Literature DB >> 35195565

Relationship Between COVID-19 Lockdown and Epidemiology of Neonatal Sepsis.

Sourabh Dutta1, Praveen Kumar1, Rajarajan Paulpandian1, Shiv Sajan Saini1, Priya Sreenivasan2, Kanya Mukhopadhyay1, Venkataseshan Sundaram1, Jogender Kumar1, Pallab Ray2.   

Abstract

BACKGROUND: We compared the hospital-based epidemiology of neonatal sepsis after the coronavirus disease 2019 lockdown (LD) versus historical epochs and the LD period versus phases of unlocking.
METHODS: This retrospective cohort study was conducted in a level 3 neonatal unit. We compared neonates born in three 24-week periods-Group LD: 22 March 2020 to 5 September 2020-the reference group, Group pre-LD: 29 September 2019 to 14 March 2020 and Group temporally corresponding to LD in 2019 (corres-LD): 24 March 2019 to 7 September 2019. We also studied linear trends from LD phase 1.0 until Unlock 4.0. The key outcome was culture-positive sepsis.
RESULTS: There were 1622, 2744 and 2700 subjects in groups LD, pre-LD and corres-LD, respectively. The incidence of any culture-positive sepsis in pre-LD was higher than LD [odds ratio (95% CI) = 1.61 (1.02-2.56)]. This was mainly due to a statistically significant reduction in Acinetobacter baumannii sepsis, with incidence rate differences of pre-LD versus LD [0.67 (95% CI: 0.37-0.97), P = 0.0001] and corres-LD versus LD [0.40 (95% CI: 0.16-0.64), P = 0.0024]. Groups pre-LD and corres-LD had higher proportion of multi-drug resistant (MDR)/extreme drug resistance/pan drug resistance sepsis than LD [77%, 77% and 44%, respectively (P values of both groups vs. LD = 0.01)]. From LD 1.0 to unlock 4.0, there were fewer episodes of MDR sepsis (Plinear trends = 0.047). On multivariable analysis, group pre-LD (vs. reference group LD), male sex, birth weight and Apgar score independently predicted culture-positive sepsis.
CONCLUSIONS: LD favorably impacted the epidemiology of neonatal sepsis in a hospital setting, with less A. baumannii and MDR sepsis, which persisted during unlocking.
Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.

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Year:  2022        PMID: 35195565      PMCID: PMC9083315          DOI: 10.1097/INF.0000000000003489

Source DB:  PubMed          Journal:  Pediatr Infect Dis J        ISSN: 0891-3668            Impact factor:   3.806


The coronavirus disease 2019 (COVID-19) pandemic has directly afflicted millions globally.[1] The pandemic has also caused collateral damage from other diseases.[2-4] A recent meta-analysis identified increased stillbirths, maternal deaths and postnatal depression during the pandemic.[5] Conversely, COVID-19–related restrictions have decreased the incidence of several non–COVID-19 viral diseases.[6-11] Respiratory viral infections decreased after the pandemic, despite more testing for viral illnesses.[12] To date, there are no reports regarding the effect of the COVID-19 pandemic on the changing epidemiology of neonatal sepsis. Ours is a level III Neonatology Unit in a public-sector university hospital in northwest India. We deliver >6000 liveborn infants annually, of which ≈40% are preterm and ≈35% small for gestational age. Like other busy public-sector units in developing countries, neonatal sepsis is a major problem. 2%–3% of neonates in our unit develop culture-positive sepsis (unpublished 5-year unit data). Etiologic organisms include Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae and coagulase-negative Staphylococcus, in that order. Multi-drug resistant (MDR) sepsis is common, like other parts of South Asia.[13] In the absence of regionalized care, our center is overburdened with sick neonates. We have a 16-bedded neonatal intensive care unit (NICU) and a 24-bedded high dependency unit (HDU). We are often unable to immediately transfer neonates requiring NICU or HDU care to the respective facilities, owing to nonavailability of vacant beds, nor can we transfer out such patients. Consequently, we manage several neonates in the labor room stabilization unit- an interim high-dependency nursery- until such time that a transfer to the NICU or HDU is feasible. A surge in the delivery rate is a surrogate for overcrowding, and we have earlier anecdotally observed an increase in sepsis rates with overcrowding. The government of India announced a public curfew on March 22, 2020, severe restrictions on March 23–24 and a stringent lockdown (LD) starting from March 25, 2020. The LD was extended until May 31, followed by unlocking in 1-month phases, during which restrictive measures were eased. As expected, there were fewer neonates delivered in our center from March 22, 2020 onwards. A few months into the pandemic, we observed a decrease in episodes of culture-positive sepsis. In the absence of formal analysis of data, we were unsure about the validity of this observation and whether it was a consequence of fewer admissions, behavioral changes, administrative measures or a combination thereof. Improvements in the pattern of neonatal sepsis may hold useful lessons for a future non-pandemic situation. Hence, we studied neonates delivered in 3 time periods, each lasting 6 months—the first starting with the LD in 2020, the second immediately prior to the LD and the third in 2019, temporally identical to the LD. We investigated trends across the phases of locking and unlocking. We hypothesized that the LD was associated with a lower incidence of neonatal sepsis, especially MDR sepsis and that unlocking was associated with a partial reversal of the same.

METHODS

We conducted a retrospective cohort study on neonates delivered in our hospital in three 24-week periods (see Figure, Supplemental Digital Content 1, http://links.lww.com/INF/E680): Group LD: 22 March 2020 to 5 September 2020. Group pre-LD: prior to the LD: 29 September 2019 to 14 March 2020. Group temporally corresponding to LD in 2019 (corres-LD): 24 March 2019 to 7 September 2019. Group LD was the reference group. We included Group corres-LD to control for the possible impact of seasonal variations on demographics and sepsis. To study the effect of stringency of measures, we included all liveborn infants delivered from 22 March 2020 to 30 September 2020 (see Figure, Supplemental Digital Content 1; http://links.lww.com/INF/E680). A composite objective measure of restrictions is the Government Stringency Index, ranging from 0 to 100, with 100 representing maximum stringency.[14] This part of the study included the following phases: The time period of LD/unlocking was almost identical to Group LD, except that the former extended to 30 September 2020, whereas the latter ended on 5 September 2020. Detailed descriptions of the containment measures can be accessed elsewhere.[15] We recorded demographic data, admission to the NICU and/or HDU, duration of hospital stay, the final outcome and sepsis data during hospital stay. Antibiotic resistance was defined as “no MDR,” MDR, extreme drug resistance (XDR) and pan drug resistance (PDR).[16] In Group LD, we performed a COVID-19 GeneXpert test in all laboring mothers and isolated the neonates from their mothers and other neonates until the mother was reported negative. We recorded the number of neonates thus isolated, and the number of neonates and mothers whose test was positive. We used χ2 test, Fisher exact test, Mann-Whitney U or Student t test as appropriate. We calculated incidence rate ratios of episodes of culture-positive, A. baumannii and antibiotic-resistant sepsis. We compared the phases of LD/unlocking by tests for linear trends [χ2 for linear trends, Jonkheere-Terpstra or Analysis of Variance for trends, as appropriate] and without linear trends (χ2, Kruskal-Wallis test or Analysis of Variance, as appropriate). We performed a multivariable logistic regression to predict “any episode of culture-positive sepsis,” with the following predictors selected a priori: Groups (Group LD: reference group), number of live births in the week that the subject was born (as a surrogate for overcrowding), sex, gestational age in weeks, birth weight in grams, 5-minute Apgar score and appropriateness for gestation. We tested for multi-collinearity using variance inflation factor and Eigenvalues. We included a constant and forced all variables into the model. We used SPSS v23 and Stata v14.2 for statistical analysis. As recruitment was based on time periods, we did not perform a formal sample size calculation.

RESULTS

There were 1622, 2744 and 2700 inborn neonates in groups LD, pre-LD and corres-LD, respectively (Table 1). Fewer neonates in group pre-LD and corres-LD were admitted in the NICU and HDU and at significantly higher postnatal ages. Neonates with gestational age <32 weeks in group pre-LD and corres-LD had shorter hospital stay. Compared with group LD, a significantly lower proportion in group pre-LD was discharged home alive.
TABLE 1.

Comparison of Demographic, Admission, and Discharge Data Between 3 Groups

VariableLD Period: Group “LD”(N = 1622)Immediate Previous Period: Group “Pre-LD”(N = 2744)Corresponding Period In 2019: Group “Corres-LD”(N = 2700)P Value: Group “LD” vs. “Pre-LD” (Reference Group = “LD”)P Value: Group “LD” vs. “corres-LD” (Reference Group = “LD”)
Gestational age, weeks
Median (1st, 3rd quartile)37.0 (34.0, 38.0)37.0 (35.0, 38.0)37.0 (34.0, 38.0)0.10.022
Mean (SD)35.77 (3.2)35.90 (3.1)35.92 (3.1)
Gestation categories*0.20.049
 Extremely preterm (<28 weeks)44 (2.7)68 (2.5)65 (2.4)
 Very preterm (28–<32 weeks)125 (7.7)220 (8.0)230 (8.5)
 Moderate to late preterm  (32–<37 weeks)574 (35.4)880 (32.1)844 (31.3)
 Term (37–41 weeks)877 (54.1)1572 (57.3)1554 (57.6)
 Post-term (>41 weeks)2 (0.1)4 (0.1)7 (0.3)
Birth weight, grams, median  (1st, 3rd quartile)2480.0 (1896.75, 2874.25)2470.0 (1915.0, 2862.0)2480.0 (1900.0, 2890.0)0.90.9
Birth weight categories*
 <1000 g59 (3.6)129 (4.7)123 (4.6)0.30.5
 1000–1499 g154 (9.5)236 (8.6)277 (10.3)
 1500–2499 g599 (36.9)1051 (38.3)979 (36.3)
 2500–4200 g809 (49.9)1324 (48.3)1318 (48.8)
 >4200 g1 (0.1)4 (0.1)3 (0.1)
Sex*
 Male883 (54.4)1418 (54.0)1426 (52.8)0.90.5
 Female737 (45.4)1259 (45.9)1268 (47.0)
 Ambiguous2 (0.1)4 (0.1)6 (0.2)
Appropriateness for gestational age*
 AGA999 (64.5)1713 (63.3)1670 (61.9)0.30.2
 SGA513 (33.1)944 (34.9)971 (36.0)
 LGA37 (2.4)50 (1.8)57 (2.1)
Apgar score at 5 min
Median (1st, 3rd quartile)7 (5, 8)7 (6, 8)7 (6, 8)<0.001<0.001
Mean (SD)7.42 (1.6)7.29 (1.6)7.23 (1.5)
Admitted in NICU*177 (10.9)184 (6.7)213 (7.9)<0.001 [OR, 0.59 (95% CI: 0.47–0.73,)]0.001 [OR, 0.70 (95% CI: 0.57–0.86)]
Admitted in HDU*297 (18.3)313 (11.4)265 (9.8)<0.001 [OR, 0.57 (95% CI: 0.48–0.68)]<0.001 [OR, 0.49 (95% CI: 0.41–0.58)]
Age transferred to NICU, d, median  (1st, 3rd quartile)2 (1, 3)3 (2, 5)3 (2, 5)<0.001<0.001
Age transferred to HDU, d, median  (1st, 3rd quartile)7 (4, 13)8 (5, 14)10 (5, 17)0.003<0.001
Duration of hospital stay among <32  weeks gestation, d, median (1st, 3rd quartile)20 (4, 39)10 (2, 30)12 (3, 29)0.0010.005
Final outcomeN = 1622N = 2744N = 2694
 Discharged home1553 (95.7)2583 (94.1)2541 (94.3)0.0280.13
 Died67 (4.1)145 (5.3)142 (5.3)
 LAMA or DOR1 (0.1)2 (0.1)4 (0.1)
 Transferred elsewhere1 (0.1)14 (0.5)7 (0.3)

Figures in brackets are percentages of the total subjects in the respective period.

AGA indicates appropriate for gestational age; DOR, discharged on request; LAMA, left against medical advice; LGA, large for gestational age; OR, odds ratio; SGA, small for gestational age.

Comparison of Demographic, Admission, and Discharge Data Between 3 Groups Figures in brackets are percentages of the total subjects in the respective period. AGA indicates appropriate for gestational age; DOR, discharged on request; LAMA, left against medical advice; LGA, large for gestational age; OR, odds ratio; SGA, small for gestational age. Group pre-LD had a significantly higher proportion of neonates with any episode of culture-positive sepsis compared with group LD [odds ratio = 1.61 (95% CI: 1.02–2.56)], but not so in the case of corres-LD (Table 2). Group pre-LD had a significantly higher incidence rate ratio (IRR) of culture-positive sepsis compared with group LD [1.77 (95% CI: 1.13–2.85)], but not when corres-LD was compared with group LD. There were significant differences in etiologic organisms between the groups. Of note, there were no episodes of A. baumannii sepsis in Group LD, whereas there were 19 (24%) and 11 (20.7%) episodes in groups pre-LD and corres-LD, respectively. The IRR of A. baumannii sepsis in group pre-LD or corres-LD versus LD could not be calculated as the denominator was zero. Hence the incidence rate differences were calculated which were statistically significantly different for pre-LD versus LD [0.67 (95% CI: 0.37–0.97)] and corres-LD versus LD [0.40 (95% CI: 0.16–0.64)].
TABLE 2.

Comparison of Sepsis-Related Data Between 3 Groups

VariableLD Period: Group “LD”(N = 1622)Immediate Previous Period: Group “Pre-LD”(N = 2744)Corresponding Period in 2019: Group “Corres-LD”(N = 2700)P Value: Group “LD” vs. “Pre-LD” (Reference Group = “LD”)P Value: Group “LD” vs. “Corres-LD” (Reference Group = “LD”)
Number of patients with any episode  of culture-positive sepsis25 (1.5)68 (2.5)51 (1.9)0.038 [OR, 1.61 (95% CI: 1.02–2.56)]0.4 [OR, 1.23 (95% CI: 0.76–2.00)]
Number of episodes of culture-positive sepsis*N = 25N = 68N = 51
 1 episode23 (92)59 (86.8)49 (96.1)0.60.4
 2 episodes2 (8)7 (10.3)2 (3.9)
 3 episodes0 (0)2 (2.9)0 (0)
Total number of episodes of culture-positive  sepsis277953
Cumulative duration of hospital stay, person-days17,21028,38727,432
Incidence rate of culture-positive sepsis  (episodes/1000 patient-days)1.572.781.930.004 [IRR, 1.77 (95% CI: 1.13–2.85)]0.19 [IRR, 1.23 (95% CI: 0.76–2.04)]
Number of episodes with specific organismsN = 27N = 79N = 53
 E. coli 4 (14.8)11 (13.9)9 (16.9)0.030.049
 K. pneumoniae 3 (11.1)3 (3.8)4 (7.5)
 A. baumannii 0 (0)19 (24.0)11 (20.7)
 S. aureus 0 (0)5 (6.3)0 (0)
 S. epidermidis 4 (14.8)15 (18.9)14 (26.4)
 Other CONS7 (25.9)16 (20.2)8 (15.1)
 E fecalis/fecium 1 (3.7)1 (1.3)0 (0)
 Miscellaneous8 (29.6)9 (11.4)7 (13.2)
Incidence rate of A baumannii sepsis  (episodes/1000 patient-days)00.670.40.0001 [IR difference, 0.67 (95% CI: 0.37–0.97)]0.0024 [IR difference, 0.40 (95% CI: 0.16–0.64)]
Incidence rate of non-A baumannii sepsis  (episodes/1000 patient-days)1.572.111.530.09 [IRR, 1.35 (95% CI: 0.84–2.21)]0.46 [IRR, 0.98 (95% CI: 0.59–1.65)]
Antibiotic resistance among total number  of episodes of sepsisN = 27N = 79N = 53
 Not MDR or worse15 (55.5)18 (22.8)12 (22.6)0.010.01
 MDR9 (33.3)35 (44.3)31 (58.5)
 XDR3 (11.1)25 (31.6)10 (18.9)
 PDR0 (0)1 (1.3)0 (0)
Incidence rate of MDR or worse (episodes/1000  patient-days)0.72.11.5<0.001 [IRR, 3.08 (95% CI: 1.64, 6.29)]0.007 [IRR, 2.14 (95% CI: 1.11, 4.48)]
Number of episodes of MDR or worse  A. baumannii sepsis018100.0070.02
(0)(22.8)(18.9)
(94.7)(90.1)
Number of episodes of MDR or worse  non–A. baumannii sepsis12 (44.4)43 (54.4)31 (58.5)0.370.23
Any culture-positive episode treated  with meropenem*19 (76.0)59 (86.8)44 (86.3)0.2 [OR, 1.23 (95% CI: 0.47–3.23)]0.3 [OR, 2.04 (95% CI: 0.69–6.25)]
Any culture-positive episode treated  with colistin*5 (20.0)32 (47.1)19 (37.3)0.018 [OR, 3.03 (95% CI: 1.03–8.33)]0.13 [OR, 2.44 (95% CI: 0.80–7.69)]
Patient care area where episodes of sepsis  occurredN = 27N = 79N = 53
 Labor room stabilization3 (11.1)27 (34.2)18 (33.9)0.020.003
 NICU17 (62.9)45 (56.9)33 (62.3)
 HDU7 (25.9)7 (8.8)2 (3.8)
Age 1st episode of sepsis, d, median  (1st, 3rd quartile)5 (3, 13.5)5 (3, 8)6 (3, 9)0.70.7
1st episode of sepsis categorized by time of onset*
 EONS11 (44.0)25 (36.8)13 (25.5)0.5 [OR for LONS = 1.35 (95% CI: 0.53–3.43)]0.1 [OR for LONS = 2.30 (95% CI: 0.84–6.31)]
 LONS14 (56.0)43 (63.2)38 (74.5)

Percent expressed of number of patients with any episode of culture-positive sepsis.

Percent expressed of total number of episodes of culture-positive sepsis.

Percent expressed of all episodes of A. baumannii sepsis.

CONS indicates coagulase-negative Staphylococcus; EONS, early-onset neonatal sepsis; IR, incidence rate; IRR, IR ratio; LONS, late-onset neonatal sepsis; OR, odds ratio.

Comparison of Sepsis-Related Data Between 3 Groups Percent expressed of number of patients with any episode of culture-positive sepsis. Percent expressed of total number of episodes of culture-positive sepsis. Percent expressed of all episodes of A. baumannii sepsis. CONS indicates coagulase-negative Staphylococcus; EONS, early-onset neonatal sepsis; IR, incidence rate; IRR, IR ratio; LONS, late-onset neonatal sepsis; OR, odds ratio. There were significantly more episodes caused by MDR/XDR/PDR organisms in group pre-LD and corres-LD compared with LD. The IRR of episodes caused by organisms that were MDR or worse when comparing group pre-LD versus LD [3.08 (95% CI: 1.64–6.29)] and group corres-LD versus LD [2.14 (95% CI: 1.11–4.48)] were statistically significant. Significantly more culture-positive episodes were treated with colistin in group pre-LD compared with group LD. Almost all isolates of A. baumannii were MDR/XDR/PDR. The difference in MDR/XDR/PDR organisms between the phases was primarily driven by the difference in A baumannii. There were no significant differences in the proportion of non–A. baumannii MDR organisms (as a percentage of all sepsis) between LD, pre-LD and corres-LD. In group LD, 425 neonates were briefly isolated from their mothers and other neonates until their mothers’ COVID-19 report was available. One-hundred-eight severe acute respiratory syndrome coronavirus-2–positive mothers were isolated from other patients in a dedicated COVID building along with their neonates. Eight of these neonates were detected to be severe acute respiratory syndrome coronavirus-2 positive. When comparing the phases of LD and unlocking, there were significant differences in gestational age and birth weight across phases, but no significant linear trends (Table 3). The proportion of subjects with any episode of culture-positive sepsis declined from LD phase 1.0 to unlock phase 4.0 but was not statistically significant. The difference in the proportion of etiologic organisms did not show a linear trend. There were progressively fewer episodes of MDR sepsis (Plinear trend = 0.047).
TABLE 3.

Comparison of the Phases of Lockdown and Unlocking

VariablesLockdown Phases 1 and 2 (N = 387)Lockdown Phase 3 and 4 (N = 252)Unlock Phase 1 (N = 310)Unlock Phase 2 (N = 339)Unlock Phase 3 (N = 296)Unlock Phase 4 (N = 266)P Value of Linear Trends*P Value Without Linear Trends
Number of live births  per day, mean (SD)8.9 (2.8)9.0 (3.2)10.3 (3.2)10.9 (4.3)9.6 (3.3)8.8 (3.0)0.70.067
Gestational age, weeks,  median (1st, 3rd quartile)37 (35, 38)37 (34, 38)36 (34, 38)36 (34, 38)37 (34, 38)37 (34, 38)0.60.028
Gestation categories
 Extremely preterm  (<28 weeks)8 (2.1)10 (4.0)10 (3.2)8 (2.4)7 (2.4)7 (2.7)0.30.059
 Very preterm  (28–<32 weeks)17 (4.4)22 (8.7)28 (9.0)31 (9.1)23 (7.8)26 (10.0)
 Moderate to late  preterm§130 (33.8)82 (32.5)120 (38.7)128 (37.8)104 (35.1)76 (29.1)
 Term (37–41 weeks)230 (59.7)138 (54.8)152 (49.0)170 (50.1)162 (54.7)152 (58.2)
 Post-term (>41 weeks)0002 (0.6)00
Birth weight, grams,  median (1st, 3rd quartile)2521250023252523251224440.70.008
(1975, 2897.5)(1862.25, 2930)(1748, 2721.5)(1910, 2878)(1907, 2918)(1900.75, 2878)
Birth weight categories
 <1000 g10 (2.6)12 (4.8)13 (4.2)14 (4.1)9 (3.0)12 (4.6)0.30.056
 1000–1499 g22 (5.7)31 (12.3)37 (11.9)32 (9.4)26 (8.8)27 (10.3)
 1500–2499 g153 (39.7)79 (31.3)133 (42.9)114 (33.6)106 (35.8)99 (37.9)
 2500–4200 g199 (51.7)130 (51.6)127 (41.0)179 (52.8)155 (52.4)123 (47.1)
 >4200 g1 (0.3)00000
Sex
 Male213 (55.5)141 (56.0)178 (57.4)178 (52.5)151 (51.0)149 (56.0)0.70.4
 Female174 (45.0)111 (44.0)132 (42.6)159 (46.9)145 (49.0)116 (43.6)
 Ambiguous0 (0)0 (0)0 (0)2 (0.6)0 (0)1 (0.4)
Appropriateness for gestation
 AGA221 (61.2)169 (68.1)185 (63.4)210 (64.8)194 (67.6)157 (60.6)0.90.4
 SGA130 (36.0)77 (31.0)99 (33.9)107 (33.0)84 (29.3)97 (37.5)
 LGA10 (2.8)2 (0.8)8 (2.7)7 (2.2)9 (3.1)5 (1.9)
Apgar score at 5 min8 (7, 8)8 (7, 8)8 (7, 9)8 (7, 8)8 (7, 9)8 (7, 8)0.040.02
Admitted in NICU36 (9.3)26 (10.3)37 (11.9)39 (11.5)34 (11.5)13 (11.3)0.30.9
Admitted in HDU80 (20.7)50 (19.8)54 (17.4)46 (13.6)62 (20.9)24 (9.0)0.002<0.001
Age transferred to NICU,  d, median (1st, 3rd quartile)2 (2, 2.75)2 (1, 2.25)2 (1.5, 3)2 (1, 3)3 (1, 5)2 (1, 4.25)0.130.4
Age transferred to HDU,  d, median (1st, 3rd quartile)4 (2, 8)7 (3, 15)9 (5, 12.25)8 (5, 13)7 (4, 15.25)5.5 (2.25, 10)0.0180.001
Any episode of culture- positive sepsis8 (2.1)4 (1.6)3 (1.0)6 (1.8)4 (1.4)3 (1.1)0.40.9
Total number of episodes  with specific organismsN = 9N = 4N = 4N = 6N = 4N = 5
 E. coli 1120010.10.04
 K. pneumoniae 000120
 A. baumannii 000002
 P. aeruginosa 000110
 S. epidermidis 200200
 Other CONS231101
 E fecalis/fecium 200000
 Miscellaneous201111
Antibiotic resistance  among total number of episodes of sepsisN = 9N = 4N = 4N = 6N = 4N = 5
 Not MDR or worse2333410.0470.9
 MDR411301
 XDR300003
Culture-positive  episode treated with meropenem5 (62.5)3 (75)3 (100)4 (66.7)4 (100)3 (100)0.10.5
Culture-positive episode  treated with colistin1 (12.5)0 (0)2 (66.7)2 (33.3)0 (0)1 (33.3)0.50.2
Outcome
 Discharged home370 (95.6)241 (95.6)297 (95.8)323 (95.3)285 (96.3)252 (94.7)0.60.7
 Died17 (4.4)10 (4.0)13 (4.2)15 (4.4)11 (3.7)13 (4.9)
 LAMA or DOR0 (0)1 (0.4)0 (0)0 (0)0 (0)0 (0)
 Transferred elsewhere0 (0)0 (0)0 (0)1 (0.3)0 (0)1 (0.4)
Duration hospital stay,  d, median (1st, 3rd quartile)4 (3, 7)5 (3, 7)5 (4, 7)4 (4, 7)4 (3, 8)4 (3, 7)0.070.018
Duration of hospital stay  among <32 weeks gestation, d, median (1st, 3rd quartile)29 (10.5, 54.5)18.5 (5, 41)17.5 (2.75, 31.5)20 (4, 29)22 (3, 39)29 (8, 57)0.10.8

2 test for linear trends of outcome categorical variables. Jonckheere-Terpstra test for linear trends of outcome numerical variables.

2 test for outcome categorical variables. Kruskal-Wallis test for outcome numerical variables.

Percent expressed of total number in respective lockdown/unlock phase.

32–<37 weeks.

Percent expressed out of total number of culture-positive episodes in respective lockdown/unlock phase.

AGA indicates appropriate for gestational age; CONS, coagulase-negative Staphylococcus; DOR, discharged on request; LAMA, left against medical advice; LGA, large for gestational age; SGA, small for gestational age.

Comparison of the Phases of Lockdown and Unlocking 2 test for linear trends of outcome categorical variables. Jonckheere-Terpstra test for linear trends of outcome numerical variables. 2 test for outcome categorical variables. Kruskal-Wallis test for outcome numerical variables. Percent expressed of total number in respective lockdown/unlock phase. 32–<37 weeks. Percent expressed out of total number of culture-positive episodes in respective lockdown/unlock phase. AGA indicates appropriate for gestational age; CONS, coagulase-negative Staphylococcus; DOR, discharged on request; LAMA, left against medical advice; LGA, large for gestational age; SGA, small for gestational age. The candidate predictors in the multivariable analysis did not show multi-collinearity, hence all were included in the model. The Group (ie, LD, pre-LD and corres-LD), male sex, birth weight and Apgar score independently predicted the occurrence of any episode of culture-positive sepsis (Table 4). The prediction accuracy was 97.9% (assuming cases with >50% predicted probability were true sepsis) and the C-statistic was 0.85 (95% CI: 0.81–0.89).
TABLE 4.

Multivariable Logistic Regression Model to Predict Patients With Any Episode of Culture-Positive Sepsis

VariableRegression CoefficientaOR95% CI of aORP value
Constant−2.25
Time period0.053
 LD (reference group)
 Pre-LD0.812.241.11–4.510.024
 Corres-LD0.511.670.83–3.350.15
Births in the week subject was born−0.0070.990.98–1.0040.2
Male sex0.812.261.55–3.29<0.001
Gestational age−0.050.950.48–1.080.5
Birth weight−0.0020.9980.997–0.999<0.001
Apgar score at 5 min0.531.691.46–1.96<0.001
Appropriateness for gestation0.2
 AGA (reference group)
 SGA−0.40.670.39–1.160.15
 LGA0.922.50.64–9.730.19

AGA indicates appropriate for gestational age; aOR, adjusted odds ratio; LGA, large for gestational age; SGA, small for gestational age.

Multivariable Logistic Regression Model to Predict Patients With Any Episode of Culture-Positive Sepsis AGA indicates appropriate for gestational age; aOR, adjusted odds ratio; LGA, large for gestational age; SGA, small for gestational age. To better understand A. baumannii, which had disappeared in group LD, we pooled data of the first episode of Gram-negative sepsis from groups pre-LD and corres-LD and compared A. baumannii versus other Gram-negative sepsis (see Table, Supplementary Digital Content 2, http://links.lww.com/INF/E681). On univariable analysis, A baumannii sepsis was associated with male sex, lower gestational age, lower birth weight and more concurrent births in the week the subject was born. In a multivariable logistic regression analysis to predict A baumannii sepsis among all cases with Gram-negative sepsis in the full study population (see Table, Supplementary Digital Content 3, http://links.lww.com/INF/E682), the only independent predictor was the number of concurrent births.

DISCUSSION

The number of live births in group LD was only 60% of the numbers in group pre-LD and corres-LD. The reduced number of live births in group LD was probably due to difficulties encountered by patients in traveling to our hospital during the LD and the fear of contracting COVID-19 at our hospital. Many mothers may have preferred to deliver in a hospital closer to home. Neonates in group LD had better Apgar scores and were discharged with better outcomes. Greater proportions in group LD were admitted in the NICU and HDU, and at a younger postnatal age. There was an overall reduction in culture-proven sepsis following the LD primarily driven by a striking reduction in A. baumannii sepsis and sepsis due to MDR/XDR/PDR organisms. This led to lower usage of colistin. Patients in the pre-LD group (compared with group LD), male sex, lower birth weight and Apgar score were independent predictors of any episode of culture-positive sepsis. It was reassuring to find that there was no increase in the incidence of culture-proven sepsis with progressive unlocking. There were no clinically meaningful differences in the average gestation between the three groups, although there was a statistically significant difference between LD and corres-LD. Our observation is contrary to previous reports, where the incidence of preterm births has declined during the pandemic.[5,17] More neonates were admitted to the NICU and HDU after the LD possibly because the decrease in absolute number of live births made it easier to find a vacant bed in our NICU or HDU. The lower postnatal age of transfer to these areas supports the latter possibility. Similarly, the relatively longer hospital stay in the LD group can be attributed to the greater availability of vacant beds and hence less pressure on the physicians to discharge patients before schedule from the hospital. The decrease in hospital deliveries coupled with an increase in the need for NICU/HDU care has not been reported before. However, a 57% decrease in children’s emergency visits has been documented during the peak of the pandemic.[18-21] Like us, Goldman et al found that the acuity of sickness and admission rate among children was higher during the peak compared with preceding epochs. In a recent meta-analysis, Chmielewska et al did not observe significant differences in the mode of delivery, births <32 weeks gestation, perinatal asphyxia, low-birth-weight status, NICU admissions or neonatal deaths between the pandemic and pre-pandemic periods.[5] The incidence of preterm births <37 weeks gestation was significantly lower only among high-income countries. This meta-analysis did not evaluate neonatal sepsis. The improvement in the epidemiology of neonatal sepsis in our study may be partly explained by earlier transfer of neonates to the NICU and HDU than what was possible prior to the LD. This is reflected in fewer episodes of sepsis in the labor room stabilization unit. The changes can also be attributed to behavioral factors. Unfortunately, we do not have data that can quantify these behavioral changes, so our observations are necessarily anecdotal and subjective. Prior to the LD, healthcare workers (HCW) and family members were expected to wash hands at entry to all patient care areas and HCWs were expected to follow hand hygiene measures at the 5 moments of hand hygiene prescribed by the World Health Organization but wearing a face mask was not mandatory. During the LD, compliance to hand hygiene measures increased substantially and there was universal usage of face masks by HCWs and family members. Before the LD, housekeeping measures included regular disinfection of equipment and surfaces, but during the LD these were followed more assiduously, with disinfection of high-contact surfaces such as door handles, telephones, etc. performed at least twice in every nursing shift. Instructions for disinfection of mobile phones were provided to all HCWs. Patients were distributed across more areas because those awaiting COVID reports were isolated in a separate 12-bedded isolation ward for mothers and a 6-bedded isolation ward for neonates, and proven cases were managed in a separate building. HCWs working in the isolation wards with suspected or proven cases of COVID-19 donned N-95 masks, caps, goggles, impervious gowns, shoe covers and gloves. There were no changes in the water sources or frequency of surveillance cultures for MDR organisms in the unit. Academic activities and meetings went online, and HCWs practiced social distancing. A. baumannii is an important cause of neonatal sepsis in developing countries.[22] The decrease in A. baumannii sepsis disproportionate to other Gram-negative sepsis in group LD is puzzling. The only independent risk factor we could identify was less overcrowding (see Table, Supplemental Digital Content 4, http://links.lww.com/INF/E683), but it is unclear why it should preferentially impact one species. A. baumannii is known to behave differently than other Gram-negative bacteria, characterized by more rapid acquisition of MDR, and resistance to desiccation and disinfectants.[23] Compared with E. coli or Klebsiella, neonates with A. baumannii sepsis have lower birth weight.[24] It is possible that infection control measures may have differential effects on A. baumannii sepsis and other Gram-negative sepsis. In a systematic review and network meta-analysis of 42 studies on adult ICU patients, compared with standard treatment alone, the addition of environmental cleaning to standard treatment plus antibiotic stewardship program or the addition of source control to standard treatment and environmental cleaning significantly reduced MDR A. baumannii sepsis.[25] On the other hand, infection control strategies that mandatorily included antibiotic stewardship programs significantly reduced sepsis due to MDR extended-spectrum beta-lactamase producing Gram-negative infections. In a study from China, the authors reported the effect of relocation of the NICU and introduction of a care bundle for prevention of ventilator-acquired pneumonia (VAP).[26] The incidence of VAP due to A. baumannii decreased from 79% to 36%, whereas VAP due to K. pneumoniae increased from 17% to 18%. Infection control measures rapidly control outbreaks of A. baumannii in neonatal units.[27,28] Our study was not specifically designed to evaluate the effect of infection control measures on the decline of MDR sepsis or organism-wise sepsis and we were unable to quantify the infection control measures. Although augmentation in infection control measures was an important feature of the LD epoch, apart from infection control measures there were several other differences between the 3 epochs. Authors of a study on older patients in the United Kingdom reported differential effects of the pandemic on etiologic organisms: Enterobacteriaceae reached an all-time low and coagulase-negative Staphylococcus an all-time high.[29] The absolute decline in MDR sepsis was not merely a consequence of overall decline in sepsis, as MDR sepsis as a proportion of all sepsis declined significantly in group LD. Our data shows that the decrease in MDR sepsis was driven by the decline in A. baumannii, which is frequently multi-drug resistant. As early-onset neonatal sepsis is attributed to maternal risk factors that are unlikely to be altered by the pandemic, and late-onset neonatal sepsis is environmentally acquired, we expected to see a greater proportion of early-onset neonatal sepsis in group LD. We observed this difference, but it was not statistically significant. It was interesting to note that there were no major differences from LD 1.0 to unlock 4.0. This could be due to the small sample sizes in each phase. The easing of restrictions may have had little impact on hospital functioning. It did not alter important predictors of sepsis, for example, gestational age, birth weight and appropriateness for gestational age. A closer look at the government stringency index shows that there was very little objective decline in the stringency of restrictions during the various phases of unlocking. We do not have data to quantify any change in behavior or infection control measures during the phases of unlocking. In the multivariable analysis, Group pre-LD independently doubled the odds of an episode of culture-positive sepsis compared with group LD. Our analysis suggests that the overall changes after the LD were associated with less culture-positive sepsis rather than overcrowding specifically around the time of birth. Groups LD and corres-LD covered virtually identical dates exactly a year apart whereas group pre-LD covered a different time of the year. Since the differences in most outcomes were larger between groups LD and pre-LD compared with groups LD and corres-LD, it suggests that seasonal differences may have accentuated the differences between Groups LD and pre-LD. We studied the incidence of sepsis, particularly A. baumannii sepsis, for 4 years prior to 2019, to evaluate the possibility that a downward sloping trend may have exaggerated the effect of the LD. However, no such trend could be observed from the year 2015 through 2018 (see Table, Supplemental Digital Content 4, http://links.lww.com/INF/E683). The strengths of our study were a large sample size and two comparison groups. Being retrospective, it was prone to several biases. There may have been unmeasured differences in patient characteristics, clinical practices, and rigor of data collection between the time periods. We limited our observation to hospital stay and may have missed cases of sepsis after transfer or discharge. Our results may not be generalizable to centers with fewer resource constraints, and less MDR sepsis. Weekly births are a sub-optimal surrogate for overcrowding. We were unable to quantify behavioral changes and infection control measures following the LD and during unlocking. We do not have data about the harm caused to neonates whose mothers were not able to reach our center due to the pandemic. Improvement in sepsis parameters may have occurred at the expense of worse outcomes among those who delivered elsewhere.

CONCLUSIONS

From the limited experience accrued from our center, we conclude that the LD may be associated with a decrease in culture-proven neonatal sepsis, primarily due to A. baumannii sepsis and antibiotic-resistant sepsis in settings like ours. Efforts must be made to consolidate the gains achieved during the pandemic by reinforcing the desirable administrative and infection control practices.
Phase of LD/UnlockingDuration (mm/dd/yyyy)Government Stringency Index
LD phases 1 and 2March 22, 2020–May 3, 202096.3–100
LD phases 3 and 4May 4, 2020–May 31, 202079.17–81.94
Unlock 1.0June 1, 2020–June 30, 202075.46–76.39
Unlock 2.0July 1, 2020–July 31, 202074.07–77.78
Unlock 3.0August 1, 2020–August 31, 202079.63
Unlock 4.0September 1, 2020–September 30, 202073.61–81.02
  26 in total

1.  Efficacy of an infection control program in reducing ventilator-associated pneumonia in a Chinese neonatal intensive care unit.

Authors:  Qi Zhou; Shoo K Lee; Si-yuan Jiang; Chao Chen; Majeeda Kamaluddeen; Xiao-jing Hu; Chuan-qing Wang; Yun Cao
Journal:  Am J Infect Control       Date:  2013-09-14       Impact factor: 2.918

2.  Case-control analysis of endemic Acinetobacter baumannii bacteremia in the neonatal intensive care unit.

Authors:  Jen-Fu Hsu; Shih-Ming Chu; Reyin Lien; Cheng-Hsun Chiu; Ming-Chou Chiang; Ren-Huei Fu; Chiang-Wen Lee; Hsuan-Rong Huang; Ming-Horng Tsai
Journal:  Am J Infect Control       Date:  2013-10-29       Impact factor: 2.918

3.  Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.

Authors:  A-P Magiorakos; A Srinivasan; R B Carey; Y Carmeli; M E Falagas; C G Giske; S Harbarth; J F Hindler; G Kahlmeter; B Olsson-Liljequist; D L Paterson; L B Rice; J Stelling; M J Struelens; A Vatopoulos; J T Weber; D L Monnet
Journal:  Clin Microbiol Infect       Date:  2011-07-27       Impact factor: 8.067

4.  Coronavirus Disease 2019 Pandemic: Impact Caused by School Closure and National Lockdown on Pediatric Visits and Admissions for Viral and Nonviral Infections-a Time Series Analysis.

Authors:  François Angoulvant; Naïm Ouldali; David Dawei Yang; Mathilde Filser; Vincent Gajdos; Alexis Rybak; Romain Guedj; Valérie Soussan-Banini; Romain Basmaci; Alain Lefevre-Utile; Dominique Brun-Ney; Laure Beaujouan; David Skurnik
Journal:  Clin Infect Dis       Date:  2021-01-27       Impact factor: 9.079

5.  Successful control of an Acinetobacter baumannii outbreak in a neonatal intensive care unit.

Authors:  R Melamed; D Greenberg; N Porat; M Karplus; E Zmora; A Golan; P Yagupsky; R Dagan
Journal:  J Hosp Infect       Date:  2003-01       Impact factor: 3.926

6.  Effect of Social Distancing Due to the COVID-19 Pandemic on the Incidence of Viral Respiratory Tract Infections in Children in Finland During Early 2020.

Authors:  Ilari Kuitunen; Miia Artama; Lotta Mäkelä; Katri Backman; Tarja Heiskanen-Kosma; Marjo Renko
Journal:  Pediatr Infect Dis J       Date:  2020-12       Impact factor: 2.129

Review 7.  Prevention and Control of Multidrug-Resistant Gram-Negative Bacteria in Adult Intensive Care Units: A Systematic Review and Network Meta-analysis.

Authors:  Nattawat Teerawattanapong; Kirati Kengkla; Piyameth Dilokthornsakul; Surasak Saokaew; Anucha Apisarnthanarak; Nathorn Chaiyakunapruk
Journal:  Clin Infect Dis       Date:  2017-05-15       Impact factor: 9.079

8.  Delayed access or provision of care in Italy resulting from fear of COVID-19.

Authors:  Marzia Lazzerini; Egidio Barbi; Andrea Apicella; Federico Marchetti; Fabio Cardinale; Gianluca Trobia
Journal:  Lancet Child Adolesc Health       Date:  2020-04-09

9.  Bacteraemia variation during the COVID-19 pandemic; a multi-centre UK secondary care ecological analysis.

Authors:  Sarah Denny; Timothy M Rawson; Peter Hart; Giovanni Satta; Ahmed Abdulaal; Stephen Hughes; Mark Gilchrist; Nabeela Mughal; Luke S P Moore
Journal:  BMC Infect Dis       Date:  2021-06-11       Impact factor: 3.090

10.  Reduction in healthcare-associated respiratory viral infections during a COVID-19 outbreak.

Authors:  L E Wee; E P Conceicao; X Y J Sim; K K K Ko; M L Ling; I Venkatachalam
Journal:  Clin Microbiol Infect       Date:  2020-07-03       Impact factor: 13.310

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