Document Type: Original Article
Senior Resident, Dayanand Medical College and Hospital, Ludhiana,Punjab,India
Professor & Head DMC &H, Ludhiana Punjab,India
Professor Department of Community Medicine Dayanand Medical College and Hospital Ludhiana, Punjab, India
Objective: To predict hospital stay by using various clinical parameters at admission.
Patients and Methods: This prospective observational study was conducted over a period of one year (Jan – Dec 2010) in a tertiary level teaching hospital in North India. Out of 344 neonates admitted, 41 left against medical advice and were excluded. At time of admission, initial vital signs were noted along with basic information. All neonates were assessed on the basis of clinical parameters and followed up to the discharge/death. Final outcome was noted in terms of total duration of hospital stay in survived and non survived neonates. In the statistical analysis, Odds ratio along with 95% confidence intervals was calculated for each parameter and significant associations (p value ≤ 0.05) were studied.
Results: Of 30 clinical variables, 18 were found to be significantly associated with prolonged hospitalization viz more than 7days in survived neonates. These include abnormal heart rate (>160/min or <100/min), abnormal respiratory rate (>60/min or <30/min), abnormal SpO2 (<90%), prolonged capillary filling time (≥3seconds), moderate hypothermia or hyperthermia, decreased consciousness level, abnormal quality of cry, reduced or no activity, presence of pallor, icterus involving soles, central cyanosis, dehydration, chest recessions, respiratory distress, abdominal distension, hypotonia and incomplete or absent Moro’s reflex in term neonates and absent or sluggish deep tendon reflexes. Similarly, three parameters were found to be significantly associated with death of non survived neonates within 7 days of hospital stay- abnormal respiratory rate (>60/min or <30/min), abnormal SpO2 (<90%), prolonged capillary filling time (≥3seconds).
Conclusion: Hospital stay of the neonate can be predicted at time of admission using these simple, easily assessed, promptly at bedside clinical parameters.