic regression, age >50 years, BMI ≥28 kg/m², trimalleolar fracture pattern, syndesmotic injury, delay to surgery ≥7 days and postoperative infection remained independent predictors of poor functional outcome at 6 months. This reinforces the concept that both non-modifiable (age, fracture complexity) and modifiable (timing of surgery, infection control) factors jointly shape prognosis. Our results are in agreement with Audet et al. and Lorente et al., who emphasise that patient-related risk factors must be considered alongside fracture severity and treatment quality when counselling patients and planning follow-up.[7,9] Balaji et al. also reported that careful attention to fracture reduction and optimisation of comorbidities can improve functional outcomes even in unstable patterns.[8]

From a clinical standpoint, elderly, overweight patients with trimalleolar fractures and syndesmotic disruption represent a high-risk group who should receive targeted counselling, more intensive rehabilitation and closer follow-up. Avoiding unnecessary delay to surgery, ensuring anatomical reduction (especially of the posterior malleolus and syndesmosis) and stringent prevention and management of postoperative infection are practical, modifiable strategies that may improve long-term functional outcomes in such patients.

In this study of 53 patients undergoing ORIF for ankle fractures, the majority (71.7%) achieved good functional outcomes by 6 months; however, nearly one-third continued to experience significant functional limitation. Poor outcomes were strongly associated with older age, higher BMI, diabetes, smoking, complex fracture patterns (particularly trimalleolar and Weber C injuries), syndesmotic disruption, delayed surgery and postoperative complications such as infection and malreduction. Multivariate analysis confirmed age >50 years, obesity, trimalleolar fractures, syndesmotic injury, surgical delay ≥7 days and postoperative infection as independent predictors of poor recovery. These findings highlight the importance of early surgical intervention, meticulous anatomical reduction, aggressive management of comorbidities and prevention of complications to optimise postoperative functional outcomes following ankle fracture fixation.

 

Acknowledgement: None

Conflict of Interest: None

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2.       de Ávila VR, Bento TP, Gomes W, Leitão J, de Sousa NF. Functional outcomes and quality of life after ankle fracture surgically treated: a systematic review. J Sport Rehabil. 2018;27(3):274-283.

3.       Swierstra BA, van Enst WA. The prognosis of ankle fractures: a systematic review. EFORT Open Rev. 2022;7(10):692-700.

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6.       Obremskey WT, et al. Rate of return of functional outcome after open reduction and internal fixation of ankle fractures. Orthopedics. 200?;38(5):227-233.

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8.       Balaji G, Bhukya S, Nema S, Rajeswari M, Vellaipandi V. Predictors of functional outcome in unstable ankle fractures treated surgically: a prospective cohort study. Malays Orthop J. 2021;15(1):85-92.

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10.    Cammas C, et al. Frequency and risk factors of complications after surgical treatment of ankle fractures. Acta Orthop Belg. 2020;86(3):433-442.

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